Identifikasi Jenis Buah "Pyrus" (Pir) Menggunakan Algoritma Adaptive Neuro Fuzzy Inference System (ANFIS)

Riyan Latifahul Hasanah

Abstract


Salah satu buah yang cukup populer di Indonesia adalah buah pir atau Pyrus. Metode identifikasi jenis buah pir yang dilakukan secara manual berdasarkan bentuk dan warnanya, akan menimbulkan kemungkinan hasil identifikasi yang kurang akurat dikarenakan identifikasi masih berdasarkan persepsi individu. Digital image processing diterapkan untuk mengatasi permasalahan di atas. Penelitian ini dilakukan untuk mengidentifikasi jenis buah pir yang terdiri dari dua jenis, yaitu Pir Monster dan Pir William. Pre-processing dilakukan dengan mengubah citra RGB menjadi L*a*b, kemudian segmentasi menggunakan algoritma K-Means Clustering. Citra tersegmentasi diekstraksi kedalam tujuh fitur, yaitu enam fitur warna (RGB dan HSV) dan satu fitur ukuran (Area). Kemudian klasifikasi dilakukan dengan menerapkan algoritma Adaptive Neuro Fuzzy Inference System (ANFIS). Hasil penelitian menunjukkan akurasi yang tinggi dalam mengidentifikasi jenis buah pir.One fruit that is quite popular in Indonesia is the pear or Pyrus. The method that determines the type of pear which is done manually based on its shape and color, will affect inaccurate results because it still involves the individual's perception. Digital image processing is applied to overcome the above problem. This research was conducted to complement the types of pears consisting of two types, namely Monster Pears and William Pears. Pre-processing is done by changing the RGB image into L*a*b, then segmentation using the K-Means Clustering algorithm. Segmented image is extracted into seven features, namely six color features (RGB and HSV) and one size feature (Area). Then the classification is done by applying the Adaptive Neuro Fuzzy Inference System (ANFIS) algorithm. The results showed high accuracy in the types of pears.

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References


Ahmad, Usman. 2010. “Aplikasi Teknik Pengolahan Citra Dalam Analisis Non-Destruktif Produk Pangan.” Jurnal Pangan 19(1): 71–80. http://www.jurnalpangan.com/index.php/pangan/article/view/119.

Fashi, Mahya, Leila Naderloo, and Hossein Javadikia. 2019. “The Relationship between the Appearance of Pomegranate Fruit and Color and Size of Arils Based on Image Processing.” Postharvest Biology and Technology 154: 52–57. https://doi.org/10.1016/j.postharvbio.2019.04.017.

Herrera, Luis J. et al. 2017. “A Model for Prediction of Color Change after Tooth Bleaching Based on CIELAB Color Space.” Proceedings of SPIE 10453. https://ui.adsabs.harvard.edu/abs/2017SPIE10453E..1XH/abstract.

Hodijah, Nur Saqinah, Retno Nugroho Whidhiasih, and Dadan Irwan. 2017. “Identifikasi Buah Mangga Gedong Gincu Cirebon Berdasarkan Citra Red-Green-Blue Menggunakan Adaptif Neuro Fuzzy Inference System.” Jurnal Penelitian Ilmu Komputer, System Embedded & Logic 5(1): 12–20. https://media.neliti.com/media/publications/231624-identifikasi-buah-mangga-gedong-gincu-ci-33e56cfa.pdf.

Hrosik, Romana Capor et al. 2019. “Brain Image Segmentation Based on Firefly Algorithm Combined with K-Means Clustering.” Studies in Informatics and Control 28(2): 167–76. https://sic.ici.ro/wp-content/uploads/2019/06/Art.-5-Issue-2-SIC-2019.pdf.

Iqbal, S. Md., A. Gopal, P. E. Sankaranarayanan, and Athira B. Nair. 2016. “Classification of Selected Citrus Fruits Based on Colour Using Machine Vision System.” International Journal of Food Properties 19(2): 37–41. https://www.tandfonline.com/doi/citedby/10.1080/10942912.2015.1020439?scroll=top&needAccess=true.

Karaboga, Dervis, and Ebubekir Kaya. 2019. “Adaptive Network Based Fuzzy Inference System ( ANFIS ) Training Approaches : A Comprehensive Survey.” Artificial Intelligence Review 52. https://doi.org/10.1007/s10462-017-9610-2.

Maulana, Febian Fitra, and Naim Rochmawati. 2019. “Klasifikasi Citra Buah Menggunakan Convolutional Neural Network.” Journal of Informatics and Computer Science 1(2): 104–8. https://jurnalmahasiswa.unesa.ac.id/index.php/jinacs/article/download/31406/28492.

Octavia, Mulia, K Jesslyn, and Gasim. 2016. “Perbandingan Tingkat Akurasi Jenis Citra Keabuan, HSV, Dan L*a*b Pada Identifikasi Jenis Buah Pir.” Jurnal Ilmiah Informatka Global 7(1): 7–11. http://ejournal.uigm.ac.id/index.php/IG/article/view/143.

Wijaya, Novan, and Anugrah Ridwan. 2019. “Klasifikasi Jenis Buah Apel Dengan Metode K-Nearest Neighbor.” SISFOKOM 8(1): 74–78. http://jurnal.atmaluhur.ac.id/index.php/sisfokom/article/view/610.

Zainuddin, Muhammad, Lince Tomoria Sianturi, and Rivalri Kristianto Hondro. 2017. “Implementasi Metode Robinson Operator 3 Level Untuk Mendeteksi Tepi Pada Citra Digital.” Jurnal Riset Komputer 4(4): 1–5. https://ejurnal.stmik-budidarma.ac.id/index.php/jurikom/article/view/681.




DOI: https://doi.org/10.31294/evolusi.v9i1.10318

ISSN: 2657-0793 (online). ISSN: 2338-8161 (print)

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