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All Journal CommIT (Communication & Information Technology) Jurnal Teknologi Kesehatan
Afiyah Rifkha Rahmika
Universitas Hasanuddin
Computer Science & IT Dentistry Health Professions Nursing Public Health

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Web Server Load Balancing Mechanism with Least Connection Algorithm and Multi-Agent System Afiyah Rifkha Rahmika; Zulkifli Tahir; Ady Wahyudi Paundu; Zahir Zainuddin
CommIT (Communication and Information Technology) Journal Vol. 17 No. 2 (2023): CommIT Journal
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/commit.v17i2.8872

Abstract

Demands for information over the Internet massively increase through the continuous expansion of website applications. Therefore, generating powerful and efficient server architecture for web servers is a must to satisfy Internet users and avoid the overloaded system. The research focuses on developing a new mechanism for load balancing to distribute incoming HTTP requests in website applications by combining the Least Connection algorithm and Multi-Agent System (LC-MAS). The proposed mechanism distributes the request based on load condition and the fewest number of active connections. The research applies virtualization technology to build servers on this proposed mechanism. The architecture is built inside a physical server with Proxmox as virtualization management and Linux Debian 7.11 as an operating system. Then, the research is tested in two scenarios (LCMAS and LC) using 500, 1,000, and 1,500 requests. The performance of this proposed mechanism is measured through the values of average response time, throughput, and error percentage. The results show that the proposed mechanism (LC-MAS) distributes the workload more equally than LC, with an average response time for 1,500 requests of 1338.8 milliseconds, 20.07% error, and 125 transactions per second. The LC-MAS makes the website application performance much better when the request increases. The LC-MAS helps in the utilization of system resources and improves system robustness.
Clustering Analysis of Life Expectancy at Birth in Central Sulawesi Province: Trends and Patterns 2022-2024 Luvi Jayanto, Deni; Poonwong, Prakasit; Fadel, Mohamed Fal Mohamed; Rahmika, Afiyah Rifkha; Zuliana, Ni’matu; Kurniasari, Mia Ashari; Hernita, Ayu
Jurnal Teknologi Kesehatan (Journal of Health Technology) Vol. 21 No. 2 (2025): 2
Publisher : POLTEKKES KEMENKES YOGYAKARTA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29238/jtk.v21i2.2760

Abstract

Life Expectancy at Birth (LEB) is a critical indicator of health and well-being, and understanding its variations across regions is essential for effective health policy development. In Central Sulawesi, Indonesia, LEB has shown improvements over recent years. This study aims to explore life expectancy trends in Central Sulawesi from 2022 to 2024 using K-means clustering analysis. The study uses secondary data from the Central Statistics Agency (BPS), focusing on health indicators, education levels, healthcare access, and socio-economic conditions. The results revealed that most districts in Central Sulawesi fall into the high life expectancy category (C3), including urban areas like Palu and Morowali, reflecting better healthcare infrastructure and socio-economic conditions. However, districts such as Parigi Moutong, Tojo Una-Una, and Banggai Kepulauan remain in the lower life expectancy categories (C1 and C2), highlighting significant disparities. These findings underscore the need for targeted interventions to address the healthcare and socio-economic challenges in lower-performing areas. The study concludes that while Central Sulawesi has made progress in improving life expectancy, regional disparities remain. Policymakers should focus on enhancing healthcare access, infrastructure, and education in underdeveloped areas to reduce these gaps on addressing the challenges faced by districts in the C1 and C2 categories.
Co-Authors Ady Wahyudi Paundu Ayu Hernita Deni Luvi Jayanto Fadel, Mohamed Fal Mohamed Kurniasari, Mia Ashari Poonwong, Prakasit Zahir Zainuddin Zuliana, Ni’matu Zulkifli Tahir