Smartics Journal is an international, peer-reviewed, open-access periodical devoted to the theory, design, and real-world deployment of technologies in electrical and electronics engineering, control systems, information systems, and computer science. Topics include artificial intelligence, software engineering, Internet of Things (IoT), and smart technologies. It publishes original research articles, technical notes, and review papers on topics such as power and energy systems, sensing and actuator networks, automation and control algorithms, enterprise and decision-support systems, and innovative applications of applied engineering. By fostering interdisciplinary collaboration between academia and industry, Smartics Journal seeks to accelerate the development and adoption of solutions that enhance efficiency, reliability, sustainability, and overall quality of life.
Journal Title
SMARTICS Journal
Language
Bahasa Indonesia or English (British/American)
Frequency
2 issues per year (April and October)
Editor in Chief
Abdul Aziz
Publisher
Faculty of Science and Technology - Universitas PGRI Kanjuruhan Malang
Scope
Electrical and Electronics Engineering, Control Systems, Information Systems, and Computer Science.
Topic
Artificial Intelligence, Software Engineering, Internet of Things (IoT), and Smart Technologies..
Vol. 11 No. 1 (2025): SMARTICS Journal (April 2025)
The reviewed articles highlight significant challenges that impact the quality, availability, and relevance of essential data for analysis. For instance, using the Multiple Linear Regression algorithm to predict gold prices is hindered by issues in variable selection and incomplete historical data. Sentiment analysis of the Grab application, employing Naïve Bayes and SVM, is limited by an imbalance in review numbers and complexities in text processing. Similarly, the societal impact of data limitations and ambiguous comments on public sentiment regarding Instagram's Free Nutritious Meal program is significant. The optimization of street lighting with Dialux Evo relies heavily on accurate geometric data and lighting parameters. Classifying stunting status in children with SVM faces challenges due to limited health data availability and quality. Additionally, the development of an inventory information system at CV Delta Power Listrindo is obstructed by reliability issues with stock data and integration from various sources. These challenges significantly hinder the accuracy and effectiveness of the analyses, emphasizing the urgent need for improvements to enhance the validity of the findings.
This issue has been available online since 30th April 2025 for the regular issue of Vol 11 No 1 (2025). All articles in this issue are authored/co-authored by
Published:
2025-05-05
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