Similarity_ DATA MINING IMPLEMENTATION USING K-NEAREST NEIGHBOR ALGORITHMTO PREDICTSENGON SAWING RESULT

Yudhana, Anton (2021) Similarity_ DATA MINING IMPLEMENTATION USING K-NEAREST NEIGHBOR ALGORITHMTO PREDICTSENGON SAWING RESULT. Journal of Natural Remedies, 21 (9). ISSN e-ISSN : 2320-335 | p-ISSN : 0972-5547

Text Similarity_ DATA MINING IMPLEMENTATION USING K-NEAREST NEIGHBOR ALGORITHMTO PREDICTSENGON SAWING RESULT.pdf Download (1MB)

Abstract

The sawing result prediction that can give overview how much Sengon sawing can yield is done by manual calculation that require a long and difficult process, so there need a method to resolve this problem. This study aim is to find whether K-Nearest Neighbor is acceptable for Sengon sawing result prediction. The Research steps is collecting the data, algorithm calculation and test performance. Manual calculation method which is done by preparation of the data training (old data) with 135 data, enter the value of the new data (testing) with 10 data, checking the distance Euclidean, look for K value, determines the outcome then test performance. Test performance done by comparing result of K-NN prediction with real data and application implement. Research Result show the manual calculation prediction and application implement got an accuracy 0.7 or 7 0%, precision 1 and recall 0.7 so K-NN algorithm is good for Sengon sawing result prediction.

Item Type:	Artikel Umum
Subjects:	T Technology > T Technology (General)
Divisi / Prodi:	Faculty of Industrial Technology (Fakultas Teknologi Industri) > S1-Electrical Engineering (S1-Teknik Elektro)
Depositing User:	Anton Yudhana,
Date Deposited:	27 Jun 2022 02:10
Last Modified:	27 Jun 2022 02:10
URI:	http://eprints.uad.ac.id/id/eprint/35562

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