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All Journal Prosiding National Conference for Community Service Project Infotech: Journal of Technology Information
Rubin Rubin
Universitas Internasional Batam
Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Economics, Econometrics & Finance Education

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Pelaksanaan Kegiatan Sosialisasi Pemilu Bersama Bawaslu di SMAN 4 Batam Cindy Lie; Sherly Tan; Elaine Elaine; Otniel Raja Maruli Situmorang; Faradhilla Nursyahda; Gracia Cindy Carlina; Rubin Rubin; Celine Alviora; Mutiara Aprillia Putri Sela; Jihan Fahira; Selvi Natalia; La Ode Candra; Revo Gahindra Herta Ananda; Marliana Marliana; Rahmi Ayunda
National Conference for Community Service Project (NaCosPro) Vol 5 No 1 (2023): The 5th National Conference for Community Service Project 2023
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat Universitas Internasional Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37253/nacospro.v5i1.8113

Abstract

General elections are an important mechanism in modern democracies to elect people's representatives or government officials which are carried out directly, publicly, freely, confidentially, honestly and fairly. General elections allow the whole community to participate in voting and electing leaders they trust as leaders of the country. However, during general elections, there are usually many problems that cause the implementation of these activities to not go smoothly, such as black campaigning, money politics, hate speech, spreading hoax news, abstention, and so on which should be an important concern in holding general elections. In this case, general election socialisation is needed as a process of conveying information in increasing public knowledge, understanding and awareness in the context of general elections. Creating a clean general election certainly requires public understanding and awareness of the dangers and consequences that will arise from various election problems. As an intelligent society must use the right to vote in general elections properly and don't waste your right to vote in selecting candidates for state leaders. This is important to implement in fostering shared awareness in creating democratic and aspirational general elections. Fair, free and transparent general elections are of course important in maintaining the democratic integrity of a country.
PERANCANGAN APLIKASI SOFTWARE DEFECT DETECTION DENGAN ALGORITMA BACKPROPAGATION, PCA DAN SVM Mangapul Siahaan; Rubin Rubin; Syaeful Anas Aklani
Infotech: Journal of Technology Information Vol 12, No 1 (2026): JUNI (In Progress)
Publisher : ISTEK WIDURI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37365/jti.v12i1.579

Abstract

Software defects are a major issue in software development because they can affect the quality, reliability, and performance of a system. As digital technology advances at an increasingly rapid pace, software complexity is also rising, thereby increasing the likelihood of software defects. This study aims to apply and compare several machine learning and artificial intelligence methods for detecting software defects. The methods used in this study include Support Vector Machine (SVM), Principal Component Analysis (PCA) as a dimension reduction technique, and Backpropagation as a neural network-based method. The research process was conducted through a series of experiments to evaluate and compare the performance of each method based on the accuracy values obtained. The results show that the combination of SVM and PCA provides the best performance in detecting software defects compared to other methods. The highest accuracy obtained was 85.78% when using 13, 15, and 16 PCA components. Meanwhile, SVM without PCA achieved an accuracy of 85.47%, and Backpropagation achieved an accuracy of 84.83%. These results indicate that the application of PCA is capable of improving SVM classification performance through a dimension reduction process that preserves important features in the dataset. However, the performance achieved is still influenced by the characteristics of the dataset, the data distribution, and the model configuration used.
Co-Authors Celine Alviora Cindy Lie Elaine Elaine Faradhilla Nursyahda Gracia Cindy Carlina Jihan Fahira La Ode Candra Marliana Marliana Mungkap Mangapul Siahaan Mutiara Aprillia Putri Sela Otniel Raja Maruli Situmorang Rahmi Ayunda Revo Gahindra Herta Ananda Selvi Natalia Sherly Tan Syaeful Anas Aklani, Syaeful