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Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control
Published by Universitas Muhammadiyah Malang
ISSN : 25032259     EISSN : 25032267     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control was published by Universitas Muhammadiyah Malang. journal is open access journal in the field of Informatics and Electrical Engineering. This journal is available for researchers who want to improve their knowledge in those particular areas and intended to spread the knowledge as the result of studies. KINETIK journal is a scientific research journal for Informatics and Electrical Engineering. It is open for anyone who desire to develop knowledge based on qualified research in any field. Submitted papers are evaluated by anonymous referees by double-blind peer review for contribution, originality, relevance, and presentation. The Editor shall inform you of the results of the review as soon as possible, hopefully within 4 - 8 weeks. The research article submitted to this online journal will be peer-reviewed at least 2 (two) reviewers. The accepted research articles will be available online following the journal peer-reviewing process.
Arjuna Subject : -
Articles 536 Documents
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Hybridization of PSO-SSA for Photovoltaic System MPPT Under Dynamic Irradiation and Temperature Iqbal, Muhammad; Suyono, Hadi; Wijono
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 11, No. 1, February 2026 (Article in Progress)
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v11i1.2410

Abstract

Maximum Power Point Tracking (MPPT) has become an important area of research to optimize the power generated by photovoltaic (PV) systems, particularly under various configurations such as series and parallel. Conventional methods including Perturb and Observe (P&O) and Incremental Conductance (InC) often fail under dynamic or partial shading conditions, while metaheuristic algorithms such as Particle Swarm Optimization (PSO) and Salp Swarm Algorithm (SSA) provide global optimization but still suffer from slow convergence and power oscillations. This study proposes a hybrid MPPT approach by combining PSO and SSA to overcome these limitations. The algorithm was implemented in MATLAB/Simulink and tested under 96 scenarios covering series and parallel configurations with irradiance and temperature variations that change both suddenly (<1 s) and gradually (>1 s). Simulation results demonstrate that the hybrid PSO–SSA consistently achieves faster convergence compared to standalone PSO or SSA, with an average convergence time of 0.286 s in series configuration (25–36% faster) and 0.282–0.284 s in parallel configuration, while achieving comparable power output to PSO. Overall, the proposed hybrid PSO–SSA algorithm provides a faster, more adaptive, and robust MPPT strategy under realistic PV operating conditions, contributing to reducing energy losses in fluctuating environments.
YOLOv9-Assisted Vision System for Health Assessment in Poultry Using Deep Neural Networks Risma, Pola; Prasetyo, Tegar; Muhammad Amri , Yahya
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 11, No. 1, February 2026 (Article in Progress)
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v11i1.2414

Abstract

Poultry farming represents one of the fastest growing sectors in global food production, yet disease outbreaks, high mortality, and labor shortages continue to threaten its sustainability. Conventional health monitoring methods based on visual inspection are time-consuming, subjective, and inadequate for early anomaly detection. In response, computer vision and deep learning have emerged as transformative tools for livestock management. While prior implementations of the YOLO object detection family, such as YOLOv5 and YOLOv8, have achieved notable success, their performance often deteriorates in dense flocks, low-light conditions, and occlusion-prone environments. This study introduces a YOLOv9-assisted vision framework tailored for poultry health assessment in commercial farm settings. The system integrates smart cameras with edge computing to enable real-time detection of behavioral and physiological anomalies without dependence on high-bandwidth or cloud-based resources. A dataset of 903 annotated poultry images, categorized into healthy and sick classes, was employed for model development. The trained model achieved 88.7% precision, 97% recall, an F1-score of 0.82, and a mAP@0.5 of 0.88, demonstrating robustness under variable illumination, bird occlusion, and high-density environments. Comparative evaluation confirmed that YOLOv9 provides a superior balance of accuracy, generalization, and computational efficiency relative to YOLOv8–YOLOv11, supporting practical deployment on edge devices. Limitations include the binary scope of health classification and reliance on a single dataset. Future directions involve extending the framework to multi-class disease recognition, cross-dataset validation, behavior-based temporal modeling, and multimodal fusion, advancing predictive analytics and welfare-oriented poultry farming.
From Digital Literacy to Public Trust: The Strategic Role of E-Government Service Quality Husin; Hakim, Lukman; Huda, Choirul
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 11, No. 1, February 2026 (Article in Progress)
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v11i1.2418

Abstract

The transformation of public services in the digital era necessitates a synergistic alignment between e-governance practices and the digital competencies of the community to ensure services that are both high in quality and user satisfaction. This study investigates the effect of e-governance and digital literacy on public satisfaction, with digital service quality serving as a mediating variable. The research focuses on the utilization of the S-Kepuharjo village digital service platform. Employing a quantitative approach, data were collected through a survey of 385 respondents and analyzed using Structural Equation Modeling (SEM) with the AMOS software. The findings reveal that e-governance has a significant impact on satisfaction, both directly and indirectly via service quality. On the other hand, digital literacy does not directly influence satisfaction but exerts a significant indirect effect when mediated by digital service quality. The study confirms that service quality acts as a critical intermediary that links governance to user satisfaction. These results highlight that the success of village-level digital transformation is largely determined by the responsiveness and effectiveness of digital services. Accordingly, enhancing the inclusiveness, accessibility, and user-oriented nature of these services is essential for fostering public satisfaction and engagement in the digital landscape.
Website Quality Evaluation of OKE Garden Using WebQual, Marketing Mix, and Importance-Performance Analysis Faiqoh, Nadya Kamilia; Popong Nurhayati; Heny Kuswanti Suwarsinah
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 11, No. 1, February 2026 (Article in Progress)
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v11i1.2420

Abstract

The rapid advancement of digital technologies has significantly impacted various service sectors, including the garden landscape industry. In response to this development, OKE Garden has implemented a website-based e-commerce platform aimed at improving service accessibility and operational efficiency. This study seeks to evaluate the usability and service quality of this digital platform from the user’s perspective by adopting the Technology Acceptance Model (TAM) as an analytical framework. Within this framework, Perceived Ease of Use (PEOU) is assessed using WebQual 4.0 indicators, while Perceived Usefulness (PU) is measured through the four elements of the marketing mix, namely Product, Price, Place, and Promotion. To analyze the alignment between user expectations and actual service performance, the Importance-Performance Analysis (IPA) method was utilized. Data were obtained from 57 respondents in the Greater Jakarta area (Jabodetabek), primarily first-time users who had previously interacted with the OKE Garden website. Prior to analysis, the data underwent validity and reliability testing to ensure robustness. The findings show that users rated the importance of website attributes higher than their actual performance, indicating a gap that highlights areas requiring improvement. Several key indicators were identified, including ease of navigation, clarity of information, data security, and pricing strategy, which were categorized in Quadrant I (high importance, low performance), indicating areas that require immediate attention. Overall, the results suggest that while digital technology adoption has taken place, user acceptance remains suboptimal. Therefore, a more comprehensive enhancement of usability and service quality is necessary to meet user expectations and improve overall satisfaction.
Performance Analysis of Estimation position a Quarter-Car Suspension System using Kalman-Bucy as a State Observer Mursyitah, Dian; Faizal , Ahmad; Maria, Putus Son; Zarory, Hilman; Adriansyah, Alpin
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 11, No. 1, February 2026 (Article in Progress)
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v11i1.2433

Abstract

This study explores the implementation of the Kalman-Bucy observer for state estimation in a quarter-car suspension system operating under various real-world conditions. The research focuses on evaluating the observer’s performance in the presence of road surface disturbances such as speed bumps, speed humps, and potholes, combined with stochastic noise and parameter variations. To test its robustness, the system is subjected to Gaussian white noise with an intensity of 10 percent in both the process and measurement signals. Sensitivity analysis is also carried out by varying the vehicle mass between 400 kilograms in unloaded conditions and 600 kilograms when fully loaded, simulating different passenger and cargo scenarios. Simulation results demonstrate that the Kalman-Bucy observer consistently provides accurate and stable estimations of vehicle position, even in noisy and dynamically changing environments. The observer effectively filters out noise and accurately tracks the system’s dynamic response across all test scenarios. The main contributions of this research include the development of a mathematical model for a quarter-car suspension system that incorporates realistic road disturbance conditions, the formulation and implementation of the Kalman-Bucy filter for continuous-time state estimation in this system, and a thorough evaluation of the filter’s effectiveness under varying noise and disturbance conditions through MATLAB-based simulations. To further evaluate the practical value of the Kalman-Bucy observer, it is integrated into a PID control framework. The combined PID and Kalman-Bucy setup is then compared with a conventional PID controller that operates using raw measurement signals. The results indicate that incorporating the Kalman-Bucy observer significantly improves control performance by reducing oscillations, improving settling time, and enhancing the system’s ability to reject disturbances. Overall, the Kalman-Bucy observer proves to be a reliable and efficient method for state estimation and control enhancement in active suspension systems, showing strong potential for real-world automotive applications.
Weighted ANOVA and Mutual Information for Enhanced Intrusion Detection System I Gede Teguh Satya Dharma; I Wayan Rizky Wijaya; I Made Agus Oka Gunawan; Made Pradnyana Ambara
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 11, No. 1, February 2026 (Article in Progress)
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v11i1.2448

Abstract

The rapid escalation in the sophistication of network attacks has exposed the limitations of traditional Intrusion Detection Systems (IDS). While machine learning has shown great promise in enhancing IDS performance, its success often hinges on the effectiveness of feature selection. Standard feature selection techniques, however, struggle in cybersecurity applications due to the highly imbalanced nature of network traffic datasets. In such settings, minority attack classes, though critical, are often overshadowed by majority classes, leading to reduced detection of rare intrusions. To address this challenge, we propose a hybrid feature selection framework that integrates Analysis of Variance (ANOVA) and Mutual Information (MI) with a novel class-frequency weighting mechanism. This weighting scheme adjusts the relevance score of each feature according to the distribution of classes, ensuring that features associated with rare attacks are more strongly emphasized during the selection process. We evaluate our method on the UNSW-NB15 dataset using a Support Vector Machine classifier. The results show that our approach achieves substantial gains in recall for underrepresented classes while simultaneously reducing feature dimensionality and maintaining efficiency. By improving the visibility of features tied to minority attacks, the proposed framework provides a more balanced and reliable solution for modern IDS. This contribution advances the detection of rare but impactful threats and highlights a scalable pathway for building more resilient cybersecurity defenses.

Page 54 of 54 | Total Record : 536

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