Penerapan Metode Deteksi Tepi dan Operasi Morfologi untuk Penentuan Lokasi Simpul Tebu

Azkiyah, Habibatul (2022) Penerapan Metode Deteksi Tepi dan Operasi Morfologi untuk Penentuan Lokasi Simpul Tebu. Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Teknologi pengolahan citra digital telah banyak dimanfaatkan dalam berbagai bidang, salah satunya pada sektor pertanian dan perkebunan. Pada sektor perkebunan, tebu merupakan salah satu komoditas penting yang berperan dalam perekonomian di Indonesia. Metode Single Bud Planting merupakan metode pembibitan tebu menggunakan satu mata tunas. Metode pembibitan ini kini sedang dikembangkan di Indonesia. Namun kesediaan alat pemotong bibit tebu satu mata tunas dengan standar operasional yang tinggi masih menjadi kendala. Peran pengolahan citra digital dapat digunakan untuk mengatasi permasalahan tersebut dengan adanya otomatisasi alat pemotong bibit. Dalam Tugas Akhir ini dirancang algoritma penentuan lokasi simpul tebu menggunakan metode deteksi tepi dan operasi morfologi. Proses yang dilakukan terdiri dari pra-pengolahan citra, segmentasi citra, deteksi tepi citra, operasi morfologi dan pelabelan simpul tebu. Algoritma yang disusun digunakan untuk mendeteksi 1 simpul, 2 simpul, dan 3 simpul tebu. Berdasarkan uji coba yang dilakukan, diperoleh metode deteksi tepi dan operasi morfologi terbaik untuk penentuan lokasi simpul tebu. Untuk deteksi 1 simpul diperoleh metode terbaik yaitu Prewitt dengan akurasi 97.5%, dan Sobel dengan akurasi 97.5%. Sedangkan untuk deteksi 2 simpul dan 3 simpul diperoleh metode terbaik yaitu Prewitt dengan akurasi masing-masing sebesar 55% dan 47.27%.
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Digital image processing technology has been widely used in various fields, one of which is in the agricultural and plantation sectors. In the plantation sector, sugar cane is one of the important commodities that play a role in the economy in Indonesia. The Single Bud Planting method is a method of breeding sugarcane using one bud. This seedling method is currently being developed in Indonesia. However, the availability of seed cutting tools with high operational standards is still an obstacle. The role of digital image processing can be used to overcome these problems with the automation of seed cutting tools. In this final project, an algorithm for determining the location of sugarcane nodes is designed using edge detection methods and morphological operations. The process consists of image pre-processing, image segmentation, image edge detection, morphological operations and labeling of sugarcane nodes. The compiled algorithm is used to detect 1 node, 2 nodes, and 3 sugar cane nodes. Based on trials conducted, the best of edge detection methods and morphological operations were obtained for the determination of the location of sugarcane nodes. To detect of 1 node, the best method is Prewitt with an accuracy of 97.5% and Sobel with an accuracy of 97.5%. Meanwhile, to detect of 2 nodes and 3 nodes, the best method is Prewitt with an accuracy 55% and 47.27%, respectively.

Item Type:	Thesis (Other)
Additional Information:	RSMa 006.42 Azk p-1 2022
Uncontrolled Keywords:	Deteksi Simpul Tebu. Metode Deteksi Tepi. Operasi Morfologi. Pengolahan Citra Digital. Sugarcane Nodes Detection. Edge Detection Methods. Morphological Operation. Digital Image Processing.
Subjects:	Q Science > QA Mathematics
Divisions:	Faculty of Mathematics and Science > Mathematics > 44201-(S1) Undergraduate Thesis
Depositing User:	Mr. Marsudiyana -
Date Deposited:	08 Jun 2026 06:58
Last Modified:	08 Jun 2026 06:58
URI:	http://repository.its.ac.id/id/eprint/133635

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