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All Journal OKTAL : Jurnal Ilmu Komputer dan Sains
Julya Rahmah Shanty
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Astronomy Chemistry Computer Science & IT Electrical & Electronics Engineering Social Sciences

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PENERAPAN K-NEAREST NEIGHBORS PADA PERCEPTRON UNTUK KLASIFIKASI DATASET KECIL DENGAN TIGA FITUR Arjuna Ranma Putra; Julya Rahmah Shanty; Maria Lodiana Leki; Muhammad Aqshal Hidayat Fizhillillah; Rifky Firmansyah; Devi Yunita
OKTAL : Jurnal Ilmu Komputer dan Sains Vol 3 No 11 (2024): OKTAL : Jurnal Ilmu Komputer Dan Sains
Publisher : CV. Multi Kreasi Media

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Abstract

In developing machine learning models for small datasets, choosing the right method is key to producing accurate classification. This research applies the Single Layer Perceptron (SLP) algorithm to classify a small dataset with three main features, namely Feature1, Feature2, and Feature3. The SLP algorithm is used to learn patterns in the data, with model evaluation using the k-fold cross-validation technique. This technique ensures each piece of data is used as test and training data in turn, to obtain more accurate evaluation results. In addition, the k-Nearest Neighbor (k-NN) algorithm was used to find the optimal K parameter value to improve the accuracy of the model. This study used 13 sample data to train and test the model.
Co-Authors Arjuna Ranma Putra Devi Yunita Maria Lodiana Leki Muhammad Aqshal Hidayat Fizhillillah Rifky Firmansyah