Otomatisasi klasifikasi kematangan buah mengkudu berdasarkan warna dan tekstur

Authors

  • Selvia Ferdiana Kusuma Teknik Informatika - Politeknik Kediri
  • Ratri Enggar Pawening Sekolah Tinggi Teknologi Nurul Jadid
  • Rohman Dijaya Universitas Muhammadiyah Sidoarjo

DOI:

https://doi.org/10.26594/register.v3i1.576

Keywords:

classification of noni, color, classification, texture, klasifikasi mengkudu, klasifikasi, KNN, SVM, tekstur, warna

Abstract

 

Buah Mengkudu merupakan komoditi ekspor yang sedang berkembang di Indonesia. Proses pengklasifikasian kematangan buah Mengkudu perlu dilakukan agar kualitas buah Mengkudu yang di ekspor dapat terjamin. Proses klasifikasi dengan jumlah yang banyak akan sulit apabila dilakukan secara manual. Oleh karena itu, penelitian ini diperlukan untuk menghasilkan proses otomatisasi klasifikasi kematangan buah Mengkudu. Metode yang diusulkan untuk melakukan otomatisasi klasifikasi adalah proses pengenalan karakteristik buah Mengkudu berdasarkan fitur tekstur dan warna. Fitur tektur dan fitur warna didapatkan melalui proses pengolahan citra digital buah Mengkudu. Penelitian ini membuktikan bahwa pengklasifikasian buah Mengkudu dengan algoritma Support Vector Machines (SVM) menghasilkan nilai persentase lebih tinggi dari pada menggunakan algoritma k-Nearest Neighbors (KNN). Hasil persentase tertinggi yang didapatkan yaitu sebesar 87.22%.

 

 

 

Noni fruit is an export commodities that were flourishing in Indonesia. Noni fruit maturity classification process should be done in order the quality of the noni fruit which is exported can be guaranteed. Classification process in large quantities will be difficult if it is done manually. Therefore this research is needed to produce an automation classification process of noni fruit ripeness. The proposed method is characteristic introduction of noni fruit based on texture and color features. Texture and color features are obtained from digital image processing of noni fruit. This research proves that the classification of noni fruit with SVM algorithm produces better accuracy than using KNN algorithm. The highest accuracy is equal to 87.22%.

Author Biography

Selvia Ferdiana Kusuma, Teknik Informatika - Politeknik Kediri

Dosen Teknik Informatika

References

Dijaya, R., Suciati, N., & Herumurti, D. (2016). Kombinasi Fitur Bentuk, Warna dan Tekstur untuk Identifikasi Kesuburan Telur Ayam Kampung Sebelum Inkubasi. Jurnal Buana Informatika, 7(3), 205-214.

El-Bendary, N., Hariri, E. E., Hassanien, A. E., & Badr, A. (2015). Using machine learning techniques for evaluating tomato ripeness. Expert Systems with Applications, 42(4), 1892–1905.

El-Bendary, N., Zawbaa, H. M., Hassanien, A. E., & Snasel, V. (2011). PCA-based home videos annotation system. International Journal of Reasoning-based Intelligent Systems, 3(2), 71-79.

Elhariri, E., El-Bendary, N., Hassanien, A. E., Badr, A., Hussein, A. M., & Snášel, V. (2014). Random Forests Based Classification for Crops Ripeness Stages. Proceedings of the Fifth International Conference on Innovations in Bio-Inspired Computing and Applications IBICA 2014 (pp. 205-215). Ostrava: Springer.

Gawande, A. P., & Dhande, S. S. (2014). Implementation of fruit Grading System by Image Processing and Data Classifier-A Review. International Journal of Engineering Research and General Science, 2(6), 411-413.

Hakim, L., Mutrofin, S., & Ratnasari, E. K. (2016). Segmentasi Citra menggunakan Support Vector Machine (SVM) dan Ellipsoid Region Search Strategy (ERSS) Arimoto Entropy berdasarkan Ciri Warna dan Tekstur. Register: Jurnal Ilmiah Teknologi Sistem Informasi, 2(1), 11-16.

Mulato, F. Y. (2015). Klasifikasi kematangan buah jambu biji merah (psidium guajava) dengan menggunakan model fuzzy. Yogyakarta: Program Studi Matematika Fakultas Matematika Dan Ilmu Pengetahuan Alam Universitas Negeri Yogyakarta.

Nursalim, S., & Himawan, H. (2014). Klasifikasi bidang kerja lulusan menggunakan algoritma k-nearest neighbor. Jurnal Teknologi Informasi, 10(1), 31-43.

Pawening, R. E., Dijaya, R., Brian, T., & Suciati, N. (2015). Classification of textile image using support vector machine with textural feature. Information & Communication Technology and Systems (ICTS) (pp. 119-122). Surabaya: IEEE.

Saifudin, & Fadil, A. (2015). Sistem identifikasi citra kayu berdasarkan tekstur menggunakan gray level coocurrence matrix (glcm) dengan klasifikasi jarak euclidean. Sinergi, 19(3), 181-186.

Singh, S. M., & Hemachandran, K. (2012). Content based Image Retrieval based on the integration of Color histogram, Color Moment and Gabor Texture. International Journal of Computer Applications, 17, 13-22.

Soman, S., Ghorpade, M., & Sonone, V. (2012). Content based image retrieval using advanced color and texture features. International Conference in Computational Intelligence (ICCIA), 3(4), 1-5.

Suryowinoto, S. M. (1997). Flora eksotika, tanaman peneduh. Yogyakarta: Kanisius.

Winarti, C. (2005). Peluang pengembangan minuman fungsional dari buah Mengkudu (morinda citrifolia L). Jurnal Litbang Pertanian, 24(4), 149-150.

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Published

2017-01-01

How to Cite

[1]
S. F. Kusuma, R. E. Pawening, and R. Dijaya, “Otomatisasi klasifikasi kematangan buah mengkudu berdasarkan warna dan tekstur”, Register: Jurnal Ilmiah Teknologi Sistem Informasi, vol. 3, no. 1, pp. 17–23, Jan. 2017.

Issue

Vol. 3 No. 1 (2017): January

Section

Article

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