APPLICATION OF DECISION SUPPORT SYSTEM METHOD WITH TOPSIS TO IDENTIFY POVERTY-PRONE AREAS IN BREBES REGENCY

Poverty is a complex multidimensional problem that requires accurate identification of priority areas for the effectiveness of poverty alleviation programs. Brebes Regency faced a poverty rate of 14.22% in 2021, exceeding the Central Java average of 11.26%, with inaccurate targeting of social assistance leading to misallocation of resources. This study implements a Decision Support System (DSS) based on the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method to identify poverty-prone areas in Brebes Regency systematically and accurately. The methodology employs a quantitative approach with multicriteria analysis, including four variables: average income, malnutrition of toddlers, number of Certificates of Inability (SKTM), and number of recipients of Direct Cash Assistance (BLT). Data was collected from 297 villages via surveys, interviews, and BPS secondary data. The system uses web architecture with data normalization, criterion weighting, and OpenStreetMap-integrated geographic visualization. Results show TOPSIS identified poverty vulnerability hierarchy with 100% accuracy via manual and automated verification. Padakaton Village ranks highest at 0.6000 as a priority area. Alpha and beta testing confirmed perfect functional validity. Decile-based color-coding visualization aids spatial poverty interpretation. The DSS-TOPSIS system provides objective, measurable recommendations for strategic poverty alleviation decisions in Brebes Regency with high calculation transparency.