Acta Informatica Pragensia, 2021 (vol. 10), issue 2
Editorial
Inspiring Technologies for Digital Inclusivity
Kang Leng Chiew
Acta Informatica Pragensia 2021, 10(2), 121-122 | DOI: 10.18267/j.aip.1572253 
This editorial aims to summarise the special issue entitled Inspiring Technologies for Digital Inclusivity, which was prepared from selected papers from the 12th International Conference on IT in Asia (CITA'21). The special issue consists of five scientific articles.
Article
Modelling COVID-19 Hotspot Using Bipartite Network Approach
Boon Hao Hong, Jane Labadin, Wei King Tiong, Terrin Lim, Melvin Hsien Liang Chung
Acta Informatica Pragensia 2021, 10(2), 123-137 | DOI: 10.18267/j.aip.1514171
COVID-19 causes a jarring impact on the livelihoods of people in Malaysia and globally. To prevent an outbreak in the community, identifying the likely sources of infection (hotspots) of COVID-19 is important. The goal of this study is to formulate a bipartite network model of COVID-19 transmissions by incorporating patient mobility data to address the assumption on population homogeneity made in the conventional models and focus on indirect transmission. Two types of nodes – human and location – are the main concern in the research scenario. 21 location nodes and 31 human nodes are identified from a patient’s pre-processed mobility...
A Neural Network-Based Approach in Predicting Consumers’ Intentions of Purchasing Insurance Policies
Wen Teng Chang, Kee Huong Lai
Acta Informatica Pragensia 2021, 10(2), 138-154 | DOI: 10.18267/j.aip.1523964
Insurance is a crucial mechanism used to lighten the financial burden as it provides protection against financial losses resulting from unexpected events. Insurers adopt various approaches, such as machine learning, to attract the uninsured. By using machine learning, a company is able to tap into the wealth of information of its potential customers. The main objective of this study is to apply artificial neural networks (ANNs) to predict the propensity of consumers to purchase an insurance policy by using the dataset from the Computational Intelligence and Learning (CoIL) Challenge 2000. In addition, this study also aims to identify factors that affect...
Sentiment Analysis for Thai Language in Hotel Domain Using Machine Learning Algorithms
Nattawat Khamphakdee, Pusadee Seresangtakul
Acta Informatica Pragensia 2021, 10(2), 155-171 | DOI: 10.18267/j.aip.1555673
Sentiment analysis is one of the most frequently used aspects of Natural Language Processing (NLP), which utilizes the polarity classification of reviews expressed at the aspect, sentence or document level. Several businesses and organizations utilize this technique to improve production, as well as employee and service efficiency. However, the users’ reviews in our study were expressed in an unstructured data form, which contained spelling errors, leading to complex classifications for both the users and the machine. To solve the problem, a supervised technique of Machine Learning (ML) algorithms can be applied to the data extraction, where...
Trialability and Purposefulness: Their Role Towards Google Classroom Acceptance Following Educational Policy
Solomon Oluyinka, Maria Cusipag
Acta Informatica Pragensia 2021, 10(2), 172-191 | DOI: 10.18267/j.aip.1544921
With the COVID-19 pandemic experiences of Filipino students, the face-to-face mode of instruction in the classroom has been phased out in exchange for online learning platforms such as Google Classroom (GCR) among some K-12 learners. As advised by the Commission on Higher Education (CHED), most colleges and universities had to try available learning management systems; hence, this research study aimed to investigate the role of trialability and purposefulness towards GCR acceptance among tertiary institutions following the CHED educational policy. The researchers came up with eight hypotheses, which suggested that purposefulness may influence educational...
E-Commerce Readiness Assessment in Sarawak
Ahmad Termidzi Bin Serojai, Hamimah Binti Ujir, Irwandi Hipni Bin Mohamad Hipiny
Acta Informatica Pragensia 2021, 10(2), 192-206 | DOI: 10.18267/j.aip.1533845
This study explores the factors of e-commerce adoption among Sarawakians. One of the factors is the level of cybersecurity awareness. We aim to assess the readiness for e-commerce among Sarawakians due to the lack of study conducted on the subject. A research model based on the perceived risk (PR), perceived usefulness (PU) and perceived quality of products (PQ), and the intention (I) of adoption of e-commerce services in Sarawak is proposed. The validity of the proposed model is then tested using various validity tests such as item reliability, construct validity, convergent validity and discriminant validity via the SmartPLS software. Once the validity...