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All Journal JURIKOM (Jurnal Riset Komputer) Journal of Computer System and Informatics (JoSYC)
Davit Irawan
Universitas Bina Insan, Lubuklinggau
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Industrial & Manufacturing Engineering

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Penerapan Api Whatsapp Dalam Pelayanan Uji Plagiasi Universitas Bina Insan Berbasis Web Mobile Fido Rizki; Davit Irawan; Asep Toyib Hidayat
JURIKOM (Jurnal Riset Komputer) Vol 9, No 3 (2022): Juni 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v9i3.4054

Abstract

Currently, the service for plagiarism testing or plagiarism testing at Bina Insan University is through a sending system using gmail, where this plagiarism test is carried out as a requirement for students to get a diploma, the file that is carried out for the plagiarism test is the result of the student's thesis which is made into a journal, software that used to check this plagiarism using the Turnitin service. Plagiarism checking itself is currently carried out by the LPPM section where the checking process is that students first send a journal from the results of the thesis that has been approved by the Supervisor to be tested for plagiarism, from the current system there are many obstacles and shortcomings including when sending using In gmail, there is often a buildup and irregularity of the existing data, which causes the process of checking student journals to be tested for plagiarism a little longer, not to mention that students rarely open their gmail to see the results that have been sent by the LPPM team. The solution that the author offers in this research is to create a new mobile web-based system, where this system will later be equipped with the Whatsapp API feature, the Whatsapp API acts as a liaison between the system and the user, where the way it works is that every process that has been carried out in the system automatically The Whatsapp API will automatically provide notifications both to students and the LPPM admin itself, the results obtained from this research are that the presence of the Whatsapp api can speed up and simplify the data collection and testing process that will be carried out.
Model Hybrid dalam Penentuan Stok Barang Bangunan Melalui Pendekatan Machine Learning Intan Bintang Adinda; Davit Irawan; Joni Karman; Ahmad Sobri
Journal of Computer System and Informatics (JoSYC) Vol 7 No 1 (2025): November 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v7i1.8065

Abstract

This study aims to develop a machine learning-based construction material stock prediction model using a hybrid approach that combines K-Means Clustering as a sales pattern grouping method and Support Vector Machine (SVM) as a classification method to predict material sales levels. This research was motivated by the problem of stock management at Toko Usaha Jaya in Lubuklinggau City, which is still done manually, thus potentially causing excess stock that increases storage costs and stock shortages that can lead to lost sales opportunities and decreased customer satisfaction. The data used includes material names, initial stock quantities, quantities sold, remaining stock, and selling prices collected during the period from January to December 2023. The results show that the hybrid model is capable of grouping materials into three categories, namely very popular, fairly popular, and less popular, with a Silhouette Score of 0.42, indicating fairly good clustering quality. Furthermore, the SVM model produced a classification accuracy rate of 99%, reflecting an increase in stock prediction accuracy compared to manual management methods. These findings indicate that the application of the K-Means and SVM hybrid model can improve inventory management efficiency and support more accurate and effective data-driven decision making.
Co-Authors Ahmad Sobri Asep Toyib Hidayat Fido Rizki Intan Bintang Adinda Joni Karman