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p-Index From 2021 - 2026
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All Journal Al-Buhuts (e-journal) Malcom: Indonesian Journal of Machine Learning and Computer Science
Nurhaedar, Nurhaedar
Unknown Affiliation
Computer Science & IT Economics, Econometrics & Finance

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Barang Rongsokan dan Peluang Bisnis Berbasis Ekonomi Sirkular Di Sulawesi Selatan: Tinjauan Literatur Kualitatif Tahalua, Imran; Nurhaedar, Nurhaedar; Azwar Wijaya Syam; Muhammad Dakhri; Muh. Yasin Noor W.K
Al-Buhuts Vol. 21 No. 1 (2025): Al-Buhuts
Publisher : Institute Agama Islam Negeri (IAIN) Sultan Amai Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30603/ab.v21i1.6468

Abstract

This study aims to analyze the potential and challenges of scrap-based business practices within the framework of the circular economy in South Sulawesi Province. The method employed is a qualitative approach using a systematic literature review. Data sources were obtained from relevant national and international academic publications, policy documents, and institutional reports related to waste management, the informal sector, and circular economy implementation in Indonesia, particularly in South Sulawesi. The literature analyzed spans the past five years (2020–2025) and was selected based on thematic relevance, source credibility, and its contribution to theoretical and policy development. The findings indicate that the most dominant types of scrap materials within the informal supply chain include ferrous metals, PET and HDPE plastics, and electronic waste. Informal actors such as waste pickers, local collectors, and micro-enterprises play a central role in the collection and distribution of these materials. However, they face various structural barriers, including limited access to technology, finance, legal recognition, and persistent social stigma. The study also finds that the lack of institutional synergy and spatial mapping hinders the logistical efficiency of local recycling systems. This research highlights the need for integrating affirmative policies, enhancing environmental literacy, and fostering community-based social innovations as foundational strategies to build an inclusive, resilient, and sustainable circular economy ecosystem in South Sulawesi.
Performance Analysis of Google Cloud Platform for Web-Based Applications Amiruddin, Amiruddin. A; Rahmawati, Rahmawati; Nurhaedar, Nurhaedar; Musa, Musa
MALCOM: Indonesian Journal of Machine Learning and Computer Science Vol. 6 No. 1 (2026): MALCOM January 2026
Publisher : Institut Riset dan Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57152/malcom.v6i1.2351

Abstract

Selecting an appropriate cloud computing service remains a major challenge in web-based application development, as it directly affects performance, scalability, security, and operational costs. Google Cloud Platform (GCP) offers multiple computing services, yet empirical comparisons among its core services are still limited. This study aims to evaluate and compare the performance of Compute Engine, App Engine, and Kubernetes Engine in hosting web-based applications. A quantitative experimental approach was employed using a Node.js and PostgreSQL-based e-commerce application, tested under various workload scenarios using Apache JMeter. Performance metrics, including response time, throughput, latency, scalability, reliability, security, and cost, were analyzed. The results indicate that Compute Engine provides stable performance for predictable workloads, App Engine delivers low latency with higher operational costs, and Kubernetes Engine offers the best scalability and resource efficiency. Performance optimization techniques such as caching and CDN integration further improved API responsiveness. This study concludes that Kubernetes Engine is the most suitable choice for large-scale and dynamic web applications. Optimal GCP service selection should align with workload characteristics and organizational requirements.
Co-Authors Amiruddin, Amiruddin. A Azwar Wijaya Syam Muh. Yasin Noor W.K MUhammad Dakhri Musa Musa Rahmawati, Rahmawati Tahalua, Imran