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Komang Sudana Yasa Pande
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Computer Science & IT

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PENGEMBANGAN SISTEM PENDUKUNG KEPUTUSAN PENENTUAN PRIORITAS PEMBERIAN BANTUAN BIMTEK KEPADA INDUSTRI KECIL DAN MENENGAH (IKM) DENGAN METODE ANALITYCAL HIERARCHY PROCESS (AHP) DAN SIMPLE ADDITIVE WEIGHTING (SAW) Komang Sudana Yasa Pande; Made Windu Antara Kesiman; Gede Aditra Pradnyana
SINTECH (Science and Information Technology) Journal Vol 3 No 1 (2020): SINTECH Journal Edition April 2020
Publisher : LPPM STMIK STIKOM Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (3.032 KB) | DOI: 10.31598/sintechjournal.v3i1.391

Abstract

The Buleleng Regency's Office of Trade and Industry has one of the tasks to develop and empower Small and Medium Industries (IKM) in Buleleng. One of the ways undertaken by the agency is to provide assistance to Bimtek entrepreneurship training or Technical Guidance. Bimtek is technical guidance assistance from government programs to improving and developing small and medium industries. However, sometimes this assistance is inconsistent because decisions are often changed. For this reason a decision support system was developed using AHP and SAW methods with 8 criterias including: number of monthly production, average product prices, number of equipment owned, number of employees, length of business establishment, annual sales value, total annual raw material and distance to Buleleng Government Commerce and Industry Office. The system developed can help the Buleleng Government Commerce and Industry to determine bimtek beneficiaries according to predetermined criterias. The development of this decision support system was built using the SDLC Method with a waterfall model. There are 4 tests performed including: blackbox testing, whitebox testing, accuracy testing, and user response testing. This study successfully developed a decision support system after passing the blackbox test and the whitebox test. Accuracy test showed very good results with an accuracy rate of 86.67%. The user response test conducted on 4 users including: admin, staff, IKM support and the general public has a mean percentage of 92.3% which is in a very good range.
Co-Authors Gede Aditra Pradnyana Made Windu Antara Kesiman