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All Journal Pro Bisnis Telematika Jurnas Nasional Teknologi dan Sistem Informasi JOIV : International Journal on Informatics Visualization Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal CoreIT JITK (Jurnal Ilmu Pengetahuan dan Komputer) Building of Informatics, Technology and Science Journal of Information Systems and Informatics Journal of Computer Science and Engineering (JCSE) Jurnal Teknik Informatika (JUTIF) Jurnal Pendidikan dan Teknologi Indonesia
Azhari Shouni Barkah
Universitas AMIKOM Purwokerto
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering

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Journal : Jurnal Teknik Informatika (JUTIF)

 1 
AN EVALUATION OF THE SUCCESSFUL IMPLEMENTATION OF THE INFORMATION SYSTEM PLATFORM MERDEKA MENGAJAR USING HUMAN ORGANIZATION TECHNOLOGY FIT MODEL APPROACH Abidin, Uun; Hariguna, Taqwa; Barkah, Azhari Shouni
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 1 (2025): JUTIF Volume 6, Number 1, February 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.1.4282

Abstract

The implementation of technology in education has great potential to improve the quality of learning that supports the implementation of the Merdeka curriculum. The Merdeka Mengajar platform (MMP) is designed to help educators by providing various features including self-development, inspiration and teaching. Uneven ICT infrastructure and teachers' personal abilities are problems in the implementation of the MMP, so it is necessary to analyze the success of the implementation of the MMP. The purpose of this study is to analyze the success of the implementation of the information system for the Merdeka Mengajar Platform by adopting the Hot Fit Model by expanding the Technology component with the ICT Infrastructure variable, expanding the Human component with the personal competence variable, expanding the organizational component with the organizational culture variable and the training & learning variable which can affect the successful implementation of the MMP. The data obtained were 328 respondents who were analyzed using SmartPLS 3.2.9. The analysis results obtained the proposed conceptual model has an accuracy of 58.6%. Net benefits are influenced by system use, user satisfaction, personal competence, structure, environment, organizational culture, and training & learning. Service quality, system quality, information quality, and ICT infrastructure have a positive impact on system use and user satisfaction.
Comparative Analysis of DBSCAN, OPTICS, and Agglomerative Clustering Methods for Identifying Disease Distribution Patterns in Banjarnegara Community Health Centers Setiyawan, Dillyana Tugas; Berlilana, Berlilana; Barkah, Azhari Shouni
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 3 (2025): JUTIF Volume 6, Number 3, Juni 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.3.4577

Abstract

The variation in disease distribution patterns across community health centers in Banjarnegara Regency necessitates a precise segmentation analysis to support effective allocation of healthcare resources. This study aims to compare the effectiveness of three clustering methods DBSCAN, OPTICS, and Agglomerative Clustering in grouping Puskesmas based on the type and number of diseases they manage. The evaluation methods used include the Silhouette Score and the Davies-Bouldin Index, which assess the quality of the clustering results. The analysis indicates that Agglomerative Clustering produces the most stable cluster structures, reflected in its highest Silhouette Score, compared to DBSCAN and OPTICS, which tend to yield more noise and less optimal clustering quality. These findings suggest that hierarchical clustering approaches are more effective in the context of healthcare service distribution data at the primary care level. The results of this study are expected to serve as a foundation for the formulation of data-driven and region-based health policies, particularly in designing more targeted interventions and optimizing the distribution of healthcare services.
Analysis of Technology Adoption Factors in Learning among Vocational Students using UTAUT2 Model Harimanto, Bambang; Berlilana, Berlilana; Barkah, Azhari Shouni
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 5 (2025): JUTIF Volume 6, Number 5, Oktober 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.5.4940

Abstract

Technology acceptance in vocational education is a key factor in supporting the effectiveness of teaching and learning processes in the digital era. This study aims to analyze the factors influencing technology acceptance among students of the Computer and Network Engineering (TKJ) Department at SMK Ma'arif 1 Kroya using the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) framework. The model includes the variables Performance Expectancy, Effort Expectancy, Social Influence, Facilitating Conditions, Hedonic Motivation, Price Value, Habit, Behavioral Intention, and Actual Usage. The results reveal that five key variables—Performance Expectancy, Effort Expectancy, Social Influence, Hedonic Motivation, and Price Value—significantly influence Behavioral Intention, while Habit, Facilitating Conditions, and Behavioral Intention directly affect Actual Usage. All constructs in the model meet validity and reliability criteria, and no multicollinearity was detected (VIF < 3.3). The coefficient of determination (R²) values of 0.612 for Behavioral Intention and 0.673 for Actual Usage indicate strong predictive power of the model. These findings confirm the relevance of the UTAUT2 framework for understanding and enhancing technology acceptance in vocational education settings and provide valuable insights for improving technology integration in technical learning environments.
Optimizing Early Network Intrusion Detection: A Comparison of LSTM and LinearSVC with SMOTE on Imbalanced Data Nugroho, Khabib Adi; Hariguna, Taqwa; Barkah, Azhari Shouni
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.2025.6.6.4672

Abstract

This study aims to improve network intrusion detection systems (IDS) by addressing class imbalance in the CICIDS 2017 dataset. It compares the effectiveness of Long Short-Term Memory (LSTM) networks and Linear Support Vector Classifier (LinearSVC) in detecting intrusions, with a focus on the impact of Synthetic Minority Over-sampling Technique (SMOTE) for balancing the dataset. The dataset was preprocessed by removing irrelevant features, handling missing values, and applying Min-Max normalization. SMOTE was applied to balance the training dataset. Results showed that LSTM outperformed LinearSVC, especially in recall and F1-score, after applying SMOTE. This research highlights the benefits of combining LSTM with SMOTE to address class imbalance in IDS and emphasizes the importance of temporal sequence models like LSTM for detecting network intrusions. Future work could involve using the full dataset, exploring advanced feature engineering, and implementing more complex architectures to further enhance performance. This research underscores the critical need for improving network security by addressing the challenges of class imbalance in intrusion detection systems, which is vital for ensuring the real-time identification and mitigation of sophisticated cyber threats in the ever-evolving landscape of network security.
Co-Authors Abidin, Uun Abidin, Zaheera Zainal Ajis Solihin, Afit Anggun Purnomo Bagaskoro, Galih Berlilana Berlilana Darmono Fandy Setyo Utomo Harimanto, Bambang Harimato, Bambang Heru Supriyanto Imam Tahyudin Kusreynada, Sabrina Uhti Latif, Imam Sofarudin Melia Dianingrum Muhtyas Yugi Nanjar, Agi Nugroho, Khabib Adi Ramadani, Nevita Cahaya Rizki Wahyudi Rujianto Eko Saputro Selamat, Siti Rahayu Setiyawan, Dillyana Tugas Sumiati, Ai Irma Taqwa Hariguna