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Journal : Electronic Integrated Computer Algorithm Journal

Time Efficiency and Cost-Benefit Analysis of New Student Admissions Mobile Application: A Case Study in A Vocational School Palembang Putri, Indah Pratiwi; Marcelina, Dona; Heryati, Agustina; Permatasari, Indah; Dopri
Electronic Integrated Computer Algorithm Journal Vol. 2 No. 1 (2024): VOLUME 2, NO 1: OCTOBER 2024
Publisher : Yayasan Asmin Intelektual Berkah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62123/enigma.v2i1.46

Abstract

This study aims to analyze the effectiveness of using an Android mobile application in the new student admission system at a vocational school. The application is designed to replace the manual registration methods, which were previously conducted through Google Forms and WhatsApp communication. By integrating push notifications using Firebase Cloud Messaging (FCM) and a MySQL database, the system enables real-time communication between administrators and prospective students, as well as the automation of admission data management. The Time Efficiency method is used to measure the time saved in the registration and notification process compared to the manual method. Meanwhile, the Cost-Benefit Analysis method is applied to evaluate the ratio between the system implementation costs and the benefits produced, such as reduced operational costs, increased registration speed, and improved administrative staff efficiency.
Comparative Study Towards Energy Efficiency in Wireless Sensor Networks Using Asynchronous Duty Cycle Putri, Indah Pratiwi; Marcelina, Dona; Cahyani, Septa
Electronic Integrated Computer Algorithm Journal Vol. 2 No. 2 (2025): VOLUME 2, NO 2: APRIL 2025
Publisher : Yayasan Asmin Intelektual Berkah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62123/enigma.v2i2.57

Abstract

Energy efficiency is a critical determinant in the design and operation of Wireless Sensor Networks (WSNs), as sensor nodes are typically powered by constrained battery resources. Asynchronous duty cycle mechanisms have emerged as a viable strategy to optimize energy consumption while preserving network functionality. This research presents a comparative analysis of multiple energy-efficient Medium Access Control (MAC) protocols, including Low-Energy Adaptive Clustering Hierarchy (LEACH), Energy-Efficient Sensor Routing (EESR), B-MAC, L-MAC, WiseMAC, and hybrid approaches such as TDMA-CSMA. Performance metrics such as energy efficiency, latency, throughput, and packet delivery ratio (PDR) are evaluated under varying network conditions. The findings indicate that AI-driven protocols, particularly those incorporating Artificial Neural Networks (ANN), significantly outperform conventional methodologies by enhancing cluster head selection, distributing energy load effectively, and extending network lifetime. Hybrid ADC emerges as the most robust solution, demonstrating an optimal trade-off between energy efficiency and network reliability across dynamic traffic scenarios. Furthermore, This research highlights the implications of integrating adaptive duty cycling with intelligent network optimization, underscoring its potential to enhance WSN sustainability. The results provide a comprehensive framework for refining MAC protocol architectures, offering actionable insights for optimizing next-generation WSN deployments.