Article Per Year (5 Year)
p-Index From 2020 - 2025
0.444
P-Index
This Author published in this journals
All Journal Jurnal Teknik Industri: Jurnal Keilmuan dan Aplikasi Teknik Industri Journal of Engineering and Technological Sciences
Abu, Mohd Yazid
Unknown Affiliation
Aerospace Engineering Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Electrical & Electronics Engineering Industrial & Manufacturing Engineering

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Application of the Mahalanobis-Taguchi System in Renal Profile of the Methadone Flexi Dispensing Program Mat Saad, Siti Khadijah; Mohd Zaini, Sri Nur Areena; Abu, Mohd Yazid
Jurnal Teknik Industri: Jurnal Keilmuan dan Aplikasi Teknik Industri Vol. 24 No. 1 (2022): June 2022
Publisher : Institute of Research and Community Outreach - Petra Christian University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.9744/jti.24.1.1-12

Abstract

Patients under the methadone Flexi dispensing (MFlex) program are required to do blood tests like renal profile. To ensure the patient has a kidney failure, a doctor assesses one parameter like creatinine. Unfortunately, the existing system does not have a stable ecosystem towards classification and optimization due to inaccurate measurement methods and lack of justification of significant parameters, which will influence the accuracy of diagnosis. The objective is to apply the Mahalanobis-Taguchi system (MTS) in the MFlex program. The data is collected at Bandar Pekan clinic with 34 parameters. Two types of MTS methods are used, such as RT-Method and T-Method, for classification and optimization. As a result, the RT-Method can classify healthy and unhealthy samples, while the T-Method can evaluate the significant parameters in terms of the degree of contribution. Fifteen unknown samples have been diagnosed with different positive and negative degrees of contribution to achieving lower MD. The best-proposed solution is type 5 of 6 modifications because it shows the highest MD value than others. In conclusion, a pharmacist from Bandar Pekan clinic confirmed that MTS could solve a problem in the classification and optimization of the MFlex program.
Prediction of Rainfall Trends using Mahalanobis-Taguchi System Jamil, Muhammad Arieffuddin Mohd; Abu, Mohd Yazid; Zaini, Sri Nur Areena Mohd; Aris, Nurul Haziyani; Pinueh, Nur Syafikah; Jaafar, Nur Najmiyah; Muhammad, Wan Zuki Azman Wan; Ramlie, Faizir; Harudin, Nolia; Sari, Emelia; Ghani, Nadiatul Adilah Ahmad Abdul
Journal of Engineering and Technological Sciences Vol. 56 No. 2 (2024)
Publisher : Directorate for Research and Community Services, Institut Teknologi Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/j.eng.technol.sci.2024.56.2.9

Abstract

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.
Co-Authors Aris, Nurul Haziyani Emelia Sari Ghani, Nadiatul Adilah Ahmad Abdul Harudin, Nolia Jaafar, Nur Najmiyah Jamil, Muhammad Arieffuddin Mohd Mat Saad, Siti Khadijah Mohd Zaini, Sri Nur Areena Muhammad, Wan Zuki Azman Wan Pinueh, Nur Syafikah Ramlie, Faizir Zaini, Sri Nur Areena Mohd