Judul: Permintaan energi rumah tangga di pulau Jawa
Abstrak: Reducing of subsidies would increase energy prices that affect the level of energy consumption and consumer welfare. Analyze the behavior of households in Java in consuming energy was the aim of this study, this include their price elasticity, income elasticity, and cross elasticity of energy commodities. The methode of this study is the linear approximate version of the almost ideal demand system (LA-AIDS) model using data from the National Socio-Economic Survey (SUSENAS) covering the period from 2007 to 2010 for household in Java along with the kerosene’s conversion to gas program undertaken by the government. The own price elasticities of energy (except for the electricity) showed that they are elastic so the increase of their price will effectively reducing its consumption. While the cross elasticities showed that the energy comodities are substitute each other, but in very low level. The kerosene’s conversion to gas has been shifting household kerosene consumption in Java into commodities LPG, city gas, and coal.
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Judul: The impact of oil fuel price subsidy policy on economic performance and poverty in Indonesia
Abstrak: The objectives of this study were to analyze the factors that influence the supply and demand of oil fuel and to analyze the impact of oil fuel price subsidy policy on economic performance, poverty, and welfare in Indonesia. A simultaneous econometric model of Indonesia oil fuel price subsidy was estimated using a two stage least squares (2SLS) method and SYSLIN procedure for the data set period of 1986-2006. The forecast simulation was set for the period 2010- 2014 with NEWTON method and SIMNLIN procedure. The supply of oil fuel, which was represented by the amount imported, was influenced negatively by its world price and positively by its consumption, consumen price index, and its lag endogenous. The demand for oil fuel was influenced negatively by its retail price and positively by its consumption, its substitutes price, and its lag endogenous. The price subsidy of oil fuel was influenced positively by its world price, domestic exchange rate, government domestic revenue, and its lag endogenous. The price subsidy of oil fuel, except LPG, was elastic against world price of crude oil and domestic exchange rate in the short and long run. The forecast simulation of increases of world crude oil price was resulted in the increase of retail oil fuel price, decreasing economic growth, and increasing the inflation and poverty rate. The government policy to decrease oil fuel subsidy will result in deteriorating the economic performance, poverty alleviation program, and also welfare will be in large deficit. The less severe result happen when government applied kerosene conversion program to LPG. The deteriorating impact of the last two simulation were likely caused by the drop of government expenditure and the negative economic growth altogether. In such developing country like Indonesia, the role of government expenditure was central and important in boosting the economic. Such hypothesis was proven when oil fuel subsidy decreases and the level of government expenditure was kept constant, the result was surprisingly positive to economic performance and poverty alleviation program, even though the sustainable fiscal policy will be rather violated. To overcome the negative impact of the decreasing of oil fuel price subsidy and kerosene conversion program to LPG, government should kept the fiscal budget constant through budget reallocation strategy. By doing this, there were budget available for establishing fiscal space or putting more fund to strategic and most important development program including compensation program for the poor as well as poverty alleviation programs.
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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