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Kusuma, Kasa
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Computer Science & IT

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Application of the PSI-VIKOR Method in Determining Priorities for Poor Areas Based on Poverty Indicators in Central Java Kusuma, Kasa; Cholil, Saifur Rohman
Journal of Applied Informatics and Computing Vol. 9 No. 4 (2025): August 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i4.9888

Abstract

Poverty remains a significant challenge in developing countries, including Indonesia. Although the national poverty rate has declined, Central Java still shows relatively high rates. This study aims to identify priority areas in Central Java requiring government intervention to support effective poverty alleviation planning. Data were sourced from the Central Statistics Agency (BPS) of Central Java Province in 2023. A Decision Support System (DSS) approach was applied using the integrated Preference Selection Index (PSI) and VIKOR methods. PSI was used to determine objective criteria weights based on preference variations, while VIKOR ranked regions based on compromise solutions closest to ideal conditions.The ranking results were visualized spatially through a digitization process using QGIS to produce thematic maps. Analysis showed that Purworejo, Wonogiri, and Batang are high-priority regencies, whereas Semarang City, Banyumas, and Kendal have relatively stable socio-economic conditions. Validation using the Normalized Discounted Cumulative Gain (NDCG) method yielded a score of 0.9268, indicating strong alignment with historical data. These findings confirm the effectiveness of the PSI–VIKOR approach in supporting data-driven poverty alleviation strategies. The novelty of this study lies in the integrated application of PSI–VIKOR for spatial poverty prioritization, which has not previously been implemented in the Indonesian context.
Co-Authors Cholil, Saifur Rohman