Judul: Faktor–faktor yang Memengaruhi Penyerapan Tenaga Kerja di Pulau Sumatera 2006-2010
Abstrak: Sumatera as the largest island in Indonesia, has an average of economic growth and investment is quite high. The purpose of this research is to analyze the factors which affect the sectoral labor demand in Sumatera island and to analyze the development of labor demand in Sumatera island. Method used in this study is analyzing data panel with 50 observation panel 2006-2010 at 10 province of Sumatera. The results of this research are factors wich affect labor demand in Sumatera island in 2006-2010 on agriculture, industry, and construction is GDP, PMA, and UMP. Factors wich affect labor demand in Sumatera island in 2006-2010 on mining is PDRB and on service is GDP, PMDN, UMP. Province that dominates of labor demand in agriculture, industry, construction, and service is North Sumatera. Province that dominates of labor demand in mining is Bangka Belitung. The province has the smallest amount of labor demand in agriculture and mining is Kepulauan Riau and Bengkulu. The province has the smallest amount of labor demand in industry, construction, and service sectoral is Bangka Belitung.
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Judul: Faktor-faktor yang Mempengaruhi Penyerapan Tenaga Kerja di Indonesia
Abstrak: The goal of economic development in individual countries, both developed and developing countries. Employment is one of the economic resources, the expansion of employment would create an economic development. This study aims to 1) analyze the conditions of employment in Indonesia, and 2) to analyze the factors affecting employment in Indonesia, using panel data on 33 provinces in Indonesia in 2008 and 2011. The independent variables used are the regional gross domestic product (GDP), real wages, and investment. While the dependent variable used is the number of people working. Results of this study indicate that the Gross Regional Domestic Product (GDP), Real Wage and Investment has a significant influence and positively related to employment
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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