Jurnal Teknologi Informasi dan Pendidikan

Analysis of Factors Influencing the Decision to Select Thai Nguyen University of Information Technology and Communication

Bui Ngoc Tuan — 2025-01-21

This article presents a study that aims to examine and analyze the factors that influence students' decisions in choosing the Thai Nguyen University of Information and Communication Technology. The research intends to assist universities in gaining a deeper understanding of the crucial factors that students consider when selecting a university. Consequently, this will lead to the development of more effective admission policies and strategies. The study involved collecting data from a random sample of first-year students at Thai Nguyen University of Information and Communication Technology during 2022. Data was gathered using questionnaires and both qualitative and quantitative research methods, utilizing SPSS 20 software. The findings from factor analysis indicated that a multiple regression model was suitable for assessing the factors that influence decisions to enroll in the Thai Nguyen University of Information and Communication Technology. Variables such as CSVC1 (Adequate classrooms meeting to learning needs), CSCV4 (Modern and well-equipped library with ample study materials), HP3 (Generous scholarships for various groups), VL3 (Supportive policies for employment during studies), DT2 (Curriculum aligned with social needs), DT4 (High-earning graduates), and DNGV1 (Highly qualified and standardized faculty) showed significant correlations with the dependent variable - students' career choices. The results demonstrated that the proposed model was well-fitted, with favorable levels of compatibility indices (CFI, TLI) and accuracy (GFI, RMSEA). Additionally, the outcomes of the Structural Equation Modeling (SEM) supported the appropriateness of the proposed model and its capability to explain the relationships between variables in the study. Based on these research findings, the article provides recommendations, including enhancing faculty quality, improving infrastructure and facilities, diversifying programs, and enhancing university information dissemination to elevate the quality and quantity of future admissions.

The Impact of Digital Technology and 21st Century Skills on Employee Performance

Fanny Okta Yoma — 2025-01-29

In the ever-evolving digital age, it is important to understand the impact of digital technology and 21st century skills on employee performance. In this systematic literature review, researchers explored the relationship between digital technology, 21st century skills and employee performance through synthesizing 24 relevant articles indexed by scopus, google scholar and dimension in the period 2019-2024. The review revealed a number of important insights into how digital technology adoption and 21st century skills development impact employee productivity and effectiveness across a range of organizational contexts. The researcher highlights the salient findings, challenges faced, and practical implications of this research. As such, this article makes an important contribution to our understanding of ways to improve employee performance in the changing digital age, and points the way for future research and practice in this area.

Comparison of Machine Learning for Mental Health Identification (The DASS-21 Questionnaire)

Retno Wardhani — 2025-02-25

Stress appears at almost any age. Stress can disrupt mental and physical balance, and even students can experience it. Early detection of an individual's emotions is crucial. Researchers hope that by taking such actions, an individual can maintain self-control and prevent the stress they are experiencing from worsening. Bodily characteristics such as speech, body language, eye contact, and facial expressions indicate stress, depression, and anxiety. Psychological activities and human life are associated with physiological emotions. The three categories of negative thoughts or sad emotions are stress, anxiety, and depression. This research assesses or finds students who experience anxiety, depression, and stress. This study compares methods for determining mental health through the distribution of DASS-21 scale questionnaires. The researcher classified the research results using Naive Bayes, Decision Tree, k-NN, SVM, and Logistic Regression methods. According to experiments, SVM is effective for identifying mental health anxiety, depression, and stress with accuracy, recall, and precision of 0.86, 0.90, and 0.80. At Universitas Islam Lamongan, 138 engineering faculty students answered the DASS-21 questionnaire.

Designing an E-Learning Application with Diagnostic Learning Style Testing for Enhancing Personalization in Educational Technology Courses

Denny Kurniadi — 2025-03-06

Teaching the importance of personalized learning in educational technology courses encourages students to understand how tailored educational approaches can enhance learning outcomes. Diagnostic learning style testing, including visual, auditory, kinesthetic (VAK), and technology usage dimensions, has been widely recognized as an effective method for addressing diverse student needs. The purpose of this paper is to design an e-learning application with diagnostic learning style testing to enhance personalization in educational technology courses. This system evaluates learning styles based on five dimensions and uses diagnostic results to recommend personalized learning strategies. The application is implemented as a web-based platform, providing both theoretical insights and practical application. By utilizing this system, educators and learners can gain actionable insights into individual learning preferences, ensuring better alignment between teaching methods and student needs. Additionally, the e-learning application can be accessed via mobile devices, allowing for flexible and adaptive learning experiences anytime and anywhere.

Influence of Self-Efficacy and Affiliation Motivation on Student Learning Behavior Using Google Gemini

Listi Septiana Avita Putri — 2025-03-12

Tujuan dari penelitian ini adalah untuk menganalisis pengaruh efikasi diri dan motivasi afiliasi yang dimediasi oleh perilaku belajar siswa dalam pemanfaatan teknologi kecerdasan buatan, dengan fokus khusus pada Google Gemini. Penelitian ini menggunakan metode kuantitatif dengan pendekatan survei, yang melibatkan siswa SMK Batik 2 Surakarta sebagai subjek. Skala Likert mulai dari "Sangat Tidak Setuju" hingga "Sangat Setuju" (1-4) digunakan untuk mengumpulkan data. Pemodelan Persamaan Struktural (SEM) dan Signifikansi Mediasi (Uji Sobel) digunakan untuk menguji efek tidak langsung. Efek tidak langsung ini meliputi pengaruh efikasi diri yang dimediasi oleh perilaku belajar siswa terhadap pemanfaatan Google Gemini, dan pengaruh motivasi afiliasi yang dimediasi oleh perilaku belajar siswa terhadap penggunaan Google Gemini. Temuan penelitian menunjukkan bahwa efikasi diri dan motivasi afiliasi memberikan pengaruh positif dan signifikan terhadap perilaku belajar siswa. Meskipun demikian, korelasi antara efikasi diri, motivasi berafiliasi, dan kecerdasan buatan, seperti Google Gemini, tidaklah substansial. Hal ini menunjukkan bahwa pemanfaatan teknologi tidak semata-mata bergantung pada faktor internal, seperti kepercayaan diri dan motivasi sosial.

Development of a Lecture Monitoring Information System for Management Department at the State University of Medan

Haryadi Haryadi — 2025-03-15

The development of information technology, especially websites, is necessary to increase the efficiency and accuracy of monitoring and evaluating lectures in higher education, especially during the Covid-19 pandemic. This study aims to develop a web-based lecture monitoring information system and test the feasibility level of the information system developed based on validation/assessment from a team of experts and students. This research uses a Research and Development (R&D) approach with the ADDIE model (Analysis, Design, Development, Implementation, Evaluation). System designed using Appsheet with Google Sheets database. Media Validation was carried out by a Visual Media Expert Lecturer and tested on 70 class commissioner students in the management department at State University of Medan. In general, the results of the media aspect validation as measured by two indicator aspects of interface and multimedia are classified as very feasible at 88.89%, and the results of the field trial assessment as measured by four indicator aspects of correctness, reliability, integrity, and usability are also categorized as very feasible at 89.89%.

Design of Back-End Education Management System Application Using Iterative Incremental Method

Muhammad Hanan Rafif Farizta — 2025-03-17

Education plays a central role in shaping individuals and advancing society. One critical aspect of improving educational quality is the active involvement of parents, which significantly influences students' learning experiences at school. However, the main challenge lies in effective student data management and the lack of transparency in monitoring student progress. This research uses a case study at SMPN 1 Magetan and aims to design and implement the back-end of an Education Management System (EMS) application, focusing on the student module. By employing the Iterative Incremental method, this program is designed to be responsive to user needs and changes in the school environment. Interviews with teachers, students, and parents revealed difficulties in accessing information such as attendance, permissions, disciplinary records, and student personal data. The EMS application is designed to enhance parental involvement through transparent and easily accessible features. Development was carried out in two main phases, focusing on API usage efficiency. Rigorous testing, including load testing, ensured the application's readiness, with an average response time of 449.5 ms for 50 and 100 simultaneous users. The Iterative Incremental approach proved effective in creating a responsive and adaptive educational application, supporting the development of a future generation of Indonesians competitive at the global level.

Capacity Management Strategy for Handling Traffic Load with Dijkstra Algorithm at PT XYZ

Najma Syarifa Rahmah — 2025-03-19

In the digital era marked by rapid data growth, network congestion occurs when network capacity cannot handle the transmitted data volume, becoming a significant challenge that impacts the Quality of Service (QoS). This study proposes an effective capacity management strategy, which includes alternative routing, load balancing, and capacity enhancement, involving the optimized Dijkstra Algorithm and a Decision Support System (DSS) to improve QoS. The Dijkstra Algorithm is effective in reducing the load on congested routes and ensuring balanced traffic distribution, which enhances the capacity and reliability of the network. The results indicate a reduction in packet loss from 142.353 to 66.340 packets (or 53,39%) and an increase in the number of packets successfully transmitted from 122.542 to 198.555 packets (or 61,98%). Specific node capacity increases have significantly bolstered data transmission success. This comprehensive strategy not only improves the reliability of data transmission and network performance consistency but also enables the network to adapt to growing demands without degrading performance, confirming the efficacy of capacity management in addressing capacity challenges and improving QoS.

Power System & Short Circuit Analysis in PLTGU PLN UPDK Keramasan Using ETAP

Karin Alisya — 2025-03-26

This study aims to analyse the power flow and short circuit faults in the Gas and Steam Power Plant (PLTGU) of PT PLN Keramasan using ETAP software. Power flow analysis is carried out to determine the distribution of voltage, current, and power in the PLTGU electrical system and to ensure the efficiency and stability of system operations. The results of the power flow simulation show that the PT PLN Keramasan PLTGU can generate and distribute power with a stable voltage under various load conditions. In addition, short-circuit fault analysis aims to identify potential impacts. The short-circuit fault analysis finds important areas that are vulnerable to faults and require special protection. ETAP allows simulating various fault scenarios and establishing effective protection systems to reduce damage. This study emphasises the use of ETAP software as a powerful analytical tool in the planning and operation of the PLTGU electrical system. Power flow and short circuit analysis with ETAP is proven to improve the reliability, efficiency and safety of PT PLN Keramasan's PLTGU operations.

Fertigation Monitoring and Control System for Home Chili Cultivation Based on Internet of Things (IoT)

Lindawati Lindawati — 2025-03-26

This study developed an advanced Internet of Things (IoT)-based fertigation system aimed at optimizing growth and resource efficiency in contemporary agriculture. The system is meticulously designed by integrating various sensors that facilitate real-time monitoring of critical agronomic parameters such as soil moisture, temperature, nutrient concentrations, and tank solution levels. These sensors acquire essential data, which is processed using fuzzy logic to effectively manage irrigation control. Additionally, the system incorporates a mobile application, enabling remote monitoring and control, thus providing agricultural practitioners the convenience of managing their fields from any location. results from the study demonstrate a notable 30% increase in water use efficiency and a significant 25% improvement in crop yield compared to conventional manual irrigation techniques. This innovative fertigation system presents a comprehensive and effective solution for modern agriculture, supporting enhanced decision-making for crop management, reducing resource wastage, and augmenting overall agricultural productivity, thereby contributing to sustainable farming practices.

Designing UI/UX for Academic Module of Education Management System Using Design Thinking

Yohanes Nico Kristiawan — 2025-03-26

Learning is the process of altering behavior through the acquisition of knowledge, useful skills, and moral precepts from a variety of sources. The role of media in education is becoming more and more important in the current digital era to improve human resources. By improving resource management, openness, and information exchange, education management systems raise academic standards. The COVID-19 pandemic has sped up digital learning, but issues with accessibility and flexibility still exist and require creative solutions.
The digitalization of education is getting closer to reality thanks to growing internet usage, improved infrastructure, and greater technology literacy. The Education Management System (EMS) website at SMPN 1 Magetan was created using a Design Thinking methodology, which is examined in this paper. The goal of the academic module design is to improve user experience and management effectiveness. Key system features were defined by analyzing the user needs that were discovered through interviews. Low-fidelity wireframes were the first step in the design process, which continued to high-resolution prototypes. The prototype, when tested using the Maze tool, received a pleasant and user-friendly experience, with an average System Usability Score (SUS) of B and a Single Ease Question (SEQ) score of 5.5 to 6.0 out of 7 from all role like Student, Teacher, Parent, and Administrative Staff.

Digital Transformation of Resident Services: Quality and Satisfaction Analysis at Andalas Residence

Haryanti Haryanti — 2025-03-27

Resident services at Andalas Residence have been relying on traditional methods that often face obstacles such as delays in response, lack of transparency, and difficulties in data management. This article aims to analyze and develop a digital technology-based resident service satisfaction survey system using the waterfall method. This research was conducted by distributing questionnaires to 286 respondents of Andalas Residence residents. The data obtained was analyzed using the Structural Equation Modeling-Partial Least Square (SEM-PLS) statistical method. The results showed that the application of digital transformation not only improved the quality of service but also the overall efficiency of dormitory management.

Leveraging Artificial Intelligence and Technology for Enhancing Halal Supply Chain Management

Muhammad Ghalih — 2025-03-27

Halal Supply Chain Management (HSCM) is transforming the way halal products are certified, tracked, and distributed. However, challenges such as regulatory compliance, technological readiness, cost, and stakeholder trust continue to impact AI adoption in the halal industry. This study employs the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method to analyze the causal relationships among key factors influencing AI adoption in halal supply chains. Seven key criteria were identified: Technological Infrastructure, Regulatory Compliance, Cost of Implementation, Data Security & Privacy, Scalability & Adaptability, Stakeholder Readiness, and Consumer Trust & Perception. The findings reveal that Technological Infrastructure is the most influential factor driving AI adoption, impacting Regulatory Compliance, Scalability, and Consumer Trust. Conversely, Consumer Trust & Perception emerged as the most dependent factor, highlighting the importance of transparency in AI-based halal certification. Regulatory Compliance plays a dual role as both a cause and an effect, emphasizing the need for standardized AI-driven halal certification frameworks. The results suggest that investment in AI-driven traceability, blockchain-based halal authentication, and automated compliance verification can significantly improve halal supply chain efficiency and consumer confidence. This study provides valuable insights for policymakers, halal certification bodies, and industry stakeholders by identifying key enablers and barriers to AI adoption. Future research should explore hybrid Multi-Criteria Decision-Making (MCDM) approaches, economic feasibility analyses, and real-world case studies to further validate AI-driven solutions in halal supply chains.

New Student Admission Forecasting Model with Support Vector Machine Method: Case Study of Bali State Polytechnic

I Putu Bagus Arya Pradnyana — 2025-04-16

Every educational institution, both formal and non-formal, organizes new student admissions every year. This process requires institutions to improve the quality of education, services, and accreditation, both in terms of student competence, facilities, and infrastructure. Therefore, effective and efficient planning is needed, especially in making strategic decisions. This research aims to forecast the number of new student admissions using the Support Vector Machine (SVM) method. SVM is one of the artificial intelligence techniques known to have a high level of accuracy in data analysis and forecasting. The results showed that the SVM method was able to produce predictions with a low error rate. The test results using Root Mean Square Error (RMSE) show that the Electrical Engineering study program has the best RMSE value of 7.292, making it the study program with the highest level of forecasting accuracy in this study. This finding proves that the SVM method can be effectively implemented in forecasting new student admissions, so that it can help institutions in developing better and data-based admission strategies.