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Dinamik
Published by Universitas Stikubank
ISSN : 08549524     EISSN : 26231786     DOI : 10.35315/dinamik.v28i1
Core Subject : Science,
Computer Science & IT
The Jurnal DINAMIK aims to: Promote a comprehensive approach to informatics engineering and management incorporating viewpoints of different applications (computer graphics, computer networks and security, computer vision, computational intelligence, databases, big data, IT project management, and other fields relevant to information technology. Encourage scientists, practicing engineers, and others to conduct research and similar activities.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 505 Documents
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Pengembangan Prototipe Aplikasi Pembelajaran English Proficiency Test Berbasis Generative AI dengan Pendekatan Adaptif Berbasis Kerangka CEFR Ani Anisyah; Muhammad Rizki; Ihsan Ghozi Zulfikar; Muhammad Alam Basalamah; Ade Mulyana
Dinamik Vol 31 No 2 (2026)
Publisher : Universitas Stikubank

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35315/dinamik.v31i2.10614

Abstract

TOEFL and IELTS are among the most widely used assessments for evaluating English language proficiency. However, test-takers often face difficulties in the Structure and Written Expression section of TOEFL and the Writing section of IELTS, which frequently hinder them from reaching their target scores. Traditional learning methods, which lack personalization, further limit the provision of materials tailored to individual needs. To address these challenges, this study proposes the integration of intelligent and adaptive technologies into language learning. Machine learning provides a promising approach for classifying English proficiency levels in accordance with the Common European Framework of Reference for Languages (CEFR). Additionally, Generative Artificial Intelligence (AI) powered by Large Language Models (LLMs) enables the generation of personalized learning content suited to learners’ specific requirements. This study introduces the development of an adaptive learning application for TOEFL and IELTS preparation, built on Generative AI and guided by the CEFR framework. The application was developed using a prototyping approach with iterative refinement to ensure relevance to user needs. Logistic Regression was identified as the most effective model for CEFR-level prediction. Furthermore, usability testing with the System Usability Scale (SUS) yielded a score of 77.5, categorized as “good,” demonstrating the feasibility of the proposed solution.. Keywords—English Proficiency Test, CEFR, Generative AI, Natural Language Processing, Large Language Model (LLM
Perbandingan Framework Keamanan Siber (NIST CSF, CIS CONTROLS, ISO/IEC 27001, dan COBIT 2019) menggunakan Analytic Hierarchy Process untuk Penguatan Ketahanan Siber TNI Suhara Golan Sidabutar; I Nengah Putra Apriyanto; Tatar Bonar Silitonga; Priyanto Priyanto
Dinamik Vol 31 No 2 (2026)
Publisher : Universitas Stikubank

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35315/dinamik.v31i2.10631

Abstract

The escalation of global cyber threats, including ransomware, data breaches, and Advanced Persistent Threats, requires defence organizations to adopt measurable cybersecurity frameworks that are aligned with operational needs. This article compares four cybersecurity frameworks, namely the NIST Cybersecurity Framework (CSF), CIS Critical Security Controls, ISO/IEC 27001, and COBIT 2019, to determine the most appropriate alternative for strengthening the cyber resilience of the Indonesian National Armed Forces (TNI). The study employs a descriptive-comparative design with a quantitative approach based on the Analytic Hierarchy Process (AHP). Expert judgments are collected through pairwise comparisons across the criteria of governance, risk management, operational and technical controls, compliance and certification, implementability, and cost. The synthesis of priority weights indicates that NIST CSF obtains the highest priority, particularly in the risk management dimension. The findings also underline the need to adapt NIST CSF to the military context, including confidentiality requirements, response speed, and integration with doctrine and operational procedures.
Pengembangan Media Promosi Perumahan Berbasis Virtual Reality Mobile Dengan Reticle-Based Gaze Interaction Daffa Atha Perdana; Tommy Bustomi; Farindika Metandi
Dinamik Vol 31 No 2 (2026)
Publisher : Universitas Stikubank

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35315/dinamik.v31i2.10641

Abstract

Conventional promotional media such as brochures, scale models, and two-dimensional images provide limited spatial exploration for prospective homebuyers. This study developed a mobile Virtual Reality application for housing promotion integrating 360° panoramas, reticle-based gaze interaction, gyroscope orientation, a minimap, and lighting and faucet controls. Development followed the Multimedia Development Life Cycle. A raycast aligned with the camera view triggers an action after the reticle remains on a target for two seconds. Android functions were evaluated using Black Box Testing, while visual effectiveness was assessed with 36 respondents through a web-based panoramic tour using the EPIC Model. All functional scenarios succeeded in five repetitions. Testing on an ASUS ROG Phone 9 FE showed a relatively stable frame rate of approximately 30 FPS, with initial loading and scene transitions taking about two seconds. All questionnaire items were valid, with correlations above 0.329, and Cronbach’s Alpha reached 0.917. The overall EPIC score was 4.37, categorized as Very Effective, with Impact obtaining the highest score of 4.41. The findings show that the panoramic tour was effective as a visual promotional medium, while the reticle-based interaction mechanism functioned as designed.
Pipeline Klasifikasi Kelayakan Bantuan Siswa berbasis Data Administrasi Sekolah dengan Interpretasi Fitur Saefurrohman Saefurrohman; Novita Mariana; Budi Hartono; Rina Candra Noor Santi; Veronica Lusiana
Dinamik Vol 31 No 2 (2026)
Publisher : Universitas Stikubank

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35315/dinamik.v31i2.10653

Abstract

This study develops a classification pipeline for assessing student aid eligibility using administrative school data with feature interpretation to support accountable preliminary review. The dataset consists of 1,242 anonymized student records from one senior high school in Ambarawa, Central Java. Prior to modeling, direct identity attributes and label-leakage-prone features, such as eligibility reasons and aid card numbers, were removed. Five classification algorithms were evaluated using an 80:20 stratified train-test split and five-fold cross-validation. Random Forest was selected as the main model because it provided a balance between predictive performance and feature interpretability, achieving an accuracy of 0.6988, an F1-score of 0.6939, and a ROC-AUC of 0.7736. Gradient Boosting achieved a higher ROC-AUC of 0.7867; however, its performance gain was relatively small, while the feature importance results from Random Forest were easier to communicate to non-technical school staff in an implementation context. Feature interpretation indicates that father’s income was the most influential predictor, with an importance score of 0.1894, whereas distance and transportation mode provided secondary accessibility signals. The proposed pipeline is not intended as an automated decision-making mechanism, but as a tool for generating a priority list of candidates requiring human verification and local retraining before being adapted by other schools.
Prioritizing Key Stunting Risk Factors Using a Fuzzy DEMATEL-Based Group Decision Making Approach Taufiq Dwi Cahyono; Wiwien Hadikurniawati
Dinamik Vol 31 No 2 (2026)
Publisher : Universitas Stikubank

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35315/dinamik.v31i2.10678

Abstract

The Multi-Criteria Group Decision Making (MCGDM) approach uses the fuzzy DEMATEL method to assess the criteria for stunting in toddlers. This involves data with numerical values, being fuzzy numbers, numbers that represent subjective judgments by eight decision makers. The study aims to identify and prioritize the critical factors that contribute to stunting in children, which can help policymakers to develop effective interventions to reduce stunting rates. The approach combines fuzzy set theory and the DEMATEL method to handle the uncertainty and vagueness of the decision-making process. The results show that the proposed approach can effectively identify and prioritize the critical factors that contribute to stunting, which can help policymakers to develop targeted interventions to reduce stunting rates. The study contributes to the field of multi-criteria decision-making by providing a novel approach that can handle the uncertainty and vagueness of the decision-making process in evaluating complex problems such as stunting. The MCGDM results are based on four criteria and the ranking is determined using the fuzzy DEMATEL. The analysis and calculations show that the main criteria based on the highest value obtained is mother nutrition.

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