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All Journal IAIC Transactions on Sustainable Digital Innovation (ITSDI) Journal of Artificial Intelligence and Engineering Applications (JAIEA)
Saputra, Didi Rahmat
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Automotive Engineering Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Library & Information Science Materials Science & Nanotechnology

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Understanding Air Pollution Through Machine Learning: Predictive Analytics for Urban Management Saputra, Didi Rahmat; Nugroho, Hadi; Julianingsih, Dwi; Queen, Zabenaso
IAIC Transactions on Sustainable Digital Innovation (ITSDI) Vol 6 No 1 (2024): October
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/itsdi.v6i1.679

Abstract

Air pollution poses a critical challenge in urban areas, including Indonesia, significantly affecting public health and the environment. While machine learning (ML) has been used to predict air pollution levels, integrating ML with urban management strategies for actionable policy recommendations remains underexplored. This study employs structural equation modeling (SEM) using SmartPLS to analyze air pollution metrics, ML predictive analytics, urban management strategies, environmental data sources, and policy recommendations. Based on responses from 400 experts in environmental science and urban management, the findings reveal that ML-driven insights significantly enhance urban management strategies and policy effectiveness. The study concludes by providing evidence-based recommendations for policymakers to improve air quality in urban areas, emphasizing the importance of integrating ML and data-driven approaches into sustainable urban management. These findings contribute to addressing Indonesia urgent air pollution crisis and advancing urban sustainability.
A Smart Control System Model for Pharmaceutical and Medical Equipment Storage Using Fuzzy Logic and IoT Didi Rahmat Saputra; Fadhila Azzahra; Lahuddin; Ade Octaviansyah
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 4 No. 2 (2025): February 2025
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v4i2.866

Abstract

The primary goal of this study is to develop an innovative Smart Control System designed to maintain optimal temperature and humidity levels within a medical storage environment. By integrating Fuzzy Logic with Internet of Things (IoT) technology, we aim to enhance/optimize environmental control. Our experimental approach involved constructing an IoT-based prototype utilizing an Arduino Uno board equipped with high-precision temperature and humidity sensors, and DHT22 components for automated temperature and humidity stabilization. A fuzzy logic algorithm was employed/utilized to analyze real-time sensor data and generate/produce adaptive control outputs in response to environmental fluctuations. This smart control system is expected to significantly enhance/make a significant contribution to medical inventory management by reducing product damage and ensuring the safety of medical supplies. This research paves the way for future advancements in applying advanced technology for environmental control in healthcare settingsKeywords: Smart Control System, Fuzzy Logic, Internet Of Things (IoT)
Co-Authors Ade Octaviansyah Fadhila Azzahra Hadi Nugroho Julianingsih, Dwi Lahuddin Queen, Zabenaso