UPLB ICS Peak One

Embracing digitalization has become crucial for businesses aiming to stay competitive. However, some companies remain hesitant to adopt this change due to limited digital proficiency and concerns about the benefits. This study focused on Ricman Roofing Materials Trading, a business in the industry for over a decade that has a minimal technological advance- ments. To address their challenges, the study developed RRMT- Software, a web-based application tailored to the company’s daily operations. The technologies used to develop the software include React, Express, Supabase, and Node. Its features—file management, inventory management, a project dashboard, and data visualization—were developed in close collaboration with employees to ensure a seamless transition and alignment with current practices, thereby boosting efficiency without disrupting workflows. The usability of the application was evaluated using the System Usability Scale (SUS) questionnaire, achieving an average SUS score of 82, indicating a high level of usability.

This study addresses the persistent challenges of the University of the Philippines Los Ba ˜nos (UPLB) constituents in navigating campus spaces, particularly in locating class venues. The Hanap mobile application is designed to help students alleviate these wayfinding challenges. This study aimed to de- velop, implement, and evaluate the application based on its usability and capability to aid users in campus navigation to a chosen destination. Testing by admin and non-admin users revealed an average System Usability Scale (SUS) score of 85.58, indicating excellent usability in providing users with a tool for campus navigation. This also means that the application excels in effectiveness, efficiency, and overall ease of use.

Social networks have been a core part of the current age of the Internet. Through these channels, however, disinformation has sprawled all over the major social media platforms, making it a point of difficulty to determine which type of news a person shares to their network. This study aims to create a simulation program to simulate the spread of information throughout homogeneous and heterogeneous networks using the Susceptible-True-False-Recovered (STFR) model. Using NetLogo to create the simulation, four scenarios were made that would reflect an actual situation in the real world. Results show that resistance is an important factor that prevents the spread of information in social networks. Recovery as a factor affects the lifespan of information. Further improvements to the study in- clude datasets that portray and identify the Filipino social media landscape as well as research on exact values in information spreading and disinformation spreading in online social networks.

Mental health issues continue to be a prominent concern, yet the mental health stigma is a significant barrier that prevents people from seeking professional help. Persuasive games are a promising way to address this, but tend to have poor game design, making people show less interest in these types of games. This demonstrates the need to use human-computer interaction techniques in creating persuasive games to make them more enjoyable. This study aims to explore the effectiveness of the networked persuasive game, Soulbound, which was designed and developed using human-computer interaction techniques, in raising awareness and encouraging mental health action. Soulbound was developed using Unity, C#, and Unity Gaming Services, and its effectiveness was measured through the pre- test post-test control group design involving 68 participants. The game was shown to be effective in reducing mental health stigma and increasing the willingness to take action. As the game was also found to be enjoyable by the respondents, its success could have been attributed to the human-computer interaction techniques that were used. Registered psychometricians were also interviewed to confirm these findings. Further research is recommended to explore whether these techniques directly impacted the effectiveness of the game.

To lessen the burden of teachers, a chatbot may be developed to answer student queries. Since there are different chatbot implementations using varying word embedding tech- niques, there is a need to evaluate the performance of chatbots using different embedding techniques to determine the best chatbot implementation for answering student queries. This study aimed to analyze and compare the performance of different chat- bot implementations using varying word embedding techniques in answering student queries. The study developed 3 chatbot implementations using the three word embedding techniques Bag-of-Words, Term Frequency - Inverse Document Frequency, and Word2Vec. A feed forward neural network was used for all chatbot implementations to classify the proper output. The study used the University ChatBot Queries and Responses dataset from Kaggle to simulate student queries. Accuracy, F1-score, word embedding time, and training time were the metrics used to evaluate the chatbots. In terms of overall performance, results show that the best chatbot implementation is the Term Frequency - Inverse Document Frequency chatbot implementation. However, the study used a small dataset and results may differ when using larger datasets. Thus, it is recommended for further studies to use larger datasets to determine if the performance of these chatbot implementations will change.