Identifikasi Tingkat Kerusakan Peralatan Labor Teknik Komputer Jaringan Menggunakan Metode Decision Tree

Authors

  • Dinda Permata Sukma Independent Researcher
  • Sarjon Defit Universitas Putra Indonesia YPTK Padang
  • Gunadi Widi Nurcahyo Universitas Putra Indonesia YPTK Padang

DOI:

https://doi.org/10.37034/jsisfotek.v3i4.78

Keywords:

Data Mining, Algorithm, Decision Tree, Identify, Damage

Abstract

The computer laboratory is a place for practical learning for students, where computers have an important role in the smooth running of the practice. The use of computer labor at any time is very vulnerable to damage. If there is damage it will disrupt the teaching and learning process. Utilization of data mining in determining the level of damage is one of them. SMKN 1 Sintuk Toboh Gadang has 3 laboratories, TKJ (Network Computer Engineering), RPL (Software Engineering) and Technician labor. Application of the Decision Tree method in identifying damage to computer laboratory equipment, especially TKJ (Computer Network Engineering) labor. The data obtained in this study are computer equipment sourced from the computer laboratory of SMKN 1 Sintuk Toboh Gadang. Based on the analysis of the computer laboratory, there are 50 computer laboratory equipment. Furthermore, if the data is processed, several variables are needed to identify the level of damage to labor equipment including the name of the tool, number of tools, inspection, duration of use, and condition. The result of testing this method is to test whether the labor equipment can still be used or repaired. The purpose of this research is to help computer labor technicians to identify computer labor equipment that can still be used or repaired so that no damage occurs during practical learning hours. Furthermore, the best method in determining the level of damage to computer laboratory equipment is the Decision Tree Algorithm method. Decision Tree Algorithm is a predictive model using a decision tree structure and makes complex decisions simpler. The results of the research method show that the condition variable has the highest Gain value, namely 0.4734353, then the variable length of use is obtained with a Gain value of 0.896038. The factors that cause damage include the condition of the tool and the duration of use.

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Published

2021-09-04

How to Cite

Sukma, D. P. ., Defit, S. ., & Nurcahyo, G. W. . (2021). Identifikasi Tingkat Kerusakan Peralatan Labor Teknik Komputer Jaringan Menggunakan Metode Decision Tree. Jurnal Sistim Informasi Dan Teknologi, 3(4), 275–280. https://doi.org/10.37034/jsisfotek.v3i4.78

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