Judul: Identifikasi Daun Tanaman Jati Menggunakan Jaringan Saraf Tiruan Backpropagation dengan Ekstraksi Fitur Ciri Morfologi Daun
Abstrak: Teak identification is very useful in life. Knowledge about kind of teak is very important for teak farmers to understand the characteristics, benefits, as well as the buying and selling price of teak. This research built an automatic teak identification system using backpropagation Neural Network with leaf morphology feature extraction. The five basic leaf characteristics that were used in this research are area, perimeter, diameter, length, and width of the leaf. The five basic characteristics were then derived into 12 derivative characteristics. The data were the images of teak leaves of Biotrop, Emas, Jobika, Muna, Prima, and Super. Each data consists of 20 images with the size of 1200 x 2300 pixel. In order to obtain the best accuracy, k-fold cross validation with k=5 was used. The result shows that the best accuracy was 84.17% with 17 hidden neuron of neural network
Keyword: Artificial Neural Network (ANN), Backpropagation, Feature Extraction, Leaf, Teak

Judul: Identifikasi tanaman jati menggunakan Probabilistic Neural Network dengan ekstraksi fitur ciri morfologi daun
Abstrak: Teak plant (Tectona grandis Linn. F) is one type of forest products that has considerable potential to be developed in Indonesia. The large number of teak plant species causes difficulties in identifying teak plant species identity. It takes knowledge of an expert in the field of teak plants to be able to identify the species of teak. The leaves are a source of easy observation and is available as a source of observations over time. This research proposed a new system to identify the teak plant leaves using Probabilistic Neural Network (PNN) classification and the extraction of characteristic features using Morphology. The system identifies 6 species of teak plant. The data are divided into four subsets and used as training data and test data. The PNN is trained using 90 leaves of the 6 species of teak plant. The identification using PNN produced 77.5% average accuracy.
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Judul: Impact Of water policy on poverty reduction and women roles in water management In Zimbabwe
Abstrak: Water management is a key factor in the battle to remove the scourge of extreme poverty and to build secure and prosperous lives for people in the developing world. The water sector in Zimbabwe is complicated by the large number of actors; it is interwoven within various ministries. The research used secondary data and review of literature to evaluate how the current water policy has contributed towards marginalising women and the poor. It looked at how actors can also marginalise or put other actors at risk thereby undermining their role through prioritisation of certain projects, stakeholder participation and usage policy. From a descriptive analysis it is found that women are further relegated and marginalised. The poor are further impoverished through marginalisation and vulnerability. The policy environment favours business and state interests against those of grassroots actors and women. It recommends the establishment of home grown pro- poor water management strategies.
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