The purpose of this study is to look into the use of augmented reality (AR) technology in education materials for fruits and the nutrition. Augmented Reality (AR) is the primary technology for this proposed application project. AR is a real-world interactive experience in which real-world items are augmented with computer-generated perceptual information. The idea of this project is to use AR to complement the traditional method of learning with flashcards. Because schools are closed during this outbreak, traditional learning is unavailable. This study proposes the use of 3D animation in Augmented Reality (AR) to illustrate each of the fruits to overcome and improve traditional learning among students. The use of 3D animation with the Augmented Reality (AR) method on fruits and nutrition learning content outperforms the 2D illustration method in terms of student understanding. Furthermore, case studies on the application of AR technology to fruit learning content revealed that the proposed algorithm could be used as an alternative to determine the best way to teach and learn about fruits and nutrition. With this AR application, it can complement the traditional methods. To achieve the objectives of this project there are 4 main phases that need to be carried in developing this project. The first phase in developing this project is to study the data and learning interaction of fruits and the nutrition in handheld augmented reality. The second phase is designing process along with the development of the project. The third phase is to integrate the AR application. The final phase is to evaluate the user learning experience in fruits using the AR application. The project's expected outcome is evaluated using data collection and analysis from the users through the final phase.
Smart tourism is a 21st-century technological phenomenon where tourism suppliers and tourists are interconnected. The Malaysia National Tourism Policy’s 2020-2030 concurs that one of the tactical strategies to increase visitor’s economy in the rural areas is through ‘digitalization’. Parallel to this, community-based tourism’s (CBT) homestay programs have long been a government’s endeavor in assisting rural tourism’s economics. In heading towards smart tourism, CBT must be consistent with the progress. However, current investigation on CBT’s readiness to accept smart tourism in Malaysia is still infancy. This is a proposed study with objectives to explore the concept of smart CBT within Malaysian context, to investigate the readiness of CBT in Malaysia to adopt smart tourism, and to identify the strategies for Malaysia National Tourism Policy. The study will employ qualitative approach where semi-structured interview will be conducted with industry experts associated with tourism and homestays from different regions in Malaysia. The expected findings will establish the current setting of smart tourism in the CBT context, which will derive input for Malaysia National Tourism Policy.
This study examines the link between psychological empowerment, relationship quality and word of mouth in a brand Facebook page. It is intended to help brand marketers establish and apply successful relationship marketing strategies in the online environment. Successful implementation of relationship marketing in social networking sites will contribute to favorable consumer behaviors such as positive word of mouth. Based on the data collected from 10 hospitality brand Facebook pages, Partial Least Square (PLS) analysis was used to examine the structural interrelationship between psychological empowerment, relationship quality and online word of mouth. The empirical findings of this study were threefold. First, higher consumer psychological empowerment resulted in higher relationship satisfaction. Second, greater relationship satisfaction led to higher relationship commitment and relationship trust. Third, better relationship quality (relationship satisfaction, relationship commitment and relationship trust) contributed in greater positive online word of mouth.
Sebuyau is a coastal fishing village located about 100km away from the main city of Kuching, Sarawak. Local communities depend on fishing activities, agriculture, small businesses, and cottage industry products as their economic resources. Sebuyau can be highlighted as one of the potential tourist attractions in Samarahan District through boat rentals to tourists for fishing and river cruise activities. Boat rental for fishing and river cruise activities is a community-based tourism (CBT) product that provides opportunities for boat operators or fishermen to engage in social entrepreneurship by using their existing boats. It is an approach to diversifying their sources of income with a lower impact on natural resources. However, to ensure a sustainable transformation, the local community needs to be given exposure, knowledge, and guidance to shift the activities of ordinary fishermen or individual boat owners to boat operators who are able to generate income from boat rental activities. Therefore, higher education institutions need to take proactive roles to assist local communities in ensuring this transformation is achievable. This article discusses the role of the higher education institution in developing entrepreneurial skills among boat operators in Sebuyau. In addition, this article also discusses the achievements of the local communities who have successfully managed their boat rental activities as a result of an approach involving the roles of higher education institutions.
Software fault prediction is widely used in the software development industry. Moreover, software development has accelerated significantly during this epidemic. However, the main problem is that most fault prediction models disregard object-oriented metrics, and even academician researcher concentrate on predicting software problems early in the development process. This research highlights a procedure that includes an object-oriented metric to predict the software fault at the class level and feature selection techniques to assess the effectiveness of the machine learning algorithm to predict the software fault. This research aims to assess the effectiveness of software fault prediction using feature selection techniques. In the present work, software metric has been used in defect prediction. Feature selection techniques were included for selecting the best feature from the dataset. The results show that process metric had slightly better accuracy than the code metric.
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