Article Per Year (5 Year)
p-Index From 2020 - 2025
0.23
P-Index
This Author published in this journals
All Journal Journal of Software Engineering and Information System (SEIS)
Mirano, M. Fitter
Unknown Affiliation
Computer Science & IT Decision Sciences, Operations Research & Management Engineering

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
TEKNIK MACHINE LEARNING UNTUK ANALISA KLASIFIKASI KUALITAS UDARA: A REVIEW Alfian, Haris; Wahyuni, Sri; Revalino, Aqil; Mirano, M. Fitter; Rahmayana, Elsa; Mukhtar, Harun
Journal of Software Engineering and Information System (SEIS) Vol. 4 No. 2 (2024)
Publisher : Department of Information System Muhammadiyah University of Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/seis.v4i2.7617

Abstract

Air quality has a significant impact on human health and the environment, making its monitoring and classification extremely important. This review explores the application of machine learning techniques in analyzing and classifying air quality. Various methods such as decision trees, support vector machines, neural networks, and ensemble learning are evaluated to assess their effectiveness in processing complex and multidimensional air sensor data. This study also discusses challenges in data collection and preprocessing, selection of relevant features, and interpretation of classification results. Furthermore, this review identifies recent trends and future research opportunities in the use of machine learning to improve the accuracy and efficiency of air quality monitoring systems. The analysis results show that machine learning techniques have great potential to enhance our understanding of air quality dynamics and support better decision-making in environmental management
Co-Authors Alfian, Haris Harun Mukhtar Rahmayana, Elsa Revalino, Aqil Sri Wahyuni