Prediction of Rainfall Trends using Mahalanobis-Taguchi System

Muhammad Arieffuddin Mohd Jamil; Mohd Yazid Abu; Sri Nur Areena Mohd Zaini; Nurul Haziyani Aris; Nur Syafikah Pinueh; Nur Najmiyah Jaafar; Wan Zuki Azman Wan Muhammad; Faizir Ramlie; Nolia Harudin; Emelia Sari; Nadiatul Adilah Ahmad Abdul Ghani

doi:10.5614/j.eng.technol.sci.2024.56.2.9

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Muhammad Arieffuddin Mohd Jamil Faculty of Manufacturing and Mechatronics Engineering Technology, Universiti Malaysia Pahang Al-Sultan Abdullah, 26600 Pekan, Pahang, Malaysia , Malaysia
Mohd Yazid Abu
myazid@umpsa.edu.my
Faculty of Manufacturing and Mechatronics Engineering Technology, Universiti Malaysia Pahang Al-Sultan Abdullah, 26600 Pekan, Pahang, Malaysia , Malaysia
Sri Nur Areena Mohd Zaini Faculty of Manufacturing and Mechatronics Engineering Technology, Universiti Malaysia Pahang Al-Sultan Abdullah, 26600 Pekan, Pahang, Malaysia , Malaysia
Nurul Haziyani Aris Faculty of Manufacturing and Mechatronics Engineering Technology, Universiti Malaysia Pahang Al-Sultan Abdullah, 26600 Pekan, Pahang, Malaysia , Malaysia
Nur Syafikah Pinueh Faculty of Manufacturing and Mechatronics Engineering Technology, Universiti Malaysia Pahang Al-Sultan Abdullah, 26600 Pekan, Pahang, Malaysia , Malaysia
Nur Najmiyah Jaafar Faculty of Manufacturing and Mechatronics Engineering Technology, Universiti Malaysia Pahang Al-Sultan Abdullah, 26600 Pekan, Pahang, Malaysia , Malaysia
Wan Zuki Azman Wan Muhammad Institute of Engineering Mathematics, Universiti Malaysia Perlis, Kampus Pauh Putra, Perlis 02600 Arau, Malaysia, Malaysia
Faizir Ramlie Razak Faculty of Technology and Informatics, Department of Mechanical Engineering, Universiti Teknologi Malaysia, Jalan Sultan Yahya Petra, 54100 Kuala Lumpur, Malaysia, Malaysia
Nolia Harudin Universiti Tenaga Nasional, 43000 Kajang, Selangor, Malaysia, Malaysia
Emelia Sari Universitas Trisakti, Faculty of Industrial Technology, Department of Industrial Engineering, 11440, Kyai Tapa No 1, West Jakarta, Indonesia, Indonesia
Nadiatul Adilah Ahmad Abdul Ghani Faculty of Civil Engineering Technology, Universiti Malaysia Pahang Al-Sultan Abdullah, Lebuh Persiaran Tun Khalil Yaakob, 26300 Pahang, Malaysia , Malaysia

Vol. 56 No. 2 (2024)

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Published April 30, 2024

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Full comprehension of precipitation patterns is crucially needed, especially in Pekan, a district in Pahang, Malaysia. The area is renowned for its elevated levels of precipitation, making it imperative to precisely categorize and enhance the analysis of rainfall patterns to facilitate effective resource allocation, agricultural productivity, and catastrophe readiness. The variability of rainfall patterns is contingent upon geographical location, necessitating the collection of a comprehensive data set that includes several characteristics that influence precipitation to make reliable predictions. Data were collected from the Vantage Pro2 weather station, which is located on the UMP Pekan campus. This study used the RT method to classify rainfall and T-Method 1 to determine the degree of contribution of each parameter. Significant parameters were validated using a data set from the same type of weather station but in a different district. The results showed that the Mahalanobis-Taguchi Bee Algorithm (MTBA) is more effective than the Mahalanobis-Taguchi System (MTS) in finding the significant parameters, but the parameters were a subset of MTS Teshima. Finally, the validation with T mean-based error (Tmbe) using Mean Absolute Error (MAE) revealed a pattern of errors to provide insight to find the significant parameters of MTS.

Jamil, M. A. M., Abu, M. Y., Zaini, S. N. A. M., Aris, N. H., Pinueh, N. S., Jaafar, N. N., Muhammad, W. Z. A. W., Ramlie, F., Harudin, N., Sari, E., & Ghani, N. A. A. A. (2024). Prediction of Rainfall Trends using Mahalanobis-Taguchi System. Journal of Engineering and Technological Sciences, 56(2), 287–303. https://doi.org/10.5614/j.eng.technol.sci.2024.56.2.9

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