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All Journal Jurnal Informatika dan Teknik Elektro Terapan Elsains : Jurnal Elektro Jurnal Minfo Polgan (JMP) Jurnal Aplikasi Bisnis dan Komputer Malcom: Indonesian Journal of Machine Learning and Computer Science Jurnal Inovatif Wira Wacana ABDI UNISAP: Jurnal Pengabdian Kepada Masyarakat Journal of Data Science and Information System
Pekuwali, Arini Aha
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Humanities Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics Public Health Social Sciences Other

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Journal : Journal of Data Science and Information System

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Penentuan Kelayakan Pemberian Kredit Menggunakan Metode SAW Pada PT. Leasing Arthaprima Finance Kotamobagu Arundaa, Rillya; Pekuwali, Arini Aha
Journal of Data Science and Information Systems Vol. 2 No. 1 (2024): Volume 2 Number 1 February 2024
Publisher : Journal of Data Science and Information Systems

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58602/dimis.v2i1.101

Abstract

In cash loan credit service companies, the determination of creditworthiness to consumers is carried out by the credit analyst. The Credit Analyst Department is required to work quickly and thoroughly in the selection of the number of incoming credit applications so that it does not rule out the possibility of miscalculations, misreading data, and so on. This study aims to apply the SAW method in determining credit consumers who are eligible for credit loans. There are 4 criteria used, namely Personality, Ability, Credit Guarantee, and Economic Conditions. In determining the eligibility of credit, 2 comparative values are used, namely the eligibility criteria (value 60) and the current criteria (value 100). Consumers are declared eligible for cash credit loans if the calculation of the preference value is more than 60. According to the calculation results in 10 alternative data, 7 consumers were obtained who were eligible for cash loan loans and 3 consumers who were rejected because their preference values did not meet the threshold value.
Co-Authors Abineno, Reynaldi Thimotius Agustin Lobo, Murry Albert Amelia Florida Kiha Ananau, Desrita Jera Anawoli, Rita Rambu Sori Arundaa, Rillya Bano, Vidriana Oktoviana Damanuna, Bryan Austhon dembi tamar, diniyanti Desy Asnath Sitaniapessy Djara, Ferdinan Yonathan Djara, Ferdinand Yonathan Halakadu, Afendi Alan Hamu, Melan Astriani Mburu Hanggawaly, Bryan Aryanda Haur, Lidwina Rosdiani Ndunga Hawu Yogia Pradana Uly Ina, Novantri Tamu Jawang, Uska Peku Kornelis, Vanesa Widia Ayusi Laka Tamar, Ayunia Lay, Yulita Leda Lede, Pingky A. R. Leo Li, Obed Hunggu Limbu, Alfian Alfred Umbu Lobo, Murry Albert Agustin Makatita, Audrey Loiuise Mira, Trisari Dewi N. B. Nawu, Alsetia Kahi Ndamung, Enjelita Pati Ndapamuri, Melycorianda Hubi Ngguna, Jeaneth Panja, Alfred Domu D. Prasetyo, Fajar Indra Rada, Yustina Ratu, Leonard Marten Doni Ratu, Leonard Marthen Doni Sitaniapessy, Dessy Asnath Suryaningsih Ndahawali Talakua, Alfrian Carmen Talakua, Alfrian Carmer Willem, Maria Adreana Elisabeth Wunga, Florida Yina, Sonia