Skripsi

PREDIKSI KEKASARAN PERMUKAAN MATERIAL BAJA S45C PADA PROSES CNC MILLING MENGGUNAKAN METODE DECISION TREE REGRESSOR

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Penilaian

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In Manufaturing Industry, machining process is one of the important field of study because product with high quality and high preecision is in demand. One of the factor that influence the quality of a product is surface roughness. Surface Roughness alone got influenced by a lot of factor such as condition of the cutter, cutting parameter , feed rate, depth of cut and the material itself. Decision Tree Regressor is a supervised learning that known for it accurate intepretation ability. In this experiment, the author conducted an experiment by doing a prediction with decision tree regressor from the results of Milling processes on CNC machines. In this experiment, author made a Decision tree regression prediction on surface roughness average for S45C steel. This experiment was done on Vocational School 2 Palembang with 10 diameter mm, 4 flute cutter and the milling machine type is CNC Milling OPTImill F 105 CNC. After data collection, analysis were carried out using the Decision Tree Regressor. The database of this experiment is 119 data large with 5 variations of Vc, 5 variations of fz and 4 variations of ax. In the prediction model, the data was divided 95 training data and 24 testing data. After programaming process in Google Colab environtment with Python choosen as programming language, the mean absolute error result obtained was 43,4%

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2407003911	T148104	T1481042024	Central Library (REFERENCES)	Available but not for loan - Not for Loan

Detail Information

Series Title

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Call Number

T1481042024

Publisher

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

Collation

xxv, 59 hlm.; ilus.; tab.; 29 cm

Language

Indonesia

ISBN/ISSN

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Classification

621.910 7

Content Type

Text

Media Type

unmediated

Carrier Type

unspecified

Edition

-

Subject(s)

Milling
Prodi Teknik Mesin

Specific Detail Info

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Statement of Responsibility

UIN Farrah

Other version/related

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