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All Journal Jurnal Informatika: Jurnal Pengembangan IT
Sahlan Sahlan
STMIK Bani Saleh
Computer Science & IT

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Penerapan Intelligence System berbasis Case Base Reasioning dan Metode K-Nearest Neighbor Untuk Identifikasi Gangguan IT Support Muhamad Dedi Suryadi; Sahlan Sahlan; Ndaru Ruseno
Jurnal Informatika: Jurnal Pengembangan IT Vol 4, No 2-2 (2019): Special Issue on Seminar Nasional - Inovasi Dalam Teknologi Informasi & Teknol
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v4i2-2.1868

Abstract

Delay in handling and solving IT problems both hardware / software greatly affects the company's business processes. Sometimes, IT helpdesk personnel still difficult to find solutions and make decisions to solve IT problems. This is because there is currently no system that can help IT Helpdesk personnel in finding solutions to be able to solve the problems being faced quickly and accurately. When going to look for solutions to the problems being faced can not display solutions that are appropriate or close to the existing historical data. In identifying IT problems, the authors use case-based reasoning or Case-Based Reasoning (CBR) by carrying out the process of finding the case with the highest proximity and proximity measurement using the K-Nearest Neighbor (k-NN) algorithm. This study aims to explain the application of Case-Based Reactioning (CBR) and K-Nearest Neighbor (k-NN) Algorithm to identify IT problem disturbances. The results showed that the application of Case-Based Reasioning and K-Nearest Neighbor (k-NN) Algorithm after being tested by 5 Experts got accurate results.
Co-Authors Muhamad Dedi Suryadi Ndaru Ruseno