IDENTIFICATION OF HERBAL PLANT BASED ON LEAF IMAGE USING GLCM FEATURE AND K-MEANS

Identifikasi Tumbuhan Berdasarkan Citra Daun Menggunakan GLCM Feature dan K-means

  • Recha Abriana Anggraini (1*) Information System, Universitas Bina Sarana Informatika, Jakarta, Indonesia
  • Fanny Fatma Wati (2) Information System, Universitas Bina Sarana Informatika, Jakarta, Indonesia
  • Muhammad Ja’far Shidiq (3) Computer Science STMIK Nusa Mandiri, Jakarta, Indonesia
  • Ade Suryadi (4) Information System, Universitas Bina Sarana Informatika, Jakarta, Indonesia
  • Haerul Fatah (5) Information System, Universitas Bina Sarana Informatika, Jakarta, Indonesia
  • Desiana Nur Kholifah (6) Software Engineering, Universitas Bina Sarana Informatika, Jakarta, Indonesia

  • (*) Corresponding Author
Keywords: Leaf Image, GLCM, Herbal Plants, K-Means Clustering

Abstract

Medicinal plants are one of the groups of plants that have enormous benefits for humans because they can help the medical process for healing disease. Herbal plants can be used as ingredients for medicines, medicines produced from herbal plants are also natural. Lack of knowledge of herbal plants causes people to prefer chemical-based medicines to help cure their diseases, even though chemical-based drugs have side effects on human health. This study aims to identify types of herbal plants based on the extraction of contrast, correlation, energy, and homogeneity features as well as shape recognition based on metric and eccentricity values. The method used in this research is GLCM features and K-means clustering. In this study, the data used consisted of 352 data divided into 320 training data and 32 testing data. This research succeeded in identifying and classifying herbal plant species using GLCM features and K-means clustering segmentation with an average accuracy value of 85.94%.

References

Anggraini, R. A., Wati, F. F., Shidiq, M. J., Suryadi, A., Fatah, H., & Kholifah, D. N. (2020). IDENTIFIKASI TUMBUHAN BERDASARKAN CITRA DAUN MENGGUNAKAN GLCM FEATURE DAN K-MEANS.

Auliasari, K., & Kertaningtyas, M. (2018). Studi Komparasi Klasifikasi Pola Tekstur Citra Digital Menggunakan Metode K-Means Dan Naïve Bayes. Jurnal Informatika, 18(2), 175–185.

Chaki, J., & Parekh, R. (2011). Plant leaf recognition using shape based features and neural network classifiers. International Journal of Advanced Computer Science and Applications, 2(10), 41–47.

Ganis, K., Santoso, I., & Isnanto, R. R. (n.d.). Klasifikasi Citra Dengan Matriks Ko-Okurensi Aras Keabuan (Gray Level Co-Occurrence Matrix-GLCM) Pada Lima Kelas Biji-Bijian. Universitas Diponegoro.

Goëau, H., Joly, A., Bonnet, P., Bakic, V., Barthélémy, D., Boujemaa, N., & Molino, J. F. (2013). The ImageCLEF plant identification task 2013. MAED 2013 - Proceedings of the 2nd ACM International Workshop on Multimedia Analysis for Ecological Data, 23–28. https://doi.org/10.1145/2509896.2509902

Hidanti, M., Zahra, A. A., & Isnanto, R. R. (2016). SISTEM IDENTIFIKASI JENIS TANAMAN OBAT MENGGUNAKAN MATRIKS KOOKURENSI ARAS KEABUAN (GLCM) DAN JARAK CANBERRA. FORTEI 2016.

Jundullah, A., & Syahrul Mubarok, M. (2016). Analisis dan Implementasi Deteksi Citra Spam Menggunakan Gray Level Co-occurences Matrix dan Naive Bayes. Indonesia Symposium on Computing (IndoSC) 2016, 319–334. https://doi.org/10.21108/indosc.2016.164

Liantoni, F., & Nugroho, H. (2015). KLASIFIKASI DAUN HERBAL MENGGUNAKAN METODE NAÏVE BAYES CLASSIFIER DAN KNEAREST NEIGHBOR | Liantoni | Jurnal Simantec. Jurnal Simantec, 5(1), 9–16.

Ni’mah, F. S., Sutojo, T., & Setiadi, D. R. I. M. (2018a). Identifikasi Tumbuhan Obat Herbal Berdasarkan Citra Daun Menggunakan Algoritma Gray Level Co-occurence Matrix dan K-Nearest Neighbor. Jurnal Teknologi Dan Sistem Komputer, 6(2), 51. https://doi.org/10.14710/jtsiskom.6.2.2018.51-56

Ni’mah, F. S., Sutojo, T., & Setiadi, D. R. I. M. (2018b). Identifikasi Tumbuhan Obat Herbal Berdasarkan Citra Daun Menggunakan Algoritma Gray Level Co-occurence Matrix dan K-Nearest Neighbor. Jurnal Teknologi Dan Sistem Komputer, 6(2), 51–56. https://doi.org/10.14710/jtsiskom.6.2.2018.51-56

Purnamasari, I., & Sutojo, T. (2017). PENGENALAN CIRI GARIS TELAPAK TANGAN MENGGUNAKAN EKSTRAKSI FITUR (GLCM) DAN METODE K-NN. Jurnal VOI (Voice Of Informatics), 6(1), 32–41.

Rahmadewi, R., Purwanti, E., & Efelina, V. (2018). Identifikasi Jenis Tumbuhan Menggunakan Citra Daun Berbasis Jaringan Saraf Tiruan Artificial Neural Networks. Jurnal Media Elektro, VII(2), 38–43. https://ejurnal.undana.ac.id/jme/article/view/427

Sutojo, T., Setiadi, D. R. I. M., Tirajani, P. S., Sari, C. A., & Rachmawanto, E. H. (2018). CBIR for classification of cow types using GLCM and color features extraction. Proceedings - 2017 2nd International Conferences on Information Technology, Information Systems and Electrical Engineering, ICITISEE 2017, 2018-January, 182–187. https://doi.org/10.1109/ICITISEE.2017.8285491

Wu, S. G., Bao, F. S., Xu, E. Y., Wang, Y. X., Chang, Y. F., & Xiang, Q. L. (2007). A leaf recognition algorithm for plant classification using probabilistic neural network. ISSPIT 2007 - 2007 IEEE International Symposium on Signal Processing and Information Technology, 11–16. https://doi.org/10.1109/ISSPIT.2007.4458016

Published
2020-03-16
How to Cite
Anggraini, R., Wati, F., Shidiq, M., Suryadi, A., Fatah, H., & Kholifah, D. (2020). IDENTIFICATION OF HERBAL PLANT BASED ON LEAF IMAGE USING GLCM FEATURE AND K-MEANS. Jurnal Techno Nusa Mandiri, 17(1), 71-78. https://doi.org/10.33480/techno.v17i1.1087
Article Metrics

Abstract viewed = 530 times
PDF downloaded = 441 times