Article Per Year (5 Year)
p-Index From 2020 - 2025
2.663
P-Index
This Author published in this journals
All Journal Jurnal Promkes: The Indonesian Journal of Health Promotion and Health Education Building of Informatics, Technology and Science Jurnal Pelayanan dan Pengabdian Masyarakat (Pamas) Journal of Midwifery and Public Health Journal Peqguruang: Conference Series Indo-MathEdu Intellectuals Journal Jurnal Penelitian dan Pengembangan Kesehatan Masyarakat Indonesia (JPPKMI) Media Publikasi Promosi Kesehatan Indonesia (MPPKI) GENIUS JOURNAL (General Nursing Science Journal) Journal of Public Health Sciences Journal of Ageing And Family Jurnal Pengabdian Kepada Masyarakat Babakti Journal Research Midwifery Politeknik Tegal
Fitriani, Sinta
Sekolah Tinggi Ilmu Kesehatan Respati
Religion Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Education Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Medicine & Pharmacology Neuroscience Nursing Physics Public Health Social Sciences Transportation Other

Published : 15 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search
Journal : Building of Informatics, Technology and Science

 1 
Sistem Pendukung Keputusan untuk Kelayakan Kredit Berdasarkan Profil Keuangan Menggunakan Metode TOPSIS Fitriani, Sinta; Masrizal, Masrizal; Irmayani, Deci
Building of Informatics, Technology and Science (BITS) Vol 7 No 1 (2025): June (2025)
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v7i1.7394

Abstract

Decision Support System (DSS) is one of the essential tools in assisting complex decision-making processes, including creditworthiness assessment based on customers’ financial profiles. This study aims to design a DSS capable of evaluating credit eligibility more accurately, objectively, and efficiently by applying the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method. This method is used to rank customer alternatives based on their proximity to an ideal solution by considering several criteria such as income, expenses, collateral, and credit history. The data used in this research were obtained from customer financial datasets containing information related to their financial profiles. The system was tested using simulation data, and the results showed that the TOPSIS method can provide creditworthiness evaluations with a high level of accuracy while reducing time and errors compared to manual assessment methods. The final research results identified the best alternative as A3 with a score of 0.8859, indicating the most optimal credit eligibility level. These findings are expected to serve as a valuable reference for financial institutions in making credit approval decisions, improving transparency, and minimizing risks in the credit process. The implementation of the TOPSIS method has proven to be an effective approach in supporting data-driven decision-making.
Co-Authors Ade Rahmat Agustini, Fenty Amalia Siti Zahra Apriasih, Hapi Danefi, Tupriliany Fadhila, Muhamad Rifky Mugni Febriana, Delia Firdaus, Islami Nur Hartiningrum, Chanty Yunie Hidayani , Wuri Ratna Irmayani, Deci Kusuma , Rimba Mudzanatun , Mudzanatun Mussawirrohimah, Tarisa Nurhayati, Sholiha Puspita, Pipih Eka Rahmayanti, Widi Rahmidini, Annisa Ramdani, Narachman Rikky Gita Hilmawan Salsabila, Milania Sofia, Dedeh Rosmaniar Sukma, Riyanti Latifah Sumartini, Erwina Tagum, Kenny Nino H. Turiano, Lorraine Yanti Heryanti Yogaswara, Dadan Yulianti, Ririn Yunie HR, Chanty Zahra, Amalia Siti