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All Journal Jurnal Sains dan Teknologi Journal Of Informatics And Busisnes
Susilo, Anang
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Perbandingan Kinerja K-Nearest Neighbors dan Naive Bayes Untuk Klasifikasi Perilaku Nasabah Pada Pembayaran Kredit Bank Susilo, Anang
Jurnal Sains dan Teknologi (JSIT) Vol. 3 No. 2 (2023): Mei - Agustus
Publisher : CV. Information Technology Training Center - Indonesia (ITTC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47233/jsit.v3i3.1264

Abstract

:Credit customers are people who use banking services or other financial services. to use bank money in its business activities, so it expects that the bank's credit can meet business capital needs. To reach information to increase profits and reduce company losses, we need a method that can provide knowledge to support the company's data. Research data can be obtained from processing classification data from credit customer data that are categorized as potential or not potential in the next credit grant. Data processing can be done using machine learning, namely classification techniques. This technique will produce a predictive churn model to determine which customer categories belong to a group. potential smooth or jammed. The Naive Bayes method was chosen because it can produce maximum accuracy with little training data. Meanwhile, the K-Nearest Neighbor method was chosen because it is robust against noise data. The performance of the two methods will be compared, so that it can be seen which method is better in classifying documents. The results obtained show that the Naive Bayes method has better performance with an accuracy rate of 70%, while the K-Nearest Neighbor method has a fairly low accuracy rate of 40%. Thus, it can be seen the accuracy value displayed by applying the classification algorithm. K-Nears Neighbors and Naïve Bayes. Parameter category. which in this study are account numbers, names of debtors, collectibility in the categories: current, DPK (on special mention), substandard, doubtful, loss. Then clarified with a description of the type of loan, collectability of ADK (computer data archive), type of business.
Pengembangan Sistem E-Voting Berbasis Bahasa Pemprograman Php Dalam Pemilihan Ketua Bem Universitas Sragen (Unissra) Susilo, Anang; Sudarmojo, Oki Derajat
Journal Of Informatics And Busisnes Vol. 3 No. 4 (2026): Januari - Maret
Publisher : CV. ITTC INDONESIA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47233/jibs.v3i4.4190

Abstract

The Era of Digitalization, Positioning E-Voting as an Alternative to Information Technology in the Election of the Chairperson of the Student Executive Board (BEM) at Sragen University. As is known, currently the Election of the Chairperson of BEM still uses a manual method so that it is at risk of errors in counting, requires a lot of time, and reduces student participation. This study aims to develop an E-Voting System Based on the PHP Exam Programming Language in the Election of the Chairperson of the Student Executive Board (BEM) at Sragen University. E-Voting is considered easier and more efficient because all processes have been carried out by computers. In addition, E-Voting also simplifies the process of counting votes, because it is done online, the incoming votes can be immediately known without having to count the ballots like the manual election process. Meanwhile, in the process of making and designing a web-based E-Voting System for the Election of the Chairperson of BEM Sragen University, it was built using the Waterfall System Development Method, the PHP Programming Language and using the Exam Database. The e-voting system is expected to improve the accuracy of election results, expedite the vote counting process, and increase student involvement. Furthermore, this system can reduce election costs and increase transparency in the vote counting process.
Co-Authors Sudarmojo, Oki Derajat