Android-Based Accreditation Document Mining Management using Image Processing and Text Mining

Abstract

This study aimed to develop the Android-based Accreditation Document Mining Management using Image Processing and Text Mining. The application was designed to scan documents and automatically classifies the area, parameter and indicator where it should be filed conforming with the Accrediting Agency of Chartered Colleges and Universities in the Philippines (AACCUP), Inc. accreditation instrument. It also has additional features such as Browse Document and view as Portable Document Format (PDF), Search, and View Recent Validations for faculty accreditors. A web service was also developed to quickly search for the accreditation documents prepared and scanned by the Cavite State University - Silang Campus' Accreditation Task Force using the Document Mining Management Android Application. The researcher employed a descriptive-developmental approach in the study using the Agile Software Development Life Cycle. The application was tested and evaluated by forty (40) Accreditation task force members, thirty (30) faculty accreditors and thirty-five (35) IT practitioners using ISO 25010:2011 quality standard assessing the Functionality, Performance Efficiency, Usability, Reliability, Security, and Portability. The data collected were analyzed and interpreted using descriptive statistics specifically weighted mean. Likewise, to check the differences on the means of the system evaluators, One Way Analysis of Variance (ANOVA) was utilized. The evaluation justifies that there is no significant difference among the evaluation of the respondents in the utilization of the application. The development of the Android-based Accreditation Document Mining Management using Image Processing and Text Mining serves as a new platform in preparing documents for accreditations conducted by different voluntary accrediting agencies.