Test Analysis of the Development Conversion and Recognition Prior Learning Models on Vocational Teachers’ Education 
Fuad Abdillah1, Slamet PH2, Sukardi3
1Fuad Abdillah, Vocational Education S3 Doctoral Program, Yogyakarta State University Yogyakarta, Indonesia.
2Slamet PH, Faculty of Engineering, Yogyakarta State University,Yogyakarta, Indonesia.
3Sukardi, Faculty of Engineering, Yogyakarta State University, Yogyakarta, Indonesia.
Manuscript received on 03 September 2019 | Revised Manuscript received on 13 September 2019 | Manuscript Published on 23 September 2019 | PP: 1456-1460 | Volume-8 Issue-5C, May 2019 | Retrieval Number: E12130585C19/19©BEIESP | DOI: 10.35940/ijeat.E1213.0585C19
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: This study aims to: (1) develop a conversion and recognition of prior learning (RPL) model on the vocational teachers’ education in the field of automotive engineering: (2) determine the software quality developed by the functional suitability, efficiency of performance, compatibility, usability, reliability aspects, maintainability, portability, and security testing based on ISO 25010. The method applied in this Research and Development (R & D) is the Brogg and Gall. The results of the study revealed that: (1) the conversion and prior learning recognition (RPL) models on vocational teachers’ education were in accordance with the requirements of the field (2) Test results on the functional suitability scored 10.5 and a mean of 3.45; the efficiency of performance had a score of 9.5 and a mean of 3.15; compatibility scored 8 with a mean of 4; the usability had a score of 19.5 and mean of 3.2; while the reliability aspect had a score of 13.5 and a mean score of 3,37. Furthermore, the conversion and prior learning recognition models are flexible in use and competent. Regarding the portability aspect, it is compatible with Mozilla Firefox, Google Chrome, and Internet Explorer browsers. It is free from XSS and SQL injection vulnerabilities seen from the security information system.
Keywords: Vocational Teachers’ Education, Test Conversion and Recognition of Prior Learning Model.
Scope of the Article: Pattern Recognition