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A hybrid fuzzy time series forecasting model with 4253HT smoother
No full textLink to publisher's homepage at https://amci.unimap.edu.my/Forecasting time series data is crucial for predicting upcoming observations, especially in the
market and business. Proper actions can be taken when there are some figures on future data,
which are predicted based on the previous data. The fusion of fuzzy time series in forecasting has
made forecasting using linguistic variables possible. However, the existence of extreme values in
the time series data has led to inaccurate forecasting since the values are too large or too small.
Hence, this paper proposes a hybrid fuzzy time series forecasting model with the 4253HT
smoother to reduce the uncertainty of data. In this study, students’ enrolment data at the
University of Alabama are implemented to illustrate the proposed hybrid forecasting model. The
results show that the proposed model improves the forecasting performance since the mean
square, root mean square, and mean absolute errors have been reduced. In the future, the
implementation of data smoothing using the 4253HT smoother can be used in other fuzzy time
series and intuitionistic fuzzy time series forecasting models
Factors affecting the educator’s ability on learners’ attraction in learning the programming subject specifically to the engineering students at UiTM Pulau Pinang
No full textLink to publisher's homepage at https://amci.unimap.edu.my/Teaching the subject of computer programming, especially to engineering students at higher education institutions, requires a comprehensive teaching approach, flexible pedagogy and hybrid teaching creativity to cultivate learners’ attraction and realise a realistic learning atmosphere. Research demonstrated that students are not attentive to learning the programming subject owing to several factors such as teaching materials and pedagogy, class size and programming difficulties. Hence, this paper concentrates on the factors related to educators contributing to the students’ attraction to learning the programming subject. This study was conducted at Universiti Teknologi MARA, Pulau Pinang Branch with a total of 241 students from the engineering schools responding to the online survey. The data collected were analysed using descriptive statistics and factor analysis. The reliability test or Cronbach’s Alpha values was performed before analysing the questionnaire. The IBM SPSS was used in evaluating the data collected from the questionnaire and through factor analysis, it was found that the educators’ roles affected the students’ attraction and understanding ability in learning the programming subject. The results obtained from factor analysis indicated that the personality traits of programming lecturers and instructional material (additional references) are the major contributors to the attraction of students toward programming subjects. This finding can help educators to improvise and innovate new teaching approaches to make the computer programming class fascinating and enhance the students’ learning
