Technical and Vocational Education and Training (TVET) is an education system that delivers necessary information, skills, and attitudes related to work or self-employment. However, the TVET program is not preferred by most Malaysian students due to several factors such as students’ interest, parental influence, employers’ negative impression, facility in vocational institutions, inexperienced TVET instructors, and society’s negative perception. Consequently, it raises the issue of skilled workers shortage. The gravest threat will be far-reaching, pushing our economy into depreciation. Therefore, it is important to identify the students’ traits and interests before conducting further investigation to turn and thrive in this phenomenon. This study aims to utilise several classifiers (Decision Tree, Neural Network, Logistic Regression and Naïve Bayes) to predict students’ inclination to join TVET programmes. A total of 428 secondary school students from Kedah, Malaysia, are chosen as our survey respondents. The best classifier is determined according to the lowest misclassification rate. The findings revealed that the Decision Tree-based Gini Index with three branches prevail against other classifiers with a misclassification rate of 0.1938. Therefore, the classifier could act as a steer for the Kedah Department of Education (DOE), related parties, and the TVET agency in implementing effective strategies to enliven and inspire students to join TVET programs.
Technical and Vocational Education and Training (TVET) is one of the ways to produce skilled workers who are crucial to drive the economic of our country. Despite several strategies made by the government, TVET still does not seem to be a popular choice among secondary school students when choosing their tertiary education pathway. Hence, this study aims to analyse the students’ perception of TVET based on the demographic analysis of gender and current study stream in school in Kedah. The sole focus is on the students who are not enrolling in TVET so that more reasons why they are not likely to join TVET can be discovered. For the data collection process, 428 secondary school students from Kedah are chosen as the respondents. Descriptive analysis of the data is performed using Microsoft Excel and Google Data Studio. The results reveal that male and female students have positive perceptions of TVET even though they do not enrol in TVET. Furthermore, most students from various streams also show their interest in TVET. However, the majority of students are undecided about the assertions in the questionnaire due to unfamiliarity with this course. As a result, it is recommended that the government continue promoting TVET among secondary school students hence preparing them with specific skills that meet the current industrial requirement.
The advent of Coronavirus-19 (COVID-19) has created a new threat in terms of economy and life. Frankly, the adverse effects of COVID-19 can put our life at risk if we are contaminated. The recent promising cases in Malaysia have certainly intensified from day to day, going from bad to worse. The primary factor that causes the raising problem of COVID cases is the absence of cooperation between Malaysian and government. This research aims at visualizing the current situation of COVID-19 and thus raising consciousness among Malaysians to solve this dilemma. To fulfill the objectives, there are two stages of processes need to be performed. Using the dataset from Internet, the first section would use Microsoft Excel to create visualization tools such as a pie chart and a line chart. Next, the second part will scrap the Twitter data to explore how Malaysians are aware of COVID by using “Twint” function in Python software. The finding reveals that current COVID situation in Malaysia is in a severe stage since the chart shows that it has an exponential growth. Moreover, the Twitter activity has indicated that the people are not paying attention to the COVID topic shared by Malaysia Ministry of Healthy (MOH) Consequently, the new positive cases increase dramatically after September 2020 in Malaysia. In conclusion, the people are more concern to the COVID news from MOH during the implementation of MCO and CMCO. The people lose concern when the number of cases dropped or the MCO and CMCO is ended.
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