Judul: Faktor-faktor yang mempengaruhi produksi produk turunan minyak sawit di Indonesia
Abstrak: Production of palm oil downstream products in Indonesia is still low compared to primary products, namely palm oil. demand for palm oil, margarine and soap increased every year. therefore, Indonesia needs to increase the production of palm oil derivative products, not only to meet consumer demand but also related to value-added. Relevant government policies in order to encourage the development of downstream palm oil industry, through the instrument of monetary policy interest rates can affect the production of palm oil derivative products are cooking oil, margarine and soap. The research objectives are (1) Analyzing the factors that influence the production of palm oil derivative products in Indonesia, cooking oil, margarine and soap. (2) Analyzing the impact of policy rate cuts on the production of cooking oil, margarine and soap in Indonesia. In order to address these objectives, a simultaneous equations model of derived from the production of palm oil in Indonesia is estimated by Two Stage Least Squares (2SLS) method. Domestic palm oil production is influenced significantly by the domestic price of cooking oil palm, palm oil price growth rate domestk, interest rate, and cooking oil production t-1. Domestic production of margarine significantly influenced by the production of margarine t-1. Production of domestic soap significantly influenced by the level of interest rates, the growth rate of industrial labor, and the production of soap domestuk t-1. in order to develop the production of palm oil derivatives suggested that the government should export oriented derivative products (cooking oil, margarine and soap) to increase foreign exchange and provision of low interest rates in order to increase investment in downstream industries.
Keyword: 

Judul: Analisis faktor-faktor yang mempengaruhi ekspor minyak sawit dan minyak inti sawit Indonesia
Abstrak: Indonesia as the biggest crude palm oil and palm kernel oil exporter in the world, can not continuosly keep on exporting the crude palm oil and palm kernel oil. Indonesia needs to develop the downstream production of crude palm oil and palm kernel oil industry to give the added value, to employ many labors and also as the environmental recovery function. Therefore, it’s needed a right policy from the government to support the downstream production of crude palm oil and palm kernel oil industry. The purposes of this research are: (1) to analyze the development of Indonesia’s palm oil export; (2) to analyze the development of Indonesia’s palm kernel oil export; (3) to analyze the affecting factors of Indonesia’s palm oil export; (4) to analyze the affecting factors of Indonesia’s palm kernel oil export. This research is using time series data from 1990-2011. The Indonesia’s crude palm oil and palm kernel oil export model was estimated by the doubled linear regresion with Ordinary Least Square (OLS) estimation method. Export models were divided into 6 single formulations, which are Indonesia’s palm oil export with destination country to India, Netherlands, and Singapore, also another single formulations of Indonesia’s palm kernel oil export with destination country to Malaysia, Netherlands and China. The result of this research indicates in a short period the tax rate would be an important instrument in order to limit the Indonesia’s palm and palm kernel oil export on the Indonesia’s downstream production of palm and palm kernel industry development. The facilities which must be built by the government in order to support the development of the downstream industry of crude palm oil and palm kernel oil are infrastructure development, application of tax holiday, and also by deleting the local regulation which blocks the development of the downstream industry of crude palm oil and palm kernel oil.
Keyword: Ordinary Least Square (OLS) Method, Bogor Agricultural University (IPB), palm kernel oil, export tariff, export, crude palm oil

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