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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

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70356/josapen.v2i2.33

Abstract

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.
The design of an information system for managing teaching staff salaries Maastri, Adi; S, Ahmad
Journal of Computer Science Application and Engineering (JOSAPEN) Vol. 3 No. 1 (2025): JOSAPEN - January
Publisher : PT. Lentera Ilmu Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70356/josapen.v3i1.45

Abstract

Effective management of teaching staff salaries is crucial for maintaining operational efficiency and ensuring employee satisfaction within educational institutions. Traditional manual systems often suffer from inefficiencies, data inconsistencies, and security risks, highlighting the need for a dedicated solution tailored to salary management. This study addresses this gap by designing a comprehensive information system that automates and streamlines salary-related processes. Utilizing the waterfall development methodology, the system was structured through sequential phases of analysis, design, coding, testing, and implementation. The proposed system incorporates key features such as user authentication, hierarchical access control, and automated periodic salary updates. It accommodates multiple user roles, including teachers, financial operators, and administrators, ensuring secure and role-specific access to salary data. Use case and activity diagrams were developed to illustrate the system’s functionality, including login validation and the submission of salary update forms. By bridging the gap between theoretical frameworks and practical implementation, this study contributes a robust, user-friendly solution that enhances transparency and reduces administrative workload.
Workload Analysis System Optimization through the Integration of an Interactive Dashboard Karisa, Tiara; S, Ahmad
Journal of Computer Science Application and Engineering (JOSAPEN) Vol. 3 No. 2 (2025): JOSAPEN - July
Publisher : PT. Lentera Ilmu Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70356/josapen.v3i2.62

Abstract

In the era of digital transformation and bureaucratic reform, optimizing organizational performance in police institutions demands effective workload management. Workload analysis (Analisis Beban Kerja/ABK) is essential for ensuring fair task distribution that aligns with personnel capacity and competence. The Community Development Unit (Binmas) of the South Sumatra Regional Police plays a pivotal role in building public trust and cooperation. However, the absence of an integrated system to analyze workload distribution has resulted in potential inefficiencies, imbalanced task assignments, and increased work stress. Recent findings highlight a significant link between workload and stress levels among police personnel, emphasizing the urgency of system optimization. This study proposes the integration of an interactive dashboard to enhance the effectiveness of workload analysis in the Binmas Unit. Drawing on successful implementations such as the e-dikbangspes system and SI-ABK Precision application, the research underscores how dashboard technology can streamline data access, improve staffing decisions, and support the development of a more responsive organizational structure. By focusing on the Binmas Unit, this study aims to close the existing technological gap and contribute to improved personnel management and institutional performance through digital innovation in workload monitoring.