Judul: Pemodelan Sistem Pakar Berbasis Komputasi Lunak untuk Evaluasi Kesesuaian Lahan Komoditas Serealia: Studi Kasus Kabupaten Bogor
Abstrak: Nowadays, the threat of food shortages are happen in Indonesia. Most of crops are cereals commodities. Cereals cultivation often experience some problems in defining if the land is good or not for the plant. Expert system can help researcher and practitioners to choose the suitable kind of cereals for land. In this research, a model of fuzzy rule within fuzzy inference system using artificial neural network and genetic algorithm was built. The model was used to develop an expert system of land suitability for cereals commodity. This model implement soft computing which combine fuzzy system, artificial neural network and genetic algorithm. In this research, an expert system model of land suitability for cereals plant were built. The model implement soft computing methods for inference engine which combine fuzzy system and genetic algorithm. There are 16 parameters to define the land suitability which consists of 12 numeric parameters and 4 categorical parameters. The kind of cereals that will be used are wetland paddy and corn. Trapezoid membership functions was used here. Genetic algorithm was used for tuning the membership function of fuzzy for land suitability which is consist of very suitable (S1), quite suitable (S2), marginal suitable (S3) and not suitable (N). This research has produced a model of soft-computing-based expert system. The experimental result by entering some of test cases in the system and compared with the results of the expert show that the system was built in accordance with the results of the expert with accuracy 85% for rice and 90% for corn. Errors of land suitability class grouping occurs because the input value was on the edge of the membership function. We suggest the usage of actual data for future research, so that the output of the model appropriate to real condition. Each parameter should be weighted based on its importance.
Keyword: cereals, expert system, fuzzy, genetic algorithm, land suitability evaluation, soft computing

Judul: Modul evaluasi kesesuaian lahan budidaya tanaman dengan menggunakan logika Fuzzy
Abstrak: Land suitability evaluation is the process of predicting land suitability class and land utilization potential for agriculture. Land suitability is evaluated by comparing the plant requirements with the available landscape characteristics related to climate, topography, texture, drainage, soil physics, soil fertility, salinity and alkalinity, as well as land preparation. In this research, we develop a system based on fuzzy inference to determine the rating, threshold levels and land suitability class from land characteristics data obtained. The data given as input are a crisp value or a linguistic value. Land suitability is evaluated using a boundary method. The fuzzy inference method used is the max – min method and the defuzzification method used is the center average defuzzifier method
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Judul: Infeksi Virus Parainfluenza Pada Anjing
Abstrak: Virus parainfluenza anjing termasuk famili Paramyxoviridae, berbentuk pleomorf dengan ukuran bervariasi (bergaris tengah antara 100-500 nm), berpembungkus peka ether, berisi genom RNA dan secara serologis mempunyai kesamaan dengan virus SV-5 kera; dikenak sebagai salah satu kausa penting dari sindrom "kennel cough". Infeksinya dapat mengenai anjing semua umur yang belum pernah terinfeksi atau mendapatkan vaksinasi mengakibatkan gejala klinis ringan yang terbatas pada traktus respirasi atu infeksi yang secara klinis tidak memperlihatkan gejala nyata. Gejala klinis yang nampak setelah masa inkubasi (1-5 hari) terlewati berupa batuk yang tidak berat selama beberapa hari, berbagai tingkat tonsilitis dan pharyngitis dan kadang-kadang ditemukan kenaikan temperatur rektal antara 1-2 derajat C dari temperatur normal rat-rata. Anjing terinfeksi mengandung virus pada traktus respirasi bagian atas dan bawah serta limfonoduli sampai hari ke 9 setelah infeksi. Penyebaran virus antar anjing terjadi secara aerogen.
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