Penerapan Metode Topsis dalam Sistem Pendukung Keputusan Penerimaan Bantuan Sosial di Kelurahan Tapos Depok

Abstract

ABSTRAK Proses seleksi penerima bantuan sosial di Kelurahan Tapos Depok masih dilakukan secara manual, sehingga memakan waktu lama dan rentan subjektivitas. Hal ini menimbulkan masalah efektivitas dan ketepatan sasaran penerima bantuan. Berdasarkan hal tersebut, rumusan masalah penelitian ini adalah bagaimana merancang sistem pendukung keputusan yang objektif, cepat, dan sistematis menggunakan metode TOPSIS. Penelitian ini bertujuan menerapkan metode TOPSIS dalam sistem seleksi penerima bantuan sosial dengan kriteria penghasilan, jarak, jumlah anggota keluarga, usia, dan kelompok rentan. Sistem dibangun menggunakan Java dan MySQL dengan pendekatan kuantitatif melalui tahapan normalisasi, pembobotan, penentuan solusi ideal, perhitungan jarak, dan perangkingan. Hasil penelitian menunjukkan kriteria dengan bobot terbesar adalah penghasilan (0,30), diikuti jarak (0,25), jumlah anggota keluarga (0,20), usia (0,15), dan kelompok rentan (0,15). Sistem mampu menghasilkan peringkat penerima bantuan secara objektif dengan nilai preferensi tertinggi 0,175 serta meningkatkan kecepatan, akurasi, dan mengurangi subjektivitas dalam proses seleksi. ABSTRACT The social assistance recipient selection process in Tapos Village, Depok, is still carried out manually, which is time-consuming and prone to subjectivity. This raises issues regarding effectiveness and accuracy of recipient targeting. Hence, the research problem is how to design an objective, fast, and systematic decision support system using the TOPSIS method. This study aims at applying TOPSIS method to a social assistance recipient selection system, using criteria such as income, distance, number of family members, age, and vulnerable groups. The system is developed using Java and MySQL using a quantitative approach through the stages of normalization, weighting, determining the ideal solution, calculating distances, and ranking. The results shows that the criterion with the highest weighting is income (0.30), followed by distance (0.25), number of family members (0.20), age (0.15), and vulnerable groups (0.15). The system is able to produce objective recipient rankings with the highest preference score of 0.175, improving speed, accuracy, and reducing subjectivity in the selection process.