How important is the tuition fee during the COVID-19 pandemic in a developing country? Evaluation of filipinos' preferences on public university attributes using conjoint analysis.

In a developing country like the Philippines, it is critical to understand the important factors which lead college students to their current colleges and universities, especially during the COVID-19 pandemic. This study utilized the conjoint analysis approach with an orthogonal design for evaluating understudy's inclination in choosing a college with the various attributes such as the tuition fee, distance or location, employability, academic reputation, recommended by friends and peers, recommended by family or relatives, and the availability to transfer was assessed. A total of 518 Filipino students studying at public and state universities participated in answering the 16 combined attributions about university preference using purposive sampling approach. Based on the utilities estimate, the most important attribute was the tuition fee of the preferred university with an importance value of about 32.839%, followed by the employability rate of the university with about 6% gap difference. The mid-concerned attributes were the distance/location with an estimated of 11.139%, recommendation of friends or peers with approximately 11.689% tying together, and the academic reputation with an estimated of 10.638%. The two least important attributes were identified to be the availability to transfer, having with only about 2.713%, and the recommendation of parents with only 2% difference at approximately 4.453%. The outcomes of this study can aid college chairmen and enrolment specialists tweak their advertising procedures by giving significant data to the chief gatherings engaged with settling college decision choices.

Utilization of Random Forest Classifier and Artificial Neural Network for Predicting Factors Influencing the Perceived Usability of COVID-19 Contact Tracing "MorChana" in Thailand.

With the constant mutation of COVID-19 variants, the need to reduce the spread should be explored. MorChana is a mobile application utilized in Thailand to help mitigate the spread of the virus. This study aimed to explore factors affecting the actual use (AU) of the application through the use of machine learning algorithms (MLA) such as Random Forest Classifier (RFC) and Artificial Neural Network (ANN). An integrated Protection Motivation Theory (PMT) and the Unified Theory of Acceptance and Use of Technology (UTAUT) were considered. Using convenience sampling, a total of 907 valid responses from those who answered the online survey were voluntarily gathered. With 93.00% and 98.12% accuracy from RFC and ANN, it was seen that hedonic motivation and facilitating conditions were seen to be factors affecting very high AU; while habit and understanding led to high AU. It was seen that when people understand the impact and causes of the COVID-19 pandemic's aftermath, its severity, and also see a way to reduce it, it would lead to the actual usage of a system. The findings of this study could be used by developers, the government, and stakeholders to capitalize on using the health-related applications with the intention of increasing actual usage. The framework and methodology used presented a way to evaluate health-related technologies. Moreover, the developing trends of using MLA for evaluating human behavior-related studies were further justified in this study. It is suggested that MLA could be utilized to assess factors affecting human behavior and technology used worldwide.

Utilizing Structural Equation Modeling-Artificial Neural Network Hybrid Approach in Determining Factors Affecting Perceived Usability of Mobile Mental Health Application in the Philippines.

Mental health problems have emerged as one of the biggest problems in the world and one of the countries that has been seen to be highly impacted is the Philippines. Despite the increasing number of mentally ill Filipinos, it is one of the most neglected problems in the country. The purpose of this study was to determine the factors affecting the perceived usability of mobile mental health applications. A total of 251 respondents voluntarily participated in the online survey we conducted. A structural equation modeling and artificial neural network hybrid was applied to determine the perceived usability (PRU) such as the social influence (SI), service awareness (SA), technology self-efficacy (SE), perceived usefulness (PU), perceived ease of use (PEOU), convenience (CO), voluntariness (VO), user resistance (UR), intention to use (IU), and actual use (AU). Results indicate that VO had the highest score of importance, followed by CO, PEOU, SA, SE, SI, IU, PU, and ASU. Having the mobile application available and accessible made the users perceive it as highly beneficial and advantageous. This would lead to the continuous usage and patronage of the application. This result highlights the insignificance of UR. This study was the first study that considered the evaluation of mobile mental health applications. This study can be beneficial to people who have mental health disorders and symptoms, even to health government agencies. Finally, the results of this study could be applied and extended among other health-related mobile applications worldwide.