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All Journal International Journal of Electrical and Computer Engineering IAES International Journal of Artificial Intelligence (IJ-AI) International Journal of Advances in Applied Sciences Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Jurnal Ilmiah Informatika Komputer Jurnal Psikologi Jurnal Ilmiah Teknologi dan Rekayasa Prosiding KOMMIT Prosiding PESAT Majalah Ilmiah Matematika Komputer Majalah Ilmiah Ekonomi Komputer TELKOMNIKA (Telecommunication Computing Electronics and Control) JUTI: Jurnal Ilmiah Teknologi Informasi Jurnal Teknologi Informasi dan Ilmu Komputer JUITA : Jurnal Informatika Jurnal Ilmiah KOMPUTASI Sistemasi: Jurnal Sistem Informasi Computatio : Journal of Computer Science and Information Systems Jurnal Ilmiah FIFO Informatika Pertanian JURNAL MANAJEMEN INFORMATIKA (JUMIKA) Prosiding Seminar Nasional Darmajaya Petir JUTEKIN (Jurnal Manajemen Informatika) JURTEKSI Journal of Information System, Applied, Management, Accounting and Research Jurnal Teknik Informatika (JUTIF) International Journal of Management Science and Information Technology (IJMSIT) Jurnal Nasional Teknologi Komputer Formosa Journal of Computer and Information Science Jurnal Sistem Informasi International Journal Multidisciplinary Science
Dewi Agushinta R.
Gunadarma University
Religion Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Library & Information Science Materials Science & Nanotechnology Mathematics Physics Social Sciences

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Analysis of PT PLN (Persero)'s New Installation Waiting List Using the K-Means Clustering Algorithm Ernawati Ernawati; Dewi Agushinta R
Formosa Journal of Computer and Information Science Vol. 5 No. 1 (2026): March 2026
Publisher : PT FORMOSA CENDEKIA GLOBAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55927/fjcis.v5i1.16429

Abstract

This study examines the application of the K-means clustering algorithm to analyze new installation waiting list data obtained from the last three months of 2024. Only entries categorized under new installation requests were selected as the primary dataset. The analysis began by determining the optimal number of clusters: a high volume of new installation waiting lists (C1), a medium volume (C2), and a low volume (C3). Data mining processes were carried out using the RapidMiner tool, producing the following results: 6 UIDs/UIWs were classified into the high cluster (C1), 7 into the medium cluster (C2), and 9 into the low cluster (C3). The clustering performance was subsequently validated using the Davies–Bouldin Index, yielding a final score of 0.486, consistent with the RapidMiner output.
Performance Analysis of the SimInvest Application Programming Interface Using Load Testing Cut Dahri Fajrina El Qahar; Dewi Agushinta Rahayu; Lana Sularto
International Journal of Management Science and Information Technology Vol. 6 No. 1 (2026): January - June 2026
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA), Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijmsit.v6i1.7215

Abstract

This study evaluates the performance capacity of the SimInvest application programming interface (API), with emphasis on stock transaction and portfolio services that are frequently accessed during peak market activity. The study used an applied performance-testing design through Apache JMeter by simulating concurrent user loads of 100, 500, 1,000, 2,000, and 4,000 users. The observed indicators were response time, transactions per second, and error rate. The findings show that the application remained usable under 100 and 500 concurrent users, with low aggregate error rates of 4.80% and 4.48%, although several history-related endpoints already showed failed requests. When the load reached 1,000 users, the total error rate increased to 53.17%, indicating a clear decline in service reliability. Under 2,000 and 4,000 users, the system recorded error rates of 49.04% and 65.32%, with repeated failures in Account Cash, Cash Withdrawal, Order List, Portfolio, RDN History, RDN Info, and Trade List services. These findings indicate that the present infrastructure requires API optimization, query tuning, server-capacity improvement, load balancing, and real-time monitoring to maintain reliable fintech services during traffic spikes.
Comparative Analysis Of Machine Learning Algorithms For Dengue Fever Prediction Based On Clinical And Laboratory Features Sriyanto, Sriyanto; Aziz, RZ Abdul; Rahayu, Dewi Agushinta; Zuriati, Zuriati; Abdollah, Mohd Faizal; Irianto, Irianto
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 6 (2025): JUTIF Volume 6, Number 6, Desember 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.6.5309

Abstract

Dengue fever (DF) remains a global health problem requiring accurate early detection to prevent severe complications. This study applies machine learning (ML) algorithms to clinical and laboratory data for improving diagnostic accuracy. Six classifiers were compared: Decision Tree (DT), K-Nearest Neighbor (KNN), Logistic Regression (LR), Naïve Bayes (NB), Neural Network (NN), and Support Vector Machine (SVM). The dataset consists of 1,003 patient records with nine feature columns, of which 989 were used after preprocessing. Class distribution was imbalanced, with 67.6% positive and 32.4% negative cases. Model performance was evaluated using 10-fold cross-validation based on accuracy, precision, recall, F1-score, confusion matrix, and ROC curve analysis. The results indicate that DT achieved the highest performance with 99.4% accuracy, 99.4% precision, 99.7% recall, and 99.6% F1-score, slightly outperforming NN. KNN, LR, and SVM produced comparable results, while NB showed substantially lower accuracy (44.3%) and limited discriminatory power. ROC analysis confirmed these findings, with DT, NN, SVM, and LR achieving AUC values between 0.992 and 0.999, whereas NB performed poorly. These findings highlight the strong potential of ML algorithms, particularly DT, to support medical decision systems, strengthen informatics-based decision support applications, and enhance the accuracy and speed of dengue diagnosis in clinical practice.
Bridging gaps in health artificial intelligence: challenges in MDPI research articles Irwan Bastian; Aqilla Rahman Musyaffa; Lukman Nulhakim; Novia Putri Bahirah; Dewi Agushinta R.
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 15, No 4: August 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v15.i4.pp3053-3067

Abstract

Technological advancements in artificial intelligence (AI) have transformed healthcare by improving early disease detection, personalized treatment, predictive analytics, and clinical decision support systems. However, AI adoption in healthcare faces critical challenges, including data privacy concerns, algorithmic bias, regulatory barriers, usability issues, and system interoperability. Addressing these issues requires standardized regulations, ethical frameworks, and interdisciplinary collaboration to ensure responsible AI integration. This study systematically analyzes research trends in health AI over the past six years through a systematic literature review (SLR) and a bibliometric analysis using VOSviewer. The review focuses on Multidisciplinary Digital Publishing Institute (MDPI) journal articles to identify key contributors, emerging trends, and research gaps in AI-driven healthcare. Findings highlight dominant research areas, including machine learning for diagnosis, AI-driven hospital management, and predictive analytics, while exposing persistent challenges such as a lack of standardized AI models, ethical concerns, and accessibility disparities. By mapping the research landscape, this study provides evidence-based insights and recommendations to address AI adoption barriers, improve transparency, and guide future research in healthcare AI. The results contribute to developing a more equitable, efficient, and trustworthy AI-driven healthcare system.
Co-Authors -, Hustinawaty Abdollah, Mohd Faizal Achmad Benny Mutiara Adam Huda Nugraha Aditia Arga Pratama Ahmad Hidayat Akbar, Rizky Alif Ahmad Syamsudduha Andi Shahreza Harahap Anggari, Elevanita Anindito Yoga Pratama Anindito Yoga Pratama Anindito Yoga Pratama Anindito Yoga Pratama Antonius Angga Kurniawan Aqilla Rahman Musyaffa Ardhani Reswari Yudistari Armita Widyasuri Aziz, RZ. Abdul Besty Ghina Cut Dahri Fajrina El Qahar Cyntya Widyarsih Delvita Dita Putri Anggrayni Diana Ikasari Diana Tri Susetianigtias Dini Sundani Dyah Pratiwi Emirul Bahar Ernawati Ernawati Ety Sutanty Fajar Nugraha Ferina Ferdianti Fitrianingsih Fitrianingsih Gagah Lanang Ramadhan Grace Desi Geoloni Hafiz Ma'ruf Hanifah Aprilia Nur’aini Haniyah Haniyah Hardianti, Ayu Harya Iswara A.W. Henny Medyawati Henny Medyawati Henri Muel Herry Sussanto Hustinawaty Hustinawaty, Hustinawaty Ihsan Jatnika Ika Setiowati Suprihatin Indira Mahayani Irianto Irianto Irwan Bastian Jhordy Wong Johanna Sindya Widjaya Jonathan Hindharta Khoirul Islam Lana Sularto Lia Ambarwati Lintang Yuniar Banowosari Lintang Yuniar Banowosari Lukman Nulhakim M. Abdul Mukhyi Mariono Reksoprodjo Martina Octavia Mega Maralisa Putri Metty Mustikasari Muhammad Edy Supriyadi Murniyati Murniyati Neneng Winarsih Ngakasah, Siti Aliyah Notonegoro, Radityo Hendratmojo Jati Novia Putri Bahirah Nursanta, Edy Octavia, Martina Paranita Asnur Paujiah, Syifah Putri, Rizka Yulianti Regy Dwi Septian Remi Senjaya Remi Senjaya riamande jelita tambunan Rifki Kosasih Rindani, Fiena Rizka Yulianti Putri Rodiah Rodiah Rr. Dharma Tintri Edi Raras Rustam M. Ali Sandi Agung Sarifuddin Madenda Satria, Agung Sigit Widiarto Soeltan Zaki Sova, Erma Sri Rahayu Puspita Sari Sriyanto Sriyanto sugrio dwi darmawan Suryadi H. S. Suryadi Harmanto Trihapningsari, Denisha Vega Valentine Yahya Novi Andi Cuhwanto Yoga Yuniadi Yogi Oktopianto Yurista Vipriyanti Yusuf Triyuswoyo Yuti Dewita Arimbi Zuriati, Zuriati