Journal of Computer Science Application and Engineering
Introduction Journal of Computer Science Application and Engineering (JOSAPEN) is a peer-reviewed open-access journal organized by the Lentera Ilmu Publisher, Indonesia. The journal invites academicians (student and lecturer), researchers, and engineers to contribute to the development of theoretical and practice-oriented theories of Computer Science and Electrical Engineering, which covers some major areas such as 1) Artificial Intelligence, 2) Image and Data Processing, 3) Information Technology and System, 4) Internet of Things (IoT), 5) Microprocessor and Embedded System, 6) Electrical and Electronics Engineering, 7) Control systems and Robotics, 8) Computer Networks, 9) Information Security, and other related areas. This journal also invites reviewers and editors to be involved in the review process. This journal will become a discussion forum between the author and the reviewer and mediated by the editor. Focus And Scope The Journal of Computer Science Application and Engineering (JOSAPEN) publishes original papers in the fields of computer science, informatics engineering, and electrical, which cover, but are not limited to, the following scope: Computer Science, Computer Engineering and Informatics: Computer Architecture, Parallel and Distributed Computer, Pervasive Computing, Computer Network, Embedded System, Human—Computer Interaction, Virtual/Augmented Reality, Computer Security, Software Engineering (Software: Lifecycle, Management, Engineering Process, Engineering Tools and Methods), Programming (Programming Methodology and Paradigm), Data Engineering (Data and Knowledge level Modeling, Information Management (DB) practices, Knowledge Based Management System, Knowledge Discovery in Data), Network Traffic Modeling, Performance Modeling, Dependable Computing, High Performance Computing, Computer Security, Human-Machine Interface, Stochastic Systems, Information Theory, Intelligent Systems, IT Governance, Networking Technology, Optical Communication Technology, Next Generation Media, Robotic Instrumentation, Information Search Engine, Multimedia Security, Computer Vision, Information Retrieval, Intelligent System, Distributed Computing System, Mobile Processing, Next Network Generation, Computer Network Security, Natural Language Processing, Business Process, Cognitive Systems. Telecommunication and Information Technology: Modulation and Signal Processing for Telecommunication, Information Theory and Coding, Antenna and Wave Propagation, Wireless and Mobile Communications, Radio Communication, Communication Electronics and Microwave, Radar Imaging, Distributed Platform, Communication Network and Systems, Telematics Services and Security Network; Electronics: Electronic Materials, Microelectronic System, Design and Implementation of Application Specific Integrated Circuits (ASIC), VLSI Design, System-on-a-Chip (SoC) and Electronic Instrumentation Using CAD Tools, digital signal & data Processing, , Biomedical Transducers and instrumentation, Medical Imaging Equipment and Techniques, Biomedical Imaging and Image Processing, Biomechanics and Rehabilitation Engineering, Biomaterials and Drug Delivery Systems; Electrical and Power Engineering: Electrical Engineering Materials, Electric Power Generation, Transmission and Distribution, Power Electronics, Power Quality, Power Economic, FACTS, Renewable Energy, Electric Traction, Electromagnetic Compatibility, High Voltage Insulation Technologies, High Voltage Apparatuses, Lightning Detection and Protection, Power System Analysis, SCADA, Electrical Measurements; Instrumentation and Control Engineering: Optimal, Robust and Adaptive Controls, Non Linear and Stochastic Controls, Modeling and Identification, Robotics, Image Based Control, Hybrid and Switching Control, Process Optimization and Scheduling, Control and Intelligent Systems, Artificial Intelligent and Expert System, Fuzzy Logic and Neural Network, Complex Adaptive Systems.
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Enhanced Dynamic Programming Approaches for Efficient Solutions to the Traveling Salesman Problem
Anson, Adriel Moses
Journal of Computer Science Application and Engineering (JOSAPEN) Vol. 2 No. 2 (2024): JOSAPEN - July
Publisher : PT. Lentera Ilmu Publisher
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DOI: 10.70356/josapen.v2i2.32
This study aims to enhance dynamic programming techniques for efficiently solving the Traveling Salesman Problem, a fundamental combinatorial optimization challenge. Given its NP-hard classification, traditional exact algorithms become computationally infeasible as the problem size increases. The research revisits foundational dynamic programming principles, notably the Held-Karp algorithm, and identifies existing limitations. The study begins with a comprehensive literature review, followed by an analysis of the dynamic programming challenges specific to TSP. Novel algorithms are then developed, implemented, and rigorously tested against benchmark instances. Performance evaluation is conducted using metrics such as execution time, memory usage, and solution optimality across different problem sizes. Results demonstrate significant improvements in efficiency and scalability, with enhanced algorithms achieving optimal solutions in reduced time and computational resource usage. However, the exponential growth in complexity remains a challenge for larger instances. The study concludes with recommendations for future research, focusing on further algorithmic refinements and exploring hybrid approaches to address large-scale TSPs.
The Effectiveness of Smart Waste Recycling Management Applications
Sulistio, Beni;
S, Ahmad
Journal of Computer Science Application and Engineering (JOSAPEN) Vol. 2 No. 2 (2024): JOSAPEN - July
Publisher : PT. Lentera Ilmu Publisher
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DOI: 10.70356/josapen.v2i2.33
This study evaluates the effectiveness of smart waste recycling management applications, which leverage IoT sensors, AI algorithms, and big data analytics to enhance waste management efficiency. Analyzing data from five regions, it is evident that these technologies have significantly improved waste collection efficiency and recycling rates. IoT sensors optimized collection routes, resulting in a 15-23% increase in efficiency and a 10-17% rise in recycling rates, while reducing operational costs by $9,000 to $13,000 per month. AI algorithms enhanced sorting accuracy and recycling rates, particularly in regions with diverse waste types, leading to an 18% improvement in efficiency and up to a 20% increase in recycling rates. Big data analytics facilitated better decision-making and long-term planning, contributing to a 15-20% efficiency boost and a 12-17% rise in recycling rates. These findings underscore the potential of smart waste management technologies to transform waste management practices, highlighting the need for continued investment and expansion of these systems.
Analysis for Technology Acceptance of Internal Apps at Regency Level in Indonesia
Ines
Journal of Computer Science Application and Engineering (JOSAPEN) Vol. 2 No. 2 (2024): JOSAPEN - July
Publisher : PT. Lentera Ilmu Publisher
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DOI: 10.70356/josapen.v2i2.34
This study investigates the factors influencing technology acceptance of internal applications within regency-level government institutions in Indonesia, utilizing the Technology Acceptance Model (TAM). The analysis focuses on key variables including perceived usefulness (PU), perceived ease of use (PEOU), attitude toward using (ATU), behavioural intention to use (BITU), and actual system usage (ASU). The results reveal strong correlations across all variables, indicating a high level of acceptance and positive engagement with the apps among government employees. Additionally, reliability testing shows high internal consistency, with Cronbach's Alpha values exceeding 0.9 for most variables, confirming the stability and dependability of the measurements. These findings suggest that government employees generally find the internal apps beneficial and user-friendly, leading to favorable attitudes and continued usage. This research provides valuable insights that can inform the development and implementation of future digital initiatives at the regency level in Indonesia.
Innovative Solutions for High School Inventory Management: An Information System Approach
Frida
Journal of Computer Science Application and Engineering (JOSAPEN) Vol. 2 No. 2 (2024): JOSAPEN - July
Publisher : PT. Lentera Ilmu Publisher
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DOI: 10.70356/josapen.v2i2.35
This paper explores the development and implementation of an innovative information system designed to enhance inventory management in high schools. Traditional inventory methods, often reliant on manual tracking, are prone to errors and inefficiencies, which can hinder resource allocation and decision-making. By adopting an information system approach, schools can automate processes, improve data accuracy, and provide real-time access to inventory information. The study outlines key features such as real-time tracking, automated alerts, and role-based access controls, which are critical to the system's effectiveness. The results demonstrate significant improvements in workflow efficiency, data accuracy, and overall resource management. Despite the challenges associated with system implementation, including cost and training requirements, the benefits make this approach a compelling solution for modernizing high school inventory practices. The paper concludes with recommendations for broader adoption and further research to optimize these systems for educational settings.
Enhancing Hospital Efficiency through IoT and AI: A Smart Healthcare System
Ahmad, Asiyah
Journal of Computer Science Application and Engineering (JOSAPEN) Vol. 2 No. 2 (2024): JOSAPEN - July
Publisher : PT. Lentera Ilmu Publisher
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DOI: 10.70356/josapen.v2i2.36
In the rapidly evolving healthcare landscape, the integration of Internet of Things (IoT) and Artificial Intelligence (AI) is transforming hospital efficiency. This study explores how these technologies can enhance hospital operations by optimizing resource management, improving patient care, and reducing operational costs. IoT devices enable real-time monitoring of patient health and hospital assets, facilitating timely interventions and maintenance. Concurrently, AI-driven analytics improve decision-making processes by predicting patient needs and optimizing resource allocation. The synergy between IoT and AI creates a smart healthcare system that offers advanced data processing and actionable insights, leading to improved patient outcomes. Despite challenges such as data privacy concerns and infrastructure investments, the potential benefits of IoT and AI in healthcare are substantial. This paper presents a comprehensive framework for integrating these technologies into hospital operations, highlighting their impact on efficiency and patient care. The findings suggest that IoT and AI can significantly enhance hospital performance, paving the way for a smarter healthcare system.