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Technologia Journal
Published by PT Anagata Sembagi Education
ISSN : -     EISSN : 30469163     DOI : https://doi.org/10.62872/ezf7zc71
Core Subject : Science,
Computer Science & IT
This journal publishes original articles on current issues and international trends in the field of information engineering and information systems.
Arjuna Subject : Ilmu Komputer (semua kategori) - Sistem Informasi
Articles 34 Documents
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Preliminary Analysis of e-Government Implementation and Readiness in Sikka Regency: A Foundational Study for the AVELINE Evaluation Model Agustinus Lambertus Suban
Technologia Journal Vol. 2 No. 4 (2025): Technologia Journal-November
Publisher : Pt. Anagata Sembagi Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62872/j412jw89

Abstract

This study presents a preliminary analysis of e-government implementation and readiness in Sikka Regency, East Nusa Tenggara, as the empirical foundation for developing the AVELINE Evaluation Model a context-sensitive framework designed to assess e-government maturity in developing local governments. Using a mixed-methods approach, the research integrates quantitative survey data from 120 respondents across 15 government agencies with qualitative insights from in-depth interviews and document analysis. The findings indicate a moderate overall readiness index (3.04 out of 5), reflecting partial progress in digital transformation. Among the five assessed dimensions, policy and governance readiness scored highest (3.47), while citizen engagement and human resource readiness remained lowest (2.76 and 2.85, respectively). The study identifies key inhibitors such as limited ICT infrastructure, insufficient digital literacy, and fragmented inter-agency coordination, which hinder effective SPBE (Electronic-Based Government System) implementation. Conversely, strong policy commitment and emerging leadership support provide a foundation for improvement. Empirical results confirm significant correlations between infrastructure, human resources, and organizational readiness, emphasizing that technological success depends on institutional and socio-environmental factors. Theoretically, this research contributes to the development of the AVELINE Evaluation Model, integrating six dimensions Administrative, Viability, Environmental, Legal, Information, and Network readiness into a holistic tool for assessing e-government maturity. Practically, recommendations for infrastructure enhancement, human resource capacity building, and participatory governance. Overall, the findings highlight that digital transformation in Sikka Regency remains in a transitional phase technologically functional but organizationally fragile underscoring the need for a tailored, context-aware evaluation framework to guide sustainable e-government development in underdeveloped regions
Information Security in The Cloud Era: Strategies and Implementation Nyoman Gunantara
Technologia Journal Vol. 2 No. 4 (2025): Technologia Journal-November
Publisher : Pt. Anagata Sembagi Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62872/40mq7e60

Abstract

Cloud computing has become a fundamental driver of global digital transformation, providing organizations with scalability, operational efficiency, and flexibility. However, the migration to cloud environments has also intensified cybersecurity challenges, including data breaches, misconfigurations, identity compromise, and evolving cyber-threats. This systematic literature review analyzes strategic and implementation approaches to cloud information security across multiple sectors. The study applies a structured methodology aligned with academic SLR standards to identify key security practices, technological controls, and governance frameworks. Findings reveal that effective cloud security requires a holistic model integrating Zero Trust Architecture, encryption, identity and access management, artificial intelligence-driven threat monitoring, and compliance with regulatory frameworks. Organizational readiness, human capability, and governance maturity significantly influence implementation outcomes. The study concludes that adaptive, multi-layer security models combined with continuous workforce development and regulatory harmonization are critical for building sustainable cloud resilience
Application of Large Language Models (LLMs) for Optimising Indonesian Language-Based Public Service Chatbots Ali Ibrahim; Sitti Rachmaeati Yahya; Iwan Adhicandra
Technologia Journal Vol. 2 No. 4 (2025): Technologia Journal-November
Publisher : Pt. Anagata Sembagi Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62872/74q5b220

Abstract

This study examines the potential of Large Language Models to optimise Indonesian language-based public service chatbots by integrating linguistic, technological, and administrative perspectives. Using a mixed-method approach that combines a systematic literature review with secondary benchmarking of state-of-the-art LLMs, the research evaluates model performance in Indonesian semantic comprehension, contextual reasoning, and domain adaptability. The findings show that LLMs can significantly improve chatbot accuracy, inclusivity, and responsiveness, outperforming rule-based systems that struggle with informal expressions, multi-intent queries, and policy-specific terminology. Benchmarking highlights that GPT-4 and PaLM-2 achieve high contextual coherence and low hallucination rates, while Indonesian-centric models such as IndoGPT demonstrate strong local language adaptability. However, risks related to data privacy, bias, hallucination, and governance limitations present substantial challenges for implementation. The study proposes a strategic framework that emphasizes AI governance, interoperable data infrastructure, institutional capacity building, hybrid retrieval–generation design, and citizen engagement to ensure responsible adoption. Overall, the integration of LLM-powered chatbots has the potential to transform Indonesia’s digital public service landscape, provided that deployment is accompanied by robust oversight, ethical safeguards, and sustainable technological planning
Problem-Based Learning Models in Computer Science Education Supported by Digital Platforms: A Systematic Literature Review Anggun Nugroho; Joko Santoso; Agus Purwanto; I Wayan Karang Utama; Affan Irfan Fauziawan
Technologia Journal Vol. 3 No. 1 (2026): Technologia Journal-February
Publisher : Pt. Anagata Sembagi Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62872/a8nnzd66

Abstract

Computer science education requires strong problem-solving skills, algorithmic thinking, and collaboration. Problem-Based Learning (PBL) is widely regarded as a relevant pedagogical approach to address these demands, particularly when supported by digital platforms that enable collaborative, exploratory, and contextual learning. This study aims to synthesize PBL models in computer science education supported by digital platforms, identify the roles of digital platforms in facilitating PBL, and evaluate its impacts and implementation challenges. A Systematic Literature Review with a qualitative synthesis approach was conducted on peer-reviewed journal articles and conference proceedings published between 2014 and 2024. A total of 36 studies were included and analyzed through thematic analysis and narrative synthesis. The findings indicate that digital PBL is implemented through several dominant patterns, including full PBL, hybrid PBL, and project-based PBL, with a strong emphasis on authentic problems reflecting real-world computing practices. Digital platforms function as pedagogical mediators that support collaboration, solution exploration, and reflective learning. Although digital PBL demonstrates positive effects on problem-solving skills, motivation, and collaboration, its effectiveness is highly dependent on pedagogical alignment, instructor readiness, and students’ digital literacy.

Page 4 of 4 | Total Record : 34

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