This paper presents the development of a mobile application with contextual information delivery using proximity beacon.The aim of this study is to help the tourism industry in attracting more visitors. To execute the functions, a prototype was developed and based at Melaka Zoo, Malaysia. There are two mobile technologies used in the development of the prototype namely geofence and proximity beacon using Bluetooth. There are three phases involved in developing the prototype; feasibility study and requirement analysis, design, and development and testing. The functionality and the network performance of the developed application was successfully tested and validated. All designed and developed functions of the application were working correctly. In addition, the network performance of geofence and beacon were acceptable. Further work is recommended to ensure that the application can be applied successfully in other domains such as smart campus, smart home and smart mall applications. Besides, the development can be extended to the iOS platform.

A case study was carried out on students who were being exposed to some theoretical concepts of the correlation and regression topics to investigate their ability to compute and interpret the Pearson's correlation coefficient and the slope of regression. The findings revealed that a low percentage of students (19.43%) successfully completed their interpretation of correlation coefficient and 33.18% of the students managed to interpret the computed value of regression slope completely. It was also found that the students' ability to interpret regression slope was significantly associated with the ability to interpret the correlation coefficient correctly. It is hoped that the findings obtained from this study will shed some light on improving teaching practices of statistics educators so as to help students in gaining better understanding on interpreting the correlation and regression analysis.

Malaysia’s tourism is affected by the Covid19 pandemic and the MCO implementation, where borders are closed and non-essential activities are halted. Negative effects are also felt by Malaysians and are reflected in social media. This study examines two research questions, finding the issues that Twitter users have been addressing on tourism activities during the MCO period and analyze users’ sentiment regarding their ability to travel after MCO. 5000 data were extracted manually from 11357 data scraped from Twitter, of which 3243 were pre-processed keywords using RapidMiner. The results show that the topic of the debate focuses on three themes, namely the destination of tourism, future planning, and public emotions. In addition, 63% gave a positive view and 22% negative sentiment on domestic tourism. Overall, users of Twitter gave an optimistic outlook on domestic travel and hoped that Covid19 would soon be over.

As a result of the pandemic Covid19 and the enforcement of Movement Control Order (MCO) in Malaysia, it is difficult for the Ministry of Education to explain the selection of courses at the university. Current systems such as “Selangkah ke UiTM,” “eSemak Politeknik” and “EduAdvisor” concentrate only on SPM graduates. As a result, this study proposes a recommendation system that can provide recommendations for the course to suit students’ personalities. Diploma of Computer Science students from the Faculty of Computer and Mathematical Science (FSKM) at UiTM Melaka are selected as a case study. This system uses the rule-based approach that took psychometric test results: “Inventori Minat Kerjaya” and mapped it to the traits needed for the five courses offered at the faculty to help students determine the most appropriate course. This prototype system consists of 170 test questions, and the results of the top 3 IMK personalities are chosen to be mapped to the courses offered. Usability and accuracy testing has been carried out at an average rate of 77.5%, and accuracy is 66.7%.

This paper describes a preliminary study on the adaptation of data visualization and the Internet of Things (IoT) to monitor the soil moisture of plant irrigation to sustain botanic tourism. It is compulsory to perform a daily irrigation schedule until the plants can live independently. However, due to the Covid-19 pandemic, insufficient infrastructure, work rotation at the share-farm, and unpredictable weather, it caused inconvenience for the workers to fulfill the irrigation routines twice a day. Hence, this research aimed to design and develop a mobile-based application with monitoring features that could help workers to monitor and visualize the soil moisture at the botanical area. It is using data visualization technique and enables them to perform irrigation remotely through the application via the IoT connection that linked to a water pump. It is proven that all the features of the system were functioning well and managed to receive good system usability of 77.4%.