Judul: Sistem real time berbasis jaringan syaraf tiruan untuk prediksi masa kadaluarsa biskuit dengan sensor dielektrik
Abstrak: Biscuit is type of dried food which found frequently on expired condition in market, therefore prediction method should be implemented in avoidance of this condition. Recently, prediction of shelf-life of biscuit has been done by laboratory test, but this test has some disadvantages, i.e.: time-consuming, expensive, also required trained panelists, complex equipment and suitable ambience. One alternative method is the dielectric sensor integrated with Artificial Neural Networks (ANN) in an intelligent real-time system. The aim of this research is to select the measurement attribute dielectric (dielectric parameters, the condition of the circuit and frequency), to formulate design of sensors can measure the value of selected parameters, to design an ANN model, and to integrate sensor and ANN dielectric to predict the shelf-life of biscuits in real time. Selection dielectric parameters and conditions of the circuit (CC/Constant current or CV/Constant Voltage) performed with Linear Regression, Feature Selection (Relief) and Artificial Neural Networks. Dielectric parameters for determining the best shelf life of biscuits are parallel capacitance (Cp). Cp constantly in the top five at three selection method, especially in ANN. Whereas the best condition of the circuit's for determining the shelf life of biscuits are CC, because always at the first sequence of three methods of selection. Selection of the frequency range 42 Hz - 5 MHz done graphically. Frequency range is able to differentiate a good shelf-life is a biscuit with a low frequency range from 42 to 351.65 Hz and the high frequency of 4721.13 to 50054.56 Hz. Selection results of the previous stage for dielectric parameter, the condition of the circuit and frequency is used for sensor design formulation basic. Approach the design tools in accordance with the results of the selection is a RC circuit. Capacitance (C) be the parameters of the sensor dielectric designed. The frequency of this sensor set 5-6 kHz, because the results are more sensitive reading capacitance values of different shelf-life and type biscuits. Designing neural network model is the next stage. This model is designed by using a data input capacitance (C), frequency (f) and Dielectric Constanta (k) from the sensor readings. Moreover, the input data on ANN is a type of packaging, type of biscuit and actual shelf-life (in packaging). ANN learning algorithm is Back propagation. For training process, trial and error is processed in the activation function, learning function, amount of nodes per hidden layer variation, and number of hidden layer. The best training architecture (lowest MSE and highest R) is ANN with the 5 hidden layer, 10 nodes per hidden layer, the hidden layer activation function tansig, the output layer activation function purelin, learning function trainlm and 86 epoch. ANN combined with dielectric parameters has lowest MSE (9,8648 x 10-5) and R highest (99.80%) in the training performance. ANN models are integrated with dielectric sensor using microcontroller AVR ATMega 8535. This integration to measure in real time the dielectric value (variable input) of an unknown product shelf life and readable on computer. To facilitate interaction with the user, an interface is built with MATLAB GUI toolbox. So, integration of ANN and capacitance
Keyword: Artificial Neural Network, biscuit, dielectric sensor, intelligent real time system, shelf-life

Judul: Pendugaan Umur Simpan Tepung Cookies Menggunakan Metode Akselerasi Dengan Pendekatan Kadar Air Kritis
Abstrak: Label pangan adalah salah satu kewajiban yang harus dicantumkan oleh produsen pangan. Hal ini diatur dalam UU Pangan no 18 tahun 2012. Informasi umur simpan ditujukan agar konsumen mendapatkan jaminan mutu dan keamanan dari produk yang dikonsumsi. Tujuan penelitian ini adalah untuk menduga umur simpan tepung cookies yang diproduksi oleh salah satu industri tepung di Bogor. Tepung cookies yang diproduksi merupakan tepung komposit dengan kombinasi bahan utama tepung beras dan tepung sorgum. Metode yang digunakan pada penelitian adalah Accelerated Shelf-life Testing (ASLT) yaitu dengan mengkondisikan lingkungan produk yang dapat mempercepat reaksi penurunan mutu. Pendekatan kadar air kritis digunakan pada penelitian karena kadar air merupakan parameter penting dalam menentukan mutu tepung. Tahapan penelitian meliputi penentuan kadar air awal (Mo), kadar air kritis (Mc), penyimpanan sampel pada berbagai RH untuk mendapatkan kurva ISA, penentuan model sorpsi isotermis, uji ketepatan model, penentuan kemiringan kurva (b), pengukuran variabel umur simpan lainnya, serta pendugaan umur simpan dengan menggunakan persamaan Labuza. Model yang tepat untuk menggambarkan kurva isotermis sorpsi pada tepung cookies adalah model Oswin dengan nilai MRD 0,26. Hasil penelitian menunjukkan bahwa umur simpan tepung cookies dengan pendekatan air kritis berdasarkan Standar Nasional Indonesia (SNI) tepung beras pada RH 71% dengan menggunakan kemasan aluminium foil, LDPE (Low Density Polyethylene), dan plastik PP (Poly Propylene) berturut-turut adalah 324 hari, 30 hari, dan 144 hari dan pada RH 82% adalah 172 hari, 16 hari, dan 77 hari., Food labels are one of the obligations that must be included by food producers. This is regulated in Food Law No 18 of 2012. Shelf life information is intended so that consumers can guarantee the quality and safety of the products they consume. The purpose of this study was to estimate the shelf life of cookies flour produced by a flour industry in Bogor. Cookies flour produced is a composite flour with a combination of rice flour and sorghum flour. The method used in this research is Accelerated Shelf-life Testing (ASLT), namely by conditioning the product environment which can accelerate the reaction of quality degradation. The critical moisture content approach was used in this study because the water content is an important parameter in determining flour quality. The research stages include determining the initial moisture content (Mo), critical water content (Mc), storing samples at various RH to obtain the ISA curve, determining the isotherm sorption model, testing the accuracy of the model, determining the slope of the curve (b), measuring other shelf life variables, and estimation of shelf life which is calculated based on the Labuza equation. The best fit model in describing the moisture sorption isothermic curve in cookies flour was the Oswin model with MRD values 0,26. The results show that the shelf life of cookies flour with a critical water approach based on the Indonesian National Standard (SNI) for rice flour at 71% RH using aluminium foil, LDPE (Low-Density Polyethylene), and PP (Polypropylene) packaging, respectively was 324 days, 30 days, and 144 days and at 82% RH was 172 days, 16 days, and 77 days.
Keyword: cookies flour, critical moisture content, Labuza, shelf life

Judul: Trichomonas Gallinae Penyebab Trichomonosis Pada Unggas
Abstrak: Trichomonas gallinae adalah protozoa yang bergerak aktof dengan keempat flagella yang mempunyai layar dan pada salah satu sisinya terdapat membran seperti sirip ikan yang berombak. Spesies dari genus Trichomonas ini mempunyai arti penting pada unggas, karena dapat menyebabkan infeksi pada alat pencernaan bagian atas.
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