Nur Ayuningtya, Dewi (2021) PENERAPAN DIGITAL IMAGE PROCESSING UNTUK MENGUKUR PERTUMBUHAN PAKCOY PADA BUDIDAYA TANAMAN HIDROPONIK INDOOR. Sarjana thesis, Universitas Brawijaya.
Abstract
Pertanian hidroponik indoor turut berkontribusi dalam pertumbuhan ekonomi Indonesia. Namun, hasil pertanian yang kurang pengawasan mengakibatkan gagal panen. Maka, monitoring pertumbuhan tanaman dengan pengolahan citra digital dilakukan. Pertumbuhan tanaman dapat dihitung dari luas daunnya, sehingga para petani dapat memantau pertumbuhan tanaman mereka dan memberikan perlakuan yang sesuai. Penulis merancang sistem monitoring pertumbuhan pakcoy menggunakan metode Color Image Segmentation dengan membandingkan dua ruang warna, HSV dan CIELAB. Hasil akhir pengukuran berupa luas area daun dalam satuan cm2. Selain itu, monitoring dilakukan pada pagi, sore, dan malam hari untuk dilihat waktu manakah yang paling efektif. Hasil pengujian menunjukkan implementasi metode CIELAB untuk monitoring pertumbuhan pakcoy memiliki tingkat akurasi lebih tinggi dibandingkan metode HSV, hingga 96%. Performa sistem paling baik pada malam hari, yang hanya mendapatkan sumber cahaya dari LED strip putih. Selain itu, pertumbuhan pakcoy hasil monitoring tidak selalu bertambah tiap harinya karena kondisi tanaman dan lingkungannya yang selalu berubah-ubah.
English Abstract
Agriculture is an important sector in contributing to economic growth in Indonesia. Farmers who don’t own any land are starting to cultivate indoor using hydroponics to help meet the demand for crops. However, less supervisions to agriculture field have an impact on crop failure and losses. Thus, monitoring plant growth with digital image processing is carried out. Plant growth can be analyzed through images and the leaf area of the plant can be calculated, so that farmers can easily aggregate plant growth based on quantity. The author designed a pakcoy growth monitoring system using the Color Image Segmentation method with two different color spaces, HSV and CIELAB. The measurement results are leaf area in pixels which are then converted into cm2 units. These two methods will be compared and assessed for accuracy. In addition, monitoring system data collection is carried out in the morning, afternoon, and evening to see the best time for monitoring. The test results show that the design and implementation of image processing on the pakcoy monitoring system is successful. The CIELAB method has a higher accuracy rate than the HSV method, with an accuracy rate of up to 96%. The most effective time to perform this system is at night, 22.00 WIB, where the white LED strip is the only lighting source. Moreover, the growth of pakcoy in the monitoring data doesn’t always increase every day. This is caused due to the position of the leaves that change, the condition of wilt and less green leaves, and the effect of light coming from the outdoor is not always the same every day. Keyword— Area of leaf, Color Image Segmentation, CIELAB, HSV, Indoor Hydroponic, Pak choy
Other obstract
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| Item Type: | Thesis (Sarjana) |
|---|---|
| Identification Number: | 621.381 |
| Uncontrolled Keywords: | Kata kunci— Area daun, Color Image Segmentation, CIELAB, HSV, Hidroponik Indoor, Pakcoy-- Area of leaf, Color Image Segmentation, CIELAB, HSV, Indoor Hydroponic, Pak choy |
| Subjects: | 600 Technology (Applied sciences) > 621 Applied physics > 621.3 Electrical, magnetic, optical, communications, computer engineering; electronics, lighting > 621.38 Electronics, communications engineering > 621.381 Electronics |
| Depositing User: | Unnamed user with email gaby |
| Date Deposited: | 20 Oct 2021 04:48 |
| Last Modified: | 24 Feb 2022 02:13 |
| URI: | http://repository.ub.ac.id/id/eprint/184287 |
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