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<http://digilib.unila.ac.id/id/eprint/57004> <http://purl.org/dc/terms/title> "RANCANG BANGUN SENSOR KELENGASAN DAN SUHU TANAH \r\nBERBASIS JARINGAN SYARAF TIRUAN"^^<http://www.w3.org/2001/XMLSchema#string> .
<http://digilib.unila.ac.id/id/eprint/57004> <http://purl.org/ontology/bibo/abstract> "Kelengasan tanah memegang peranan penting dalam pertumbuhan maupun \r\nperkembangan tanaman. Peran kelengasan tanah yang sangat penting inilah \r\nmenjadikan ketersediaan air menjadi salah satu faktor yang mempengaruhi hasil \r\nproduksi tanaman. Akan tetapi, untuk mengukur kelengasan tanah ini dibutuhkan \r\nwaktu yang relatif lama dan biaya yang relatif mahal. Diperlukannya terobosan\r\nteknologi untuk mengatasinya. Teknologi yang dapat digunakan ialah dengan \r\nmenggunakan sensor lengas tanah yang dirancang dengan menggunakan prinsip\r\nJaringan Syaraf Tiruan (JST) untuk mendapatkan model matematika yang nantinya \r\nakan diintegrasikan ke dalam mikrokontroler. Dengan demikian, pengukuran di lapang \r\n(in situ) dengan segera dapat diketahui. \r\nTujuan umum dari penelitian ini ialah merancang alat pengukuran kelengasan tanah \r\nberdasarkan Jaringan Syaraf Tiruan (JST) dengan tiga parameter yaitu suhu tanah, \r\nresistensi, dan kedalaman probe (dua elektroda). Tujuan khusus dari penelitian ini \r\nuntuk mendapatkan model matematika untuk sensor kelengasan tanah berdasarkan \r\nJaringan Syaraf Tiruan (JST). Penelitian in dilakukan pada bulan Maret hingga Juli \r\n2019 di Laboratorium Rekayasa Sumber Daya Air dan Lahan, Jurusan Teknik \r\nPertanian, Universitas Lampung\r\nBerdasarkan penelitian yang dilakukan telah telah dihasilkan model matematika yang \r\nmendapatkan nilai RMSE dan koefesien determinasi (R2\r\n) sebesar 1,0366 dan 0,9923 \r\ndengan fungsi aktifasi yang memiliki hasil terbaik ialah logsig-logsig-logsig. Alat \r\nyang telah di uji coba menghasilkan error yang sangat kecil yaitu dengan RRMSE \r\nsebesar 9,55 % (0,0955) dan RMSE sebesar 3,99605434. \r\nKata kunci: Jaringan Syaraf Tiruan, Lengas Tanah, Rancangan Alat, Suhu Tanah.\r\nSoil moisture plays an important role in plant growth and development. The role of soil \r\nmoisture is very important, making the availability of water one of the factors that \r\ninfluence crop production. However, to measure this soil moisture requires a relatively \r\nlong time and relatively expensive cost. The need for technological breakthroughs to \r\novercome them. The technology that can be used is to use a soil moisture sensor that is \r\ndesigned using the principle of Artificial Neural Networks (ANN) to get a \r\nmathematical model that will later be integrated into the microcontroller. Thus, \r\nmeasurements in the field (in situ) can immediately be known.\r\nThe general objective of this research is to design a soil moisture measurement tool \r\nbased on Artificial Neural Networks (ANN) with three parameters namely soil \r\ntemperature, resistance, and probe depth (two electrodes). The specific purpose of this \r\nstudy is to obtain a mathematical model for soil moisture sensor based on Artificial \r\nNeural Networks (ANN). This research was conducted from March to July 2019 at the \r\nWater and Soil Engineering Laboratory, Department of Agricultural Engineering, \r\nUniversity of Lampung. \r\nBased on the research conducted, a mathematical model has been obtained that gets the \r\nRMSE value and the coefficient of determination (R2) of 1.0366 and 0.9923 with the \r\nactivation function that has the best results is logsig-logsig-logsig. The tools that have \r\nbeen tested produce a very small error, namely with RRMSE of 9.55% (0.0955) and \r\nRMSE of 3.99605434.\r\nKeywords: Artificial Neural Networks, Soil Moisture, Tool Design, Soil Temperature"^^<http://www.w3.org/2001/XMLSchema#string> .
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