Data Ranking Optimization: Hybrid Fuzzy AHP-VIKOR with Information Gain Ratio Attribute Reduction - Muzakir, Muhammad; Kusrini, Kusrini; Arief, Muhammad Rudyanto (KLIK- KUMPULAN JURNAL ILMU KOMPUTER, 2024)
Poverty in Indonesia, including in Banjarmasin City, South Kalimantan Province, remains a significant issue despite the government's implementation of various mitigation programs. One of the primary challenges is the distribution of social assistance, which often fails to reach the intended beneficiaries. To address this problem, this study aims to apply the Hybrid Fuzzy Analytic Hierarchy Process (AHP) - Technique for Order Preference by Similarity to Ideal Solution (VIKOR) algorithm to the integrated social welfare data (DTKS) in Banjarmasin City. The hybrid Fuzzy AHP - VIKOR approach is employed in this study to rank social assistance recipients based on the available dataset, which consists of 2,879 records. Fuzzy AHP is utilized for the weighting and classification process, while VIKOR is applied to rank the alternatives. The combination of these two methods is expected to yield a more accurate ranking that aligns with the actual needs identified in the DTKS data for Banjarmasin City. The findings of this study demonstrate that the application of AHP and VIKOR methods produces more accurate rankings in accordance with the real data. These results have significant implications for enhancing the effectiveness of poverty alleviation programs and aiding the Banjarmasin City government in prioritizing the distribution of social assistance. By integrating the Fuzzy AHP and VIKOR methods, this study provides a deeper understanding of the more targeted distribution of social assistance, which is anticipated to improve the effectiveness of poverty alleviation programs in Banjarmasin City and beyond.