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Journal articles on the topic 'Decision-Making assistance'

Author: Grafiati
Published: 4 May 2024

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1

Weijmar Schultz, WCM, and HBM van de Wiel. "Assistance with decision-making." Journal of Psychosomatic Obstetrics & Gynecology 26, no. 2 (June 2005): 83–84. http://dx.doi.org/10.1080/01674820500154475.

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2

Grgić-Hlača, Nina, Christoph Engel, and Krishna P. Gummadi. "Human Decision Making with Machine Assistance." Proceedings of the ACM on Human-Computer Interaction 3, CSCW (November 7, 2019): 1–25. http://dx.doi.org/10.1145/3359280.

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3

Evans, Mark, Rowan P. Ogeil, and James G. Phillips. "Cannabis, Decision‐Making, and Online Assistance Seeking." American Journal on Addictions 28, no. 6 (September 18, 2019): 473–79. http://dx.doi.org/10.1111/ajad.12960.

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Li, Zhuoyan, Zhuoran Lu, and Ming Yin. "Decoding AI’s Nudge: A Unified Framework to Predict Human Behavior in AI-Assisted Decision Making." Proceedings of the AAAI Conference on Artificial Intelligence 38, no. 9 (March 24, 2024): 10083–91. http://dx.doi.org/10.1609/aaai.v38i9.28872.

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With the rapid development of AI-based decision aids, different forms of AI assistance have been increasingly integrated into the human decision making processes. To best support humans in decision making, it is essential to quantitatively understand how diverse forms of AI assistance influence humans' decision making behavior. To this end, much of the current research focuses on the end-to-end prediction of human behavior using ``black-box'' models, often lacking interpretations of the nuanced ways in which AI assistance impacts the human decision making process. Meanwhile, methods that prioritize the interpretability of human behavior predictions are often tailored for one specific form of AI assistance, making adaptations to other forms of assistance difficult. In this paper, we propose a computational framework that can provide an interpretable characterization of the influence of different forms of AI assistance on decision makers in AI-assisted decision making. By conceptualizing AI assistance as the ``nudge'' in human decision making processes, our approach centers around modelling how different forms of AI assistance modify humans' strategy in weighing different information in making their decisions. Evaluations on behavior data collected from real human decision makers show that the proposed framework outperforms various baselines in accurately predicting human behavior in AI-assisted decision making. Based on the proposed framework, we further provide insights into how individuals with different cognitive styles are nudged by AI assistance differently.
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Dollberg, G. "Computerized Decision-Making Assistance for Managing Neonatal Hyperbilirubinemia." PEDIATRICS 117, no. 1 (January 1, 2006): 262–63. http://dx.doi.org/10.1542/peds.2005-2267.

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Habhouba, D., S. Cherkaoui, and A. Desrochers. "Decision-Making Assistance in Engineering-Change Management Process." IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews) 41, no. 3 (May 2011): 344–49. http://dx.doi.org/10.1109/tsmcc.2010.2059013.

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Sameeh El halabi, Amna, Zeyad T. El Sayad, and Hany M. Ayad. "VRGIS as assistance tool for urban decision making." Alexandria Engineering Journal 58, no. 1 (March 2019): 367–75. http://dx.doi.org/10.1016/j.aej.2018.07.016.

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Wright, Megan S. "Supported Decision Making in the United States: Supporters Provide Decision-Making Assistance but Are Not Decision Makers." AJOB Neuroscience 14, no. 3 (July 3, 2023): 252–54. http://dx.doi.org/10.1080/21507740.2023.2243877.

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9

De Peuter, Sebastiaan, and Samuel Kaski. "Zero-Shot Assistance in Sequential Decision Problems." Proceedings of the AAAI Conference on Artificial Intelligence 37, no. 10 (June 26, 2023): 11551–59. http://dx.doi.org/10.1609/aaai.v37i10.26365.

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We consider the problem of creating assistants that can help agents solve new sequential decision problems, assuming the agent is not able to specify the reward function explicitly to the assistant. Instead of acting in place of the agent as in current automation-based approaches, we give the assistant an advisory role and keep the agent in the loop as the main decision maker. The difficulty is that we must account for potential biases of the agent which may cause it to seemingly irrationally reject advice. To do this we introduce a novel formalization of assistance that models these biases, allowing the assistant to infer and adapt to them. We then introduce a new method for planning the assistant's actions which can scale to large decision making problems. We show experimentally that our approach adapts to these agent biases, and results in higher cumulative reward for the agent than automation-based alternatives. Lastly, we show that an approach combining advice and automation outperforms advice alone at the cost of losing some safety guarantees.
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Ardelt, Michael, Peter Waldmann, Florian Homm, and Nico Kaempchen. "Strategic Decision-Making Process in Advanced Driver Assistance Systems." IFAC Proceedings Volumes 43, no. 7 (July 2010): 566–71. http://dx.doi.org/10.3182/20100712-3-de-2013.00006.

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ÖhlméYr, Bo, Kent Olson, and Berndt Brehmer. "Understanding farmers' decision making processes and improving managerial assistance." Agricultural Economics 18, no. 3 (May 1998): 273–90. http://dx.doi.org/10.1111/j.1574-0862.1998.tb00505.x.

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Öhlmér, B. "Understanding farmers' decision making processes and improving managerial assistance." Agricultural Economics 18, no. 3 (May 1998): 273–90. http://dx.doi.org/10.1016/s0169-5150(97)00052-2.

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13

Simmons, M. B., and P. M. Gooding. "Spot the difference: shared decision-making and supported decision-making in mental health." Irish Journal of Psychological Medicine 34, no. 4 (October 23, 2017): 275–86. http://dx.doi.org/10.1017/ipm.2017.59.

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Respecting a person’s choices about the mental health services they do or do not use is a mark of quality support, and is often pursued for moral reasons, as a rights imperative and to improve outcomes. Yet, providing information and assistance for people making decisions about the mental health services can be a complex process, and has been approached in various ways. Two prominent approaches to this end are ‘shared decision-making’ and ‘supported decision-making’. This article considers each of these approaches, discussing points of similarity and difference and considering how the two might complement one another. By exploring the contribution that each approach can make, we conclude by proposing how future application of these approaches can account for the broader context of decisions, including support for ongoing decision-making; the multitude of service settings where decision-making occurs; and the diversity in supportive practices required to promote active involvement.
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Duncan-Reid, Jackson, and Jason S. McCarley. "Strategy Use in Automation-Aided Decision Making." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 65, no. 1 (September 2021): 96–100. http://dx.doi.org/10.1177/1071181321651259.

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When human operators make signal detection judgments with assistance from an automated decision aid, they perform better than they could unaided but fail to reach optimal sensitivity. We investigated the decision strategies that produce this suboptimal performance. Participants ( N = 130) performed a two-response classification task that required them to mentally estimate the mean of a set of randomly sampled values each trial. The task was performed with and without assistance from a 93% reliable decision aid. Psychometric functions were fit to the classification data, and data were fit with two cognitive models of automation use. The first model assumed that participants made automation-aided judgments using a contingent criterion strategy, adjusting their response cutoff for yes vs. no responses following a cue from the aid. The second strategy, a discrete state model, assumed that participants made aided judgments by simply deferring to the aid on some proportion of trials. A measure of model fit favored the discrete-state process model, with parameter estimates indicating large individual differences in deferral rate between participants (range = 2% and 95%).
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Campbell, Anne. "Strategies for Improving Dialysis Decision Making." Peritoneal Dialysis International: Journal of the International Society for Peritoneal Dialysis 11, no. 2 (April 1991): 173–78. http://dx.doi.org/10.1177/089686089101100215.

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It is important that every professional involved with guiding ESRD patients through the maze of dialysis decision making critically analyze his or her own behaviors, possible biases and thought processes influencing discussions with patients. Health care professionals need to continue to strive to improve their skills for assuring optimal assistance to their patients in making decisions about the best types of treatments for them. In this era of evermore challenging patients and technologies, the skills for informing patients and assisting them with effective decision making about issues such as medical management, dialysis, transplantation or treatment termination are vita! for assuring quality care.
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Suehiro, Yuki, Takahiro Wada, and Kohei Sonoda. "Assistance Method for Merging by Increasing Clarity of Decision Making." IEEE Transactions on Intelligent Vehicles 4, no. 1 (March 2019): 48–58. http://dx.doi.org/10.1109/tiv.2018.2886692.

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17

Gustafsson, B., L. C. Hydén, and T. Salonen. "Decision-making on social assistance in major cities in Sweden." Scandinavian Journal of Social Welfare 2, no. 4 (October 1993): 197–203. http://dx.doi.org/10.1111/j.1468-2397.1993.tb00039.x.

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18

Zhang, Ziying, Nele Russwinkel, and Sabine Prezenski. "Modeling Individual Strategies in Dynamic Decision-making with ACT-R: A Task Toward Decision-making Assistance in HCI." Procedia Computer Science 145 (2018): 668–74. http://dx.doi.org/10.1016/j.procs.2018.11.064.

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19

Andhika, Nadya, and Randi Rian Putra. "SISTEM PENDUKUNG KEPUTUSAN MENENTUKAN PENERIMA BLT DENGAN KEMISKINAN EKSTRIM MENGGUNAKAN METODE WEIGHT PRODUCT PADA DESA KLAMBIR V KEBUN." Jurnal Indonesia : Manajemen Informatika dan Komunikasi 4, no. 2 (May 10, 2023): 552–61. http://dx.doi.org/10.35870/jimik.v4i2.251.

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Recently, the receipt of Direct Cash Assistance has not been on target, where only the poor have received the Direct Cash Assistance. The unequal distribution of direct cash assistance is caused by decisions that are difficult to consider due to manual data processing. For this problem, the researcher hopes to help the decision maker no longer have trouble making decisions in determining the recipients of this Direct Cash Assistance because of the existence of a decision support system. This decision support system uses many criteria that must be met by the recipient of the direct cash assistance. This decision support system uses the weight product method which can assist in making decisions in determining who is more appropriate to receive Direct Cash Assistance through the ranking results obtained from the results of calculations using the weight product method.
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Khediri, Abderrazak, Mohamed Ridda Laouar, and Sean B. Eom. "Improving Intelligent Decision Making in Urban Planning." International Journal of Business Analytics 8, no. 3 (July 2021): 40–58. http://dx.doi.org/10.4018/ijban.2021070104.

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Generally, decision making in urban planning has progressively become difficult due to the uncertain, convoluted, and multi-criteria nature of urban issues. Even though there has been a growing interest to this domain, traditional decision support systems are no longer able to effectively support the decision process. This paper aims to elaborate an intelligent decision support system (IDSS) that provides relevant assistance to urban planners in urban projects. This research addresses the use of new techniques that contribute to intelligent decision making: machine learning classifiers, naïve Bayes classifier, and agglomerative clustering. Finally, a prototype is being developed to concretize the proposition.
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Nungsiyati, Nungsiyati, Didi Susianto, Noca Yolanda Sari, and Siti Mukodimah. "Komparasi Multi Criteria Decision Making Method Penerimaan Bantuan Siswa Miskin." JTKSI (Jurnal Teknologi Komputer dan Sistem Informasi) 6, no. 2 (May 27, 2023): 177. http://dx.doi.org/10.56327/jtksi.v6i2.1276.

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Poor Student Assistance (BSM) is government assistance in the form of a sum of cash that is given directly to students who come from poor families. BSM recipients are students who have been determined by the Ministry of Education and Culture (Kemdikbud) based on a predetermined mechanism. Assistance provided by the government to students from underprivileged families is not transparent so some BSM are not on target. In an effort to minimize target inaccuracies, a study was made with Multi Criteria Decision Making (MCDM) which is a decision-making method for determining the best alternative out of a number of alternatives based on certain criteria. The ranking of beneficiaries is determined using a comparison of the Simple Additive Weighting Method and the Weighted Product Method, which are the MCDM model. Manual testing was carried out on 5 (five). From the test results of the Simple Additive Weighting Method, Alternative 4 obtained the highest score. While the results of the Weighted Product method test show the highest results in Alternative 3. The difference in the calculation results of the two methods used is influenced by several factors such as the performance rating value of each alternative, the weight of the criteria, and mathematical calculations for each method, and because the criteria used do not have different weights so that the calculation results become less significant.
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22

Situm, Mario. "Editorial: New challenges and opportunities in strategic decision making." Corporate and Business Strategy Review 2, no. 1 (2021): 4–6. http://dx.doi.org/10.22495/cbsrv2i1editorial.

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We are pleased to present the recent issue of the journal “Corporate and Business Strategy Review”. In this issue, current findings from the research are presented, which will support researchers with ideas for future work and provide managers and consultants with resources to support the development of solutions and assistance in decision-making.
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23

Sahroni, Qoif, and Derman Janner Lubis. "Penerapan Metode TOPSIS Untuk Menentukan Penerima Bantuan Santri Kurang Mampu Pada Lembaga Pendidikan Islam Pondok Pesantren." TeknoIS : Jurnal Ilmiah Teknologi Informasi dan Sains 13, no. 2 (July 9, 2023): 155–68. http://dx.doi.org/10.36350/jbs.v13i2.211.

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In The educational unit is one of the tools to achieve educational goals in Indonesia. Most educational institutions in Indonesia are still experiencing some problems in selecting candidates for assistance, because they are still evaluating in a conventional way so that it is feared that the recipients of the assistance will be students or students not fairly and appropriately. target. Therefore, it is necessary to create a Decision Support System for Recipients of Santri or Student Assistance, to determine which students or students fall within the criteria for being eligible to receive such assistance. The criteria used are 6 criteria, namely parents' income, crafts, type of floor of the house, average report card score, parents' occupation, and vehicle ownership. Making this system uses the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method, which is a decision-making method with a hierarchical structure, which is indeed included in the Multi Criteria Decision Making (MCDM).
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Hairah, Ummul, and Edy Budiman. "Internet Data Quota Assistance for Students Using Reference Point MOORA Decision Analysis." JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING 5, no. 1 (July 16, 2021): 1–10. http://dx.doi.org/10.31289/jite.v5i1.5050.

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Decisions are made by those who are authorized and responsible decision makings for an institution or organization. Many decisions involve stakeholders who are individuals and organizations who can be affected by the future consequences of these decisions, including decision-making on Internet data quota assistance distributed by the Ministry of Education and Culture to support students' online learning from home (LFH). This Assistance Policy is very appropriate and well provided during the Covid-19 Pandemic. However, in an effort to optimize and objectify distribution so that it is right on target, this research is proposed solutions for applying the analysis decision-making mode using Multi-criteria Decision-making (MCDM). The criteria used include the amount of internet data consumption, Academic credits, courses, and student's economic capacity. The criteria weighting method uses Rank-order Centroid (ROC) and reference point MOORA for determining the best alternative. Â The results showed that the implementation of the MCDM ROC-Reference MOORA method affected the preference value and alternative ranking of internet data quota assistance. This shows that the criteria weight value and the analysis method are critical aspects in decision-making. Differences in weight, even the slightest change in weight, can drastically change the final decision
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25

Hall, Crystal C., Martha M. Galvez, and Isaac M. Sederbaum. "Assumptions About Behavior and Choice in Response to Public Assistance." Policy Insights from the Behavioral and Brain Sciences 1, no. 1 (October 2014): 137–43. http://dx.doi.org/10.1177/2372732214550833.

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Assumptions about decision making and consumer preferences guide programs and products intended to help low-income households achieve healthy outcomes and financial stability. Despite their importance to service design and implementation, these assumptions are rarely stated explicitly, or empirically tested. Some key assumptions may reflect ideas carried over from an earlier era of social-service delivery. Or they may reflect research on decision making by higher income populations that do not hold or have not been tested in a low-income context. This disconnect between assumptions and evidence potentially results in less effective policy design and implementation—at substantial financial and social cost. This piece examines how insights from psychology can help policymakers analyze the core assumptions about behavior that underlie policy outcomes. Three policy areas serve as case studies, to examine some implicit and explicit assumptions about how low-income individuals make decisions under public and nonprofit assistance: banking, nutrition, and housing. Research on preferences and decision making evaluates these foundational assumptions. This perspective provides a unique and under-utilized framework to explain some behavioral puzzles, examine and predict the actions of individuals living in poverty, and understand what are often disappointing program outcomes. Recommendations suggest how psychology and behavioral decision making can impact policy research and design.
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Faisal, Ahmad, and Depi Rusda. "Sistem Pendukung Keputusan Penerimaan Bantuan Dana Desa BLT dengan Metode SAW Berbasis WEB." JURIKOM (Jurnal Riset Komputer) 9, no. 1 (February 25, 2022): 131. http://dx.doi.org/10.30865/jurikom.v9i1.3886.

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The object of research that will be made is to determine the receipt of village funds in the village of Kampung Melayu, namely Direct Cash Assistance (BLT) according to system rules. The purpose of previous research regarding research on determining recipients of rice social assistance to the poor in Kampung Melayu village with the Simple Additive Weighting (SAW) method aims to determine prospective recipients of poor rice to complete practical decision making and have alternative choices for decision making in order to determine poor people who are entitled to receive rice social assistance for the poor (Raskin) in the village. Based on the criteria used to determine the decision to receive rice social assistance for the poor, namely the amount of income, marital status, number of dependents and age. The results of this study are shown for the village government to be able to determine the people who are entitled to receive social assistance for poor rice (Raskin)
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Aurellia, Oviletta, and Untoro Apsiswanto. "PENERAPAN METODE SIMPLE ADDITIVE WEIGHTING (SAW) UNTUK MENYELEKSI PENERIMA BANTUAN LANGSUNG TUNAI DANA DESA (BLT DD)." EDUSAINTEK: Jurnal Pendidikan, Sains dan Teknologi 9, no. 3 (November 11, 2022): 930–42. http://dx.doi.org/10.47668/edusaintek.v9i3.624.

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With many government programs to improve the social status of the community, one of which is the Village Fund Direct Assistance (BLTDD) program in Pujo Basuki Village, Central Lampung, with the hope that the community's economy can be helped by this program. Selecting the right beneficiary to receive such assistance must be done in a precise and accurate manner. From these issues, it is necessary to have a method to support decision making in order to determine the residents of this assistance program appropriately with the SAW (Simple Additive Weighting) method in the process of making a decision..
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28

Klein, Joseph, and Herman Ronen. "The Contribution of a Decision Support System to Educational Decision-Making Processes." Journal of Educational Computing Research 28, no. 3 (April 2003): 273–90. http://dx.doi.org/10.2190/3u4e-xqr0-mk52-agam.

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In the light of reports of bias, the present study investigated the hypothesis that administrative educational decisions assisted by Decision Support Systems (DSS) are characterized by different pedagogical and organizational orientation than decisions made without computer assistance. One hundred and ten high school teachers were asked to suggest solutions to problems that arose in two school incidents. After reaching decisions, respondents were asked to rank, in order of importance, the considerations that guided them. The data were processed by DSS software, which calculated the highest-scoring option for each incident. This option was compared with the one chosen by the respondents, taking into account variables of seniority, educational level, specialization, and self-efficacy. DSS-aided decisions promoted greater moderation and enhanced cooperation among interested parties in comparison to decisions made without computer aid. The implications of these findings for future division of decision-making tasks between people and computers is discussed.
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Watson, Nori, and Christina Bell. "Cultural Considerations in Tube Feeding Decision-Making." Perspectives on Communication Disorders and Sciences in Culturally and Linguistically Diverse (CLD) Populations 21, no. 2 (August 2014): 63–73. http://dx.doi.org/10.1044/cds21.2.63.

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Tube feeding is a common intervention considered in the care of older adults. The objective of this paper is to provide an overview of the current literature on the relationship between cultural factors and tube feeding in older adults, to help prepare speech-language pathologists (SLPs) to consider these cultural factors in communicating with their patients and families who may be faced with a tube feeding decision. Although evidence indicates that this intervention lacks benefit in advanced dementia, the decision to provide tube feeding can be complicated and challenging. SLPs are often consulted to provide assistance in the evaluation of an older adult with eating and feeding problems, and have an important role in tube feeding decision-making. SLPs and the healthcare teams they work with need to be aware of regional, national, international, ethnic, cultural, and institutional differences in tube feeding decision-making and utilization. SLPs and their healthcare teams need culturally sensitive communication and assessment skills to gently elicit and address cultural influences in this decision.
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30

Hah, Hyeyoung, and Deana Shevit Goldin. "How Clinicians Perceive Artificial Intelligence–Assisted Technologies in Diagnostic Decision Making: Mixed Methods Approach." Journal of Medical Internet Research 23, no. 12 (December 16, 2021): e33540. http://dx.doi.org/10.2196/33540.

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Background With the rapid development of artificial intelligence (AI) and related technologies, AI algorithms are being embedded into various health information technologies that assist clinicians in clinical decision making. Objective This study aimed to explore how clinicians perceive AI assistance in diagnostic decision making and suggest the paths forward for AI-human teaming for clinical decision making in health care. Methods This study used a mixed methods approach, utilizing hierarchical linear modeling and sentiment analysis through natural language understanding techniques. Results A total of 114 clinicians participated in online simulation surveys in 2020 and 2021. These clinicians studied family medicine and used AI algorithms to aid in patient diagnosis. Their overall sentiment toward AI-assisted diagnosis was positive and comparable with diagnoses made without the assistance of AI. However, AI-guided decision making was not congruent with the way clinicians typically made decisions in diagnosing illnesses. In a quantitative survey, clinicians reported perceiving current AI assistance as not likely to enhance diagnostic capability and negatively influenced their overall performance (β=–0.421, P=.02). Instead, clinicians’ diagnostic capabilities tended to be associated with well-known parameters, such as education, age, and daily habit of technology use on social media platforms. Conclusions This study elucidated clinicians’ current perceptions and sentiments toward AI-enabled diagnosis. Although the sentiment was positive, the current form of AI assistance may not be linked with efficient decision making, as AI algorithms are not well aligned with subjective human reasoning in clinical diagnosis. Developers and policy makers in health could gather behavioral data from clinicians in various disciplines to help align AI algorithms with the unique subjective patterns of reasoning that humans employ in clinical diagnosis.
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KABASSI, KATERINA, MARIA VIRVOU, and GEORGE A. TSIHRINTZIS. "WEB SERVICES USER MODEL SERVER PERFORMING DECISION MAKING." International Journal of Pattern Recognition and Artificial Intelligence 21, no. 02 (March 2007): 245–64. http://dx.doi.org/10.1142/s0218001407005454.

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This paper presents a user model server based on Web Services. User model servers are very important because they allow reusability of user modeling reasoning mechanisms which are typically very complex and difficult to construct from scratch. In this paper we show how the potential of interoperability, reusability and component sharing offered by the technology of Web Services have been exploited in the design of a user model server that performs decision making. The reasoning of the user modeling is based on a multi-criteria decision making theory and has been implemented as a Web Service to provide intelligent assistance to users over the Web. Reusability has been shown through the successful application of the user model server into two different applications: an e-mail and a file manager application.
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Fitri, Dinda Locita, and Aji Supriyanto. "IMPLEMENTATION OF THE AHP-TOPSIS METHOD IN DECISION MAKING OF SOCIAL ASSISTANCE RECIPIENTS IN KARANGANYAR GUNUNG SEMARANG." Jurnal Teknik Informatika (Jutif) 3, no. 6 (December 26, 2022): 1483–90. http://dx.doi.org/10.20884/1.jutif.2022.3.6.315.

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The government's program of Social Assistance (Bansos) aims to improve the welfare of poverty in order to increase economic value, targeting that the recipients of the social assistance are the poor. There are still some obstacles in receiving social assistance, which are considered to be uneven, duplicate data and mistargeted. There are various models of determining poverty, one of which is based on calculations from the Central Statistics Agency (BPS). These provisions are used by the government in providing social assistance to be right on target. The determination of social assistance recipients according to BPS has 14 poverty criteria, namely: eating as much as a day, medical expenses, sources of income, sources of lighting, cooking fuel, toilet facilities, consumption of types of food, floor area, types of walls, sources of drinking water, savings , type of floor, buying clothes, and education of the head of the household. Using the Analytical Hierarchy Process (AHP) and the Technique Order Preference by Similarity to Ideal Solution (TOPSIS) which are used to rank Social Assistance recipients. The AHP method is used to weight the poverty criteria, while the TOPSIS method is used to rank alternative social assistance recipients, so as to produce recommendations for social assistance recipients. The test was carried out using 45 data from prospective social assistance recipients, the result was that the eligible recipients were in first place A4 with a value of -11.09028, in second place A5 with a preference value of -9.40301, third place A2 with a value of -7.30247 , fourth in A1 with a preference value of -4.33412, and fifth in A3 with a preference value of 9.35849.
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Spanoudaki, Elpiniki, Maria Ioannou, John Synnott, Calli Tzani-Pepelasi, and Ntaniella Roumpini Pylarinou. "Investigative decision-making: interviews with detectives." Journal of Criminal Psychology 9, no. 2 (April 25, 2019): 88–107. http://dx.doi.org/10.1108/jcp-02-2018-0005.

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PurposeThe purpose of this paper is to explore investigative decision-making processes in the context of major crimes as experienced by the law enforcement agents.Design/methodology/approachEpisodic interviews were conducted with six agents from medium-sized police forces in the UK. Following the framework of naturalistic inquiry, qualitative content analysis took place with the assistance of Atlas.ti software. To ensure the validity of findings, the within method triangulation was preferred, by additionally analysing the interview transcripts with Alceste.FindingsFindings from this study revealed a variety of internal factors at play, shaping the decision-making course into an act of balancing various desired goals. Detectives appear to assess a situation based on their experiences confirming that the naturalistic decision-making model may assist in understanding investigative decision-making.Research limitations/implicationsDue to the busy schedule of law enforcement agents the number of participants was limited and availability difficult; therefore, this study can be thought of as a pilot study that will inspire researchers to use the same method for in-depth understanding of investigative decision-making.Practical implicationsResults captured the ill-defined goals in the police environment and provided ways of decreasing their impact on investigative decision-making thus should help detectives to understand their decision-making limitations and strengths.Social implicationsThis project will enhance the psychological understanding of investigative decision-making.Originality/valueThis project assists in understanding the psychological aspect of investigative decision-making during police duty and provides the opportunity to law enforcement agents to re-evaluate situations in order to improve the investigative decision-making process; while adds to existing literature.
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Liu, Han, Vivian Lai, and Chenhao Tan. "Understanding the Effect of Out-of-distribution Examples and Interactive Explanations on Human-AI Decision Making." Proceedings of the ACM on Human-Computer Interaction 5, CSCW2 (October 13, 2021): 1–45. http://dx.doi.org/10.1145/3479552.

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Although AI holds promise for improving human decision making in societally critical domains, it remains an open question how human-AI teams can reliably outperform AI alone and human alone in challenging prediction tasks (also known as complementary performance). We explore two directions to understand the gaps in achieving complementary performance. First, we argue that the typical experimental setup limits the potential of human-AI teams. To account for lower AI performance out-of-distribution than in-distribution because of distribution shift, we design experiments with different distribution types and investigate human performance for both in-distribution and out-of-distribution examples. Second, we develop novel interfaces to support interactive explanations so that humans can actively engage with AI assistance. Using virtual pilot studies and large-scale randomized experiments across three tasks, we demonstrate a clear difference between in-distribution and out-of-distribution, and observe mixed results for interactive explanations: while interactive explanations improve human perception of AI assistance's usefulness, they may reinforce human biases and lead to limited performance improvement. Overall, our work points out critical challenges and future directions towards enhancing human performance with AI assistance.
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Neely, C. L., M. Bourne, S. Chesterman, T. G. Vågen, V. Lekaram, L. A. Winowiecki, and R. Prabhu. "Inclusive, Cross-Sectoral and Evidence-Based Decision-Making for Resilience Planning and Decision-Making in a Devolved Context." European Journal of Development Research 33, no. 4 (May 27, 2021): 1115–40. http://dx.doi.org/10.1057/s41287-021-00410-3.

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AbstractSuccessfully achieving the sustainable development goals requires addressing complex, interrelated, wicked problems across multiple scales and contexts and decision-making that tackles nested layers of goals and targets across the interrelated social, economic and environmental dimensions of sustainability. The Stakeholder Approach to Risk-informed and Evidence-based Decision-making (SHARED) bridges processes, tools and accessible evidence to support inter-sectoral and multi-stakeholder decision-making and implementation aimed at achieving resilience aspirations and associated investments. Adaptive collaborative management and multiple-loop learning serve as a basis for the systematic approach to institutional learning that supports shifts in underlying institutional understanding and values leading to actionable organisational change. This paper describes a contextual application of tailored technical assistance and institutional support to the Turkana County Government in Kenya, a newly devolved governance structure, under conditions of complexity. The SHARED Turkana County decision case demonstrates how the approach responded to a policy aspiration, resulting in greater and more intentional use of evidence in planning and budget allocations, cross-sectoral and multi-stakeholder partnerships, inclusive and transformative projects and a consultative and evidence-based five-year County Integrated Development Plan.
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Zaliluddin, Dadan. "Bibliometric Analysis of “Accuracy of Multi Criteria Decision Making (MCDM) of Assistance Recipients with Fuzzy Logic Algorithm”." West Science Interdisciplinary Studies 1, no. 07 (July 31, 2023): 329–39. http://dx.doi.org/10.58812/wsis.v1i07.82.

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The issue of making decisions accurately and swiftly is crucial in the present and is bolstered by an abundance of data; therefore, making correct decisions can save the future. With a large amount of data and numbers, however, the decision-making process will become even more muddled if the statistical ranking values are identical. Therefore, a method is required to determine whether a hazy decision becomes clearer or a decision that is nearly identical is the best. The method used has existed for more than 50 years, and it is fuzzy logic. In the selection of fuzzi, the term Multi-Criteria Decision Making (MCDM) is frequently used, and it continues to be used and expanded. As a result, the increasing number of articles that contain information about Fuzzy Logic Multi-Criteria Decision Making (MCDM) can be used as research material using Bibliometric analysis based on the Scopus. With Bibliometric analysis, tens of thousands of related articles can be analyzed and displayed with VOSviewer software using a variety of categories including authors, titles, citations, updates, and other information to demonstrate the most recent direction of future research on fuzzy logic Multi Criteria Decision Making (MCDM).
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Ding, Siew Hong, Teing Tien Goh, Pei Sze Tan, Siew Ching Wee, and Shahrul Kamaruddin. "Implementation of Decision Tree for Maintenance Policy Decision Making - A Case Study in Semiconductor Industry." Advanced Materials Research 591-593 (November 2012): 704–7. http://dx.doi.org/10.4028/www.scientific.net/amr.591-593.704.

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Suitable maintenance policy implemented in particular machine able to improve the machine performance as well as the product quality. However, selecting a suitable maintenance policy is a vital and hard work because it has to be decided from analysis of various criteria including failure mechanism and resources limitation. Thus, decision tree is suggested in this paper to provide assistance for maintenance crew in conducting a systematic and efficient decision making process in determining the suitable maintenance policy. In the end of the paper, a case study in semiconductor industry is conducted to illustrate the practicability of developed decision tree.
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Fazri, Rizka Aulia. "Perbandingan Metode Simple Additive Weighting dan Weighted Product Pada Keputusan Pemberian Bantuan (Desa Cisarua, Kabupaten Sukabumi)." JATISI (Jurnal Teknik Informatika dan Sistem Informasi) 8, no. 1 (March 19, 2021): 273–86. http://dx.doi.org/10.35957/jatisi.v8i1.674.

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Providing assistance is one of the programs carried out by the government through representatives of each region to help community’s economy, especially those related to the problems caused by Covid-19 pandemic. Ideally, the determination of the provision of assistance can be done quickly, objectively and on target. However, the decision-making process in Cisarua village, Sukabumi district is still done manually where there is no method used in that process leads decision makers to face problems in determining assistance recipients with the large number of people and multicriteria. Thus requiring a long time, leading to subjective judgements and providing assistance that is not on target. Simple Additive Weighting (SAW) and Weighted Product (WP) are multicriteria methods that can be applied in the decision-making process, both methods are compared to find out the best method in determining the appropriate and targeted assistance recipients. The research starts from the problem identification which includes data collection, analysis, and application of the multicriteria method to the interpretation of method comparison results. The SAW method is more appropriate to be applied in determining the provision of assistance in Cisarua village by producing a higher number of rankings and percentage value of suitability level than the WP.
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Wu, Shisong, and Zhaojie Dong. "An Auxiliary Decision-Making System for Electric Power Intelligent Customer Service Based on Hadoop." Scientific Programming 2022 (January 19, 2022): 1–11. http://dx.doi.org/10.1155/2022/5165718.

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Aiming at the problems of low security, high occupancy rate, and long response time in the current power intelligent customer service assistant decision-making system, a power intelligent customer service assistant decision-making system based on the Hadoop big data framework is designed. By analyzing the Hadoop big data framework, according to the characteristics and core elements of the HDFS distributed file system, the MapReduce programming model, and the data mining algorithm, the basic process of power intelligent customer service assistance decision-making is established. We analyze the overall and functional requirements of the system, design the overall architecture and application architecture of the system, design the E-R diagram and table structure of the database according to the database design principle, and realize the design of power intelligent customer service auxiliary decision-making system based on Hadoop big data framework. The test results show that the proposed method has high system security and low system occupancy and can effectively shorten the system response time. The systems run more flawlessly as compared to the existing methods and give impressing results with lesser CPU utilization. The response time was recorded to be about 12.2 seconds for 1000 power intelligent customer servers, which is much lower than that of the competitors.
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Wah, Choo Kok, Rozana Zakaria, and Azlan Adnan. "Decision Making Framework for Earthquake Disaster Prevention and Mitigation." Applied Mechanics and Materials 105-107 (September 2011): 330–33. http://dx.doi.org/10.4028/www.scientific.net/amm.105-107.330.

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Malaysia is a country with very low seismic. Most of the buildings in our country may not consider seismic load during structure design, thus the level of safety for remains unknown. Recently, earthquake events have become more frequent. Therefore, engineers have to be alert and kept updated with the knowledge and behavior of earthquake trend in this area. It is vital to assess the precaution measures that can be taken and consider them in the future building design. Therefore, a decision making framework in designing earthquake resistant building especially for school building in Malaysia is needed to help engineers to consider earthquake risk in the building design. This framework employed NERA Program with the assistance of SAP2000 software for analysis of the performance of earthquake resistant building.
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41

Krummheuer, Antonia L. "Instrumental and moral assistance." Pragmatics and Society 11, no. 3 (July 31, 2020): 440–62. http://dx.doi.org/10.1075/ps.17026.kru.

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Abstract The present paper takes an ethnomethodological and conversation analytical perspective on assisted shopping as it is done by a person with acquired brain injury in collaboration with her caregiver. My interest is directed towards the interactional and embodied organization of the situated selecting and decision-making processes, while I am aiming to understand the interactional organization of assistance and agency. The embodied interaction analysis is based on two video-recorded examples in which a caregiver treats the institutional resident’s shopping choice as either unproblematic or undesirable. I will differentiate five phases in which the participants systematically organize the selection process. In these phases, the participants take different roles either as shopper or as assistant caregiver; as to the later, I will distinguish between moral and instrumental assistance. The analysis demonstrates an inherent tension in the assistance during shopping activities, as it is oriented to both the incompetence that justifies the need for assistance and to the interactional construction of a competent and independent shopper.
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Shopalazuli, Sadakta, Baihaqi Baihaqi, and Erdiwansyah Erdiwansyah. "Sistem Informasi Pengambilan Keputusan Penerima Rehab Rumah Menggunakan Metode Weighted Sum Model (WSM) Pada Desa Bira Lhok Kecamatan Montasik." Jurnal Nasional Komputasi dan Teknologi Informasi (JNKTI) 4, no. 6 (December 19, 2021): 405–14. http://dx.doi.org/10.32672/jnkti.v4i6.3556.

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The house renovation program provided by the Aceh Besar regional government, especially in Gampong Bira Lhok, Montasik District, is an assistance program for the welfare of villagers whose housing conditions are far from livable. The problem faced by the Gampong government in the decision system for recipients of house renovation assistance at this time is that it still uses the decision system of deliberations between the Gampong apparatus and the Village Head so that it takes time to make decisions. Therefore, it is necessary to have a Decision Support System (SPK) to determine the acceptance of the house rehab program for residents with livable housing conditions based on computer information systems. This final project research aims to build a decision-making information system for home rehabilitation recipients using the Weighted Sum Model (WSM) method in Bira Lhok Village, Montasik District. The system development method used is the SDLC (Software Development Life Cycle) method using PHP and MySQL programming. The final project research resulted in a decision making information system for home rehabilitation recipients using the web-based Weighted Sum Model (WSM) with a factor weighting form interface, a form for prospective beneficiaries, a form for income criteria, assets, food and buildings, as well as a report on the assessment list of prospective recipients of rehabilitation assistance. House. Based on the results of the system that was built, the presence of an information system for decision making for home rehabilitation recipients using the Weighted Sum Model (WSM) method has made it easier for the Gampong Bira Lhok government to make decisions for recipients of home rehabilitation assistance quickly.
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Yunaldi, Andri. "Sistem Pendukung Keputusan Seleksi Bantuan Siswa Miskin Menerapkan Kombinasi Metode SAW dan ROC." JURNAL MEDIA INFORMATIKA BUDIDARMA 3, no. 4 (October 28, 2019): 376. http://dx.doi.org/10.30865/mib.v3i4.1511.

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Decision support system (DSS) is a system that helps decision makers in this case the principal, so that the decisions produced are considered effective and appropriate to solve the problems faced. Specifically in determining the provision of assistance to poor students, the determination of the criteria is aimed at making the recipient of the assistance in accordance with the purpose of the assistance itself. In this study, the authors applied a combination of SAW and ROC methods in selecting beneficiaries. ROC (Rank Order Centroid) is a method that can produce weight values, while Simple Additive Weighting (SAW) is a method used to rank poor prospective student assistance recipients as an alternative. The results of the study are expected to contribute to the development of science, especially the principal in the selection decision for recipients of poor student assistance
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Cahyanu, Ebet Tri, Siska Dewi Lestari, and Herry Hermawan. "Sistem Pendukung Keputusan Bagi Penerima Bantuan Siswa Miskin (BSM) Menggunakan Metode Simple Additive Weighting (SAW) di SMA Negeri 1 Raren Batuah Kabupaten Barito Timur." Journal of Applied Informatics and Computing 3, no. 2 (December 6, 2019): 114–18. http://dx.doi.org/10.30871/jaic.v3i2.1752.

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Raren Batuah 1 High School is a senior high school education level located at Unsum Village, Raren Batuah District, East Barito Regency, at Raren Batuah 1 High School, assistance is provided in the form of subsidies for Poor Student Assistance for the smooth teaching and learning process for students less fortunate. To help the selection process for recipients of Poor Student Assistance, a decision support system has been designed using the Simple Additive Weighting (SAW) method by prioritizing the criteria of parental income, the number of dependents of parents, and the value of student report cards that will be used for a reference decision making for the right recipient of Poor Student Assistance. Decision Support System Application (DSS) for Poor Student Assistance Recipients was designed using Flowchart and implemented using the Microsoft Visual Basic.Net 2010 programming language.
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Stranz, Hugo, Patrik Karlsson, and Stefan Wiklund. "The wide-meshed safety net. Decision-making on social assistance eligibility in Sweden." European Journal of Social Work 20, no. 5 (November 14, 2016): 711–23. http://dx.doi.org/10.1080/13691457.2016.1255596.

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Hou, Yi, Praveen Edara, and Carlos Sun. "Situation assessment and decision making for lane change assistance using ensemble learning methods." Expert Systems with Applications 42, no. 8 (May 2015): 3875–82. http://dx.doi.org/10.1016/j.eswa.2015.01.029.

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47

Geravand, Milad, Christian Werner, Klaus Hauer, and Angelika Peer. "An Integrated Decision Making Approach for Adaptive Shared Control of Mobility Assistance Robots." International Journal of Social Robotics 8, no. 5 (June 3, 2016): 631–48. http://dx.doi.org/10.1007/s12369-016-0353-z.

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48

Cole, Terri, and Jennifer Brown. "Behavioural Investigative Advice: Assistance to Investigative Decision-making in Difficult-to-detect Murder." Journal of Investigative Psychology and Offender Profiling 11, no. 3 (July 23, 2013): 191–220. http://dx.doi.org/10.1002/jip.1396.

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Mukodimah, Siti, Dini Rika Febriani, Muhamad Muslihudin, and Tuti Puspitasari. "DECISION MAKING MODEL FOR MEASURING THE FEASIBILITY OF SOCIAL ASSISTANCE FOR TPS3R AREA OF PRINGSEWU DISTRICT." IJISCS (International Journal of Information System and Computer Science) 7, no. 1 (April 30, 2023): 60. http://dx.doi.org/10.56327/ijiscs.v7i1.1544.

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Poverty is a major social welfare problem in Indonesia. Various efforts have been made by the government to overcome the main problems of social welfare in accordance with the Constitution of the Republic of Indonesia Number 11 of 2009 concerning social welfare, such as the provision of social assistance, social rehabilitation, social security, social empowerment, and social protection. In fact, various efforts made by the government in overcoming social welfare problems in Indonesia are considered not optimal. The lack of optimal distribution of government social assistance is affected by several factors, among others, the large number of data used as parameters and data collection and calculations that are still carried out simply and manually cause errors so that the results obtained are not on target. The study was conducted by examining the determining variables of eligibility for social assistance recipients using theSimple Additive Weighting method. To optimize the determination of the eligibility of beneficiaries in the TPS3R area of Pringsewu district, in this study the determining criteria will be applied to a system using the Decision Support System model. The decision-making system will be carried out by applying several variables as a basis for decision making including, Domicile, Family Economic Status, Employment, Income, Beneficiary Status Assistance, Number of Dependents and Home Conditions. By using the Decision Support system, poverty alleviation programs in the TPS3R area of Pringsewu district can be carried out quickly, effectively and efficiently and on target
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Usman, Syahrul, Firman Aziz, and Muhammad Lutfi. "Sistem Pendukung Pengambilan Keputusan Pemberian Bantuan dengan Metode AHP." JURNAL MEDIA INFORMATIKA BUDIDARMA 5, no. 2 (April 25, 2021): 540. http://dx.doi.org/10.30865/mib.v5i2.2870.

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Every humanitarian organization needs to raise funds and channel these funds. Distribution of funds from donors is often not in accordance with the programs that have been planned by social service agencies. This study aims to prioritize logistical assistance for flood disasters using the Analytical Hierarchy Process (AHP) Method as a supporting material that can be taken into consideration in making decisions about providing assistance on the crowdfunding platform which is used as an online fundraising medium, the AHP method is used as a supporting material for analyze the reference variables that are considered in making a decision to provide assistance. AHP analysis results recommend the order of potential beneficiaries from the highest priority to the lowest. In determining assisting decisions by sorting prospective recipients based on priority, the AHP method produces a consistency ratio value that is less than 0.1 so it can be concluded that the results of these decisions have consistent characteristics as supporting materials for decision making
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