The Decision Support System for Determining Poor Families Who Receive Blt Uses The Simple Additive Weighting (SAW) Method Case Study: Batubulan Village Perbekel Office

Many government programs have been created to overcome poverty in an area. However, the assistance provided is not on target so it has not reached the hands of the people who really need it. This happened because the determination of prospective poor families to receive BLT was not optimal. Seeing this, the author helped the Head of Social Welfare by creating a Decision Support System for Determining Poor Families Using the Simple Additive Weighting (SAW) Method. Case Study: Batubulan Village Perbekel Office so that it could provide two categories namely poor and not poor. The SAW method was chosen because it can determine the weight value of each criterion and then continue with the ranking process which will select a number of alternatives, in this case families that are categorized as poor families. With this ranking process, correct assessments and accurate results are obtained both in manual calculations and system calculations.

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Publication Details

Journal
BERKALA SAINSTEK
Published
2025-04-15
DOI
https://doi.org/10.19184/bst.v13i1.48772
Primary Topic
Data Mining and Machine Learning Applications
Type
article
Field-Weighted Citation Impact
0.00
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article

The Decision Support System for Determining Poor Families Who Receive Blt Uses The Simple Additive Weighting (SAW) Method Case Study: Batubulan Village Perbekel Office

Ayu Manik Dirgayusari, I Gde Eka Dharsika, Ni Made Ayu Mita Diani
BERKALA SAINSTEK
Data Mining and Machine Learning Applications
article

The Decision Support System for Determining Poor Families Who Receive Blt Uses The Simple Additive Weighting (SAW) Method Case Study: Batubulan Village Perbekel Office

Ayu Manik Dirgayusari, I Gde Eka Dharsika, Ni Made Ayu Mita Diani
article en

Abstract

Many government programs have been created to overcome poverty in an area. However, the assistance provided is not on target so it has not reached the hands of the people who really need it. This happened because the determination of prospective poor families to receive BLT was not optimal. Seeing this, the author helped the Head of Social Welfare by creating a Decision Support System for Determining Poor Families Using the Simple Additive Weighting (SAW) Method. Case Study: Batubulan Village Perbekel Office so that it could provide two categories namely poor and not poor. The SAW method was chosen because it can determine the weight value of each criterion and then continue with the ranking process which will select a number of alternatives, in this case families that are categorized as poor families. With this ranking process, correct assessments and accurate results are obtained both in manual calculations and system calculations.

BERKALA SAINSTEKVol. 13(1)
Universitas Teknologi Indonesia (ID)
Openalex Percentile: Top 89%
Data Mining and Machine Learning Applications
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