Judul: Optimization Of Fuzzy Local Binary Pattern In Threshold And Operator Selection Using Multi Objective Genetic Algorithm
Abstrak: This research proposes multi-objective genetic algorithm non-dominatedsorting (MOGA NSGA-II) of fuzzy local binary pattern to optimize LBP operator and fuzzy threshold for identification of Indonesia medicinal plant. Multiobjective genetic algorithm (MOGA) is genetic algorithm (GA) which developed specifically for problems with multiple objectives. We evaluated 1,440 medicinal plant leaf images which are belonging to 30 species. The images was taken from Biofarmaka IPB, Cikabayan Farm, Green house Center Ex-Situ Conservation of Medicinal Plant Indonesia Tropical Forest and Gunung Leutik. FLBP is used to handle uncertainty on images with various patterns. FLBP approach is based on the assumption that a local image neighbourhood may be characterized by more than a single binary pattern. The experimental results show that the correct selection of FLBP operator and threshold can improve the identification from 66.44% to 85%. It can be concluded that this propose method is capable to improve medicinal plants identification species efficiently and accurately.
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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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