Judul: Design of Averrhoa carambola L. Fruit Maturity Detection using Convolutional Neural Network and Integrated with Raspberry Pi
Abstrak: Belimbing merupakan hasil pertanian yang memiliki tingkat produksi yang tinggi, budidaya yang mudah, dan waktu kematangan yang relatif singkat. Petani umumnya mengklasifikasi tingkat kematangan buah biasanya masih dilakukan secara manual. Penelitian ini telah dibuat alat yang dapat menentukan tingkat kematangan buah belimbing secara presisi dan realtime. Convolutional Neural Network (CNN) digunakan untuk metode penentuan tingkat kematangan buah berdasarkan citra yang didapatkan. Tiap citra dilatih menggunakan tensorflow dengan model CNN yang berbeda, yaitu mobilenetV1, mobilenetV2, dan inceptionV3 dan diimplementasikan pada Raspberry Pi. Hasil pengujian alat menunjukkan model CNN mobilenetV1 memiliki akurasi sebesar 73.07% dengan kecepatan inferensi objek dalam waktu ±1150 milisekon. inceptionV3 sebesar 76.92% dengan kecepatan ±7000 milisekon, dan mobilenetV2 sebesar 61.54% dengan kecepatan ±900 milisekon., Starfruit is an agricultural product that has a high production rate, easy cultivation, and a relatively short maturity time. Farmers generally classify the level of fruit maturity manually. This research were produced a device that can determine the level of star fruit ripeness with precision and realtime. Convolutional Neural Network (CNN) is method that were used of determining the level of fruit maturity based on the image obtained. Each image was trained using tensorflow with a different CNN model, that is mobilenetV1, mobilenetV2, and inceptionV3 and implemented on the Raspberry Pi. The test results show that the CNN mobilenetV1 model has accuracy at 73.07% with the object inference velocity in ± 1150 milliseconds. InceptionV3 at 76.92% with inference in ±900 milliseconds , and mobilenetV2 at 61.54% with inference in ±7000 milliseconds.
Keyword: Raspberry Pi, Convolutional Neural Network, Belimbing

Judul: Pengembangan Model Probabilistic Neural Networks untuk Sortasi Belimbing Manis Berdasarkan Citra RGB
Abstrak: Starfruits (Averrhoa Carambola L.) is one of agroproducts which is liked by most society. Typically it is seen like a star when sliced athwartly. The characteristics of starfruits type which pre-eminent are size big, colour draw, smooth fibre, water containment, and fresh sweet. One of the vital process in post-harvest treatment is sortation. Fruits are grouped according to size measure and ripe phase. Starfruits which marketed have to fulfill the standard which accepted by consumer widely, either in domestic market and also global market. This matter in order to give best quality and also improve product competitiveness by farmer. Determination of starftruits sweetness is generally based on fruit colour visually. But, change of colour gradually complicated determination the taste of fruit. This needs more intelligent sortation methods and tools that overcome the sortcomings of manual process. Probabilistic Neural Network (PNN) is one of Artificial Neural Network (ANN) variants that can be used to develop a computer-based sortation engine for starfruits. This research aim is to develop PNN model for starfruits sortation based on RGB image value. Conclusion at this research indicates that PNN can be used to classify starfruits with high accuration reach 92%.
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Judul: Hamiltonian formulation for linear waves motion in two layers fluid
Abstrak: The surface wave could be considered as a wave that separates two fluids, namely water and air. Based on this assumption, it is introduced the interfacial wave, a wave between two layers of fluid with different density. The formulation of interfacial waves motion begins with deriving the base equation of irrotational ideal fluid. Furthermore, according to irrotational fluid assumption, the base equation can be stated in velocity potential. In this derivation, the fluids domain is assumed to be restricted by rigid lid boundary conditions, both at the upper and lower limit. Therefore, the interfacial waves motion can be explained in a hamiltonian formulation. In the hamiltonian formulation, total energy is defined as the sum of kinetic and potential energy. The hamiltonian system is obtained from reduction of kinetic energy by using the Dirichlet Neumann Operator. The resulted kinetic energy equation is nonlinear. Therefore, this form is linearized by first part of the Taylor expansion. This linearization gives a dispersion relation of linear wave. Based on this dispersion relation, the phase speed of the linear wave depends on the density ratio of the two layers fluid.
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