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Unmanned Aerial Vehicle is a multirotor vehicle with more than one rotor to produce lift for the vehicle to fly in the air. Multirotor has become the object of research, one of which is in agriculture. Fertilization is more concerned about liquid fertilization, which is directly spraying on the leaves or foliar fertilizer. Foliar fertilizer sprayed with the hope that the stomata on the leaves can directly absorb the nutrients given. The UAV will fly carrying liquid (liquid) foliar fertilizer and spraying it on a predetermined land using a flight path that has been programming in the UAV. In previous research, we have used a multirotor type UAV combined with a foliar spraying system with a 1-liter liquid fertilizer, which can only spray land with a limited area. The limited liquid capacity will be a problem for the UAV because it is necessary to fill the liquid many times if used to spraying a wider area. Therefore, it is necessary to optimize the liquid load on the UAV so that its capacity will increase. If UAV’s liquid foliar fertilizer’s capacity increases, it will increase the area of foliar fertilizer spraying. This research focuses on increasing the UAV’s lift capacity and designing a UAV system equipped with a sprayer. The increase in lift is related to the payload to be carried by the UAV. This research targets to optimally increase the load of liquid foliar fertilizer. In this research, the UAV was designing using a multi-rotor type. The measurements taken are the success rate of the system in flying over the crop field, testing the measurement of power, current, battery capacity, and different loading 40, 45,50, 55 percent of the total weight from an unmanned aerial vehicle.

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Tingkat dehidrasi tidak hanya bisa dirasakan secara langsung akan tetapi dapat diamati dan dilihat secara fisik berbasis visual. Secara visual salah satu gejala dari dehidrasi dapat dilihat dari warna urine. Gejala ini biasanya tidak begitu diperhatikan dan dianggap biasa. Padahal gejala hipohidrasi atau dehidrasi merupakan dampak yang merugikan dari asupan air yang tidak memadai sehingga mempengaruhi warna urine yang dihasilkan. Kesulitan panca indra manusia membedakan gejala dehidrasi dan melihat perbedaan warna urine secara visual sering diterjemahkan berbeda-beda, dikarenakan tingkat kemiripan warna yang dihasilkan. Beberapa penelitian menunjukkan adanya pemanfaatan teknologi kamera dengan sistem cerdas dapat membantu kesulitan dan keterbatasan panca indra manusia. Penelitian ini menggunakan citra urine diambil dari sample orang dewasa yang dikelompokkan berdasarkan kategori warna urine hasil penelitian terdahulu. Pengambilan fitur dari setiap citra urine diambil nilai warna dari  YCbCr. Model warna yang dihasilkan dari setiap sampel akan diidentifikasi menggunakan algoritma Random Forest dengan cross-validation. Hasil dari percobaan yang dilakukan menunjukkan akurasi 90% dari 30 dataset yang diujikan dengan nilai precision 90.2%, recall 90%, Mean absolute error 0.2473, dan Root mean squared error sebesar 0.3208.