Browsing by Author "Zul Hilmi Abdullah"
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Publication Issues And Challenges In Online Teaching And Learning During Movement Control Order (MCO)(INTI International University, 2020) ;Shaharudin Ismail ;Halimaton Sa’adiah AriffinZul Hilmi AbdullahCOVID-19 is an infectious disease caused by a newly discovered strain of coronavirus; a type of virus known to cause respiratory infections in humans. This new strain was unknown before December 2019. The first case of COVID-19 in Malaysia was detected on 24 January 2020. The Movement Control Order, commonly referred to as the MCO, has been announced by The Prime Minister on 16 March 2020. As the results, many non-essential sectors including higher education institutional (HEI) in Malaysia are close. The teaching and learning processes need to implement in a new norm – Online Teaching and Learning. Lecturers and students experience a new way of teaching and learning processes. This paper discusses issues and challenges faced by lecturers and students on Teaching and Learning process via Online Teaching and Learning mode during the Malaysia Movement Control Order (MCO). Keywords : Online Teaching and Learning, Movement Control Order (MCO). - Some of the metrics are blocked by yourconsent settings
Publication A New Efficient Credit Scoring Model For Personal Loan Using Data Mining Technique For Sustainability Management(UMT, 2022) ;Rabihah Md. Sum ;Waidah Ismail ;Zul Hilmi AbdullahNurul Fathihin Mohd Noor ShahCredit scoring models are used in decision-making processes to produce an accurate prediction of an applicant’s creditworthiness. A five-step credit scoring model for personal loans was developed using the seven-step credit scoring model by Siddiqi. It uses real data provided by a bank. This study aims to remove the unnecessary complexity of the credit scoring process. The five-step credit scoring model consists of data massaging, factor analysis, data mining modelling, credit scoring and post-modelling. To ensure accuracy, factors that were significant in determining the creditworthiness of applicants were used in the model, which are the type of installment, age, monthly expenses, job sector, payment method and income-to-finance ratio. Furthermore, by presenting a systematic and structured step for developing a credit scoring model, this study contributed to the research on credit scoring. Based on the findings of this study, banks may use this model to create their own credit scoring model to assess the creditworthiness of personal loan applicants. By managing risks with this model, banks can create a long-term solution for credit system management and aid in the decision-making process