Judul: Penggabungan Fitur Morfologi, Local Binary Pattern Variance, dan Color Moments untuk Aplikasi Mobile Identifikasi Citra Tumbuhan Obat
Abstrak: This research proposed a new Android mobile application for medicinal plants identification using some features of leaf, i.e. texture, shape, and color. This research used 51 species of medicinal plants and each species consists of 48 images, so the total images used in this research are 2448 images. Local Binary Pattern Variance (LBPV) is used to extract the texture, morphological feature is used to extract the shape, and color moments is used to extract color feature based on color distribution. Further research was conducted on the combination of features to get a better result in medicinal plants identification. The combination technique used is the Product Decision Rule (PDR). This research uses the Probabilistic Neural Network (PNN) technique to classify the morphological, LBPV, and color moments features vector. The experimental results show that the combination of the morphological, LBPV, and color moments features can improve the accuracy of medicinal plants identification. The accuracy of the combination of the morphological, LBPV, and color moments features is 72.16%.
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Judul: Penggabungan Fitur Fuzzy Local Binary Pattern dan Fuzzy Color Histogram untuk Aplikasi Mobile Identifikasi Citra Tumbuhan Obat.
Abstrak: This research develops a mobile application based on Android operating system for identifying medicinal plant images. The identification is conducted based on texture and color feature. This research uses medicinal plants leaf images. The total medicinal plants used in this research is 51 species taken from Biofarmaka IPB, Cikabayan Farm, Green house Center Ex-Situ Conservation of Medicinal Plant Indonesia Tropical Forest and Kebun Raya Bogor. Each species consist of 48 images, thus the total image used in this research is 2448. This research investigates effectiveness of the fusion between the Fuzzy Local Binary Pattern (FLBP) and the Fuzzy Color Histogram (FCH) in order to identify medicinal plants. The FLBP method is used for extracting medicinal plants texture. This method extends the Local Binary Pattern (LBP) approach by employing fuzzy logic for representing the local patterns of texture images. Fuzzification allows the distribution of the LBP values is used as a feature vector. Moreover, the FCH method is used for extracting medicinal plants color. This method considers the color similarity of each color pixel associated with all the histogram bins through fuzzy-set membership function. Next, Fuzzy C-Means (FCM) algorithm is used to compute the membership values. The fusion of FLBP and FCH is done by using Product Decision Rules (PDR) method. This research uses Probabilistic Neural Network (PNN) method to classify the FLBP and FCH feature vector. The experimental results show that the fusion between FLBP and FCH can improve the accuracy of medicinal plants identification (FLBP: 59.61%, FCH: 50.78%, fusion of FLBP and FCH: 74.51%).
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Judul: Dynamic New Keynesian Model for Unemployment and Inflation Rate.
Abstrak: This paper deals with a scientific analysis of the equilibrium level of hiring, employment and unemployment. The basic model being used is a standard new Keynesian model, which states that utility function depends on consumptions and working hours. Utility maximization refers to a standard labour supply equation, with the marginal cost’s dynamics on new Keynesian model simply reflects movements in real wages and productivity. Furthermore, trade-off between output and inflation stabilization can be considered using the new Keynesian Phillips curve. Dynamic general equilibrium model is a model that can be used to study interactions between market imperfections and nominal rigidities, which is capable of overcoming the main shortcoming of the standard new Keynesian model. In the general equilibrium model there are three groups of the economy agents, namely households, firms and monetary authority. The results of this research science that bargaining processes between firms and workers will yield optimal wage. Increase in labour will cause wages to fall, but the unemployment rate can be reduced. An increase in the firm’s monopoly power will shift the labour demand curve downward, which will reduce the number of workers that firm is willing to hire for any given bargained wage.
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