KLASIFIKASI KEKASARAN PERMUKAAN BAJA S45C PADA PROSES MILLING CNC DENGAN METODE DECISION TREE C4.5

GATMIR, INSANI ARIF and Yani, Irsyadi (2024) KLASIFIKASI KEKASARAN PERMUKAAN BAJA S45C PADA PROSES MILLING CNC DENGAN METODE DECISION TREE C4.5. Undergraduate thesis, Sriwijaya University.

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Abstract

The development of the industrial sector, especially the manufacturing industry, demands the creation of products with good quality. One of the important parameters of manufacturing products is the quality of surface roughness. Besides striving for optimal surface roughness quality, machining processes can enhance operational functionality to save time and costs through modeling techniques. One method that can be used to classify surface roughness is the decision tree. This research analyzes the influence of CNC Milling machining parameters on the surface roughness of S45C Steel using the C4.5 decision tree method. The parameters tested are cutting speed, feed rate, and depth of cut. Based on the C4.5 decision tree , the results show that cutting speed is the most influential parameter with the highest gain ratio value of 0.18, followed by feed rate at 0.0911, and depth of cut at 0.0121. With evaluation using the K-fold cross-validation method, the highest average accuracy was obtained with 5-fold at 80%, while for 2-fold it was 33%, 3-fold 60%, 6-fold 76%, and 10-fold 73%.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	milling, kekasaran permukaan, decision tree
Subjects:	T Technology > TJ Mechanical engineering and machinery > TJ1-1570 Mechanical engineering and machinery
Divisions:	03-Faculty of Engineering > 21201-Mechanical Engineering (S1)
Depositing User:	Insani Arif Gatmir
Date Deposited:	21 Jun 2024 03:57
Last Modified:	21 Jun 2024 03:58
URI:	http://repository.unsri.ac.id/id/eprint/147264

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