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All Journal Pendas : Jurnah Ilmiah Pendidikan Dasar The IJICS (International Journal of Informatics and Computer Science) Jatilima : Jurnal Multimedia Dan Teknologi Informasi Jurnal Teknologi Sistem Informasi dan Sistem Komputer TGD Proceedings of The ICECRS Ulead : Jurnal E-pengabdian Jurnal Masyarakat Indonesia ORAHUA : Jurnal Pengabdian Kepada Masyarakat
Pristiwanto
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Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Languange, Linguistic, Communication & Media Mathematics Other

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OPTIMALISASI PENILAIAN KELAYAKAN KREDIT DENGAN ALGORITMA BACKPROPAGATION Lubis, Mai Sarah Nur; Ramadhani, Putri; Pristiwanto
Pendas : Jurnal Ilmiah Pendidikan Dasar Vol. 9 No. 04 (2024): Volume 09, Nomor 04, Desember 2024
Publisher : Program Studi Pendidikan Guru Sekolah Dasar FKIP Universitas Pasundan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23969/jp.v9i04.18159

Abstract

The implementation of the backpropagation algorithm in customer loan eligibility using Artificial Neural Networks (ANN) with the backpropagation method represents an effective approach for evaluating and predicting loan eligibility. This algorithm allows the use of historical data to train a model capable of identifying complex patterns in customer data, including payment behavior, credit history, and other relevant factors. By leveraging this technique, financial institutions can enhance accuracy in assessing credit risk, optimize loan decisions, and reduce the risk of non-performing loans. Loan eligibility assessment is a crucial aspect in the banking industry for minimizing credit risk and increasing profitability. This study proposes a loan eligibility assessment method using the Backpropagation algorithm within Artificial Neural Networks (ANN). The method aims to identify customer eligibility based on historical data and related features such as income, credit history, and age. The research findings indicate that the ANN Backpropagation model can provide accurate predictions of customer loan eligibility with lower error rates compared to traditional methods. These findings suggest that applying the ANN Backpropagation algorithm can enhance the effectiveness of the credit assessment process, minimize credit default risk, and potentially optimize loan decisions in the banking industry.
Implementation of the MARCOS Method in a Decision Support System for Foundation Scholarship Determination Sinambela, Sugi Hartono; Rajagukguk, Denni M; Pristiwanto; Muhammad Iqbal Batubara; R.L harmady Tamba
The IJICS (International Journal of Informatics and Computer Science) Vol. 9 No. 3 (2025): November
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/ijics.v9i3.9574

Abstract

The scholarship selection process often involves multiple criteria and is prone to subjectivity when conducted manually. This study aims to implement the Multi-Attributive Ideal-Real Comparative Analysis (MARCOS) method in a Decision Support System (DSS) to determine foundation scholarship recipients objectively and systematically. The research applies a quantitative approach by evaluating several student alternatives based on academic and non-academic criteria, including academic achievement, parents’ income, number of dependents, organizational activity, and social status. The MARCOS method is employed through decision matrix construction, normalization, weighting, utility value calculation, and ranking. The results indicate that the proposed system is able to generate clear and consistent rankings of scholarship candidates. Validation results show an accuracy of 80% when compared with the foundation’s manual decision process. These findings demonstrate that the MARCOS-based Decision Support System can improve accuracy, transparency, and efficiency in scholarship determination and can be adapted to other multi-criteria decision-making problems.
Workshop Penerapan VLAN Menggunakan Routerboard Mikrotik dan Ruijie Reyee RG-ES208GC Siregar, Saidi Ramadan; Muhammad Sayuti; Hery Sunandar; Pristiwanto
ORAHUA : Jurnal Pengabdian Kepada Masyarakat Vol. 3 No. 02 (2026): Januari
Publisher : Faatuatua Media Karya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70404/orahua.v3i02.637

Abstract

Akibat lahan yang tidak cukup pada daerah perkotaan maka banyak bangunan dibangun secara bertingkat. khususnya pada bangunan yang menunjang keberlangsungan sistem informasi demi melancarkan aktivitas instansi-instansi atau perusahaan-perusahan misalnya gedung sekolah, gedung perkuliahan, gedung perbankan, gedung badan usaha milik negara dan sebagainya. Tentunya memiliki dampak dalam pemasangan kabel jaringan komputer serta pemborosan anggaran jika perencanaan dan tata kelola tidak tepat guna. Solusi yang paling efektif dan efisien meski menerapkan virtual local area network (vlan) pada bangunan bertingkat. Banyak keuntungan yang didapatkan salah satunya adalah estetika jalur kabel jaringan yang rapih yakni menghindari bundelan kabel yang banyak. Selain dari pada itu memudahkan dalam mengelola jaringan komputer dan memiliki batasan hingga ribuan nomor vlan tentu ini adalah suatu keuntungan yang besar jika dibandingkan dengan membeli fisik kabel yang sangat banyak. Hasil yang diharapkan pada kegiatan workshop adalah menambah pengetahuan siswa-siswi tingkat kejuruan yakni Sekolah Menengah Kejuruan (SMK) tentang jaringan komputer serta dapat melakukan konfigurasi routerboard mikrotik. Kemudian para siswa-siswi yang mengikuti kegiatan diharapkan juga mempunyai kompentensi pada pasar industri sesuai dengan kebutuhan perusahaan-perusahaan dan instansi-instansi yang berkaitan dengan jaringan komputer dan sistem teknologi informasi hingga berlangsungnya sistem informasi yang diinginkan yakni input data, proses hingga hasil output yang dihasilkan dari system yang digunakan.
Co-Authors Arief, Mhd. Abrar Azlan Barus, Apriwati Denni M Rajagukguk Emy Rosnawati Faisal Ridho, Faisal Furqan Hery Sunandar Lubis, Mai Sarah Nur Matias Julyus Fika Sirait Maulidina Muhammad Amin Muhammad Amin Muhammad Iqbal Batubara Muhammad Sayuti Putri Ramadhani, Putri R.L harmady Tamba Saidi Ramadan Siregar Saidi Ramadan Siregar Siagian, Novriadi Antonius Simangunsong, Pandi Barita Nauli Sinambela, Sugi Hartono Sitorus, Syahrial Sri Budi Purwaningsih, Sri Budi Taufany, Firdaus Enov At Tuti Andriani Zain, Nur Khofifah