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All Journal Indonesian Journal of Electronics and Instrumentation Systems Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Proceedings of KNASTIK Jurnal sistem informasi, Teknologi informasi dan komputer JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Bulletin of Computer Science Research Jurnal Pengabdian kepada Masyarakat Bina Darma Algoritme Jurnal Mahasiswa Teknik Informatika Arcitech: Journal of Computer Science and Artificial Intelligence Jurnal Pengabdian Kolaborasi dan Inovasi IPTEKS MDP Student Conference
Wijang Widhiarso
Universitas Multi Data Palembang
Agriculture, Biological Sciences & Forestry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Environmental Science Languange, Linguistic, Communication & Media Library & Information Science Mathematics Social Sciences Other

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Journal : MDP Student Conference

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Metode Topsis Untuk Menentukan Karyawan Terbaik Yuda, Andika Dirma; Widhiarso, Wijang
MDP Student Conference Vol 4 No 1 (2025): The 4th MDP Student Conference 2025
Publisher : Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/mdp-sc.v4i1.10996

Abstract

PT. Supra Indolub Perkasa is an official distributor of ExxonMobil Lubricants in Indonesia. Currently, the company faces challenges in the employee evaluation process, which remains conventional, lacks proper documentation, and has limitations in terms of objectivity and accuracy. This process often takes a long time, is prone to data entry errors, and lacks transparency, which can lead to suboptimal decision -making. Therefore, this study aims to develop a Web -Based Decision Support System (DSS) using the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method. The system is developed by implementing the RUP (Rational Unified Process) methodology and the Laravel framework to support a more systematic employee data management process. The evaluation criteria include attendance, technical skills, non-technical skills, and personality aspects. The results of the study indicate that this system can improve accuracy, accelerate the evaluation process, and support fair, transparent, and data -driven decision-making. With this system, the company can more easily determine the best employees in an objective manner.
Implementasi SOLID dan Optimalisasi Query pada Aplikasi Pencatatan Kemiskinan Usman, Usman; Widhiarso, Wijang; Rachmadi, Muhammad
MDP Student Conference Vol 4 No 1 (2025): The 4th MDP Student Conference 2025
Publisher : Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/mdp-sc.v4i1.11176

Abstract

This research aims to improve the efficiency and performance of the poverty recording application at the Communication and Information Office of Musi Banyuasin Regency by implementing SOLID design principles and query optimization techniques. Using a quasi-experimental approach, the study compares the system before and after code refactoring, The analysis results indicates that the application of SOLID principles and optimization techniques resulted in reduced volume of source code and improved code recommendations. This resulting application is more modular, efficient, and easier to maintain.
Perangkat Lunak Untuk Memprediksi Penyakit Hati Jenis Hepatitis Menggunakan Algoritma Support Vector Machine (SVM) Andres, Yohanes; Widhiarso, Wijang
MDP Student Conference Vol 4 No 1 (2025): The 4th MDP Student Conference 2025
Publisher : Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/mdp-sc.v4i1.11250

Abstract

Hepatitis is an inflammation of the liver that can be caused by viral infections, genetic factors, alcohol, and medications. This disease is difficult to diagnose clinically due to its varying symptoms. This study aims to classify the types of hepatitis using the Support Vector Machine (SVM) algorithm. The method employed is SVM with various kernels, utilizing a dataset consisting of 620 records with 19 features and 1 class attribute. The data is split into 80% for training and 20% for testing. The results show that the polynomial kernel delivers the best performance with an accuracy of 96%, precision of 100%, recall of 81%, and F1-score of 89%. The conclusion of this study is that the SVM method with a polynomial kernel can serve as an effective tool in detecting the presence or absence of hepatitis.
Co-Authors ALFIARINI, ALFIARINI Andres, Yohanes Asyraq, Cerwyn Cendy Prakarsah Chandra Wijaya Dafid Dafid Deni Apriadi Derry Alamsyah Edi Winarko Edo Renaldo Ericco Andreas Ervina Patricia Arifin Farisi, Ahmad Hafiz Irsyad Kersen Kersen Khan, Zicola Vladimir VIky Kurniawan, Wiji Manalu, Josua Michael Michael Muhammad Irfan Muhammad Rachmadi, Muhammad Muhammad Rizky Pribadi Purwasih, Opita Ricky Putra Sardika Robi Yanto Sardika, Ricky Putra SATRIAWAN, MUHAMMAD AKBAR Sri Hartati Usman Usman Vera Nofita Verren Oktaviana Wiwik Handayani Yuda, Andika Dirma