Article Per Year (5 Year)
p-Index From 2021 - 2026
2.147
P-Index
This Author published in this journals
All Journal Jurnal Manajemen Informatika Building of Informatics, Technology and Science Jurnal Tata Kelola dan Kerangka Kerja Teknologi Informasi PARETO : Jurnal Ekonomi dan Kebijakan Publik KLIK: Kajian Ilmiah Informatika dan Komputer NEGREI: Academic Journal of Law and Governance Arcitech: Journal of Computer Science and Artificial Intelligence JENDELA PENGETAHUAN Ngabdimas Abdi Reksa Jurnal Pengabdian kepada Masyarakat Arumbai Indonesian Journal of Computer Science and Engineering Jurnal Pengabdian kepada Masyarakat Arumbai
Putra, Yusran Panca
Program Studi Sistem Informasi, Universitas Bengkulu
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Social Sciences Other

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

Found 3 Documents
Search
Journal : Indonesian Journal of Computer Science and Engineering

 1 
Mekanisme MVC-Pemrograman Web Pada CMS Yang Memiliki Basis AI Sirait, Migel; Qavidhufahmi, Akhmat; Montaghib, M. Ihtifanul; Setiawan, Yudi; Erlanshari, Aan; Panca, Yusran Putra; Wijanarko, Andang
Indonesian Journal of Computer Science and Engineering Vol. 2 No. 01 (2025): IJCSE Volume 02 Nomor 01, Mei 2025
Publisher : CV. Cendekiawan Muda Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70656/ijcse.v2i01.311

Abstract

Artikel ini membahas penerapan arsitektur Model-View-Controller (MVC) dalam pengembangan Content Management System (CMS) modern yang mengintegrasikan teknologi kecerdasan buatan (AI). Dengan struktur modularnya, arsitektur MVC memberikan kemudahan dalam memisahkan logika, antarmuka, dan kontrol aplikasi. Integrasi AI dalam CMS meningkatkan kemampuan otomatisasi, analisis perilaku pengguna, dan interaksi berbasis konteks. Tulisan ini menyajikan hasil studi pustaka yang mencakup penerapan MVC dan AI dalam pengembangan CMS dengan studi kasus dari framework Laravel dan implementasi di Indonesia.
Systematic Literature Review on the Convergence of Business Process Management and Process Mining Putra, Yusran Panca; Novrian, Willi; Putra, Okka Adittio
Indonesian Journal of Computer Science and Engineering Vol. 2 No. 02 (2025): IJCSE Volume 02 Number 02, November 2025
Publisher : CV. Cendekiawan Muda Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Although Business Process Management (BPM) and Process Mining (PM) have been extensively studied as distinct domains, limited research has systematically explored their convergence. this study presents a Systematic Literature Review (SLR) on the convergence between Business Process Management (BPM) and Process Mining (PM), focusing on journal publications indexed in SpringerLink from 2020 to 2025. The review aims to map current research trends, identify how PM techniques support the BPM lifecycle, and explore the main benefits and challenges of their integration within organizational contexts. Using the PRISMA methodology and the PICOS framework, thirteen high-quality studies were systematically analyzed. The findings reveal that BPM and PM are increasingly interdependent—BPM provides a structured lifecycle for continuous improvement, while PM introduces data-driven insights through process discovery, conformance checking, and performance monitoring. PM strengthens each phase of the BPM lifecycle by enhancing process transparency, real-time monitoring, and evidence-based decision-making. However, integration remains challenged by data quality issues, limited governance mechanisms, insufficient management support, and tool usability constraints. The study concludes that successful BPM–PM convergence requires not only technical advancements but also organizational readiness and strategic alignment. Future research should emphasize cross-organizational and longitudinal approaches to develop comprehensive frameworks for embedding process intelligence within digital transformation initiatives.
Segmentation of Problematic Loan Customers Using The K-Means Clustering Algorithm to Support Strategic Decision-Making (Case Study: Bank Mega Finance Bengkulu) Novrian, Willi; Afriani, Annisa; Sari, Julia Purnama; Putra, Yusran Panca
Indonesian Journal of Computer Science and Engineering Vol. 2 No. 02 (2025): IJCSE Volume 02 Number 02, November 2025
Publisher : CV. Cendekiawan Muda Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This study analyzes 5,305 records of non-performing loan customers from Bank Mega Finance Bengkulu using the K-Means Clustering algorithm within the CRISP-DM framework. Based on variables such as tenure, outstanding balance, installment amount, and payment delay duration, the analysis identified three customer risk clusters (high, medium, and low) with a Davies-Bouldin Index (DBI) of 0.201, indicating good clustering quality. The segmentation results can help determine collection priorities, loan restructuring, and risk mitigation strategies, demonstrating the effectiveness of data mining in supporting strategic decision-making in banking risk management.
Co-Authors Afriani, Annisa Ana Hadiana, Ana Annisa Paramitha F Ansiska, Paisal Darmansah Douni, James Byeker Erlanshari, Aan Faradik, Mela Julia Purnama Sari Montaghib, M. Ihtifanul Myrna Dwi Rahmatya Nizar Rabbi Radliya Nopriadi Nopriadi Novrian, Willi Okka Adittio Putra Oktoyoki, Hefri Paulina, Maria Pranatha, Hananda Fitra Pratama, Benny Qavidhufahmi, Akhmat Rauf Fauzan Sarah Astiti S.Kom., M.MT Sirait, Migel Soni Ayi Purnama Wijanarko, Andang Willi Novrian Willi Novrian Willi Novrian Willi Novrian Yudi Setiawan