Klasifikasi Jenis Pisang Berdasarkan Tekstur Isi Buah Pisang Menggunakan Metode K-Nearest Neighbour

LESE, Anggelina Oriana (2025) Klasifikasi Jenis Pisang Berdasarkan Tekstur Isi Buah Pisang Menggunakan Metode K-Nearest Neighbour. Undergraduate thesis, Universitas Katolik Widya Mandira Kupang.

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Abstract

Bananas are tropical fruits with high nutritional content and a variety of unique varieties. With the increasing demand for bananas in the agricultural and food industries, the manual classification of banana varieties poses a challenge, as it requires time and specialized expertise. This study aims to automatically identify banana varieties based on texture features using the K-Nearest Neighbour (K-NN) method. The research methodology includes data collection techniques, requirement analysis, system design, training, and classification system testing. The image sample data used in this study consists of 300 images from three categories of banana types: Pisang Ambon, Pisang Susu, and Pisang Kapok, captured from vertical and horizontal angles. The training data sample consists of 240 images, while the test data sample consists of 60 images. The classification of banana types is conducted using MATLAB R2018a software. The result of the study indicates that the K-NN method was successfully applied with a high classification accuracy, achieving a training data accuracy of 91.25% and a test data accuracy of 78,33%.

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