Skripsi

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

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Penilaian

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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%.

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2407003773	T147264	T1472642024	Central Library (Reference)	Available but not for loan - Not for Loan

Detail Information

Series Title

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Call Number

T1472642024

Publisher

Indralaya : Prodi Teknik Mesin, Fakultas Teknik Universitas Sriwijaya., 2024

Collation

xix, 97 hlm.; ilus.; tab.; 29 cm

Language

Indonesia

ISBN/ISSN

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Classification

621.907

Content Type

Text

Media Type

unmediated

Carrier Type

-

Edition

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Subject(s)

Kekasaran permukaan
Prodi Teknik Mesin

Specific Detail Info

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Statement of Responsibility

KA

Other version/related

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