Alfin, Achmad Arif (2019) Optimalisasi Tingkat Kesuburan Tanaman Tebu Pada Pada Precision Agriculture Menggunakan Metode Fuzzy Logic. Masters thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Kesuburan tanah memiliki peranan yang signifikan dalam industri perkebunan tebu untuk menjaga kesuburan tanaman sehingga diperoleh produktivitas hasil yang optimal. Sistem pengelolaan yang selama ini digunakan petani hanya merujuk pada kebiasaan dan perkiraan, sehingga belum bisa menentukan dengan tepat kebutuhan air, zat kapur dan pupuk pada masing-masing area tanaman. Oleh karena itu, diperlukan sebuah sistem yang mampu memberikan referensi pemberian volume air, kadar kapur dan pemupukan sesuai dengan tingkat kebutuhan nutrisi tanaman tebu. Penelitian ini bertujuan untuk merancang sistem yang mampu memberikan rekomendasi kebutuhan tanaman tebu berdasarkan kandungan nutrisi tanah menggunakan metode Fuzzy Logic. Tahap pertama dalam metode ini yaitu proses fuzzifikasi yang dilakukan pada empat jenis data yang digunakan sebagai parameter input, yaitu kelembaban tanah, pH tanah, umur tanaman, dan kandungan nutrisi. Langkah berikutnya memilih kriteria yang relevan dari setiap penilaian hingga diperoleh alternatif terbaik. Tahap berikutnya, dibuat fungsi keanggotaan untuk memperkirakan proses selanjutnya dan proses defuzzifikasi. Dari hasil penelitian didapatkan nilai efisiensi biaya, optimasi pertumbuhan tinggi batang dan anakan tanaman. Efisiensi biaya yang dihasilkan sebesar 37,09% dibandingkan dengan metode pabrik. Sedangkan tingkat optimasi pertumbuhan tanaman dibandingkan dengan metode pabrik, pertumbuhan anakan meningkat 8% namun pertumbuhan tinggi batang primer lebih tinggi metode pabrik 3%.
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Soil fertility has a significant role in the sugarcane plantation industry to maintain plant fertility so that optimal yield productivity is obtained. The management system that has been used by farmers only refers to habits and estimates, so that it can’t determine the exact needs of water, lime and fertilizers in each area of the plant. Therefore, we need a system that are able to provide a reference for giving water volume, lime content and fertilization according to the level of nutritional needs of sugarcane plants. This study aims to design a system that is able to provide recommendations for sugarcane needs, based on soil nutrient content using the Fuzzy Logic method. The first step in this method is the fuzzification process carried out on four types of data used as input parameters, namely soil moisture, soil pH, plant phase, and nutrient content. The next step is choosing the relevant criteria from each assessment to get the best alternative. The next stage, a membership function is created to estimate the next process and defuzzification process. From the results of the study found the value of cost efficiency, optimization of growth in stem height and plant tillers. From the results of the study obtained value of cost efficiency, optimization of growth in stem height and plant tillers. The resulting cost efficiency is 37.09% compared to the factory method. While the level of optimization of plant growth compared to the factory method, tillering growth increased 8% but the growth of primary stem height was higher by the factory method of 3%.
| Item Type: | Thesis (Masters) |
|---|---|
| Additional Information: | RTMT 658.403 Alf o-1 2019 |
| Uncontrolled Keywords: | defuzzification, fuzzification, Fuzzy Logic, irrigation, soil fertility |
| Subjects: | H Social Sciences > HD Industries. Land use. Labor > HD30.23 Decision making. Business requirements analysis. Q Science > QA Mathematics > QA9.64 Fuzzy logic T Technology > T Technology (General) T Technology > T Technology (General) > T58.5 Information technology. IT--Auditing |
| Divisions: | Faculty of Creative Design and Digital Business (CREABIZ) > Technology Management > 61101-(S2) Master Thesis |
| Depositing User: | Alfin Achmad Arif |
| Date Deposited: | 29 Oct 2021 04:52 |
| Last Modified: | 29 Oct 2021 04:52 |
| URI: | http://repository.its.ac.id/id/eprint/61340 |
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