Data - Driven Community and Extension Services for Project Decisions with Analytics

Abstract

A study was conducted entitled Data - Driven Community and Extension Services for Project Decisions with Analytics were conducted to help the selected institution in establishing its goals and making strategic decisions. The main objective of the study is to develop a system for the Cavite State University (CvSU) – Carmona campus, Philippines that would able to monitor and analyze community-related data for decision making. Specifically, it aims to develop a module for the analyzation of the possible target barangay, based on the number of households with income below in the poverty threshold, unemployment rate (by sex and barangay) and children (ages 6 to16 years old) who are not attending school (by sex and barangay); create a module for the community needs assessment that can be accessed online by the employees of the Local Government Unit (LGU) of Carmona, Cavite; recommend extension services through the use of decision tree algorithm; monitor the community extension projects; evaluate the extension project and instructor at the end of the training; provide reports which include gender distribution, trainee’s performance, expenditures of different community extension service projects, tracer report of the trainees and project’s sustainability; and evaluate the system in terms of the level of acceptability in accordance with ISO 25010 – Product Quality. Rapid Application Development model was used for the software development of the system, PHP: Hypertext Preprocessor as its programming language, C4.5 decision tree algorithm, and descriptive analytics for the visualization of the data. The system was evaluated by 63 respondent which composed of faculty members of CvSU-Carmona and employees of the LGU of Carmona, Cavite using the adapted evaluation form from the International Organization for Standardization 25010. The system obtained a computed weighted mean of 4.37 for the system testing and 4.71 for the acceptance testing with an adjectival rating of outstanding for both testings. It entails that the developed system was accepted and was able to use for project decisions.