Judul: Analisis Pola Konsumsi Mahasiswa Terhadap Pangan Asal Ternak (Studi Kasus: Mahasiswa Program Sarjana Fakultas Ekonomi dan Manajemen Institut Pertanian Bogor Tahun Masuk 2010)
Abstrak: FEM Students have a diverse characteristic, which rise to differences in consumption decisions, one of which is the consumption of the food from livestock. This study aims to analyze the consumption pattern of the food from livestock, identify the factors that influence the demand for the food from livestock, and analyze the level of price and income elasticity of the food from livestock with the application of the Almost Ideal Demand System (AIDS) model. The results of this studies showed that the higher the students income, the lower the total expenditure of FEM students allocated to consumption of food from livestock. The largest proportion of total expenditure of FEM students is used for the consumption of chicken meat, followed by cow’s milk, eggs of chicken, and beef. The own price variable, cross-price, total expenditure, gender, residence status tends to be dominant significantly affect the proportion of food from livestock expenditure on the real level (α) of 0,10. The own price elasticity of beef, chicken meat, and eggs is inelastic while the own price elasticity of cow’s milk is elastic. Most of cross-price elasticity have negative sign, its mean that the livestock has the complementary relationship with other food from livestock. The income elasticity for chicken meat, and eggs of chicken shown the value less than one, its mean that commodities are a staple goods. The income elasticity for beef and cow’s milk shown the value more than one, its mean that commodity is considered luxury good
Keyword: Bogor Agricultural University (IPB), food from livestock, elasticity, demand, consumption patterns, Almost Ideal Demand System (AIDS) Model

Judul: Analisis ppola konsumsi daging ayam olahan mahasiswa asrama putra dan putri TPB Institut Pertanian Bogor
Abstrak: The chicken flesh is one of foodstuff containing a high animal protein to fi~lfiltlh e requirement of animal protein for human being. The IPB's students in beginning level in the male & female dormitory are the consumer who consumes the chicken flesh by product. The consumption pattern is a habit of the students on buying and consumption the chicken flesh by product. The result of this study was obtained that the c~nsumption'~atterno f chicken flesh by product by dormitory students was different each other. Their reason consume the chicken flesh by product was its' delicious taste. The highest consume frequency done by the dormitory students was once per day. The students in male dormitory prefer roasted chicken while the females choose the fried chicken. They both prefer the chest slice. They both prefer to buy the chicken flesh by product in shop outside the dormitory than the cafeteria in the dormitory. The main consideration for choosing the place was cleaning. The multiple linier analyses getting the result (model 2) after the recovery model level that is R~ a number of 44.6%, showing.thG a number of 44.6% model could be explained by their stipend, the price of chicken flesh by product, gender and the kind of cuisine of chicken flesh by product are the forms of independent variable observed, remains is observed by the variable not used in the model. According to the F trial result is obtained that the forth independents variables observed are existent fluencies to the chicken flesh by product consumption expense and the t variable trial result of stipend, the price of chicken flesh by product, gender and the kind of cuisine of chicken flesh are existent influences jointly to the chicken flesh by. product consumption expense. Keywords: consumption pattern, chicken flesh by product, multiple linier analyses.
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Judul: Quantum Convolutional Neural Network (QCNN) for Classification Brain Tumor MRI Image
Abstrak: Penelitian ini bertujuan untuk mengembangkan model deteksi tumor otak menggunakan citra MRI dengan metode Quantum Convolutional Neural Network. Data yang digunakan adalah citra MRI otak yang terdiri dari citra tumor otak glioma, meningioma, hipofisis, dan negatif tumor yang dibagi kedalam data latih dan uji dengan rasio 80:20. Selanjutnya data latih dilakukan penyeimbangan dengan teknik oversampling. Dilakukan pengembangan model untuk mendeteksi tumor otak (biner), dan juga model untuk mengklasifikasikan jenis tumor otak (multiclass). Parameter yang digunakan dalam pengembangan model adalah jumlah ukuran filer = 2 dan kedalaman = 4, dengan qubit 4, dan dilatih dengan jumlah epoch sebanyak 10. Data akan diproses dengan metode Quantum Convolutional Neural Network yang terdiri dari lapisan quantum convolution, lapisan flatten, dan lapisan dense. Model multiclass mendapatkan akurasi 52%, setelah data latih diseimbangkan akurasi model meningkat menjadi 62%, sedangkan model biner mendapatkan akurasi 88%, setelah data latih diseimbangkan akurasi model meningkat menjadi 89%.
Keyword: Citra MRI, Klasifikasi Citra, QCNN, Tumor Otak