Judul: Fusion of Local Binary Patterns Features for Medicinal Plants Identification.
Abstrak: Identification plants automatically still be problem in obtaining a robust features. Local Binary Patterns (LBP) is an excellent descriptor for texture feature due to efficiency and robustness, but limited in the size of sampling point. In this research we propose fusion of LBP features, which incorporates additional information without sacrificing the robustnes of LBP features. Fusion of LBP features was done by two ways. In the first way, we perform a straightforward fusion by calculating histogram of multiple LBP features separately, then concatenating the multiple histograms together. In the first way we combine information provided by multiple operators by varying the size of sampling points and radius. In the second way, each histogram of LBP features are classified, and the feature fusion can be accomplished by classifier combination. Both ways, we employ probabilistic neural network (PNN) to classify LBP features. The experiment performed on medicinal plants and house plants. The fusion of LBP features are shown to be very powerful tools for improving accuracy.
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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: The Change of Family's Milk Consumption during Monetary Crisis
Abstrak: Krisis Moneter yang terjadi di negara kita sejak Juli 1997 lalu menyebabkan harga kebutuhan pokok yang melambung, salah satu diantaranya aclalah kenaikan harga susu. Dengan terjadiuya kenaikau harga susu ini maka terclapat keluarga-keluarga yaug melakukan perubahan kousumsi susu keluarganya. Merupakan ha! yang menarik untuk melihat perubahan pola konsumsi susu yang terjadi clan jenis susu yang seperti apa yang banyak mengalarni perubahan. Dengan melakukan smvei kepacla keluarga-keluarga yang banyak mengkonsumsi susu, yaitu keluarga yang mempunyai anak usia sekolah, clan keluarga yang berasal clari golongan penclapatan menengah, maka akan clapat memberikan gambaran perubahan konsumsi susu keluarga yang terjadi. Dalam masa krisis moneter, maka sebanyak 38.8 % clari 227 responden mengurangi konsumsi susunya dengan sebesar 8.4 % menghentikan konsumsi susunya. Terclapat sebanyak 6.6 % keluarga yang menukar jenis susu yang dikonsumsinya. Konsumsi susu lebih dipentingkan untuk golongan usia balita, dimaua pacla golongan usia ini persentase banyak balita yang tetap konsumsi susunya lebih bcsar dibaudingkan dengan golongan usia anak clan dewasa. Sebagian besar keluarga yang mengurangi konsumsi susunya merupakan keluarga yang mengalami penurunan penclapatan. Jenis susu yang paling peka terhaclap krisis moneter aclalah jenis susu cair dimana jenis susu ini paling banyak persentase keluarga yang mengurangi yaitu sebesar 45.8 %, dibandingkan dengan jenis susu bubuk, kental clan murni. Sedangkan jenis susu kental merupakan jenis susu yang tidak terlalu peka terhaclap krisis moneter dimana jenis susu ini persentase keluarga yang tetap clan naik konsumsi susu kentalnya paling besar, yaitu sebesar 67.1 %.
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