Article Per Year (5 Year)
p-Index From 2021 - 2026
2.813
P-Index
This Author published in this journals
All Journal Dinamik Bulletin of Electrical Engineering and Informatics JOIV : International Journal on Informatics Visualization JURNAL MEDIA INFORMATIKA BUDIDARMA JOURNAL OF APPLIED INFORMATICS AND COMPUTING Jurnal Teknoinfo Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika Building of Informatics, Technology and Science Jurnal Teknik Informatika (JUTIF) KLIK: Kajian Ilmiah Informatika dan Komputer J-Intech (Journal of Information and Technology) Jurnal Telematics and Information Technology (TELEFORTECH) Jurnal Media Borneo Journal of Information Technology, Software Engineering and Computer Science
Megawaty, Dyah Ayu
Unknown Affiliation
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering Library & Information Science

Published : 19 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search
Journal : Dinamik

 1 
Analisis Kepuasan Siswa terhadap Layanan Teknologi Informasi di SMK Swadhipa 1 Natar menggunakan Metode CSI Dan IPA Dani, Rama; Megawaty, Dyah Ayu
Dinamik Vol 31 No 1 (2026)
Publisher : Universitas Stikubank

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35315/dinamik.v31i1.10327

Abstract

As a vocational education institution, SMK Swadhipa 1 Natar is required to provide adequate facilities to support the development of its students' technical and practical skills. Although some facilities are already available, student complaints remain regarding the condition, availability, and utilization of these services, particularly those related to information technology.This study aims to analyze the level of student satisfaction with information technology services at SMK Swadhipa 1 Natar using a combination of Customer Satisfaction Index (CSI) and Importance Performance Analysis (IPA) methods. The study was conducted through a quantitative approach by distributing questionnaires to 100 respondents selected using stratified random sampling techniques. The data collected were analyzed to determine the overall satisfaction score and identify factors of information technology services that were a priority for improvement. The results of the CSI analysis showed that the level of student satisfaction with school information technology services was in the good category, with an average score of 82%. Furthermore, the results of the IPA analysis revealed that information technology services such as computer services in the school lab, wifi networks, and school websites consisting of school exam applications, student registration applications and information about the school on the website were in the top priority quadrant because they had a high level of importance but their performance was still low. Based on these results, it can be concluded that although in general students stated that they were quite satisfied with the information technology services available, there were several important aspects, especially technology-based information technology services, that needed more attention from the school. Thus, recommendations for improving technological infrastructure and periodic evaluation of educational information technology services can help SMK Swadhipa 1 Natar in improving the quality of educational services and student satisfaction.
Penerapan Algoritma Naïve Bayes untuk Prediksi Minat Siswa Melanjutkan Studi ke Perguruan Tinggi Al-Kasidmi, Afif; Megawaty, Dyah Ayu
Dinamik Vol 31 No 1 (2026)
Publisher : Universitas Stikubank

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35315/dinamik.v31i1.10416

Abstract

This study aims to analyze the factors that influence students' interest in continuing their education to college using a machine learning approach. Data was collected through an online questionnaire completed by 727 students between July 27 and August 22, 2025, covering 23 variables consisting of respondent identity (gender, grade level, major) as well as internal and external factors such as parental support, learning motivation, and preferred type of college. The data preparation stage was carried out through column cleaning, deletion of empty data, encoding of categorical variables, and division of the dataset into 80% training data and 20% test data. The Naive Bayes algorithm of the CategoricalNB type was used because it was suitable for the categorical nature of the data. The evaluation results showed that the model was able to predict student interest with 96% accuracy. For the class of students interested in continuing their studies, the precision, recall, and F1-score values were above 0.95, while the performance in the class of students who were not interested was slightly lower due to the smaller amount of data. These findings show that Naive Bayes is proven to be effective and reliable in classifying students' interest in continuing their studies and can be the basis for decision-making in designing more targeted educational strategies.
Co-Authors - Damayanti Aditia Yudhistira Agustina, Intan Ahmad Ari Aldino Akmal Junaidi Al-Kasidmi, Afif Andi Nurkholis Apriyani, Risa Fitria Ari Sulistiyawati Chandra, Iryanto Damayanti Damayanti dani, Rama Dedi Darwis Erwanto Gibtha Fitri Laxmi Heni Sulistiani Irsan, Aqilla Hattami Kurniawan, M. Fadli Lumbanraja, Favorisen R Palupiningsih, Pritasari Parjito, Parjito Permata, Permata Riska Aryanti Ryan Randy Suryono Saputra, Williyandi Setiawan, Dandi Setiawansyah Setiawansyah Sitna Hajar Hadad Sumanto, Sumanto Susanto, Gregorius Nugroho Sutyarso, - Ulum, Faruk Wahyuda, Hana Wang, Junhai Waqas Arshad, Muhammad Wardana, Suwarman Adi Widiyanti, Adella Wirahudha, Muhammad Arif Yadin, Yuli Yuri Rahmanto