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All Journal IJCCS (Indonesian Journal of Computing and Cybernetics Systems) JSM (Jurnal SIFO Mikroskil) Telematika Jurnal Edukasi dan Penelitian Informatika (JEPIN) Jurnas Nasional Teknologi dan Sistem Informasi SISFOTENIKA JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Jurnal Sisfokom (Sistem Informasi dan Komputer) Voice Of Informatics JSiI (Jurnal Sistem Informasi) METIK JURNAL Progresif: Jurnal Ilmiah Komputer Jurnal Informatika dan Rekayasa Elektronik Journal of Information Systems and Informatics Techno Xplore : Jurnal Ilmu Komputer dan Teknologi Informasi Jurnal Tekinkom (Teknik Informasi dan Komputer) Teknomatika (Jurnal Teknologi dan Informatika) Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Naratif : Jurnal Nasional Riset, Aplikasi dan Teknik Informatika Jurnal Minfo Polgan (JMP) Haga: Jurnal Pengabdian Kepada Masyarakat Jurnal Informatika Nusantara Journal of Computers and its Applications Jurnal Abdimastek (Pengabdian Masyarakat Berbasis Teknologi) Jurnal Pengabdian Masyarakat (JURDIMAS) Jurnal Pengabdian Kepada Masyarakat (Abdimas) Universitas Baturaja
Delpiah Wahyuningsih
Institut Sains Dan Bisnis Atma Luhur
Agriculture, Biological Sciences & Forestry Arts Humanities Biochemistry, Genetics & Molecular Biology Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Medicine & Pharmacology Neuroscience Public Health Social Sciences Transportation Other

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Penerapan Collaborative Filtering dalam Sistem Rekomendasi Berbasis Artificial Intelligence untuk Meningkatkan Personalisasi pada E-Commerce Harry Gentar Alam; Delpiah Wahyuningsih; Chandra Kirana
Jurnal Minfo Polgan Vol. 15 No. 2 (2026): Artikel Penelitian
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/jmp.v15i2.16052

Abstract

The rapid growth of e-commerce platforms has led to an explosion in the number of available products, creating a problem of information overload for users. This situation makes it difficult for users to find products that match their personal preferences, thus reducing satisfaction and potential sales conversions. This research aims to develop an Artificial Intelligence (AI)-based recommendation system by implementing the Collaborative Filtering (CF) method to increase personalization. The research approach uses a quantitative descriptive method with a Waterfall-based Software Development Life Cycle (SDLC) system development model. The processed data consists of a user-product interaction matrix (ratings, purchase history) simulated from an e-commerce scenario. A user-based CF algorithm is implemented using cosine similarity calculations and weighted rating predictions. The implementation results show that the system is capable of generating relevant recommendations. In a simulation with a rating matrix (4 users, 6 products), the predicted rating for unrated items reached a value of up to 4.64, with the best recommendation being a product with high preference similarity among users. A simple evaluation yielded a Mean Absolute Error (MAE) of 1.0 on holdout data, demonstrating competitive accuracy compared to similar studies. This system has been shown to enhance the personalization of e-commerce services, potentially improving user experience and transaction volume.
Perbandingan Metode Decision Tree dan Naïve Bayes Pada Klasifikasi Tingkat Kepuasan ASN Pemerintah Kabupaten Bangka Selatan Terhadap Penggunaan Aplikasi E- Kinerja BKN Nien Dhyita Maryama; Delpiah Wahyuningsih
Jurnal Minfo Polgan Vol. 15 No. 2 (2026): Artikel Penelitian
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/jmp.v15i2.16248

Abstract

This research intends to examine the satisfaction level of State Civil Apparatus (ASN) employees in the South Bangka Regency Administrator regarding the implementation of the BKN E- Kinerja System by utilizing Machine Learning Technology classification technique, specifically the Decision Tree and Naïve Bayes algorithms. The data from the research were gathered via surveys administered to ASN personnel utilizing Google Form featuring a Likert Scale and categories of classification established by the researcher. The variables utilized in this research encompass perceived utility, system performance and perceived user-friendliness. Data processing was conducted using the Kaggle. Platform via multiple phases, encompassing data preprocessing, division of training and testing sets, classification processes and model assessment utilizing confusion matrixm accuracy, precision, recall and f1- score. The outcome of the test shows that the Naïve Bayes Algorithm performed better tha the Decision Tree Algorithm achieved an accuracy of 84.39% while the Decision Tree reached an accuracy a value of 82.44%. In the Decision Tree model, the confusion matrix showed that 149 data instances were correctly classified in class 1 and 20 data instances in class 0. Feature importance analysis revealed that the perceived usefulness variable was the most significant factor with an importance value of 0.571632, followed through system quality and perceived ease of use. From these findings, it can be inferred that the Naïve Bayes the algorithm is more efficient for categorizing user satisfaction levels in this research dataset as it generates greater precision in comparison to the Decision Tree Algorithm. This research is anticipated to function as a assessment and the evaluation of resources in enhancing the service quality of the BKN E- Kinerja System.
Co-Authors ., Anisah anggi rahma anggraini Anisah ANISAH Anisah Anisah . Anisah Anisah Aprilia, Cindy Chandra Kirana Chandra Kirana Chandra Kirana Devi Irawan Dona Marcallina Eli Patima Elly Yanuarti Elly Yanuarti Ellya Helmud Ellya Helmud Ellya Helmud ellya helmud, ellya Erzal Syahreza Eza Budi Perkasa Fajriansyah Fajriansyah Fifin Fifin Fitriyani Fitriyani . Fitriyani Fitriyani Fitriyani, Firiyani Fitriyanti Hamidah Hamidah . Harry Gentar Alam Heriadi Heriadi Irawan, Devi Jafiansyah Jafiansyah Karuniaman Buulolo Kholilah, Devi Kirana, Chandra Kiswanto Kiswanto Kiswanto Wanto Kristine Wau Laurentinus, Laurentinus Lukas Tommy Melati Suci Mayasari, Melati Suci Michael, Louis Monica, Amanda Muhammad Rivai Nien Dhyita Maryama Ode Riski Okki, Okkita Rizan Okkita Rizan Okkita Rizan Pambudi, Dita Heru Parlia Romadiana Parlia Romadiana Perkasa, Eza Budi Pratama, Hafish Mairendra Rachmatsyah, Agus Dendi Rezky Yuranda Romadiana, Parlia Romadiana, Parlia Sarwindah Sarwindah Sundari Sundari Supardi Supardi Supardi Supardi Supardi Supardi Sutanto, Daniel Septhiady Tata Sutabri Tedy Suwanda Tri Sugihartono Wirriyawan Azzaki Yan Irawan Yanuarti, Elly Yohanes Setiawan Japriadi Yuranda, Rezky Yurindra Yurindra Yuyi Andrika, Yuyi