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Tri Anggraeni
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jitu@mmtc.ac.id
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INDONESIA
Journal of Information Technology and its Utilization
Published by Sekolah Tinggi Multi Media Yogyakarta
ISSN : 29854067     EISSN : 2654802X     DOI : https://doi.org/10.56873/jitu
Core Subject : Science, Engineering,
Computer Science & IT Engineering
To explore scientific developments in the field of information technology and its utilization, including data mining, IoT, Artificial Intelligence, Digital Processing, and Information Systems.
Arjuna Subject : Ilmu Komputer (semua kategori) - Sistem Informasi
Articles 95 Documents
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Comparative Analysis of Distance Measures in Bug Report Clustering using Agglomerative Hierarchical Clustering Hartanto, Krisnawan; Suprapto, Suprapto
Journal of Information Technology and Its Utilization Vol 9 No 1 (2026): May 2026
Publisher : Sekolah Tinggi Multi Media

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56873/jitu.9.1.6065

Abstract

Grouping bug reports into clusters can assist in verifying and validating bugs in the software development cycle. One of the clustering methods is Agglomerative Hierarchical Clustering (AHC). It relies on distance calculations to determine the degree of similarity between clusters. One of the distance calculations is the Jaccard coefficient. The Jaccard Coefficient method has the disadvantage that it only considers the same set of words between two documents but does not consider their importance. Previous research added Inverse Document Frequency (IDF) algorithm to the Jaccard coefficient to calculate the importance of word groups and in this research is referred to the weighted Jaccard coefficient. Clustering is carried out using a combination of AHC and that coefficient. The silhouette score is then compared with the silhouette score of AHC with the Jaccard coefficient. Results indicate that increasing term complexity reduces cluster quality, with silhouette scores dropping from 13.13% (bigram) to 0.45% (4-gram). Furthermore, many clusters exhibited negative silhouette scores, highlighting the difficulty of separating high-dimensional bug data using unsupervised methods. In contrast, the supervised classification baseline achieved significantly higher accuracy. This paper contributes a critical analysis demonstrating that while Weighted Jaccard captures semantic nuance, unsupervised clustering remains insufficient for this domain compared to supervised approaches.
Learning Difficulty Levels Prediction of Elementary School Student Mathematics Using Machine Learning Model Rismayani Rismayani; Novita Sambo Layuk; Madyana Patasik; Andi Hutami Endang
Journal of Information Technology and Its Utilization Vol 8 No 1 (2025): June 2025
Publisher : Sekolah Tinggi Multi Media

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56873/jitu.8.1.5906

Abstract

Difficulty learning mathematics in elementary school students is a significant problem and requires serious attention. This study aims to predict the difficulty level in elementary school students learning mathematics using a machine learning model, namely KNN. Exam scores, assignments, quizzes, and characteristics of students' difficulty level in learning mathematics were used as data in this study. A study used the KNN model to divide students into three categories of difficulty in learning mathematics: easy, moderate, and challenging. The results showed that the KNN model can accurately predict student’s difficulty levels in mathematics. Thus, applying this model can help teachers provide appropriate and effective interventions to students experiencing difficulties. Using machine learning technology, especially the KNN model, we found an accuracy of 95%. In addition, we can still accurately predict the difficulty level of elementary school students' mathematics learning. This study uses anonymous student data, the distribution of assignments, quizzes, and exam score ranges, and characteristics of mathematics learning difficulty levels. There are three prediction classes: high, medium, and low.
The Role of Lapor Sleman Application in Enhancing Information Transparency of Sleman Regency Government Aidan Rizky Ramadhani Haryanto; Rahmat Rian Hidayat; Nopriadi
Journal of Information Technology and Its Utilization Vol 8 No 1 (2025): June 2025
Publisher : Sekolah Tinggi Multi Media

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56873/jitu.8.1.5966

Abstract

Law No. 14 of 2008 requires government transparency in providing public information access. The Sleman Regency Government implemented this mandate through the Lapor Sleman application, despite mixed user reviews among its 10,000+ downloaders. This research examines how this application enhances public information transparency using a qualitative approach through interviews, observations, and documentation. The study applies the Technology Acceptance Model (TAM) theory with five constructs to analyze compliance with Information Commission Regulation No. 5/2016. Results demonstrate that Lapor Sleman successfully increases information transparency by meeting both TAM indicators and transparency requirements, evolving beyond a simple application into a multi-channel reporting service. The integration into Sleman Digital platform represents an innovative response to implementation challenges. This study contributes to e-government literature by analyzing the relationship between technological acceptance and public information transparency. To maximize Lapor Sleman's potential, the research suggests periodic evaluations, improved inter-agency coordination, expanded public education initiatives, and strategic integration with the national SP4N-LAPOR! platform. These recommendations provide a roadmap for strengthening Lapor Sleman as an inclusive, responsive technology-based public service model that can be adapted by other regional governments seeking to enhance transparency through digital platforms.
The Future of Animation: Exploring the Integration of Generative AI and the Role of Animators Troy; Samuel Gandang Gunanto
Journal of Information Technology and Its Utilization Vol 8 No 1 (2025): June 2025
Publisher : Sekolah Tinggi Multi Media

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56873/jitu.8.1.6000

Abstract

Artificial Intelligence (AI) capabilities significantly change the way creative actors in the production process work. Through a study of the impact of AI on the animation industry, this article highlights the shift of AI from basic automation to more complex roles. Multi-modal generative AI, such as Large Language Models (LLMs) and diffusion models, revolutionizes the animation workflow, changes the job description of animators, and creates new challenges and opportunities. The analysis is carried out on repetitive tasks such as in-betweening, rendering, and asset creation. Through the exploration of the application of diffusion models for the creation of image and video works, as well as the application of LLMs in the development of narratives and storyboards, animators are expected to focus more on conceptual aspects and increase their creativity. AI will be involved as an innovative partner. This partnership encourages various forms of new creative expression as well as collaborative and integrated workflows. It is undeniable that this leaves notes and challenges related to the potential shift in human resources and ethics. This article provides an explanation of the adaptations that must be made so that the integration of technology and humans can maximize human creativity, not to replace it.
Evaluating Bank DJX's Cybersecurity Maturity Level from Indonesia's Regulatory Perspective Rahmat Rian Hidayat; Juniana Husna; Son Ali Akbar
Journal of Information Technology and Its Utilization Vol 8 No 1 (2025): June 2025
Publisher : Sekolah Tinggi Multi Media

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56873/jitu.8.1.6019

Abstract

In the digitalization era of banking, cybersecurity has become a critical priority as the frequency and sophistication of cyber-attacks rise. This study evaluates Bank DJX's cybersecurity maturity (a pseudonym), focusing on compliance with POJK PTI and SEOJK regulations on cyber resilience in commercial banks. Using a qualitative approach, it assesses inherent cybersecurity risks and the effectiveness of risk management. Findings show a maturity score of 2.1, indicating effective and satisfactory practices, alongside an inherent risk score of 1.9 with a narrow gap (+0.20), suggesting that while current controls address existing threats, the capacity to manage emerging risks remains limited without further enhancements. Given the rapidly evolving threat landscape, continuous improvement is essential. Aligned with recommendations, Bank DJX is well-positioned to strengthen its cybersecurity resilience to meet regulatory demands and proactively address future threats. This study offers empirical insights into cybersecurity practices in Indonesia's digital banking sector, underscoring the importance of regulatory compliance and proactive risk management.
Evaluation of User Experience (UX) in the MIUI 14 Interface Using User Experience Questionnaire (UEQ) Method in Indonesia Diana Khuntari; Aradhea Rizky Danusessia; Arum Marwati
Journal of Information Technology and Its Utilization Vol 8 No 1 (2025): June 2025
Publisher : Sekolah Tinggi Multi Media

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56873/jitu.8.1.6020

Abstract

The advancement of the modern era has provided various boosts and innovations for smartphone development companies worldwide. This development has led smartphone manufacturers to compete in creating their own Android-based user interfaces. MIUI, a widely recognized interface due to its popularity, still has several shortcomings in delivering a good user experience, such as overheating issues, UI lag, battery drain, bloatware, promotional ads, GPS issues, OS & security updates, and conflicts between Xiaomi China and Google. This study aims to assess user experience in terms of attractiveness, perspicuity, efficiency, dependability, stimulation, and novelty as offered by the MIUI 14 interface. A descriptive quantitative approach is used in this study, employing a questionnaire as the data collection method. The questionnaire, consisting of a series of written questions, was distributed to respondents for their answers. This method is particularly effective when the number of respondents is large and geographically spread out. The questionnaire is designed to assess user experience with MIUI 14 according to the indicators in the User Experience Questionnaire (UEQ) method. Data analysis was carried out using specialized software for user experience measurement, specifically the UEQ tool. The results show that the UEQ dimensions of attractiveness, perspicuity, and dependability received positive impressions, while efficiency received a negative impression. Stimulation and novelty received neutral evaluations. MIUI 14 scored Above Average in attractiveness, Below Average in perspicuity and dependability, and Poor in efficiency, stimulation, and novelty. Suggested improvements include addressing advertising notifications, rearranging the settings layout, enhancing animation responsiveness, removing bloatware, updating security patches, and implementing the Material You design concept.
Gamification-Driven Management Information System: A Design Approach for Enhancing Students’ Final Project Supervision Troy; Ginanjar Setyo Nugroho; Kathryn Widiyanti; Samuel Gandang Gunanto
Journal of Information Technology and Its Utilization Vol 8 No 2 (2025): December 2025
Publisher : Sekolah Tinggi Multi Media

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56873/jitu.8.2.6038

Abstract

This study aims to design a gamification-based Management Information System (MIS) interface to enhance the effectiveness and engagement of students during final project supervision. The research background is based on literature findings regarding the potential of gamification in education that can encourage motivation, participation, and transparency in the learning process. The research method used is Research through Design (RtD), emphasizing the integration of gamification elements into the MIS framework, including features for recording progress, awarding points, levels, and badges related to guidance activities. The research results is a student final project MIS interface that combines managerial functions with gamification-based motivational mechanisms. This system is expected to increase student engagement, provide more transparent monitoring for supervisors, and create a more attractive and interactive guidance ecosystem. The direction of further research is directed at the development of a complete MIS prototype, limited trials, and evaluation of effectiveness through case studies.
Implementation of Web-Based Real-Time Laundry Status Tracking System Nugraha Muhammad; Muhammad Najwan Naufal Alfarid
Journal of Information Technology and Its Utilization Vol 8 No 2 (2025): December 2025
Publisher : Sekolah Tinggi Multi Media

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56873/jitu.8.2.6039

Abstract

The lifestyle of Indonesian society, particularly Generation Z, is characterized by a preference for practicality and a strong reliance on technology. This lifestyle pattern often reduces Generation Z’s interest in household chores, such as washing and organizing clothes. Laundry services have therefore become a popular solution, especially in urban areas. However, customers often face difficulties in monitoring the progress of their laundry in real time, leaving them uncertain whether their laundry is completed or still in process. To address this issue, this study aims to design and implement a web-based laundry status tracking system that provides customers with real-time information on their laundry progress. The system was developed using modern web technologies, employing the Laravel framework for the backend and Bootstrap for the frontend. The system also integrates additional features such as delivery and pickup options, payment methods, and progress tracking. Moreover, it provides a user-friendly interface for administrators to manage laundry data and for customers to monitor their orders. Testing results indicate that the system successfully provides accurate and real-time information, enhances transparency, and increases customer satisfaction. This system is expected to support laundry businesses in improving operational efficiency and service quality.
Stacking Ensemble Machine Learning for Predicting Scholarship Selection Success: A Case Study of the Kominfo Scholarship Program Bayu Yudo Numboro; Yuli Karyanti
Journal of Information Technology and Its Utilization Vol 8 No 2 (2025): December 2025
Publisher : Sekolah Tinggi Multi Media

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56873/jitu.8.2.6043

Abstract

Ensemble learning methods, which combine multiple models, have shown superior performance in various prediction tasks by leveraging the strengths of different algorithms. This study presents an application of a stacking ensemble machine learning method to predict the success of applicants in the Kominfo Scholarship program. By utilizing historical administrative data of scholarship applicants, we build a predictive model to identify candidates with a high potential to be selected and successfully complete the sponsored graduate studies. The proposed approach combines multiple base learners in an ensemble, addressing class imbalance with SMOTE oversampling and optimizing model parameters via grid search. The best-performing stacked model (combining Random Forest and XGBoost with a logistic regression meta-learner) achieved an Area Under the ROC Curve (AUC) of 0.93, outperforming individual classifiers. This paper details the data preparation, model building, and evaluation process, and discusses the implications for fair and efficient scholarship selection. The findings demonstrate that the stacking ensemble approach can enhance accuracy and objectivity in candidate selection, ensuring that deserving applicants are identified more reliably compared to conventional methods.
Earthquake Prediction in Indonesia using Descriptive Statistics, Pearson Correlation, and Ensemble Machine Learning (Random Forest, XGBoost, LightGBM) Nunu Ariatmi; Alwin Sande; Komang Nopa Sudarma; Rismayani Rismayani
Journal of Information Technology and Its Utilization Vol 9 No 1 (2026): May 2026
Publisher : Sekolah Tinggi Multi Media

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56873/jitu.9.1.6060

Abstract

Indonesia is a seismically active region because it is crossed by the meeting point of three tectonic plates: the Indo-Australian Plate, the Eurasian Plate, and the Pacific Plate, commonly referred to as the Pacific Ring of Fire. This research seeks to forecast earthquake occurrences in Indonesia by integrating descriptive statistics, Pearson correlation analysis, and ensemble-based machine learning techniques including Random Forest, XGBoost, and LightGBM. The dataset is sourced from the BMKG and covers the period from September 1 to December 20, 2024. The methods used include descriptive statistics, which can help identify trends and patterns in earthquake data such as frequency, average magnitude, and geographical distribution; Pearson correlation to show the relationship between earthquake variables such as magnitude, depth, and location; and ensemble machine learning to help predict the likelihood of earthquakes based on historical data patterns. The use of descriptive statistics, Pearson correlation, and ensemble machine learning in earthquake prediction is an important step toward enhancing understanding of earthquakes and aiding in disaster risk mitigation efforts

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