Emergency response is a crucial method for saving lives because the Philippines is one of the nation that is most vulnerable to disasters. Unexpected disasters happen all the time. The survival of those who were immediately impacted by a disaster depends on what happens in the initial hours after the accident. Even a minute difference in emergency response time has the potential to save or cost lives. Through this, the researchers were able to implement Dijkstra’s method to show the shortest paths in an application for emergency response. The ideas are organized in a way that suggests potential paths that first responders could take to locate victims. This article outlines a step-by-step process for choosing the optimum approach. Agile methodology was employed by the researchers when creating the application. The respondents gave the system a 4.52 out of 5 rating on the basis of the ISO 9126 evaluation tool, with a ‘Very Acceptable’ interpretation result. Thus, the system is now prepared for deployment.

Forecasting the number of incidences of medical cases is important in planning institutional health program strategies to draft intervention and allocate resources. The utilization of advancements in computing and the use of massive health data create possibilities for the generation of tools in a recommender system. This study focused on medical cases forecasting using exponential smoothing model for the development of resource allocation recommender system. Different data pre-processing techniques were used such as imputation and data cleaning in the historical dataset. To determine which set of alpha values can be considered and be used in the development of online resource allocation recommender system for Mabalacat City Health Unit, the mean absolute percent error and mean absolute deviation were used. Exponential smoothing with an alpha value of 0.9 and 0.3 have high forecasted values than that of Exponential smoothing using 0.1, 0.5 and 0.7 respectively.

In this study, we developed a PC-based video game that aims to promote awareness of Persistent Depressive Disorder (PDD), also known as dysthymia. Anchored to the survival horror subgenre and a hack and slash gameplay, we constructed "Escape from Oblivion" as a single-player platformer game that highlights eerie game world environments and scenarios indicative of mental health conditions. It exhibits different mental states under terrible circumstances, forcing players to see and feel what it is almost like when suffering from a mental health condition like PDD. With the necessary expertise on PDD and mental health, we consulted with an expert to co-design the video game. We also evaluated the game prototype with players in terms of game characteristics. The initial version of our game received acceptable scores during the virtual open house event. Although there are several enhancements to be incorporated, our video game Escape from Oblivion demonstrates potential in being a promotional tool for mental health awareness.

In the Philippines, according to Philippine Authority of Statistics, there is an imbalance between the student enrollment and student graduation. Almost half of the first-time freshmen full time students who began seeking a bachelor's degree do not graduate on time. The study aims to utilize how Naïve Bayes algorithm - a data classification algorithm that is based on probabilistic analysis - can be used in educational data mining specifically in student graduation. The study is focused on the application of the Naïve Bayes algorithm in predicting student graduation by generating a model that could early predict and identify students who are prone of not having graduation on time, so proper remediation and retention policies can be formulated and implemented by institutions.