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Journal of Information Technology
Published by Universitas Bhinneka Nusantara
ISSN : 23031425     EISSN : 2580720X     DOI : https://doi.org/10.32664/j-intech
Core Subject : Science,
Computer Science & IT
Journal of Information and Technology is a journal published by Bhinneka Nusantara University, Malang. The scope of this journal includes IT Governance, IS Strategic Planning, IS Theory and Practices, Management Information System, IT Project Management, Distance Learning, E-Government, Information Security and IT Risk Management, E-Business / E-Commerce, Big Data Research, and other related topics.
Arjuna Subject : Ilmu Komputer (semua kategori) - Sistem Informasi
Articles 307 Documents
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Penerapan Metode A-Star untuk Rute Evakuasi dengan Menggunakan Jaringan Long Range Wide Area Network (LoRaWAN) Charles Daniel; Moh Ali Romli
J-INTECH ( Journal of Information and Technology) Vol 13 No 01 (2025): J-Intech : Journal of Information and Technology
Publisher : LPPM STIKI MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/j-intech.v13i01.1923

Abstract

Optimal evacuation route planning is a crucial factor in disaster mitigation, especially in areas with limited communication infrastructure. This study proposes the application of the A-Star method for evacuation route optimization, supported by the Long-Range Wide Area Network (LoRaWAN) as an emergency communication system. The research methodology includes the development of an A-Star algorithm optimized with an adaptive heuristic function, integration with LoRaWAN-based sensors for real-time road condition monitoring, and simulations in various disaster scenarios. The results show that the developed system can reduce evacuation time by up to 31.4% compared to conventional methods and maintain communication connectivity up to 95% even under emergency conditions. Furthermore, the dynamic adaptation mechanism allows for automatic route changes based on current field conditions, enhancing the effectiveness of the evacuation process. Therefore, the integration of the A-Star method and LoRaWAN network proves to be a reliable and efficient solution for improving public safety during disasters.
Aplikasi Honeypot dalam Keamanan Jaringan untuk Mendeteksi Serangan Siber pada Infrastruktur TI Carlos Susanto; Moh Ali Romli
J-INTECH ( Journal of Information and Technology) Vol 13 No 01 (2025): J-Intech : Journal of Information and Technology
Publisher : LPPM STIKI MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/j-intech.v13i01.1924

Abstract

The high security risks that are susceptible to hacking and exploitation by malicious actors to steal data or information often arise due to a lack of awareness regarding the critical importance of implementing deceptive network security using honeypots. Negligence can create vulnerabilities that are easily exploited, allowing attackers to initiate breaches. A notable network security approach involves using Honeypots, a method that creates a decoy server to mimic an authentic one. Honeypots are deliberately engineered to attract the attention of cyber attackers and facilitate their access to the trap server, thereby enabling the monitoring and analysis of their activities without compromising the integrity of the primary server. To achieve optimal network security, comprehensive testing of Honeypots is essential. This testing process serves as a fundamental metric in evaluating the efficacy and performance of Honeypot systems in mitigating cyber threats.
K-Means Clustering Algorithm Measuring the Satisfaction Level of MNC TV Muslim I'murojaah Program Viewers Herayati Herayati; Andronias Siregar; Hariyanto Hariyanto
J-INTECH ( Journal of Information and Technology) Vol 13 No 01 (2025): J-Intech : Journal of Information and Technology
Publisher : LPPM STIKI MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/j-intech.v13i01.1926

Abstract

Television remains one of the most influential mass media platforms for disseminating information and entertainment to the public, with one notable example being the I’Murojaah program aired by Muslim TV on MNC Channels. The objectives of this study are to identify the level of viewer satisfaction with the I’Murojaah program, determine the indicators influencing viewer satisfaction, classify viewers based on their satisfaction levels, and provide recommendations to program managers to improve quality and viewer satisfaction. This study employs a qualitative approach using the K-Means Clustering algorithm. The data used in this study were obtained through a survey distributed to 100 respondents, covering several viewer satisfaction indicators such as content quality (6 questions) and program presentation (6 questions). The collected data were then grouped and analyzed. The results of the first cluster iteration distance calculation consisted of 84 viewers who were very satisfied, while the second cluster consisted of 16 viewers with relatively low satisfaction levels. The Davies Bouldin Index values were -0.674 for class 2 clustering, -2.001 for class 3 clustering, -1.961 for class 4 clustering, and clustering class 5 (-2.000). In conclusion, the best clustering performance results were for classes 2, 3, 4, and 5. The smallest Davies Bouldin Index value was for clustering class 2. Recommendations for program improvement include enhancing image and sound quality, ensuring that the equipment and technology used can produce optimal quality.
Preventive Attendance Record using Photo from Mobile Phone and Printed Paper using CNN Bradika Almandin Wisesa; Vivin Mahat Putri; Evvin Faristasari; Sirlus Andreanto Jasman Duli; Silvia Agustin
J-INTECH ( Journal of Information and Technology) Vol 13 No 01 (2025): J-Intech : Journal of Information and Technology
Publisher : LPPM STIKI MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/j-intech.v13i01.1927

Abstract

Face-based attendance systems are increasingly popular for their ease of use, but they are susceptible to fraud, such as using photos or videos for unauthorized attendance. This study introduces a digital attendance system that combines facial recognition with liveness detection powered by Convolutional Neural Networks (CNN). Liveness verification is achieved by analyzing subtle movements and responses to ambient lighting. The dataset includes 30 facial images, encompassing both authentic and fraudulent samples. Testing demonstrates a facial recognition accuracy of 91.3% and effective spoofing detection in static and dynamic settings. This system provides a secure, fraud-resistant attendance solution ideal for educational and corporate settings. Further enhancements are suggested to improve performance across diverse facial expressions and lighting conditions.
Decision Support System for Determining Social Assistance Recipients in Petuaran Hilir Village Using the SMART Method Debi Yandra Niska; Azura Calista Sitorus; Syafira Istiara; Rahma Hidayanti
J-INTECH ( Journal of Information and Technology) Vol 13 No 01 (2025): J-Intech : Journal of Information and Technology
Publisher : LPPM STIKI MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/j-intech.v13i01.1945

Abstract

The distribution of social assistance in rural areas is a strategic government effort to reduce social inequality and improve the welfare of underprivileged communities. However, in Petuaran Hilir Village, the process of determining aid recipients is still conducted manually, leading to various issues such as a lack of objectivity, potential unfairness, and mistargeting. Therefore, this study aims to design and implement a Decision Support System (DSS) using the Simple Multi-Attribute Rating Technique (SMART) method to determine social assistance recipients in a more systematic and transparent manner. The SMART method was chosen due to its effectiveness in simplifying multi-criteria decision-making and its practicality for implementation at the village level. The system was developed as a web-based application and tested using the black-box method, as well as validated against the manual selection results conducted by village officials. Testing results showed that the system can objectively identify and rank aid recipients based on final scores from five main criteria: income, number of dependents, home ownership status, housing condition, and type of employment. The system achieved 100% consistency with manual selection results and reduced the selection process time by up to 70%, enabling a fairer and more targeted distribution of aid based on systematically calculated scores. By eliminating manual bias in the selection process, the system significantly improves the accuracy of recipient rankings. This study also opens opportunities for further development, such as integrating real-time population data and advanced analytical features to support more responsive social policies.
Pengembangan Game Multiplayer Horror 'Angker' Berbasis Mobile Menggunakan Metode Agile Apik Banyubasa; Cindy Valencia; Hassan Narallah Matauq; R Bramaditya Ario Wirawisesa; Aditya Wicaksono; Muhammad Nasir
J-INTECH ( Journal of Information and Technology) Vol 13 No 02 (2025): J-Intech : Journal of Information and Technology
Publisher : LPPM STIKI MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/j-intech.v13i02.1970

Abstract

This study develops a mobile-based multiplayer horror game titled "Angker" using the Agile method, specifically Agile Scrum, in response to the rapid growth of the mobile game industry and increasing interest in the multiplayer horror genre. The Agile method was chosen for its flexibility in managing complex game development, allowing quick adaptation to changes and strong team collaboration. The development process was divided into eight sprints, covering planning (team role assignment, project scheduling), design (UML diagrams, UI design using Figma), feature development (character movement, multiplayer system, chat, item system, visual/audio assets, in-game store, skin transactions), internal and external testing, and final deployment. A total of 15 core features were successfully developed and implemented, including 8 technical modules such as a multiplayer lobby system, coin transaction system, interactive item system, and win condition detection system. Testing results demonstrated improvements in time efficiency, team coordination, and final product quality. The novelty of this study lies in the comprehensive integration of the Agile method in multiplayer horror game development using the Godot engine—an approach still rarely implemented, especially by small teams with limited resources.
Determinants of Data Quality in HIV/AIDS Information System (SIHA) Performance Using Task-Technology Fit and IPMA: The Case of West Papua Cheryl Nadilla Widyawati; Dedi I Inan; Ratna Juita; Muhamad Indra
J-INTECH ( Journal of Information and Technology) Vol 13 No 02 (2025): J-Intech : Journal of Information and Technology
Publisher : LPPM STIKI MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/j-intech.v13i02.1991

Abstract

This study analyzes how data quality and task-technology fit affect the effectiveness of SIHA in West Papua using IPMA and PLS-SEM. The TTF model includes Task Characteristics, Technology Characteristics, Individual Characteristics, Task-Technology Fit, and Performance Impact. This study used the Partial Least Squares Structural Equation Modeling (PLS-SEM) method with a sample size of 103 health units such as the Health Office, hospitals, health centers, and clinics in West Papua. The results showed that data quality has a significant effect on Task-Technology Fit (t = 4.008; p < 0.001) and Performance Impact (p = 0.013). Furthermore, Task-Technology Fit also has a significant effect on Performance Impact. In contrast, Task Characteristics, Technology Characteristics, and Individual Characteristics do not have a significant effect on performance. These findings confirm data quality in optimizing SIHA. The results of this study can serve as a reference in formulating policies and strategies to improve the effectiveness of health information systems in areas with limited infrastructure.
Quality Analysis of an Interactive Programming Learning Platform Based on ISO/IEC 25010 Using a String-Matching Approach on User Reviews Mochamad Chandra Saputra; Satrio Agung Wicaksono; Satrio Hadi Wijoyo; Prasetya Naufal Rahmandita; Buce Trias Hanggara
J-INTECH ( Journal of Information and Technology) Vol 13 No 01 (2025): J-Intech : Journal of Information and Technology
Publisher : LPPM STIKI MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/j-intech.v13i01.2003

Abstract

This study aims to analyze user perceptions of Quality in Use of the Khan Academy e-learning platform, focusing on two key characteristics defined in the ISO/IEC 25010 standard: satisfaction and efficiency. Based on the analysis of user review data, there is a clear difference in volume between the two aspects: 539 reviews (65%) reflected the satisfaction aspect, while only 290 reviews (35%) were related to efficiency. This indicates that users are approximately 1.86 times more likely to comment on satisfaction than on efficiency. For satisfaction, most of reviews were positive (420 reviews, or 77.9%), while 119 reviews (22.1%) expressed negative sentiments. These results suggest that most users are satisfied with their experience using Khan Academy, particularly due to factors such as flexible access time, user convenience, and the wide availability of learning materials. In contrast, the efficiency- related reviews exhibited a more even distribution, with 154 positive reviews (53.1%) and 136 negative reviews (46.9%). This closer balance indicates that while some users appreciate the platform's performance, others report encountering technical issues, including slow access speeds, navigation difficulties, and system instability. Overall, user perception of the Khan Academy e-learning system is generally positive, especially regarding satisfaction. However, the findings also underscore the importance of addressing technical performance challenges to improve efficiency and ensure a seamless learning experience. These insights provide a valuable basis for the development of user-centered e-learning systems and contribute to the evaluation of system quality from the Quality in Use perspective.
Developing Kindergarten Management System for Supporting the Regional Educational Report Anita Anita; Sutan Arif Pambudi; Nira Radita; Hilman Nuril Hadi
J-INTECH ( Journal of Information and Technology) Vol 13 No 01 (2025): J-Intech : Journal of Information and Technology
Publisher : LPPM STIKI MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/j-intech.v13i01.2004

Abstract

Administrative tasks in early childhood education centers often face challenges when conducted manually, leading to delays in reporting, data inconsistencies, and limited access for parents. Unlike conventional school management systems, this study specifically targets kindergarten-level reporting that aligns with regional government formats (Korwilkersatdik) in Indonesia. To address these issues, this study focuses on designing and developing a web-based information system to help manage administrative and reporting activities at TK Dharma Wanita 91 Pesanggaran, a kindergarten in Banyuwangi, Indonesia. The research applied a descriptive qualitative method and followed a structured software development process, including system analysis, design, implementation, and evaluation. The system was built using PHP with the CodeIgniter framework and MySQL as the database. It includes modules for student registration, payment validation, attendance tracking, lesson planning, and monthly report generation. Each module was tested using black-box testing and successfully met functional requirements. The implementation of the system significantly reduced manual workload, improved reporting accuracy, and facilitated better communication with parents. The results indicate that the system effectively supports the institution’s operational needs and aligns with reporting standards set by local education authorities. Future development may focus on adding mobile accessibility and analytical features to provide broader access and deeper insights for school management. This study demonstrates how a domain-specific information system can significantly improve the efficiency of kindergarten administration while meeting government reporting standards.
Implementasi NLP untuk Deteksi Teks Buatan AI (Chat-GPT) menggunakan Metode Naive Bayes Rafel Fernando; Yuliana Dewi Proboningrum; Septi Dwi Supriati; Nurmalitasari Nurmalitasari
J-INTECH ( Journal of Information and Technology) Vol 13 No 02 (2025): J-Intech : Journal of Information and Technology
Publisher : LPPM STIKI MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/j-intech.v13i02.2026

Abstract

The development of artificial intelligence (AI) technology, especially large language models like ChatGPT, presents challenges related to the authenticity and validity of digital content. AI's ability to produce human-like text opens up opportunities for misuse, such as plagiarism and information manipulation. This study aims to develop an AI text detection system using the Multinomial Naive Bayes algorithm, due to its ease of use and high effectiveness algorithm has become a popular choice for text classification.. The dataset used is the Human ChatGPT Comparison Corpus (H3C), sourced from the ELI5 subreddit on Reddit, consisting of 800 entries of questions and answers from both humans and AI. The labeling process involves combining answers into a single column and assigning labels based on the source. Preprocessing steps include case folding, removal of digits and punctuation, tokenization, stopword removal, normalization, and text finalization. Text features are extracted using the TF-IDF method, limited to the top 1000 features. The model is trained on 80% of the data and tested on the remaining 20%. The evaluation shows an accuracy of 93%. These findings suggest that the Naive Bayes method is effective in distinguishing AI-generated from human-generated text and has potential as an automatic AI content detection tool.

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