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Smatika Jurnal : STIKI Informatika Jurnal
Published by Universitas Bhinneka Nusantara
ISSN : 20870256     EISSN : 25806939     DOI : https://doi.org/10.32664/smatika
Core Subject : Science,
Computer Science & IT
SMATIKA: STIKI Informatika Jurnal is a journal published by Lembaga Penelitian & Pengabdian kepada Masyarakat (LPPM) of Universitas Bhinneka Nusantara Malang. The scope of this journal in the field of Computer Science, Information Systems, and Information Management.
Arjuna Subject : Ilmu Komputer (semua kategori) - Sistem Informasi
Articles 274 Documents
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The Cyber Threat Landscape in Indonesia: Attacks and Security System Analysis Sama, Hendi; Stefanie; Prasetyo, Stefanus Eko
SMATIKA JURNAL : STIKI Informatika Jurnal Vol 16 No 01 (2026): SMATIKA Jurnal : STIKI Informatika Jurnal
Publisher : LPPM Universitas Bhinneka Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/smatika.v16i01.2200

Abstract

Cybersecurity in learning systems has become increasingly important as educational institutions rely more heavily on digital platforms such as learning management systems, online assessments, and cloud-based academic services. This rapid digital transformation exposes learning environments to sophisticated cyber threats that may disrupt academic activities and compromise sensitive information. However, many institutions still lack a clear understanding of how users perceive cyber risks and how these perceptions influence the effectiveness of cybersecurity systems. Currently, there is a significant research gap regarding empirical evidence that links user behavioral psychology with technical security outcomes in the Indonesian educational context. This study aims to empirically analyze the relationship between cyber awareness, perceived impact of cyber attacks, and perceived effectiveness of cybersecurity systems in digital learning environments. A quantitative research approach was applied using data collected from 402 respondents. The data were analyzed through descriptive statistics, correlation analysis, regression analysis, and group comparison tests to examine variable relationships and demographic differences. The findings indicate that cyber awareness significantly and positively predicts perceived system effectiveness (β = 0.501, p < 0.001), demonstrating that higher awareness levels enhance overall cybersecurity performance. Conversely, the perceived impact of cyber attacks does not show a significant effect on system effectiveness, suggesting that awareness is more influential than threat perception alone. Additional results reveal gender-based differences in cyber incident experiences, while awareness levels remain similar. The practical implications emphasize the importance of cybersecurity awareness programs, digital safety education, and proactive defense strategies to strengthen protection in learning systems and improve institutional cybersecurity readiness.
A SMIL-Based Approach for Designing Interactive Multimedia Film Players Tanubrata, Markus; Wijaya, Marvin Chandra; Maksom, Zulisman; Lehman, Andrew Sebastian; Tjiharjadi, Semuil; Siahaan, Agnes Hardiani
SMATIKA JURNAL : STIKI Informatika Jurnal Vol 16 No 01 (2026): SMATIKA Jurnal : STIKI Informatika Jurnal
Publisher : LPPM Universitas Bhinneka Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/smatika.v16i01.2206

Abstract

Typically, an HTML-style application requires extensive scripting to coordinate user interactions, manage display layout, and synchronize the timing of all interaction events. With Synchronized Multimedia Integration Language (SMIL), an alternative approach to developing an interactive multimedia film application has been defined, supporting time-based multimedia cooperation and user interactivity without the need for complex scripts. This study presents the development and evaluation of an SMIL-based interactive multimedia film application. The application allows for user-selected films to be automatically selected, played, and managed (synchronized) through an interactive GUI. The two measures, the Layout Consistency Score (LCS) and Screen Utilization Efficiency (SUE), were evaluated. Experimental evaluations have shown that the average LCS for the application = 0.92, indicating that the application maintains a consistent and predictable layout across multiple instances of the interface. In addition, the average SUE score for the application was calculated to be 0.79, indicating that it uses the available screen space efficiently and does not create a visually competing cluster. These results reinforce the concept that the region-based approach of SMIL and its declarative style for creating applications enable the development of multimedia that is consistently and efficiently presented across multiple contexts. As a result, the findings of this study indicate that the SMIL approach will simplify and allow for a practical methodology to build interactive multimedia film player applications, while preserving layout quality and interactivity.
Mountain Climbing Safety Induction for Beginners Using Augmented Reality setiawan, aldi; Aldi Setiawan, M; Dijaya, Rohman; Taurusta, Cindy; Senja Fitrani, Arif
SMATIKA JURNAL : STIKI Informatika Jurnal Vol 16 No 01 (2026): SMATIKA Jurnal : STIKI Informatika Jurnal
Publisher : LPPM Universitas Bhinneka Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/smatika.v16i01.2215

Abstract

The growing popularity of mountain climbing among novice participants has been accompanied by an increased risk of accidents, largely attributable to inadequate understanding of safety procedures. Conventional safety induction methods—primarily verbal briefings and printed materials—lack interactivity and fail to adequately simulate real climbing conditions. While prior research has examined general safety education and conventional multimedia learning approaches, the application of markerless augmented reality (AR) as an interactive, mobile-based safety induction tool specifically designed for beginner mountain climbers remains underexplored . Accordingly, this study aims to develop and evaluate an Android-based markerless AR application to enhance pre-climbing safety induction for novice climbers.  The application was developed following the Multimedia Development Life Cycle (MDLC), encompassing the stages of concept development, design, material collection, assembly, testing, and distribution. Functional performance was assessed using black-box testing, while feasibility was evaluated through a Likert-scale questionnaire administered to 20 beginner climbers.  Black-box testing confirmed that all system functionalities operated as intended. The feasibility evaluation yielded a score of 87%, indicating a good to very good level of acceptance among users. By integrating markerless AR technology into mobile-based safety induction, this study addresses a critical gap in outdoor safety training research. The findings demonstrate the feasibility and practical potential of immersive AR applications to enhance safety awareness and improve the effectiveness of preparatory training for beginner mountain climbers.
Large Language Models for JSON-Based Function Call Planning from Indonesian Natural Language: A Restaurant Search Chatbot Case Study Mohammad Mauludin; Santoso, Joan; Junaedi, Hartarto
SMATIKA JURNAL : STIKI Informatika Jurnal Vol 16 No 01 (2026): SMATIKA Jurnal : STIKI Informatika Jurnal
Publisher : LPPM Universitas Bhinneka Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/smatika.v16i01.2216

Abstract

Large Language Models are increasingly adopted as planning components that translate natural language into structured representations for tool invocation, enabling executable interaction with backend systems through JSON based function calling. However, empirical studies focusing on Indonesian natural language remain limited. This paper presents a restaurant search chatbot case study that investigates JSON based function call planning from Indonesian user queries, with emphasis on the upstream planning task rather than conversational response generation. A synthetic dataset of 33,470 Indonesian restaurant search queries paired with ground truth JSON plans was constructed based on a predefined tool set and database schema. Supervised fine tuning with parameter efficient adaptation was applied to a pretrained language model. The fine tuned Mistral 7B model was evaluated using multiple metrics measuring JSON structural validity, tool sequence correctness, and parameter accuracy at different granularities. The results show strong performance, achieving a JSON structure validity rate of 0.97, tool sequence exact match accuracy of 0.92, column level accuracy of 0.97, and value level accuracy of 0.94. More stringent evaluation at the session level reveals remaining challenges in composing all parameters correctly within a single planning instance. Overall, the findings demonstrate that with carefully designed datasets and strict supervision, Large Language Models can reliably perform structured JSON based function call planning from Indonesian natural language, providing a practical foundation for extending this approach to other structured application domains where execution correctness is critical.

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