Rancang Bangun Alat Sortir Buah Jeruk Berdasarkan Tingkat Kematangan Berbasis Image Processing

Ramadhan, Nugie Rahmat (2025) Rancang Bangun Alat Sortir Buah Jeruk Berdasarkan Tingkat Kematangan Berbasis Image Processing. Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Peningkatan kualitas buah jeruk yang bernilai jual tinggi sangat penting untuk menjaga daya saing di pasar. Salah satu langkah kritis dalam proses ini adalah penyortiran. Langkah ini bertujuan untuk memisahkan buah berdasarkan tingkat kematangan agar produk yang dijual memiliki kualitas tinggi dan sesuai preferensi konsumen. Penelitian ini bertujuan merancang dan membangun alat sortir buah jeruk berbasis image processing. Alat ini memanfaatkan webcam dan algoritma Convolutional Neural Network (CNN) menggunakan arsitektur MobileNetV2. Alat ini dirancang untuk mengklasifikasikan tingkat kematangan buah jeruk berdasarkan warna kulitnya, dengan parameter berupa nilai RGB yang dianalisis oleh sistem. Hasil implementasi menunjukkan bahwa alat ini mampu menampilkan hasil sortasi berupa sistem counter dan nilai RGB pada GUI, yang dapat diakses melalui monitor. Pengujian terhadap 8 sampel jeruk menunjukkan tingkat akurasi sebesar 87.5%, dengan 7 sampel terklasifikasi secara benar.
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Improving the quality of high-value citrus fruits is essential to maintain competitiveness in the market. One of the critical steps in this process is sorting. This step aims to separate the fruit based on the maturity level so that the products sold have high quality and according to consumer preferences. This research aims to design and build an image processing-based citrus fruit sorting tool. This tool utilizes a webcam and Convolutional Neural Network (CNN) algorithm using MobileNetV2 architecture. This tool is designed to classify the ripeness level of citrus fruits based on the color of their skin, with parameters in the form of RGB values analyzed by the system. The implementation results show that this tool is able to display the sorting results in the form of a counter system and RGB values on the GUI, which can be accessed through a monitor. Tests on 8 orange samples showed an accuracy rate of 87.5%, with 7 samples classified correctly.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	Image Processing, CNN, MobileNetV2, Penyortiran Buah Jeruk, Tingkat Kematangan. ======================================================================================================================== Image Processing, CNN, MobileNetV2, Citrus Fruit Sorting, Maturity Level.
Subjects:	Q Science > Q Science (General) Q Science > Q Science (General) > Q325.5 Machine learning. Support vector machines. Q Science > Q Science (General) > Q337.5 Pattern recognition systems T Technology > T Technology (General) T Technology > TJ Mechanical engineering and machinery > TJ1398 Conveyors T Technology > TJ Mechanical engineering and machinery > TJ213 Automatic control. T Technology > TJ Mechanical engineering and machinery > TJ223.A25 Actuators. T Technology > TJ Mechanical engineering and machinery > TJ230 Machine design T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK1007 Electric power systems control T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK3070 Automatic control T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK6592.A9 Automatic tracking. T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7871.674 Detectors. Sensors T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7878 Electronic instruments T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7882.P3 Pattern recognition systems T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7888.3 Digital computers T Technology > TS Manufactures > TS155 Production control. Production planning. Production management T Technology > TS Manufactures > TS156 Quality Control. QFD. Taguchi methods (Quality control) T Technology > TS Manufactures > TS170 New products. Product Development T Technology > TS Manufactures > TS171 Product design T Technology > TS Manufactures > TS176 Manufacturing engineering. Process engineering (Including manufacturing planning, production planning) T Technology > TS Manufactures > TS183 Manufacturing processes. Lean manufacturing.
Divisions:	Faculty of Vocational > Instrumentation Engineering
Depositing User:	Nugie Rahmat Ramadhan
Date Deposited:	04 Aug 2025 06:31
Last Modified:	04 Aug 2025 06:31
URI:	http://repository.its.ac.id/id/eprint/126819

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