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Voteteknika (Vocational Teknik Elektronika dan Informatika)
Published by Universitas Negeri Padang
ISSN : 23023295     EISSN : 27163989     DOI : -
Core Subject : Science, Education, Engineering,
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering
Jurnal Vocational Teknik Elektronika dan Informatika (VoteTEKNIKA) is a peer-reviewed, scientifc journal published by Department of Electronics Engineering, Faculty of Engineering, Universitas Negeri Padang, Indonesia. The aim of this journal is to publish articles dedicated to all aspects of the latest outstanding developments in the fields of Vocational Education, Electronics Engineering and Informatics. Jurnal Vocational Elektronika dan Informatika (VoteTEKNIKA) is published twice in one year in March and September with the scopes and focus of the research, but it is not limited to : Vocational Education, Electronics, Telecommunication, Robotic Instrumentation, Control Systems, Artificial Intelligence , Internet of Things, Information Systems, Data Mining, Expert Systems, Mobile Technology & Applications, Web Technology, Computer Network, Network Management and Security, Computer & Embedded System, IT Governance, Enterprise Resource Planning, Software Testing, Modeling and Simulation
Arjuna Subject : Teknik (semua kategori) - Teknik (Lain-Lain)
Articles 606 Documents
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Implementation of Interactive Multimedia Design Principles in a Prototype Website for a Higher Education Research Institution Irma Delianti, Vera; Giatman, M; Irfan, Dedy; Effendi ​, Hansi
Voteteknika (Vocational Teknik Elektronika dan Informatika) Vol 13, No 4 (2025): Voteteknika (Vocational Teknik Elektronika dan Informatika)
Publisher : Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/voteteknika.v13i4.136976

Abstract

University research institute websites play a strategic role as media for disseminating research outputs and community service activities to the public. However, many institutional websites remain static, offer minimal interactivity, and insufficiently consider user experience. This study aims to examine the contribution of interactive multimedia design principles to improving the quality of information delivery and user interaction on university research institute websites. The research adopts a research and development approach, encompassing stages of user and content needs analysis, information architecture design, wireframe development, visual design, and interaction and navigation design. The results indicate that the application of visual consistency, clear information hierarchy, meaningful integration of text and visuals, and intuitive navigation can enhance readability, accessibility, and user engagement. The implementation of interactive multimedia design supports a more professional and effective institutional image as a medium of organizational communication. This study is limited to the design and implementation stages without empirical usability evaluation.Keywords — Interactive Multimedia Design, Institutional Website, User Experience, Research Institute, Higher Education
Sentiment Analysis of Honor of Kings Game Reviews on Google PlayStore Using Naive Bayes and SVM Rahman, Taufik; Saputra, Haikal Fulvian; Kuswanto, Herman
Voteteknika (Vocational Teknik Elektronika dan Informatika) Vol 13, No 4 (2025): Voteteknika (Vocational Teknik Elektronika dan Informatika)
Publisher : Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/voteteknika.v13i4.135131

Abstract

This study aims to conduct a sentiment analysis of user reviews of the Honor of Kings game on Google PlayStore using the Naive Bayes (NB) algorithm and Support Vector Machine (SVM) as a machine learning approach. The research gap raised in this study lies in the lack of comparative studies that quantitatively measure the performance of the two classic algorithms on Indonesian-language mobile game review data, as well as the absence of numerical mapping of sentiment distribution that describes user perceptions proportionally. The dataset used consisted of 1000 reviews, which after the manual labeling process was divided into 780 positive reviews (52%), 540 negative reviews (36%), and 180 neutral reviews (12%). The quantitative objective of this study was to measure and compare the levels of accuracy, precision, recall, F1-score, and AUC of the two models to determine the most effective algorithm in classifying user opinions. The test results showed that the SVM model produced an accuracy of 75.3% with an AUC value of 0.82, while the NB model obtained an accuracy of 71.1% with an AUC of 0.78. Based on the confusion matrix, SVM is able to reduce misclassification of negative and neutral sentiments, which are generally difficult to distinguish due to the distribution of sparse text features. Scientifically, this study contributes by showing that SVM is more optimal than NB in handling unbalanced review data, and confirms the importance of feature weighting and AUC validation as indicators of model reliability. Practically, the results of this study can be used by the developers of Honor of Kings to evaluate aspects of the user experience based on the sentiment patterns identified, especially in improving server stability, character balance, and player satisfaction.Keywords— Sentiment Analysis, Naive Bayes, Support Vector Machine, Honor of Kings, Google PlayStore. 
Determinants of Cybersecurity Behavior among Social Media Users: The Moderating Role of Self-Efficacy in the Relationship between Cybersecurity Knowledge and Social Media Use Intensity Saputra, Hadi Kurnia; Refdinal, Refdinal; Abdullah, Rijal; Mardizal, Jonni; Ambiyar, Ambiyar; Fadhilah, Fadhilah
Voteteknika (Vocational Teknik Elektronika dan Informatika) Vol 13, No 4 (2025): Voteteknika (Vocational Teknik Elektronika dan Informatika)
Publisher : Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/voteteknika.v13i4.137117

Abstract

Social media has become an integral part of daily life, but its intensive use also increases users’ exposure to various cybersecurity threats, making it important to understand the determinants of cybersecurity behavior. This study examines the effects of cybersecurity knowledge and social media usage intensity on cybersecurity behavior, as well as the role of cybersecurity self-efficacy as both a direct predictor and a moderating variable. A quantitative approach was employed using a survey of 115 university students who actively use social media, and the data were analyzed using Structural Equation Modeling–Partial Least Squares (SEM-PLS). The results indicate that cybersecurity knowledge has a positive and significant effect on cybersecurity behavior (β = 0.309, t = 3.383, p < 0.01), while cybersecurity self-efficacy emerges as the strongest predictor of cybersecurity behavior (β = 0.479, t = 4.725, p < 0.001). In contrast, social media usage intensity does not show a significant effect on cybersecurity behavior (β = 0.003, t = 0.032, p > 0.05). Furthermore, moderation analysis reveals that cybersecurity self-efficacy does not moderate the relationships between cybersecurity knowledge or social media usage intensity and cybersecurity behavior. The structural model explains 58.3% of the variance in cybersecurity behavior (R² = 0.583). These findings suggest that cybersecurity behavior among social media users is more strongly driven by cognitive and psychological factors than by usage intensity alone. Practically, effective cybersecurity interventions should prioritize strengthening users’ cybersecurity knowledge and self-efficacy rather than merely restricting social media use.Keywords— Cybersecurity behavior; Cybersecurity knowledge; Self-efficacy; Social media usage intensity; SEM-PLS
Detecting Late Payments by Students with Random Forest and Particle Swarm Optimisation Hamid, Abdul; Sugiono, Sugiono; Prihatin, Titin; Destiana, Henny; Astrilyana, Astrilyana
Voteteknika (Vocational Teknik Elektronika dan Informatika) Vol 13, No 4 (2025): Voteteknika (Vocational Teknik Elektronika dan Informatika)
Publisher : Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/voteteknika.v13i4.135375

Abstract

Delays in tuition fee payments are a crucial problem commonly faced by private universities in Indonesia. This problem not only complicates campus financial management, but also has the potential to hinder the smooth running of student studies, such as leave of absence or discontinuation of studies. To date, there are not many predictive systems used to detect potential late payments early, especially the Random Forest (RF) model with Particle Swarm Optimisation (PSO). Therefore, this study aims to develop a predictive model for student payment delays by utilising the RF algorithm optimised using the PSO feature selection method. The Dataset used consists of 15,697 student data covering academic and administrative attributes. Pre-processing was carried out to convert categorical data into numerical form so that it could be processed by the classification algorithm. The evaluation results show that the RF model without optimisation produces an accuracy of 97.37%, precision of 100%, recall of 18.68%, and AUC of 0.825 ± 0.020. After feature selection with PSO, the model performance improved, with an accuracy of 98.83%, precision of 98.20%, recall of 25.40%, and AUC remaining stable at 0.825 ± 0.035. The most influential attributes in the classification were semester, leave status, studying while working, and father's occupation. The results of this study indicate that the combination of RF and PSO can produce an efficient and accurate prediction model, which can be used as a decision-making tool in higher education administration management.Keywords— Late Payments, Classification, PSO, Random Forest, Feature Selection.
The Effects of Coding Literacy and Computational Thinking on Student Digital Entrepreneurial Intentions: The Mediating Role of Coding Self-Efficacy Saputra, Hadi Kurnia; Ganefri, Ganefri; Yulastri, Asmar; Yuliana, Yuliana
Voteteknika (Vocational Teknik Elektronika dan Informatika) Vol 13, No 4 (2025): Voteteknika (Vocational Teknik Elektronika dan Informatika)
Publisher : Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/voteteknika.v13i4.137125

Abstract

Digital transformation has intensified the importance of digital entrepreneurship as a strategic pathway for university students. This study examines the effects of Coding Literacy and computational thinking on student Digital Entrepreneurial intentions, with coding self-efficacy serving as a mediating variable. A quantitative explanatory design was employed using survey data collected from 119 undergraduate students enrolled in an introductory coding course at Universitas Negeri Padang. Data were analyzed using Partial Least Squares–Structural Equation Modeling (PLS-SEM). The results indicate that Coding Literacy significantly influences coding self-efficacy (β = 0.414, p < 0.001) and Digital Entrepreneurial intentions (β = 0.474, p < 0.001). Computational thinking also shows a significant positive effect on coding self-efficacy (β = 0.340, p = 0.002), but does not exert a significant direct effect on Digital Entrepreneurial intentions (β = 0.074, p = 0.395). Furthermore, coding self-efficacy has a strong positive effect on Digital Entrepreneurial intentions (β = 0.313, p < 0.001). Mediation analysis reveals that coding self-efficacy partially mediates the relationship between Coding Literacy and Digital Entrepreneurial intentions (β = 0.130, p = 0.002), while fully mediating the relationship between computational thinking and Digital Entrepreneurial intentions (β = 0.107, p = 0.035). The model explains 49.3% of the variance in coding self-efficacy and 60.7% of the variance in Digital Entrepreneurial intentions. These findings highlight coding self-efficacy as a critical psychological mechanism that transforms computational competencies into Digital Entrepreneurial intentions, offering important implications for the design of coding-oriented entrepreneurship education in higher education.Keywords— Coding Literacy, computational thinking, coding self-efficacy, digital entrepreneurial intention, PLS-SEM
IoT-Based Chili Plant Watering Automation Using Fuzzy Logic Somantri, Nivika Tiffany; Riski Permana, Yoga; Charisma, Atik; Basuki, Sofyan; Ketut H, Ni; Setiawan, Antrisha D.
Voteteknika (Vocational Teknik Elektronika dan Informatika) Vol 13, No 4 (2025): Voteteknika (Vocational Teknik Elektronika dan Informatika)
Publisher : Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/voteteknika.v13i4.136001

Abstract

Like humans, plants need water for growth and development. Where water plays an important role in the process of photosynthesis and transpiration as the main component in the photosynthesis process. Chili plants require several nutrients such as water and sunlight to produce the best quality chili. In an effort to improve the efficiency of watering chili plants, this research proposes an Internet of Things (IoT) based watering automation system using fuzzy logic. The system is designed to measure several environmental parameters such as soil moisture, air temperature, and relative humidity level, and use the data to make the right watering decision. This system will make it easier for chili farmers to take care of their plants without having to pay attention to the plants all the time. In this research, the system is designed using fuzzy logic using an ESP8266 microcontroller so that the system can be integrated with the web. The fuzzy logic system will produce an output in the form of a watering requirement level that is in accordance with the current environmental conditions based on data from existing sensors. These results will be used to control the watering actuator in the form of a water pump. All existing data will be integrated with the web to find out the condition of chili plants. After testing and analyzing the tool that has been made, the tool functions properly in accordance with the design. The tool will only water when conditions require watering. Then for all data taken will be integrated with the existing web. The analysis shows that testing the ambient air temperature with 10 different experiments has an average error of 1.41%, while testing the ambient humidity has an average error of 0.14%. And for testing the height of the water storage area has an average error of 5.43%.Keywords— ESP8266, Internet of Things (IoT), Fuzzy Logic, Chili Plants.

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