Simple Additive Weighting Method in the Development of a System Assessing the Feasibility of Job Training Industry
Journal Title: Indonesian Journal of Informatics Education - Year 2017, Vol 1, Issue 2
Abstract
The activities of the job training is an activity that must be implemented at Vocational Secondary School. To increase competence skills learners in the workforce, then the school must choose many places of the job training industry by the respective expertise of program participants. Therefore it is necessary that information systems can assist the school in selecting the job training industry by producing the decision support to determine the feasibility of the job training industry for use in the following period. The feasibility of job training industry that is purposed in this research is determined by the alignment of competency expertise on the job training industry with the program expertise of participants and other supporting criteria. That system is called “Sistem Pendukung Keputusan Kelayakan Tempat Praktik Kerja Industri (SPK-KTP)” or System Assessing The Feasibility of Job Training Industry. In decision-making, this system used the method of Simple Additive Weighting (SAW). In addition, the system is also equipped with features to manage the administrative activities of the job training industry, to recap the daily journal, and to recap the supervising report. SPK-KTP is the web-based information system which it is developed using the programming language PHP (Hypertext Preprocessor). System development method that used in the information system is Waterfall Model. The steps of Waterfall Model consist of analysis, design, code, and test. SPK-KTP has done testing to an expert of the information system with value 90,7%, an expert of the job training substance with value 91,6%, supervising teachers with value 83,3%, and learners with value 90,6%. Based on the result, so SPK-KTP is very feasible to use
Authors and Affiliations
Kaisah Riski Zubaeti, Aris Budianto, Dwi Maryono
Keywords
Related Articles
- EP ID EP248874
- DOI 10.20961/ijie.v1i2.12332
- Views 127
- Downloads 0
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