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All Journal Statistika Jurnal Pengajaran MIPA Epsilon: Jurnal Matematika Murni dan Terapan Jurnal Pengajaran Matematika dan Ilmu Pengetahuan Alam Jurnal Online Pendidikan Matematika Kontemporer EurekaMatika (Jurnal Online Matematika S1) E-Dimas: Jurnal Pengabdian kepada Masyarakat QALAMUNA: Jurnal Pendidikan, Sosial, dan Agama International Research Journal of Business Studies (E-Journal) Jurnal Pengabdian Kepada Masyarakat (Mediteg) Jurnal Eurekamatika Euclid Kreano, Jurnal Matematika Kreatif Inovatif International Research Journal of Business Studies Journal on Mathematics Education Research
Entit puspita
Universitas Pendidikan Indonesia
Arts Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Environmental Science Industrial & Manufacturing Engineering Mathematics Social Sciences Transportation

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PERAMALAN KUALITAS UDARA KOTA BANDUNG DENGAN METODE FUZZY MAMDANI DAN ALGORITMA GENETIKA-FUZZY TIME SERIES Fidela Neysa Kaulika; Kartika Yulianti; Entit Puspita; Rini Marwati
EPSILON: JURNAL MATEMATIKA MURNI DAN TERAPAN Vol 19, No 1 (2025)
Publisher : Mathematics Study Program, Faculty of Mathematics and Natural Sciences, Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/epsilon.v19i1.14891

Abstract

Air quality is an important element that has a significant impact on human health and comfort as well as environmental sustainability. Bandung City, as one of the major cities in Indonesia, has experienced a significant increase in the volume of motorized vehicles and the number of industrial plants, which has led to a decrease in air quality. This research aims to forecast air quality in Bandung City using the fuzzy time series method optimized by a genetic algorithm. The parameters that determine air quality used include PM2.5 concentration, PM10 concentration, and NO2 concentration. In this research, fuzzy logic is applied to process the historical data of these parameters into output data in the form of air quality estimation by forming a Fuzzy Inference System (FIS) using fuzzy Mamdani. The results showed that the combined genetic algorithm and fuzzy time series method produced more accurate air quality forecasting than the fuzzy time series method alone, with a Mean Absolute Percentage Error (MAPE) accuracy rate of 8,52%, which is included in the excellent and successful forecasting category
Co-Authors Al Jupri Alfiyyati, Lydia Zayyani Alfiyyati, Lydia Zayyani Alpian, Ilham Alpian, Ilham Cece Kustiawan Cece Kustiawan Cucu Cahyati Dadang Juandi Dewi Rachmatin Didi Suryadi Endang Sri Rahayu Endang Sri Rahayu Eyus Sudihartinih Fidela Neysa Kaulika Fitriani agustina Hafizha, Zahra Ridha Ilyas, Isti Agustia Ima Nursaadah, Ima Imam Aji Nugroho Jaelani Rahman, Jaelani Julianto S.Si Kartika Yulianti Khusnul Novianingsih Lukman ., Lukman Majid, Abu Bakar Faris Abdul Maman Suherman Muhammad Rayana Kusumanegara Nar Herrhyanto Poppy Diara Prahesti, Danica Dwi Prahesti, Danica Dwi Prof Wahyudin Reka Septiani Rini Marwati Ririn Sispiyati Ryaneka Darmawan, Ryaneka Simamora, Yesi Kurnia Siti Nur Aisyah Surya Amami Pramuditya Tia Purniati Winata, Hilma Mutiara