Perpustakaan
DESKRIPSI DATA LENGKAP
JudulIMPLEMENTASI METODE MULTI ATRIBUTIVE BORDER APPROXIMATION AREA COMPARISON (MABAC) SEBAGAI PENDUKUNG KEPUTUSAN TERHADAP CALON PENERIMA BANTUAN MODAL USAHA (BMU) STUDI KASUS (DINAS SOSIAL KOTA PALU)
Nama: MUHAMMAD ISHAR
Tahun: 2025
Abstrak
ABSTRAK Proses distribusi bantuan modal usaha memerlukan sistem seleksi yang adil dan transparan guna memastikan bahwa bantuan diberikan kepada pihak yang benarbenar memenuhi kriteria dan membutuhkan. Penelitian ini mengembangkan sebuah Sistem Pendukung Keputusan (SPK) dengan menerapkan metode Multi-Attributive Border Approximation area Comparison (MABAC) untuk membantu dalam menentukan calon penerima bantuan secara lebih objektif. Metode MABAC dipilih karena kemampuannya dalam memberikan hasil peringkat yang konsisten dan akurat berdasarkan berbagai kriteria. Adapun kriteria yang digunakan meliputi tingkat pendapatan, jumlah tanggungan, status pekerjaan, aset yang dimiliki, serta kelayakan usaha. Sistem ini dibangun menggunakan bahasa pemrograman PHP dan diimplementasikan pada data calon penerima dari wilayah kota Palu. Berdasarkan hasil pengujian, sistem mampu menyajikan peringkat calon penerima secara tepat dan sejalan dengan kondisi aktual di lapangan. Diharapkan, penerapan SPK berbasis metode MABAC ini dapat menjadi solusi pendukung dalam proses seleksi penerima bantuan yang lebih akuntabel dan efektif. Kata kunci : Sistem Pendukung Keputusan, MABAC, Bantuan Modal Usaha, Seleksi Penerima. ABSTRACT The distribution process of business capital assistance requires a fair and transparent selection system to ensure that assistance is given to those who really meet the criteria and are in need. This research develops a Decision Support System (SDM) by applying the Multi-Attributive Border Approximation area Comparison (MABAC) method to assist in determining potential beneficiaries more objectively. The MABAC method was chosen because of its ability to provide consistent and accurate ranking results based on various criteria. The criteria used include income level, number of dependents, employment status, assets owned, and business feasibility. The system was built using the PHP programming language and implemented on prospective recipient data from the Central Sulawesi region. Based on the test results, the system is able to present the ranking of prospective recipients accurately and in line with the actual conditions in the field. It is hoped that the application of SPK based on the MABAC method can be a supporting solution in the selection process of beneficiaries that is more accountable and effective. Keywords: Decision Support System, MABAC, Business Capital Assistance, Recipient Selection.

Sign In to Perpus

Don't have an account? Sign Up