Computational thinking problem framing artefacts in design science research methodology for Malaysian small and medium enterprises

Computational thinking (CT) is a fundamental skill for the 21st century and can be learned by anyone. However, there are very few studies on how CT can be used to solve real-world problems. In line with the need to understand and solve the problem, the research is based on Design Science Research Methodology (DSRM) to guide the design process, where the artefact's development is the research's main outcome. It started with an interview conducted with the key informant involved in the Public-Private Research Network (PPRN) workshop, where the researcher wanted to test the applicability of CT to solve a real problem. The purpose of the interview was to find out how CT could be applied to the problems of small and medium enterprises (SMEs). During the interview, the key informant explained that SMEs understood their problems well but could not frame them and were totally dependent on facilitators' help. This was because some SMEs lack problem framing skills, which are crucial for clarifying and expressing their main problem. Hence, the aim of this study was to develop artefacts that would enable small and medium enterprises (SMEs) to formulate the problem and develop solutions that focused on process innovation. The first artefact involved the development of a method that focused on the internal process between CT and the Work System Method (WSM). The second artefact was an instantiation presented in the form of a guidebook. Therefore, to build the artefacts, the researcher adapted the DSRM by identifying the CT elements and processes that could be used in the artefacts, merging them with the WSM and adapting the Work System Snapshot (WSS) as the basis for presenting the results of these artefacts. Meanwhile, Situational Method Engineering (SMEng) was used to develop the attributes and elements of the artefacts. The method was evaluated by experts, who were CT experts and academics. Meanwhile, two exploratory focus group studies (EFG) and two confirmatory focus group studies (CFG) were conducted with nine SMEs from different food industries to test the applicability of the guidebook. As a result, this study contributed to the improvement of DSRM, where the researcher has improved the phases of problem identification and motivation, objectives of the solution, design and development, demonstration and evaluation. Each phase was outlined with methods and processes within each iteration to ensure a rigorous development and evaluation process for the artefacts. The main outcome of this research is the development of a guidebook based on the CT problem framing process in DSRM that can be used by SMEs to find new solutions and ways to innovate their business processes

Comparative Analysis of Data Redundancy and Execution Time between Relational and Object-Oriented Schema Table

Database design is one of the important phases in designing software because database is where the data is stored inside the system. One of the most popular techniques used in database design is the relational technique, which focuses on entity relationship diagram and normalization. The relational technique is useful for eliminating data redundancy because normalization produces normal forms on the schema tables. The second technique is the object-oriented technique, which focuses on class diagram and generating schema tables. An advantage of object-oriented technique is its close implementation to programming languages like C++ or Java. This paper is set to compare the performance of both relational and object-oriented techniques in terms of solving data redundancy during the database design phase as well as measuring query execution time. The experimental results based on a course database case study traced 186 redundant records using the relational technique and 204 redundant records when using the object-oriented technique. The query execution time measured was 46.75ms and 31.75ms for relational and object-oriented techniques, respectively

Computational Thinking Work System Method: A problem-solving method for small and medium enterprises

Computational thinking (CT) has been dubbed as a fundamental skill for the 21st century and can be learned by all. However, little research exists on the practical use of CT in daily life. Therefore, this problem was addressed by applying a design science research approach and situational method engineering to propose an artefact that can help small and medium enterprises (SMEs) in the problem-solving process using CT and the Work System Method (WSM). The resulting artefact offers a systematic way of problem-solving process and allows SMEs to discover process innovation. The study has considerable implications for business owners and IS researchers. The business owner can improve the efficiency of their business process and increase the company's productivity

Exploring Important Factors in Predicting Heart Disease Based on Ensemble- Extra Feature Selection Approach

Heart disease is a significant and impactful health condition that ranks as the leading cause of death in many countries. In order to aid physicians in diagnosing cardiovascular diseases, clinical datasets are available for reference. However, with the rise of big data and medical datasets, it has become increasingly challenging for medical practitioners to accurately predict heart disease due to the abundance of unrelated and redundant features that hinder computational complexity and accuracy. As such, this study aims to identify the most discriminative features within high-dimensional datasets while minimizing complexity and improving accuracy through an Extra Tree feature selection based technique. The work study assesses the efficacy of several classification algorithms on four reputable datasets, using both the full features set and the reduced features subset selected through the proposed method. The results show that the feature selection technique achieves outstanding classification accuracy, precision, and recall, with an impressive 97% accuracy when used with the Extra Tree classifier algorithm. The research reveals the promising potential of the feature selection method for improving classifier accuracy by focusing on the most informative features and simultaneously decreasing computational burden

Exploring the actual implementation of e-wallet application in Malaysia

E-wallet, also referred to as digital wallet, is a software application designed to replace physical wallets, with the primary purpose of facilitating online transactions when users wish to make virtual payments. Nowadays, E-wallets are not limited to mobile applications, but they have also been extended to wearable devices, such as smartwatches, enabling users to make payments via their watches. This research study focuses on three main E-wallet service providers in Malaysia, namely TouchNGo E-wallet, Boost, and Grab pay, as they are the top three E-wallets in the country. The aim of this paper is to explore the real-world implementation of E-wallets among mobile phone users in Malaysia, employing the Technology Adoption Model as the theoretical framework. Six independent variables were identified to study the implementation of E-wallets, and a total of 500 respondents shared their opinions on retaining the usage of E-wallet in Malaysia. The data collected were analysed using SPSS for Pearson Correlation Analysis and Multiple Linear Regression. Out of the six variables, five independent variables were accepted, and one independent variable was rejected due to the greater significant level. The highest correlation coefficient falls under Business Resources with 0.704. The study delves into the implications and constraints, providing insights for the future advancement of E-wallets within the Malaysian context.