Analisis Fungsi Implikasi Max-Min dalam Pengambilan Keputusan Penentuan Penduduk Kurang Mampu Menggunakan Metode Fuzzy Tsukamoto - Ginting, Clusilla Via Mia Dalmatia Br; Agnesia, Mella; Rahayu, Cici; Ginting, Raheliya Br; Surbakti, Asprina Br (Jurnal Sains dan Teknologi Informasi, 2025)
Determining the underprivileged population is a crucial aspect in the distribution of social assistance to ensure it is targeted. Fuzzy logic methods, specifically the Tsukamoto Fuzzy Inference System (FIS), are capable of addressing uncertainty and subjectivity in the decision-making process. This study aims to analyze the application of the Max-Min implication function in the Tsukamoto fuzzy system to determine the category of underprivileged population based on income, number of dependents, and housing conditions. The results show that the use of the Max-Min implication function produces consistent, transparent, and reliable decisions to support government policy in distributing social assistance. Based on the test results, where Income = 1.5 million, Number of dependents = 5, and housing condition score = 4, the ability level of Mrs. Clu is included in the underprivileged category.