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.
Keyword: 

Judul: Dampak Perubahan Harga Beras Dunia terhadap Kesejahteraan Masyarakat Indonesia pada Berbagai Kondisi Transmisi Harga dan Kebijakan Domestik
Abstrak: Rice is the main staple food in Indonesia. Rice self-sufficiency policy has become a government priority to ensure the availability of food at favorable prices for farmers. It has caused a distortion in Indonesian rice market. World rice prices fluctuate from year to year and increased sharply, especially in 2007 and early 2008. The high world price becomes an important issue in Indonesia due to the inelastic nature of rice commodity. The objectives of this study are (1) to analyze price transmission and rice market integration of world markets to domestic market, (2) to analyze the impact of changes in world rice price on producer and consumer welfare with different scenarios of price transmission, and (3) to analyze changes in world price and domestic policy (government purchases price policy, import tariffs and import quotas of rice) impact on producers and consumers welfare. Market integration and rice price transmission is analyzed by estimating the Ravallion model and calculate the Market Integration Index (MII). Effect of change in world rice prices on the community welfare in various price transmission and domestic policy conditions are analyzed with simulation of Indonesian rice market integration model. The results showed that Indonesia's rice market is integrated with the world rice market with very weak degree. Changes in world market prices are transmitted to the Indonesian rice market, but not perfect. Increase in world rice prices could lead to the increase of farmers’ welfare, while consumers’ welfare decreases. World prices change will give a higher impact on public welfare when the domestic rice market conditions increasingly integrated with world markets. HPP policy is effective in stabilizing domestic rice prices and protecting farmers. But the increase in import tariffs by 10 per cent has not been able to protect farmers from world prices decline. However, the policy of 1.57 million tons annual import quotas can reduce farmers welfare and improve consumers welfare and able to protect consumers from the increase in world prices. Therefore, the strategic role of rice commodity has lead to the importance of government intervention to maintain domestic rice prices.
Keyword: 

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