MANFAAT KAMPUNG KONSERVASI TUMBUHAN OBAT KELUARGA (TOGA) GUNUNG LEUTIK, DESA BENTENG CIAMPEA BOGOR

Conservation revitalization for health endurance can be achieved by establishing a conservation village such as Kampung Konservasi TOGA Gunung Leutik. The purposes of this research are to identify the benefit of Kampung Konservasi TOGA Gunung Leutik in the form medicinal plants utilization, and the impacts of its existence to local people’s health and economy. Methods used in this research was open-ended interview, and observation. The result shows that there are 152 medicinal plant species from 57 families that are utilized by the local people and most of them are from Zingiberaceae families. There are 40 recipe can be used for treat various desease. Benefits of these medicinal plants are for spices and daily disease treatment. The existence of Kampung Konservasi Gunung Leutik gives positive impacts for local people health and economy. Keyword: medicinal plant, TOGA conservation kampoong, utilizatio

Pemanfaatan Teknologi Tepat Guna Identifikasi Tumbuhan Obat Berbasis Citra

Indonesia is a mega biodiversity country including many kind medicinal plants. It is not easy to identify the various kinds of the medicinal plants especially for common people. Therefore, we need a computer-based automatic system as a tool to identify these various types of the medicinal plants. Developing of computer-based automatic system for medicinal plant identification has been done based on leaf image. There are 30 species of medicinal plants used in this study. There are 3 features for identification, i.e. morphology, texture, and shape. To improve the accuracy of identification we applied probabilistic neural network to classify the species of medicinal plant. The experiment results showed that the accuracy of identification increase to 74.67%. Developing of search engine has been done as well. We used 32 species of medicinal plant. The number of document was 132 documents. The document consists of name, family, description, diseases, and chemical substances. To improve the accuracy of searching, we applied KNN Fuzzy to classify document into 2 categories, i.e., family and diseases. The experiment results showed that the accuracy of average of precision is 96% for only word of length query and 89% for two words of length query. The system is very beneficial for people in society because it can be used to identify medicinal plants easily and the relevant communitis become independent in maintaining family health and giving opportunities as well as income of the people. Hence, the system is promising for leaf identification and supporting plant biodiversity in Indonesia

Pemanfaatan Teknologi Tepat Guna Identifikasi Tumbuhan Obat Berbasis Citra

Indonesia is a mega biodiversity country including many kind medicinal plants. It is not easy to identify the various kinds of the medicinal plants especially for common people. Therefore, we need a computer-based automatic system as a tool to identify these various types of the medicinal plants. Developing of computer-based automatic system for medicinal plant identification has been done based on leaf image. There are 30 species of medicinal plants used in this study. There are 3 features for identification, i.e. morphology, texture, and shape. To improve the accuracy of identification we applied probabilistic neural network to classify the species of medicinal plant. The experiment results showed that the accuracy of identification increase to 74.67%. Developing of search engine has been done as well. We used 32 species of medicinal plant. The number of document was 132 documents. The document consists of name, family, description, diseases, and chemical substances. To improve the accuracy of searching, we applied KNN Fuzzy to classify document into 2 categories, i.e., family and diseases. The experiment results showed that the accuracy of average of precision is 96% for only word of length query and 89% for two words of length query. The system is very beneficial for people in society because it can be used to identify medicinal plants easily and the relevant communitis become independent in maintaining family health and giving opportunities as well as income of the people. Hence, the system is promising for leaf identification and supporting plant biodiversity in Indonesia

Kamus penyakit dan tumbuhan obat Indonesia (etnofitomedika)

*Buku ini hanya bisa dibaca & fotocopy di dalam perpustakaan / tidak dipinjamkan.**Silahkan hubungi petugas untuk mengetahui informasi lebih lanjut.Buku ini tersusun dari data etnomedika yang berasal dari berbagai laporan perjalan/survai, makalah dalam simposium/seminar yang dikumpulkan dari dua perpustakaan di Bogor

Kamus penyakit dan tumbuhan obat Indonesia (etnomrdika I)

Jilid: 1xi, 209 p. : il.; 21 c

PEMANFAATAN TEKNOLOGI TEPAT GUNA IDENTIFIKASI TUMBUHAN OBAT BERBASIS CITRA

Indonesia is a mega biodiversity country including many kind medicinal plants. It is not easy to identify the various kinds of the medicinal plants especially for common people. Therefore, we need a computer-based automatic system as a tool to identify these various types of the medicinal plants. Developing of computer-based automatic system for medicinal plant identification has been done based on leaf image. There are 30 species of medicinal plants used in this study. There are 3 features for identification, i.e. morphology, texture, and shape. To improve the accuracy of identification we applied probabilistic neural network to classify the species of medicinal plant. The experiment results showed that the accuracy of identification increase to 74.67%. Developing of search engine has been done as well. We used 32 species of medicinal plant. The number of document was 132 documents. The document consists of name, family, description, diseases, and chemical substances. To improve the accuracy of searching, we applied KNN Fuzzy to classify document into 2 categories, i.e., family and diseases. The experiment results showed that the accuracy of average of precision is 96% for only word of length query and 89% for two words of length query. The system is very beneficial for people in society because it can be used to identify medicinal plants easily and the relevant communitis become independent in maintaining family health and giving opportunities as well as income of the people. Hence, the system is promising for leaf identification and supporting plant biodiversity in Indonesia