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Tech-E
Published by Universitas Buddhi Dharma
ISSN : -     EISSN : -     DOI : -
Core Subject : Science,
Computer Science & IT
Jurnal Tech-E dikembangkan dengan tujuan menampung karya ilmiah Dosen dan Mahasiswa, baik hasil tulisan ilmiah maupun penelitian yang berupa hasil studi kepustakaan.
Arjuna Subject : -
Articles 132 Documents
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FireReady Challenge: A 2D Gamified Prototype for Community Fire Safety Preparedness Rabeah Md Zin; Ahmad Amru Mohamad Zaid; Zailah Salamon; Adi Irfan Che Ani; Nur ‘Amirah Mhd Noh
Tech-E Vol. 9 No. 2 (2026): TECH-E (Technology Electronic)
Publisher : Fakultas Sains dan Teknologi-Universitas Buddhi Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31253/te.v9i2.4304

Abstract

Fire protection remains a critical public concern, as fire-related incidents continue to cause substantial property damage, personal injuries, and loss of life. Although public awareness campaigns and routine safety drills are widely implemented, conventional didactic training methods such as posters, presentations, and demonstrations often fail to generate lasting comprehension or meaningful behavioural change. To address this gap, this paper presents the FireReady Challenge, a 2D gamified learning prototype designed to enhance community awareness and preparedness in fire safety. The game adopts the ADDIE instructional model to systematically translate key learning objectives into interactive digital experiences focused on hazard identification, safe evacuation procedures, emergency communication readiness, and proper fire extinguisher use. Gamification elements, including points, badges, real-time feedback, and time-bound missions, are embedded to strengthen motivation and user engagement. This concept design demonstrates an innovative approach to ICT-based fire safety education for community dissemination. Future research will involve pilot-scale deployment and empirical validation to evaluate learning outcomes, usability, and user acceptance.
Machine Learning Approaches to Workplace Mental Health: Predicting Treatment-Seeking Behavior Using the OSMI Dataset Nor Aishah Othman; Mariana Rosdi
Tech-E Vol. 9 No. 2 (2026): TECH-E (Technology Electronic)
Publisher : Fakultas Sains dan Teknologi-Universitas Buddhi Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31253/te.v9i2.4305

Abstract

Employee mental health is increasingly recognized as essential for sustainable organizational performance, particularly in technology sectors where work intensity and psychological strain are prevalent. This study leverages machine learning to identify predictors of treatment-seeking behavior using the Open Sourcing Mental Illness (OSMI) dataset, which includes 1,387 anonymized responses from the 2014 OSMI survey. The survey examines employees’ experiences and perceptions of mental health in the global tech industry. Through data cleaning and encoding, key factors influencing help-seeking behavior were identified, including family history of mental illness and work interference due to psychological distress. Two machine learning models, Decision Tree and K-Nearest Neighbour (KNN), were employed for prediction. The Decision Tree model achieved an accuracy of 73%, while KNN attained 100%, suggesting high predictive power, albeit with potential overfitting risks. These findings align with recent studies promoting the integration of AI-driven analytics in workplace wellness programs to detect hidden behavioral trends and enable early interventions. The results demonstrate that machine learning models can offer valuable insights into employee well-being and preventative strategies. Future research should focus on incorporating larger, more diverse datasets and adopting explainable AI (XAI) techniques to enhance interpretability, fairness, and trust in predictive systems for mental health in the workplace.
Desain Microcomputer Cloud Computing for Informatics Study Program at LIA University Based on Local Area Network (LAN) Ariya Pannadhitthana Candra; Murniasih, Intan
Tech-E Vol. 9 No. 2 (2026): TECH-E (Technology Electronic)
Publisher : Fakultas Sains dan Teknologi-Universitas Buddhi Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31253/te.v9i2.4314

Abstract

Digital transformation in higher education increasingly requires information technology infrastructure that is efficient, flexible, secure, and sustainable. Cloud computing has emerged as a strategic solution by enabling scalable resources, centralized management, and service standardization effectively. However, public cloud adoption in academic institutions frequently encounters constraints, including recurring operational costs, data security and sovereignty risks, regulatory concerns, and strong dependence on reliable internet connectivity. These issues are particularly salient for instructional laboratories that demand continuous access, predictable performance, and institutional control. This study aims to design and implement a Local Area Network (LAN)-based cloud computing system using a microcomputer as the primary server within the Informatics Study Program at LIA University. The research employs a research and development (R&D) methodology comprising needs analysis, system architecture design, implementation, and functional as well as performance testing. An open-source virtualization platform is deployed to deliver Infrastructure as a Service (IaaS) and Software as a Service (SaaS) in a private cloud environment. The results demonstrate that the proposed LAN-based local cloud provides centralized computing and storage services with low latency, high stability, and efficient utilization.
Public Sentiment Analysis of Free Nutritious Meal Program Discourse on Social Media X Using Support Vector Machine N-Gram Features Based Silaban, Daniel; Gracia Simatupang; Sardo Pardingotan Sipayung
Tech-E Vol. 9 No. 2 (2026): TECH-E (Technology Electronic)
Publisher : Fakultas Sains dan Teknologi-Universitas Buddhi Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31253/te.v9i2.4355

Abstract

The Free Nutritious Meal Program is a government policy aimed at improving the nutritional quality of society and has generated diverse public responses on social media. This study aims to analyze public sentiment toward the Free Nutritious Meal Program on social media X using the Support Vector Machine (SVM) algorithm with N-Gram features and Term Frequency–Inverse Document Frequency (TF-IDF) weighting. The data were collected through a crawling process from social media X, resulting in 1,014 tweets. After data cleaning, 931 tweets were obtained and labeled into two sentiment classes, namely positive and negative. The research stages include text preprocessing, N-Gram feature extraction (unigram and bigram), classification using the SVM algorithm, and model evaluation using the 10-Fold Cross-Validation method with the assistance of the RapidMiner tool. The experimental results show that the SVM model achieved an accuracy of 79.59%. Although the precision value for the negative class is relatively high, the recall and F1-score remain relatively low due to the imbalance in data distribution. Overall, the results indicate that public sentiment toward the Free Nutritious Meal Program on social media X is dominated by positive sentiment. The findings of this study are expected to serve as an initial evaluation for the government in understanding public perceptions of the implementation of the program.
Architectural Analysis of the Repository Pattern in Web-Based Credit Score Conversion Assessment System Based on PermenPAN-RB No. 1 of 2023 Lapatta, Nouval Trezandy; Syahrullah
Tech-E Vol. 9 No. 2 (2026): TECH-E (Technology Electronic)
Publisher : Fakultas Sains dan Teknologi-Universitas Buddhi Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31253/te.v9i2.4362

Abstract

PermenPAN-RB Regulation No. 1 of 2023 introduced a major shift in functional position assessment by emphasizing performance predicate conversion in credit score evaluation, which increases architectural demands on supporting information systems. In practice, many assessment systems remain tightly coupled and difficult to evolve when regulatory rules, integration sources, or reporting formats change. This paper presents an architecture-oriented analysis of a web-based credit score conversion assessment information system that applies the Repository Pattern as a core architectural mechanism to decouple business logic from persistence, integration, and document-generation concerns. The analysis adopts a scenario-based evaluation approach inspired by the Architecture Tradeoff Analysis Method (ATAM) and is grounded in the ISO/IEC 25010 software quality model, focusing on maintainability, modifiability, testability, scalability, and reliability. Architectural evaluation is conducted by examining layered boundaries, repository abstractions, and dependency injection mechanisms under representative regulatory-driven change scenarios, including rule adjustments, data integration extensions, and reporting modifications. The results demonstrate consistent change localization across architectural layers, where rule changes are confined to service modules, integration changes are absorbed by repository adapters, and reporting changes remain isolated within document-generation components. These findings show that repository-based architectures significantly reduce coupling, improve change isolation, and support the sustainable evolution of government information systems operating under dynamic regulatory environments.
Detection of DDoS Attacks in Networks Using Deep Learning Based on Long Short-Term Memory (LSTM) Dicky Surya Dwi Putra; Nomsa Ramaphosa
Tech-E Vol. 10 No. 1 (2026): TECH-E (Technology Electronic)
Publisher : Fakultas Sains dan Teknologi-Universitas Buddhi Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31253/te.v10i1.4378

Abstract

HTTP Flood attacks remain difficult to detect because they operate at the application layer, resemble legitimate user requests, and generate burst-based temporal traffic patterns. Previous DDoS detection studies often rely on outdated datasets, process network flows as independent records, insufficiently address class imbalance, and provide limited interpretability for security analysts. This study proposes a sequence-aware and explainable deep learning framework for HTTP Flood detection using Long Short-Term Memory (LSTM). Reconstructed HTTP traffic from the UNSW-NB15 dataset was processed through proxy labeling, data cleaning, feature normalization, and sliding-window transformation to convert flow-level records into temporal sequences. Class weighting and SMOTE oversampling were evaluated to mitigate imbalance, while SHAP and LIME were used to explain model decisions. The proposed LSTM model achieved an attack recall of 94.8%, a false negative rate of 5.2%, balanced accuracy of 94.3%, MCC of 0.824, and ROC-AUC of 0.975. The results show that temporal representation improves detection of bursty HTTP Flood behavior, whereas class weighting provides a better balance between attack sensitivity and false-alarm control. Explainability analysis further confirms that the model relies on technically meaningful indicators, including packet rate, flow duration, traffic asymmetry, and service concentration. This framework supports interpretable early-warning detection for application-layer DDoS attacks.
EDUDEAFBIZ: Deaf-Friendly Gamified Game for Entrepreneurship Learning Nik Afiqah Kamil; Rabeah Md Zin; Nur Angriani Nurja; Mohd Arami Md Jais; Noraini Lunchin
Tech-E Vol. 10 No. 1 (2026): TECH-E (Technology Electronic)
Publisher : Fakultas Sains dan Teknologi-Universitas Buddhi Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31253/te.v10i1.4636

Abstract

This study presents EduDeafBiz, a browser-based gamified learning tool designed to support entrepreneurship learning among deaf and hard-of-hearing TVET students. Although game-based learning is widely used in educational technology, limited studies have focused on visual-first, no-audio, bilingual, and sign-supported entrepreneurship games for deaf TVET learners. EduDeafBiz addresses this gap through short missions, icon-based navigation, captioned instructions, optional sign-language videos, quizzes, immediate feedback, badge rewards, and instructor-editable JSON content. The prototype was evaluated through a 60-minute classroom pilot involving 20 deaf and hard-of-hearing students using a single-group pre-test and post-test design. Usability, motivation, accessibility, and engagement were assessed using adapted SUS, IMI, an accessibility checklist, and game-use data. The mean quiz score increased from 41.2% to 77.6%. EduDeafBiz achieved an SUS score of 82.1 and an IMI score of 5.8 out of 7. All participants completed the missions, 65% replayed at least one mission, and 85% used the sign-language toggle. These preliminary pilot findings indicate that EduDeafBiz is feasible, usable, and potentially supportive of short-term entrepreneurship learning among deaf and hard-of-hearing TVET students.
A Psychometric Evaluation of a Student Personality Instrument for Academic Profiling Nor Aishah Othman; Noradilah Binti Md Nordin
Tech-E Vol. 10 No. 1 (2026): TECH-E (Technology Electronic)
Publisher : Fakultas Sains dan Teknologi-Universitas Buddhi Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31253/te.v10i1.4637

Abstract

This paper reports the results of a pilot study designed to evaluate the psychometric properties of a student personality instrument for academic profiling at Universiti Malaysia Pahang Al-Sultan Abdullah (UMPSA). The instrument consists of five sections: demographic information, career interests based on the Self-Directed Search (SDS), career choices, perceived social support measured through the Multidimensional Scale of Perceived Social Support Malay version (MSPSS-M), and subjective well-being assessed using the Satisfaction with Life Scale (SWLS). Thirty-four undergraduate students participated in the pilot study, and 30 valid responses were included in the analysis. Descriptive statistics and reliability testing using Cronbach’s alpha indicated acceptable to strong internal consistency across the main subscales, namely career interest (α = 0.815), social support (α = 0.89), and subjective well-being (α = 0.85). Construct validity was examined through corrected item-total correlations, with most items meeting the recommended 0.30 threshold. Overall, the findings provide preliminary evidence of internal consistency and item-level suitability, particularly for the MSPSS-M, while indicating that the SDS and SWLS components require further item-level refinement and validation.
Development of a Multi-Vendor Marketplace Application for Empowering MSME Products Supported by CV Tartila Group Farizi Ilham; Suprianto
Tech-E Vol. 10 No. 1 (2026): TECH-E (Technology Electronic)
Publisher : Fakultas Sains dan Teknologi-Universitas Buddhi Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31253/te.v10i1.4639

Abstract

The digitalization of micro, small, and medium enterprises (MSMEs) requires integrated systems that support product management, vendor administration, transactions, payments, verification, and reporting. However, many MSME e-commerce studies still focus on single-store systems or limited sales features, while multi-vendor marketplace systems that combine vendor management, product catalogs, payment gateways, partner verification, dashboards, and transaction reports remain limited. This study aims to develop a web-based multi-vendor marketplace application for MSMEs assisted by CV Tartila Group. A software engineering-based development approach was applied using the Waterfall model, covering requirements analysis, system design, implementation, testing, and evaluation. Requirements were collected through observation, interviews with management and MSME representatives, and literature review. The system was designed using UML and implemented through buyer, vendor, and administrator modules. Functional validation was conducted using Black Box Testing was conducted across 15 predefined functional scenarios, all of which passed, resulting in a 100% scenario pass rate. These findings indicate that the system meets basic functional requirements, but its claims remain limited to functional validation.
Acceptance, Multimedia Suitability, and Student Satisfaction Among Students Using the Jom Mudah Jawi Application for Primary School Learning Nurul Adha Md Yatim; Suhazlan Suhaimi; Ahmad Nurzid Rosli; Mohd Helmy Abd Wahab; Tengku Maaidah Tengku A Razak
Tech-E Vol. 10 No. 1 (2026): TECH-E (Technology Electronic)
Publisher : Fakultas Sains dan Teknologi-Universitas Buddhi Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31253/te.v10i1.4641

Abstract

The declining interest and skills of primary school students in writing Jawi have raised concerns about the continuity of traditional script literacy. Although augmented reality (AR)-based applications have been developed to support Jawi learning, previous studies have focused mainly on application design, while evaluations of students’ acceptance, multimedia suitability, and satisfaction remain limited. This study examined students’ post-use perceptions of the Jom Mudah Jawi application as a local culture-based AR learning tool. A cross-sectional post-use survey design was employed involving 32 pupils from a national primary school in Selangor, Malaysia. Data were collected using a structured questionnaire measuring acceptance, multimedia suitability, and student satisfaction, and were analyzed descriptively using SPSS version 22.0. The findings indicate highly positive perceptions, particularly regarding ease of use, clarity of instructions, interface design, text size, and learning satisfaction. Minor variations appeared in background design and audio quality. Theoretically, this study extends the Technology Acceptance Model to AR-based traditional script learning. Practically, the application can support teachers in Jawi instruction.

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