Application of Fuzzy TOPSIS in selecting poverty case among UiTM Perlis students due to COVID-19 pandemic / Sharifah Fhahriyah Syed Abas and Nurulain Nabilah Muhamad Fauzuk

• Main Authors: Syed Abas, Sharifah Fhahriyah (Author), Nurulain Nabilah, Muhamad Fauzuk (Author)
• Format: Article
• Language: English
• Published: UiTM Cawangan Perlis, 2022.
• Subjects: Poor. Poverty; Fuzzy logic; Article
• Online Access: Get fulltext; View Fulltext in UiTM IR

 The effects of Covid-19 are not only in terms of health, but many things arise along with its existence. One of them is poverty. Due to this, Universiti Teknologi MARA(UiTM) has taken the initiative to offer several financial aids to the affected students. However, the students must fill in the application form to obtain the aid. They need to provide the supporting documents such as parents pay slip, information on family dependent and so on, which will be inspected, graded and selected by the committee to determine the qualification for the financial aids. Due to this, it will be a long process to select the rightful applicants, which involves a significant length of time as it consisted of hundreds of applicants. Hence, the aim of this study is to select and rank the most eligible candidates among UiTM Perlis students with fairness, fast and accurate manner. In this study, the Fuzzy Technique for Others Preference by Similarity to Ideal Solution (TOPSIS) method was used to solve the problem. The model was run using Microsoft Excel. The selection of UiTM Perlis students were based on a set of criteria that had been predetermined which includes family income, occupation and the number of dependent in the family. The findings of the study showed that from 35 samples of UiTM Perlis students, the highest-ranking was student 35 (S35) with 1.0000 relative closeness. Meanwhile, the lowest ranking was student 30 (S30) with 0.6478 relative closeness. It is also shown that all samples are qualified to receive financial aid due to sufficient allocation amount provided by UiTM Perlis. As a result, the mistakes during the selection process can be reduced by using this method compared to manual selection. Thus, making it easier and faster to channel the aid. All in all, it has been demonstrated that this method is very suitable to be used in this study.