Judul: Dampak Peningkatan Produksi Beras dan Harga Beras Terhadap Pengentasan Kemiskinan Pedesaan di Indonesia
Abstrak: Rural poverty is one major problem in Indonesia is still unresolved. Rice is the main food commodities that affect the welfare of tens of millions of villagers. This study examined the relationship between poverty in rural areas using secondary data is time series data and panel data with descriptive analysis and econometric analysis. Rice production showed a tendency to increase and consumption of rice decreased. However, domestic rice prices rose an average 12.6% per year. Meanwhile, international rice prices rose an average of 10%. In 2008, the price of rice in Indonesia is 80% more expensive than international rice prices. Conditions of rural poverty in Indonesia is very fluctuating. Increasing rice production and food security reduces the number of poor in rural areas. But its influence is relatively small or not too large. Real rice price increases every 1% will increase the number of poor in rural areas by 0.24%, but when using an interval of two years, the real price of rice actually reduce the rural poor population of 0.13%. However, these studies tend to show that the increased efficiency of production systems and post harvest, expected to help solve the problem of rice in Indonesia. For further study are advised to conduct a special study in Java by using primary data and conduct analysis of production efficiency and the efficiency of post-harvest rice.
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Judul: Dampak Kebijakan Harga Pembelian Pemerintah terhadap Kesejahteraan Produsen dan Consumen di Indonesia
Abstrak: Government Purchase Price Rice Policy is one of the important instruments in order to ensure national food security. The objectives of this research were to (1) analyze the factors that influence the supply and demand for rice in Indonesia, (2) to analyze the impact of the government purchase price rice policy on the producers’ and consumers’ welfare and, (3) to formulate alternative strategies that could ensure fair welfare distribution to both the producers and the consumers. Four policy alternatives set for the period 2002-2008 were simulated with econometric model of the Indonesian supply and demand of rice industry. Time Series secondary data 1980-2008, especially from BPS, Ministry of Agriculture and BULOG was rice quantitatively analyzed using a system of simultaneous equations econometric model. The econometric model is a simultaneous equations model consisting of eight behavioral equations and three identity equations. The Two Stages Least Squares (2SLS) method was used to estimate the parameters of the behavioral equations in the model. This study showed that the government price rice policy is good for increasing rice production but not the best policy for welfare and as a result the society as a whole is worse off. This study suggests that the government purchase price rice policy should be accompanied with other policies government programs like: (1) increased irrigated area and, (2) increased rice intensification through improved infrastructural development and, (3) high time food diversification is intensified to reduce overdependence on rice.
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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