Judul: Beberapa faktor yang mempengaruhi produksi dan penawaran daging, susu, dan telur di Jawa Barat dan Lampung
Abstrak: This study was prepared due to the essential role of meat, milk, and egg as nutritions food to increase the standard of living. for these commodities. There was an increasing demand However there is a slow rate of increase, if not decrease, of the livestock population as the source of these commodities. The purpose of this study was to identify variables at the farmers level affecting the production and supply of meat, fresh milk, and fresh egg, in the light of the possibility of developing livestock production. The survey was conducted at the Province of West Java and Lampung, for the two regions reveal some differences with respect to the prospect of livestock development. By comparing these two regions, it is expected that the result will give some ideas in formulating live- stock development policy not only for the two regions, but also for other regions in Indonesia. Regression analysis of production and supply of meat does not tell us much, for the independent variables could a not explain the production and supply (R2 less than 0.20). Nevertheless, data indicated that on the average a Farmer owns only 2.7 buffaloes in west Java and 4.6 buffaloes and 2.7 cattle in Lampung. Only 17 percent of farmer In West Java sold any Of their cattle within the year proceding the data of enumeration and only 23 percent in Lampung (Table 4.14). Most of the sales are consumptive , (95 percent) such as for housing, education expenses, ritual ceremonies. From the supply point Of view, the amount and frequency OF sales were relatively smal1. Supply elasticity meat to price was 1.14566 for buffalo and 1.05049 for cattle. There was on indication that time variable has some influence On supply of meat. For instance, more cows and buffaloes are slaughtered in the month of lebaran and new year. Elasticity of milk supply to the amount of dairy cow was 0.645 to productivity 0.93892, and to ratio of milk price to dedak price 0.13874. Elasticity of ego Supply to the amount of layers was 1.06881 and to productivity of layers is 0.9643. was Judging from the results explained above, evident that the farmers have little variables selling their livestock. On the other hand due to the high elasticities at slaughtering agent, (pejagal), it could be concluded that butchers have a strong bargaining position in livestock marketing. dst. ...
Keyword: Produksi daging, Hasil-hasil peternakan, Penawaran susu, Penawaran daging, Permintaan hasil peternakan

Judul: Production efficiency analysis of dairy farm in pondok ranggon cipayung sub-district east jakarta
Abstrak: Permintaan susu sapi perah di Indonesia meningkat setiap tahunnya, namun produksinya belum memenuhi kebutuhan nasional. Peternakan sapi perah Pondok Ranggon merupakan tempat penyedia susu sapi untuk warga DKI Jakarta. Peternakan sapi perah Pondok Ranggon memiliki peranan penting dalam peningkatan produksi susu di Indonesia. Tujuan penelitian ini adalah untuk: (1) menganalisis faktor-faktor yang mempengaruhi produksi susu sapi perah, (2) menganalisis efisiensi produksi susu sapi perah, (3) menganalisis pendapatan usaha peternakan sapi perah di Pondok Ranggon. Faktor produksi susu sapi perah dianalisis menggunakan fungsi produksi Cobb-Douglas dan parameter diestimasi dengan metode Ordinary Least Squares (OLS), analisis efisiensi produksi dilakukan dengan menggunakan Nilai Produk Marginal (NPM) sama dengan harga faktor produksi, dan pendapatan usaha peternakan dilakukan dengan analisis pendapatan. Faktor-faktor yang mempengaruhi produksi susu sapi perah adalah pakan hijauan, ampas tahu, dan tenaga kerja. Nilai efisiensi masing-masing faktor produksi tidak sama dengan satu, berarti bahwa penggunanaan faktor produksi belum efisien. Nilai R/C ratio yang lebih besar dari satu, sehingga analisis pendapatan menunjukkan bahwa usaha peternakan sapi perah menguntungkan., The demand for milk of dairy cattle in Indonesia increasing every year, but the production has not fulfill the national needs. Pondok Ranggon dairy farm is a supplier milk to DKI Jakarta people. Pondok Ranggon dairy farm has an important role in improvement milk production in Indonesia. The purposes of the study were to: (1) analyze the affecting factors for the production milk of dairy cattle, (2) analyze the production efficiency of milk of dairy cattle, (3) analyze the income of Pondok Ranggon dairy farm. The production factor of milk of dairy cattle was using the production function of Cobb-Douglas analysis and estimated parameter was using Ordinary Least Squares (OLS) method, analysis production efficiency was using Value of Marginal Product (VMP) equal to production factor prices, and income of dairy farm analyze using income analysis. The affecting factors of production milk of dairy cattle is grass, tofu waste, and labors. The value of efficiency of each production factor is not equal to one, means that the use of production function have not been efficient. The value of R/C ratio is greater than one, so that the income analysis shows for dairy farm is profitable.
Keyword: analisis pendapatan, efisiensi produksi, Pondok Ranggon, susu sapi, usaha peternakan

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