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All Journal Jurnal Mantik Penusa Jurnal Mantik TRIDARMA: Pengabdian Kepada Masyarakat (PkM) BERNAS: Jurnal Pengabdian Kepada Masyarakat Jurnal Pengabdian kepada Masyarakat Nusantara Digital Transformation Technology (Digitech) Jurnal ICT : Information and Communication Technologies
Nuraisana Nuraisana
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Journal : Jurnal Mantik

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Sistem Pendukung Keputusan Penentuan Penerima Bantuan Program Keluarga Harapan (PKH) Dengan Metode Analitycal Hierarcy Process: Sistem Pendukung Keputusan Penentuan Penerima Bantuan Program Keluarga Harapan (PKH) Dengan Metode Analitycal Hierarcy Process Nuraisana Nuraisana
Jurnal Mantik Vol. 3 No. 1 (2019): May: Manajemen dan Informatika
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (986.197 KB)

Abstract

Masalah ekonomi menyebabkan terjadinya kemiskinan. Program Keluarga Harapan (PKH) menjadi salah satu solusi dalam mengurangi masalah kemiskinan tersebut yang mana Dinas Sosial Kabupaten Deli Serdang juga memiliki peran dalam melakukan verifikasi dan validasi data calon penerima bantuan. Banyaknya perhitungan terkadang menyebabkan terjadinya kekeliruan. Jika tidak diatasi maka akan memakan waktu yang cukup banyak dalam melakukan perhitungan. Sistem pendukung keputusan dengan metode Analitycal Hierarcy Process (AHP) dapat melakukan perhitungan dengan mudah, cepat dan tepat karena dihitung oleh sistem komputer. Dalam metode Analitycal Hierarcy Process diperlukan adanya kriteria untuk melakukan penilaian. Adapun hasil akhir dari metode Analitycal Hierarcy Process adalah penentuan layak atau tidak layaknya calon penerima bantuan program keluarga harapan tersebut berdasarkan penilaian yang telah ditentukan.
Classification of Feasibility of Credit for Candidated CS Finance Debtors Using Naïve Bayes Method Nuraisana; Ellisa Purba
Jurnal Mantik Vol. 4 No. 3 (2020): November: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mantik.Vol4.2020.1031.pp1885-1899

Abstract

CS Finance is one of the central financing institutions in the two-wheeler finance industry. CS Finance, which was founded in 2010 under the name PT Central Santosa Finance. The problem that is often faced is when conducting administrative assessments to determine the right prospective debtor's eligibility. We need a system that can assist CS Finance in determining the feasibility of prospective debtors quickly and precisely. The method used in this research is Naïve Bayes. The data processed is data of prospective debtors. The variables used have been determined based on four attributes, namely character, capacity, capital, and conditions; testing is carried out using Rapidminer software, and the accuracy of the Naïve Bayes algorithm for predicting the feasibility of prospective debtors based on training data shows good performance, namely 80%. Hence, it is feasible for use. To make it easier for users to predict prospective borrowers' creditworthiness, a creditworthiness classification system for prospective debtors has been created in CS Finance using the web-based naïve Bayes method.
Co-Authors Abiomega Manalu Agustina Simangunsong Elisa Purba Ellisa Purba Fiqri Irhami Jonson Sianipar Muhammad Harun Petti Indrayati Sijabat Vinsensia, Desi Wira Apriani Yuda Perwira Yulianus Zai Yuni Endah Kurniati