Penerimaan Bantuan Pangan Non Tunai (BPNT) Menggunakan Metode ARAS

Authors

DOI:

https://doi.org/10.30865/mib.v6i1.3478

Keywords:

ARAS, BPNT, Criteria, DSS, Web

Abstract

Non-Cash Food Assistance (BPNT) is social food assistance that is paid in non-cash form every month by the government. However, the problem of identifying BPNT recipients has not been identified properly and it is not certain that the poor really deserve to receive BPNT. So far, the existing system has not been optimal for selecting BPNT recipients with the existing criteria. Data management still uses a manual system and is not effective in determining who is entitled to receive BPNT and who is not. A creative solution to overcome this problem is the use of a web-based decision support system (DSS) using the Additive Ratio Assessment (ARAS) method. A system based on human and computer intelligence that creates options to improve decision making. The purpose of this research is to develop a system that helps decision making in deciding the acceptance of BPNT in poor families. This makes it easy to determine who is eligible and who is not eligible for assistance. This method is easy to apply for ranking by comparing it with other methods so that the results are more precise and accurate. The calculation process for the ARAS method using a very complex web-based system greatly facilitates and speeds up the determination of BPNT receipts. To facilitate implementation, 10 data with 5 criteria were used as sample data. Based on the calculation results of the potential beneficiaries on behalf of Selamat and Prayogi, the priority is getting assistance with a final score of < 0.07.

Author Biographies

Juniar Hutagalung, STMIK Triguna Dharma, Medan

Program Studi Sistem Informasi

Dicky Nofriansyah, STMIK Triguna Dharma, Medan

Program Studi Sistem Informasi

Mufthi Adi Syahdian, STMIK Triguna Dharma, Medan

Program Studi Sistem Informasi

References

E. Yulianti and M. Farina, “SISTEM PENDUKUNG KEPUTUSAN PENERIMA BANTUAN PANGAN NON TUNAI ( BPNT ) UNTUK KELUARGA MISKIN MENGGUNAKAN METODE SIMPLE MULTI ATTRIBUTE RATING TECHNIQUE ( SMART ),†vol. 8, no. 1, pp. 7–13, 2020, doi: 10.21063/JTIF.2020.V8.1.

https://www.bps.go.id/pressrelease/2020/07/15/1744/persentase-penduduk-miskin-maret-2020-naik-menjadi-9-78-persen.html

K. Nabila, P. Suharso, and W. Hartanto, “IMPLEMENTASI PROGRAM BANTUAN PANGAN NON TUNAI ( BPNT ) DI DESA,†vol. 15, no. 63, pp. 303–309, 2021, doi: 10.19184/jpe.v15i2.21327.

I. Riyansuni and J. Devitra, “‘ Analisis Dan Perancangan Sistem Pendukung Keputusan Penerima Bantuan Pangan Non Tunai ( BPNT ) Dengan Simple Additive Weighting ( SAW ) Pada Dinas Sosial Kota Jambi ,’†vol. 5, no. 1, pp. 151–163, 2020.

S. Pendukung, K. Seleksi, and T. Kerja, “UNTUK SECURITY SERVICE MENGGUNAKAN METODE ARAS,†vol. 2, no. 1, pp. 1–9, 2018.

N. K. Dewi, S. Aripin, R. K. Hondro, and A. Fau, “Sistem Pendukung Keputusan Pemilihan Game Untuk Anak Usia 5-10 Tahun Menggunakan Metode ARAS,†pp. 635–642, 2019.

J. N. H. S et al., “Coding : Jurnal Komputer dan Aplikasi Volume 07 , No . 03 ( 2019 ), Hal 109-119 ISSN 2338-493X IMPLEMENTASI METODE ADDITIVE RATIO ASSESMENT ( ARAS ) UNTUK REKOMENDASI PASIEN KUNJUNGAN SEHAT PADA FASILITAS KESEHATAN TINGKAT PERTAMA Coding : Jurnal Komputer dan Aplikasi ISSN 2338-493X Keterangan : m = jumlah alternative , n = jumlah kriteria , x ij = nilai kriteria dari alternatif i , x 0j = nilai optimum dari kriteria j . Jika kriteria merupakan kriteria yang bersifat biaya maka dinormalisasikan dengan rumus :,†vol. 07, no. 03, 2019.

J. Afriany and S. H. Sahir, “Efektifitas Penilaian Kinerja Karyawan Dalam Peningkatan Motivasi Kerja Menerapkan Metode Rank Order Centroid ( ROC ) dan Additive Ratio Assessment ( ARAS ),†no. September, pp. 813–821, 2019.

A. S. Nia, J. Saparauskas, and M. K. Ghorabaee, “A FUZZY ARAS METHOD FOR SUPPLY CHAIN MANAGEMENT PERFORMANCE MEASUREMENT IN SMEs,†vol. 16, no. 2, pp. 319–348, 2017.

S. D. Handayani, “Sistem Pendukung Keputusan Penentuan Mutasi Pegawai Pada Kantor Gubernur Sumatera Utara Dengan Menggunakan Metode Additive Ratio Assessment ( Aras ),†vol. 1, no. 1, pp. 27–34, 2020.

M. Aras and C. Waspas, “Pemilihan Dosen Penguji Skripsi Menggunakan,†vol. 10, pp. 354–367, 2021.

J. Khatib, S. Dalam, and K. Kunci, “Indonesian Journal of Computer Science,†vol. 10, no. 1, pp. 425–435, 2021.

V. No, “Edumatic : Jurnal Pendidikan Informatika,†vol. 5, no. 1, pp. 31–40, 2021, doi: 10.29408/edumatic.v5i1.3252.

B. Satria, C. Engineering, and S. Program, “IMPLEMENTATION OF ADDITIVE RATIO ASSESSMENT ( ARAS ) METHOD ON DECISION SUPPORT SYSTEM FOR RECIPIENT OF,†vol. 6, no. 1, pp. 121–128, 2020, doi: 10.33480/jitk.v6i1.1389.

D. M. Midyanti, R. Hidyati, S. Bahri, and U. T. Pontianak, “RUMAH DI KOTA PONTIANAK,†vol. 4, no. 2, pp. 119–124, 2019.

U. I. Gorontalo, “METODE ARAS,†vol. 4, no. 1, pp. 40–46, 2019.

R. Sistem, K. M. Electre, and A. Dalam, “JURNAL RESTI,†vol. 1, no. 10, pp. 109–116, 2021.

C. Maulana, A. Hendrawan, A. Praba, and R. Pinem, “PEMODELAN PENENTUAN KREDIT SIMPAN PINJAM MENGGUNAKAN METODE ADDITIVE RATIO ASSESSMENT ( ARAS ),†vol. 15, no. 1, pp. 7–11, 2019.

Downloads

Published

2022-01-25