Modifikasi Metode Fuzzy C-Means untuk Klasifikasi Citra Daun Padi

Authors

DOI:

https://doi.org/10.30872/jim.v17i1.6068

Keywords:

Matriks Fuzzy, fuzzy c-means, Matriks Partisi U

Abstract

Metode Fuzzy C-means merupakan algoritma pembelajaran tidak terawasi yang menggunakan derajat keanggotaan untuk menentukan cluster tiap-tiap titik data. Proses pembelajaran yang tidak terawasi menjadi keunggulan untuk dapat diterapkan pada gambar yang terdapat noise. Dilakukan modifikasi terhadap metode Fuzzy C-means yaitu dengan melakukan penentuan dan perubahan matriks partisi  menggunakan fungsi keanggotaan fuzzy untuk mendapatkan proses pembelajaran dan akurasi cluster. Penelitian ini bertujuan untuk mendapatkan model terbaik klasifikasi warna daun padi (Oryza Sativa) berdasarkan citra digital dengan menggunakan modifikasi metode fuzzy c-means yang diterapkan untuk klasifikasi. Data citra daun padi yang digunakan sebanyak  citra dengan ukuran  dimana data dibagi menjadi data latih  citra untuk mendapatkan model dan 160 citra digunakan untuk pengujian model klasifikasi. Data citra diubah menjadi matriks Red, Green, Blue (RGB) yang kemudian ditransformasi menjadi matriks fuzzy. Penetapan nilai elemen-elemen matriks partisi  dilakukan dengan membangkitkan bilangan random berdistribusi Uniform yang kemudian diubah menjadi matriks fuzzy. Model fuzzy c-means terbaik untuk klasifikasi diperoleh dengan menggunakan pusat cluster dari proses pembelajaran pada 9 percobaan terhadap parameter pangkat (). Diperoleh model terbaik modifikasi metode fuzzy c-means untuk klasifikasi pada percobaan parameter pangkat () sama dengan 2 dengan accuracy (ACC) 71%,  specificity (SPC) 76%, sensitivity (TPR) 54%, positive predictive value (PPV) 51%, dan negative predictive value (NPV) 85%.

References

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Published

2023-07-03

Issue

Vol. 17 No. 1 (2022): Informatika Mulawarman : Jurnal Ilmiah Ilmu Komputer

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