Pengaruh Ekstraksi Fitur Tekstur Pada Hasil Klastering Data Citra Buah Menggunakan Metode K-Means Cluster
- Veronica Lusiana Universitas Stikubank, Semarang, Indonesia
- Imam Husni Al Amin Universitas Stikubank, Semarang, Indonesia
-
Budi Hartono
*
Universitas Stikubank, Semarang,
Indonesia
(*) Corresponding Author
Abstract
Penelitian ini bertujuan untuk menganalisis pengaruh ekstraksi fitur tekstur menggunakan metode grey level co-occurence matrix (GLCM) dan local binary pattern (LBP) pada hasil klastering data citra. Ekstraksi fitur tekstur dilakukan pada data uji 30 citra buah matang dan citra buah busuk. Melalui percobaan diperoleh hasil metode ekstraksi fitur LBP dapat menaikan nilai fitur kontras dan menurunkan nilai fitur korelasi. Pada fitur energi, dengan atau tanpa LBP maka perbedaan nilai fitur ini tidak terlalu jauh. Metode GLCM dan LBP berpengaruh pada hasil klastering data citra menggunakan k-means clustering. Data uji tanpa ekstraksi tekstur LBP, diperoleh dua alternatif hasil. Alternatif pertama, anggota klaster 1 yaitu 24 data dan klaster 2 yaitu 6 data. Alternatif kedua, anggota klaster 1 yaitu 22 data dan klaster 2 yaitu 8 data. Pada data uji dengan ekstraksi tekstur LBP, diperoleh tiga alternatif hasil. Alternatif pertama, anggota klaster 1 yaitu 23 data dan klaster 2 yaitu 7 data. Alternatif kedua, anggota klaster 1 yaitu 17 data dan klaster 2 yaitu 13 data. Alternatif ketiga, anggota klaster 1 dan klaster 2 masing-masing 15 data.
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References
M. S. Nixon and A. S. Aguado, "Feature Extraction and Image Processing for Computer Vision, Fourth Edition," Academic Press, Elsevier, 2020.
V. Meshram, K. Thanomliang, S. Ruangkan, P. Chumchu, and K. Patil, "FruitsGB: Top Indian Fruits with quality," IEEE Dataport, July 8, 2020, doi: https://dx.doi.org/10.21227/gzkn-f379.
J. Han, J. Pei, and H. Tong, "Data Mining Concepts and Techniques, Fourth Edition," Morgan Kaufmann, Elsevier, 2023.
B. Hartono, S. Eniyati, and K. Hadiono, "Perbandingan Metode Perhitungan Jarak pada Nilai Centroid dan Pengelompokan Data Menggunakan K-Means Clustering," Jurnal Sistem Komputer dan Informatika (JSON), Volume 4, Nomor 3, 2023, Hal: 503−509, DOI 10.30865/json.v4i3.6021.
I. Verawati and R. A. A. Aunurrohim, "Klasifikasi Penyakit Daun Padi Menggunakan KNN dengan GLCM dan Canny Edge Detection," Jurnal Media Informatika Budidarma (MIB), Vol. 8, No. 1, Hal. 517-527, Januari 2024, https://doi.org/10.30865/mib.v8i1.6906.
E. D. Hartono and B. Hardiansyah, "Analisis Intensitas Cahaya Lampu Pijar dengan Menerapkan Metode Gray Level Co-occurence Matrik" Jurnal Sistem Komputer dan Informatika (JSON), Vol. 4, No. 2, Hal. 407−412, Desember 2022, https://doi.org/10.30865/json.v4i2.5366.
P. N. Andono and E. H. Rachmawanto, "Evaluasi Ekstraksi Fitur GLCM dan LBP Menggunakan Multikernel SVM untuk Klasifikasi Batik," JURNAL RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol.5, No.1, Hal. 1-9, 2020, DOI: https://doi.org/10.29207/resti.v5i1.2615.
H. Gustiawidi, B. Hidayat, and S. Darana, "Identifikasi Kualitas Kesegaran Susu Sapi Melalui Pengolahan Citra Digital Menggunakan Metode Gray Level Co-Occurrence Matrix dan Local Binary Pattern dengan Klasifikasi K-Nearst Neighbor," e-Proceeding of Engineering, Vol.5, No.3, Hal. 4843 - 4850, Desember 2018, https://openlibrarypublications.telkomuniversity.ac.id/index.php/engineering/article/view/7834.
Azwar, "Integrasi Ekstraksi Fitur Local Binary Pattern dan Gray-Level Cooccurence Metrix untuk Pengenalan Ekspresi Mulut Pembelajar," Jurnal ILKOM, Vol. 9, No. 1, Hal. 17-24, 2017, https://doi.org/10.33096/ilkom.v9i1.105.17-24.
S. H. Khaleefah, S. A. Mostafa, A. Mustapha, and M. F. Nasrudin, "Review of Local Binary Pattern Operators in Image Feature Extraction," Indonesian Journal of Electrical Engineering and Computer Science, Vol. 19, No. 1, Hal. 23-31, July 2020, http://doi.org/10.11591/ijeecs.v19.i1.pp23-31.
S. Parveen, N. Naeem, and J. Devi, 2017, Review on Local Binary Pattern (LBP) Texture Descriptor and Its Variants, International Journal of Advanced Research (IJAR), Vol. 5 , Issue 5, Hal. 708-717, May 2017. http://dx.doi.org/10.21474/IJAR01/4169.
M. F. Abdi, Kusrini, and M. P. Kurniawan, "Local Binary Pattern untuk Ektraksi Tekstur Gambar Wajah Menggunakan Masker dan Tanpa Masker," Jurnal Technologia, Vol. 13, No. 2, Hal. 108-114, April 2022. https://ojs.uniska-bjm.ac.id/index.php/JIT/article/view/6275.
N. M. Y. D. Rahayu, M. W. A. Kesiman, and I. G. A. Gunadi, "Identifikasi Jenis Kayu Berdasarkan Fitur Tekstur Menggunakan Local Binary Pattern (LBP) Dengan Metode Learning Vector Quantization (LVQ)," Jurnal Janapati, Volume 10, Nomor 3, Hal. 157-166, Desember 2021. https://doi.org/10.23887/janapati.v10i3.40804.
F. Y. R. Dunggio, Y. A. Mustofa, and A. Bode, "Penerapan Metode Local Binary Pattern untuk Pengenalan Jenis Daun Tanaman Obat Tradisional Menggunakan Algoritma K-Nearest Neighbor," Jurnal cosPhi, Vol. 3 No. 1, Hal. 26-30, 2019. https://www.cosphijournal.unisan.ac.id/index.php/cosphihome/article/view/85.
S. R. Hidiya and M. E. Lasulika, "Fitur Ekstraksi LBP Untuk Mengidentifikasi Kematangan Tomat Sayur Menggunakan Metode K-Nearest Neighbor," Jurnal cosPhi, Vol. 3, No. 1, Hal. 37-41, 2019. https://cosphijournal.unisan.ac.id/index.php/cosphihome/article/view/86.
A. H. Lutfiannisa, Maimunah, and P. Sukmasetya, "Clustering Data Pasien Berdasarkan Usia di Puskesmas Menerapkan Metode K-Means," Journal of Information System Research (JOSH), Vol. 5, No. 2, Hal. 639−647, Januari 2024, https://doi.org/10.47065/josh.v5i2.4755.
G. Sonia and R. A. Putri, "Penerapan Metode K-Means Clustering Untuk Mengelompokkan Data Kelayakan Penerima Bantuan Renovasi Rumah," Building of Informatics, Technology and Science (BITS), Vol. 5, No. 2, Hal. 442−455, September 2023, https://doi.org/10.47065/bits.v5i2.4298.
A. Nursia, W. Ramdhan, and W. M. Kifti, "Analisis Kelayakan Penerima Bantuan Covid-19 Menggunakan Metode K–Means," Building of Informatics, Technology and Science (BITS), Vol. 3, No. 4, Hal. 574−583, Maret 2022, https://doi.org/10.47065/bits.v3i4.1399.
Syaifuddin, Ramlah, I. Hakim, Y. Berliana, and Nurhayati, "Pemetaan Produksi Tanaman Tomat di Indonesia Berdasarkan Provinsi Menggunakan Algoritma K-Means Clustering," Journal of Computer System and Informatics (JoSYC), Vol. 3, No. 4, Hal. 222−228, August 2022, https://doi.org/10.47065/josyc.v3i4.2206.
A. Maulana, A. Nazir, R. M. Candra, S. Sanjaya, and F. Syafria, "Clustering Vaksinasi Penyakit Mulut dan Kuku Menggunakan Algoritma K-Means," Journal of Information System Research (JOSH), Vol 4, No. 3, Hal. 894−902, April 2023, DOI 10.47065/josh.v4i3.3363.
F. Rahmadayanti, I. Anggraini, and T. Susanti, "Pengklasterisasian Data Penyakit Hipertensi dengan Menggunakan Metode K-Means," Journal of Information System Research (JOSH), Vol. 4, No. 2, Hal. 737−741, Januari 2023, https://doi.org/10.47065/josh.v4i2.2905.
A. F. Khairani, A. Nazir, T. Darmizal, Y. Vitriani, and Yusra, "Klasterisasi Peserta BPJS Berdasarkan Rekam Medis Menggunakan Algoritma K-Means", Journal of Computer System and Informatics (JoSYC), Vol. 4, No. 3, Hal. 625−631, Mei 2023, https://doi.org/10.47065/josyc.v4i3.3442.
Mayadi, S. Setiawati, and W. Priatna, "Pengelompokan Hasil Survei MBKM Menggunakan K-Mean dan K-Medoids Clustering," Jurnal Media Informatika Budidarma (MIB), Vol. 7, No. 1, Hal.426-435, Januari 2023, https://doi.org/10.30865/mib.v7i1.5003.
A. Rahmadhani, "Pendekatan Clustering untuk Menganalisis Efisiensi dan Kinerja Mahasiswa Berdasarkan Data Menerapkan Metode K-Means," Jurnal Media Informatika Budidarma (MIB), Vol. 6, No. 4, Hal. 2461-2468, Oktober 2022, https://doi.org/10.30865/mib.v6i4.4922.
I. D. Setiawan and A. Triayudi, "Penerapan Algoritma Clustering K-Means Data Mining dalam Pengelompokan Mahasiswa Penerima Beasiswa," Journal of Computer System and Informatics (JoSYC), Vol. 5, No. 2, Hal. 430-441, February 2024, https://doi.org/10.47065/josyc.v5i2.4971.
H. Nopriandi and F. Haswan, "Analisis Klasterisasi Mahasiswa Baru dalam Memilih Program Studi dengan Menggunakan Algoritma K-Means," Journal of Information System Research (JOSH), Vol. 3, No. 4, Hal. 666−671, Juli 2022, https://doi.org/10.47065/josh.v3i4.1986.
D. Huang, C. Shan, M. Ardabilian, Y. Wang, and L. Chen, "Local Binary Patterns and Its Application to Facial Image Analysis: A Survey," IEEE Transactions on Systems, Man, and Cybernetics - Part C: Applications And Reviews, Vol. 41, No. 6, Hal 765-781, November 2011, https://doi.org/10.1109/TSMCC.2011.2118750.
J. Lizé, V. Débordès, H. Lu, K. Kpalma, and J. Ronsin, "Local binary pattern and its variants: application to face analysis," In: A. El Moussati,K. Kpalma, M. G. Belkasmi, M. Saber, and S. Guégan (eds), Advances in Smart Technologies Applications and Case Studies, SmartICT 2019, Lecture Notes in Electrical Engineering, vol 684, Springer, 2020, http://dx.doi.org/10.1007/978-3-030-53187-4_11.
J. Chaki and N. Dey, "Texture Feature Extraction Techniques for Image Recognition," Springer, 2020.
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