UV Express is one of the most used modes of public transportation in the Philippines. However, the inconvenience in commuting, such as long queues of passengers at UV Express terminals and extended waiting time for UV Express drivers and passengers, is still present. The Book-Express aims to help UV Express, which operates on a terminal-to-terminal basis, by providing a reservation and booking system through a website and mobile application. The system’s primary functionalities were validated through user acceptance testing using the metrics of functionality, usability, reliability, performance, and supportability. Consequently, the system garnered an overall score for the mobile application of 4.60, which is "Excellent", and an overall score for the website of 4.53, which is "Excellent," as well.

Disaster strikes in unexpected times. The first few hours after are critical to the survival of the victims directly hit by the event. This paper explores the utilization of the Monitoring and Reporting System with Decision Support Mechanism using web and mobile applications. The citizen of Hagonoy can use the mobile application to report a crime or a disaster, they can also access the official website to view important announcements regarding safety protocols or events. The Department of Police, Fire and MDRRMO of Hagonoy will take full responsibility for managing the emergency reports and updating the website’s content. From the experiment, the mobile application was able to show that the system can provide a feasible emergency and incident report that will help both the citizen and LGU of Hagonoy. The researcher used the prototyping model as a software development model. Overall, the system was evaluated 4.86 with an interpretation result of Very Acceptable. This means that the system is ready for deployment.

Getting a certification is one of the most complicated academic journeys for students in the world of technology. Industry certification has evolved into a distinct worldwide industry. The certification is an examination to evaluate students’ technical knowledge and competency in their chosen areas. Students and recent graduates pursue certification because it gives them an advantage in the job market and allows them to concentrate on relevant, meaningful, and in-demand computing subjects. Giving students the best academic support is essential to help them pass a certification exam evaluating their knowledge in courses. The goal of this study was to create a certification reviewer-based system that would let the reviewee provide a platform for review so that appropriate academic interventions could be automatically given before the examination process. The paper has applied the Technology Acceptance Model (TAM) to various information systems. The paper used the Rapid Application Development Model to develop the reviewer-based system. Document analysis, survey questions, and focus group conversations were used to gather the data. The validated survey questionnaire was administered to students, instructors, and practitioners during the School Year 2021-2022. The three groups of respondents were purposively selected as they complied with the requirements of the study. The data was analyzed quantitatively using the frequency distribution, weighted mean, and one-way variance analysis of variance.

The college entrance examination is vital for program admission. Typically, entrance examinations are conducted onsite using paper and pens. When the COVID-19 pandemic hit, the entrance examination was lifted and physical gatherings were prohibited. Since many schools cannot offer an online admissions exam, they rely on grades and interviews to admit and qualify students for degree programs. However, academic standards differ between schools, and grades may not be enough to assess students' capacity. Thus, this study aims to develop an Online Proctored Entrance Examination System (OPEES) with Degree Program Recommender for colleges and universities to help institutions administer onsite or online entrance tests and generate course suggestions using a rulebased algorithm. The study employed the scrum methodology in software development. OPEES allows applicants to submit applications online, and institutions can manage user accounts, tailor exams and degree programs’ criteria, manage exam dates, and assign proctors. Online proctoring using Jitsi, an opensource multiplatform voice, video, and instant messaging tool with end-to-end encryption, ensures exam integrity. The system’s features were evaluated by 102 respondents, comprised of end-users (students and school personnel) and IT professionals, using the FURPS (Functionality, Usability, Reliability, Performance, and Supportability) software quality model. In the software evaluation, the overall system proved to be functional as perceived by the respondents, as manifested by the mean rating of 4.61. In conclusion, the system's architecture was deemed feasible and offers a better way to streamline admission examinations and determine a student’s applicable degree program by enabling institutions to customize their exams and degree program requirements. It will be beneficial to look into recommendation system algorithms and historical enrollment data to improve the system’s use case.

The electro-mechanical salted egg grading system was developed to support producers by streamlining the cleaning process, delivering a sorted outcome, saving time, decrease human resources needs, labor costs, and minimized egg breakage, consequently boosting production efficiency. OpenCV (Open Source Computer Vision Library) was employed as a development platform and the Raspberry Pi 3 Model B as a microcomputer due to its speedier and more powerful CPU, which is required to operate the system's components and process the acquired images for classification. In addition, a Raspberry Pi camera module V2 was employed to capture the images for scanning, LED bulb for candling, and an SG90 micro servo for sorting. Furthermore, we used B66 and B35 V-belts for the conveyor assembly. An induction motor of 0.125 horse power is used to rotate the conveyor assembly, a chain, and sprocket to reduce its speed. The researchers also used soft bristles brushes which are ideal for cleaning the eggshell. For cleansing, sprinklers were used along with the water PVC pipe that holds pressurized water of 30 psi. The camera's captured images are categorized as clean, dirty, well-pickled, and spoilt eggs. Empirical results exhibited that the detection accuracy achieved 96% and 93% for cleanliness and quality, respectively. It establishes the model and prototype's robustness in cleaning, sorting, and grading salted eggs.

Oclean's goal is to raise awareness about the harmful effects of plastic waste in the ocean. The game was created for use on a mobile device. It's a 2D game with a single player endless mode. A scoring system and a timer were also included in the game. In addition, the game has a gallery where players could see what is happening in real life. This initiative believes that little acts can generate significant effects in the fight against plastic pollution in our oceans. In addition, interactive information about the issues of marine plastic trash was also provided. The game's set of objectives were completed, and an unending casual game about ocean cleaning and marine plastic garbage was created effectively.

Grit plays a crucial role in determining high individual success more than intellectual talent alone. However, there is no existing literature that ventured into the trait identification in an e-learning environment. This study presents a comprehensive computational-driven strategy for detecting a learner's grit using machine learning. Empirical results show that DBSCAN and Random Forest models produce average accurate prediction consistency of 92.67% against the questionnaire method. Knowledge interpretation using feature importance and association mining quantifies perseverance and sustained interest as the most pressing component of grit. Correlational analysis reveals that grit has a weak connection with course grades (short-term goal) but demonstrates a strong positive association with professional achievement (long-term goal) and maturation. Collectively, our findings substantiate that breakthrough accomplishment is contingent not solely on cognitive ability but on constant interests and resilience.

The emergence of information technology used in all factors of our everyday lives has exponentially increased the amount of unstructured data. This huge quantity of records is a great source for finding and thus, may be used for extracting actionable information. In the academe, for instance, teachers and school administrators can adjust their approach to teaching/learning by getting feedback from students through a Learning Management System that can automatically analyze the semantic orientation of words and contextual polarity of these feedbacks - categorizing them into positive and negative. Identifying and classifying words expressed in the students' feedback about learning materials can provide structured information that can guide the teacher, impact its design and target the students' needs. This study implemented a lexicon-based strategy for automatic sentiment analysis using VADER as a model. Student feedbacks are extracted from an LMS developed to demonstrate the usability and effectiveness of the adopted approach; among other features of LMS that will help teachers improve its implementation. Results of the LMS sentiment analysis are compared to human-annotated sentiments to verify and validate the output, as well as, check its accuracy using Confusion Matrix. It aims to create a structured representation of student sentiments through LMS to help teachers improve the design of learning materials.

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.

The project endeavored to design and develop a Web-based Performance Evaluation System with integration of rule-based algorithm that will analyze the performance of each reviewee based on the scores from their examination. The algorithm automatically provides suggested reading materials based on the result of the assessment. With this, the system will help the reviewees assess their own performance. The system was developed using Agile Methodology Model of Software Development. The software produced was tested using Alpha and Beta software tastings. The FURPS model was used to assess the software quality as perceived by the selected group of respondents. The system was found to be functional, meeting the designed functional requirements specifications.