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Artificial neural networks (ANN) was used to predict the quality parameters of tomato, i.e. Brix, citric acid, total carotene, and vitamin C. ANN was developed from Red Green Blue (RGB) image data of tomatoes measured using a developed computer vision system (CVS). Qualitative analysis of tomato compositions were obtained from laboratory experiments. ANN model was based on a feedforward backpropagation network with different training functions, namely gradient descent (traingd), gradient descent with the resilient backpropagation (trainrp), Broyden, Fletcher, Goldfrab and Shanno (BFGS) quasi-Newton (trainbfg), as well as Levenberg Marquardt (trainlm). The network structure using logsig and linear (purelin) activation function at the hidden and output layer, respectively, and using the trainlm as a training function resulted in the best performance. Correlation coefficient (r) of training and validation process were 0.97 - 0.99 and 0.92 - 0.99, whereas the MAE values ranged from 0.01 to 0.23 and 0.03 to 0.59, respectively.ABSTRAKJaringan syaraf tiruan (JST) digunakan untuk memprediksi parameter kualitas tomat, yaitu Brix, asam sitrat, karoten total, dan vitamin C. JST dikembangkan dari data Red Green Blue (RGB) citra tomat yang diukur menggunakan computer vision system. Data kualitas tomat diperoleh dari analisis di laboratorium. Struktur model JST didasarkan pada jaringan feedforward backpropagation dengan berbagai fungsi pelatihan, yaitu gradient descent (traingd), gradient descent dengan resilient backpropagation (trainrp), Broyden, Fletcher, Goldfrab dan Shanno (BFGS) quasi-Newton (trainbfg), serta Levenberg Marquardt (trainlm). Fungsi pelatihan yang terbaik adalah menggunakan trainlm, serta pada struktur jaringan digunakan fungsi aktivasi logsig pada lapisan tersembunyi dan linier (purelin) pada lapisan keluaran. dengan 1000 epoch. Nilai koefisien korelasi (r) pada tahap pelatihan dan validasi secara berturut-turut adalah 0.97 - 0.99 dan 0.92 - 0.99; sedangkan nilai MAE berkisar antara 0.01-0.23 dan 0.03-0.59.

There are three approaches in the current social network analysis study: Graph Representation, Content Mining, and Semantic Analysis. Graph Representation has been used for analyzing social network topology, structural modeling, tie-strength, community detection, group cohesion visualization, and metrics computations. This paper provides a taxonomy of social network analysis based on its graph representation., Comment: 11 pages, 2 tables, 2 figures

Knowledge of moisture diffusivity was important for water loss modelling during deep fat vacuum frying. The appropri- ateness of model depended on the accuracy of moisture diffusivity value. The objective of this research was to calculate carrot moisture diffusivity during deep fat vacuum frying. Moisture diffusivity was obtained from rate of water loss multiplied by L2/π2. The rate of water loss was determined from unsteady-state diffusion equation. The slope of the time vs. dimensionless concentration ratio plot was the rate of water loss. Carrot was used as a sample in this research. The rate of water loss was determined during deep fat vacuum frying with variation of absolute pressure, temperature and initial moisture content. The result showed that moisture diffusivity depended on absolute pressure, temperature and initial moisture content. The result indicated that an increase in the temperature of frying and initial moisture content caused an increase in moisture diffusivity. While an increase in the absolute pressure induced decreasing of moisture diffusivity. The moisture diffusivities were accurately predicted at absolute pressure range from 20 – 40 kPa, initial moisture content range from 198 % (db) to 940 % (db) and temperature range from 80 to 110 oC.ABSTRAKPengetahuan mengenai difusivitas air sangat penting untuk pemodelan kehilangan air selama penggorengan hampa udara. Kesesuaian model tergantung atas akurasi nilai difusivitas air. Tujuan penelitian ini adalah untuk menghitung difusivitas air sebagai fungsi tekanan absolut, suhu dan kadar air awal bahan selama penggorengan hampa udara. Difusivitas air diperoleh dari laju kehilangan air dikalikan L2/π2. Laju kehilangan air ditentukan dari persamaan di- fusi tak mantap. Kemiringan dari kurva lama penggorengan terhadap rasio konsentrasi merupakan laju kehilangan air. Penilitian ini menggunakan wortel sebagai sampel. Laju kehilangan air ditentukan selama penggorengan hampa udara dengan variasi tekanan absolut, suhu dan kadar air awal bahan. Hasil penelitian menunjukkan bahwa difusivi- tas air tergantung atas tekanan absolut, suhu dan kadar air awal. Peningkatan suhu dan kadar air awal menyebabkan peningkatan difusivitas air. Sedangkan peningkatan tekanan absolut menyebabkan penurunan nilai difusivitas air. Difusivitas air diprediksikan secara tepat pada range tekanan absolut 20 - 40 kPa, suhu 80 - 110 oC dan kadar air awal 198 - 940 % (bk).

The purpose of this research was to develop a simple computer vision system (CVS) to non-destructively measure tomato quality based on its Red Gren Blue (RGB) color parameter. Tomato quality parameters measured were Brix, citric acid, vitamin C, and total sugar. This system consisted of a box to place object, a webcam to capture images, a computer to process images, illumination system, and an image analysis software which was equipped with artificial neural networks technique for determining tomato quality. Network architecture was formed with 3 layers consisting of1 input layer with 3 input neurons, 1 hidden layer with 14 neurons using logsig activation function, and 5 output layers using purelin activation function by using backpropagation training algorithm. CVS developed was able to predict the quality parameters of a Brix value, vitamin C, citric acid, and total sugar. To obtain the predicted values which were equal or close to the actual values, a calibration model was required. For Brix value, the actual value obtained from the equation y = 12,16x – 26,46, with x was Brix predicted. The actual values of vitamin C, citric acid, and total sugar were obtained from y = 1,09x - 3.13, y = 7,35x – 19,44, and y = 1.58x – 0,18,, with x was the value of vitamin C, citric acid, and total sugar, respectively.ABSTRAKTujuan penelitian adalah mengembangkan computer vision system (CVS) sederhana untuk menentukan kualitas tomat secara non­destruktif berdasarkan parameter warna Red Green Blue (RGB). Parameter kualitas tomat yang diukur ada­ lah Brix, asam sitrat, vitamin C, dan gula total. Sistem ini terdiri peralatan utama yaitu kotak untuk meletakkan obyek, webcam untuk menangkap citra, komputer untuk mengolah data, sistem penerangan, dan perangkat lunak analisis citra yang dilengkapi dengan jaringan syaraf tiruan untuk menentukan kualitas tomat. Arsitektur jaringan dibentuk dengan3 lapisan yang terdiri dari 1 lapisan masukan dengan 3 sel syaraf masukan, 1 lapisan tersembunyi dengan 14 sel syaraf berfungsi aktivasi logsig dan 5 lapisan keluaran dengan fungsi aktivasi purelin menggunakan algoritma pelatihan back­ propagation. CVS yang dikembangkan dapat digunakan untuk memprediksi nilai parameter kualitas tomat yaitu Brix, vitamin C, asam sitrat, dan gula total, meskipun dibutuhkan persamaan kalibrasi. Persamaan kalibrasi untuk Brix, nilai aktualnya diperoleh dari persamaan y = 12,16x – 26,46 dengan x adalah nilai Brix prediksi. Sedangkan kadar vitamin C, asam sitrat, dan gula total aktual secara berturut-turut diperoleh dari y = 1,09x - 3.13, y = 7,35x – 19,44, dan y =1.58x – 0,18, dengan x adalah nilai vitamin C prediksi, asam sitrat prediksi, dan gula total prediksi.

Pada penelitian ini dilakukan pengeringan bahan herbal dan obat-obatan tradisional yang peka terhadap panas yaitu daun sambiloto menggunakan pengering bertekanan rendah. Tekanan yang rendah akan membuat titik uap air akan turun sehingga air akan menguap pada suhu di bawah 100°C. Suhu rendah ini juga bertujuan untuk mengurangi tingkat kerusakan kandungan kimia bahan peka panas. Sedangkan tujuan penelitian adalah menganalisis konstanta laju pengeringan daun sambiloto selama proses pengeringan menggunakan pengering tekanan rendah. Pengeringan daun sambiloto dilakukan pada suhu dan tekanan yang bervariasi yaitu variasi suhu 30°C, 40°C, 50°C dan variasi tekanan 61 kPa, 48 kPa dan 35 kPa. Pengeringan daun sambiloto dilakukan dari kadar air ± 70% hingga ± 10%. Selama proses pengeringan perubahan kadar air diukur dengan interval waktu 10, 20, 30, 60, 90, 120, 150 dan 210 menit. Pengukuran kadar air dilakukan dengan cara termogravimetri. Analisis konstanta laju pengeringan menggunakan persamaan lapis tipis. Hasil penelitian menunjukkan nilai konstanta laju pengeringan pada tekanan rendah berkisar 0,01-0,0175 men1. Pengeringan menggunakan tekanan rendah dapat meningkatkan laju pengeringan. Persamaan empiris konstanta laju pengeringan sebagai fungsi suhu dan tekanan yang dinyatakan sebagai kprediksi = 0,00075T0,823P-0,021 dapat diaplikasikan untuk memprediksi perubahan kadar air daun sambiloto selama pengeringan pada tekanan rendah. Kata kunci: konstanta laju pengeringan, pengeringan bertekanan rendah, daun Sambiloto Herbs (traditional medicine) such as sambiloto leaves are senisitive to heat, therefore the drying process of herbs were performed at low-pressure. At low pressure, evaporation of water in the herbs can be carried out at a temperature below 100°C. The low temperature of drying may reduce the destruction of heat-sensitive chemicals inside the herbs. The present study aimed at analyzing the drying-rate constant of sambiloto leaves during low-pressure drying. Sambiloto leaves were dried at varied temperature of 30°C, 40°C, and 50°C, and varied pressure of 61 kPa, 48 kPa, and 35 kPa. The water content of sambiloto leaves was reduced from ± 70% to ± 10%. The change in water content was measured after 10, 20, 30, 60, 90, 120, 150 and 210 minutes, by using thermogravimetry technique. The drying-rate constant was calculated using the equation of thin films. The drying-rate constant was 0.01 – 0.0175 min-1. It was observed that the drying-rate increases as the pressure decreases. To predict the change of water content in sambiloto leaves during low-pressure drying process, an empirical equation for the drying-rate constant as a function of temperature and pressure was derived from the experimental data, kprediction= 0,00075T0,823P-0,021. Key words: drying-rate constant, low-pressure drying, sambiloto leaves

The natural colour of fruit flaky product is one of specific property prefered by consumer. To maintain the natural colourof the fruit flaky during frying, it is necessary to pay attention the characteristic changes of raw material and control the process in order not to have much changes to get the intended colour. The objective of this research is to develop empirically mathematical model of fruit flaky colour changes during vacuum frying process by considering the change of water and sucrose contents in the product. Sample of the research were jack fruits fried in the temperature of 70–100OC, frying duration of 15–60 minutes, and vacuum pressure of 13-23 kPa. The observed parameters are colour (L), colour (a), colour (b), water and sukrose contents before and after frying. The result showed that colour changes (L, a and b) were influenced by free water vaporization and sukrose decreasing in product, so empirically, the developed mathematical model of colour changes (L, a and b) can be used to predict fruit flaky colour changes during vacuum frying. ABSTRAK Warna alami pada produk keripik buah adalah merupakan salah satu sifat khas yang disukai oleh konsumen, untukmempertahankan warna alami keripik buah agar tidak banyak mengalami perubahan selama dalam penggorengan, perlu diperhatikan perubahan karakteristik bahan baku dan pengendalian proses, agar warna keripik buah yang dihasilkan sesuai dengan yang diinginkan. Penelitian ini bertujuan untuk mengembangkan secara empirik model matematik perubahan warna keripik buah selama dalam proses penggorengan vakum dengan mempertimbangkan ke dalam model perubahan kadar air dan kadar sukrosa di dalam padatan. Sampel penelitian adalah buah nangka digoreng pada suhu70-100 OC, lama penggorengan 15-60 menit dan tekanan vakum 13-23 kPa. Parameter yang diamati adalah warna (L), warna (a), warna (b), kadar air dan kadar sukrosa sebelum dan setelah sampel digoreng. Hasil penelitian menunjukkan perubahan warna L, a dan b dipengaruhi oleh penguapan air bebas dan penurunan kadar sukrosa di dalam padatan, sehingga secara empirik model matematik perubahan warna L, a dan b yang dikembangkan dapat digunakan dengan baik untuk memprediksi perubahan warna keripik buah selama dalam proses penggorengan secara vakum.

Kebutuhan akan keamanan sistem informasi merupakan hal yang sangat penting bagi suatu perusahaandalam menjamin kesuksesan proses bisnisnya. Hal ini mempunyai hubungan yang signifikan apabila dikaitkandengan meningkatkannya jumlah insiden keamanan komputer serta kerugian yang ditimbulkannya. Dewasa ini,konsep keamanan yang merupakan sebuah proses manajemen yang berkelanjutan dan melibatkan seluruhkomponen dari suatu perusahaan, telah meninggalkan cara konvensional yang hanya mengandalkan keamananpada kemampuan perangkat lunak atau perangkat keras. Salah satu alternatif solusi manajemen keamanantersebut adalah dengan membentuk CSIRTs (Computer Security Incident Response Teams) pada organisasi atauperusahaan. Penelitian tentang Model Organisasi CSIRTs telah dirintis oleh CMU/SEI (Carnegie MellonUniversity/Software Engineering Institute) sejak tahun 1998. Pada tesis ini, akan dilakukan suatu studikelayakan salah satu model organisasi CSIRTs tersebut, yang disegmentasikan pada perusahaan berskala besar.Studi ini, akan menggunakan metoda CBA (Cost Benefit Analysis) untuk pengujian dari sisi ekonomi, dan CMMI(Capability Maturity Model Integration) dari sisi manajemen.Kata kunci: keamanan sistem informasi, CSIRTs, Model Organisasi CSIRTs, perusahaan berskala besar, CBA,CMMI.

Polyphenols play important roles in taste and flavour development as well as antioxidative property of cocoa products. Chemical changes of the polyphenols occurring during conventional roasting was due to exposure to the oxygen of surrounding air at high temperature(110-200oC) for 20 up to 60 min, depend on the degree of roasting. Shorter time was needed to roast the cocoa nib by using microwave energy. The objective of this research was to investigate changes of polyphenol compounds during microwave roasting of ground cocoa nibs. Deshelled and ground cocoa nib passing through 20 mesh screen was roasted using microwave oven at 20% power for 5 min. Conventional roasting conditions were also adopted for treating the sample using an electric oven at 140 oC for 40 min as comparison. The polyphenols was extracted with acetone 80% and then freez dried. The crude extract was characterized for total polyphenols. Polarity of the polyphenolic fractions was analyzed from the crude extract as well as the ethyl acetate soluble extract by HPLC. Chemical bond of the compounds were detected by Fourier Transform Infrared Spektrophotometer (FTIR). Results indicated that the conventional roasting tend to decrease the polyphenols content while microwave roasting was increase, though the data showed significantly no difference (p≤0,05) . HPLC separation suggested that the roasting of the sample increased in polarity, though FTIR spectra showed similarity in quantity of O-H, C-H, and C=C bonds respectively The microwave oven roasting gave one small additional fraction compared to both sample extracts from the conventional roasted and the unroasted samples which gave two fractions. Further, the ethyl acetate soluble extract from the microwave sample gave eight chromatographic fractions while from those conventional roasted and the unroasted gave two fractions and one fraction, respectively.