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Anifudin Azis
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Computer Science & IT Control & Systems Engineering

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Journal : IJCCS (Indonesian Journal of Computing and Cybernetics Systems)

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An Evaluation of Suitable Landscape to Crop Food Cultivation By Using Neural Networks Anifudin Azis; Bambang Hendro Sunarminto; Medhanita Dewi Renanti
IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 1, No 1 (2006): January
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijccs.17

Abstract

Penentuan jenis tanaman pangan yang sesuai ditanam pada lahan tertentu berdasarkan nilai-nilai karakteristik lahan sangat diperlukan sebagai pendukung pengambilan keputusan, koordinasi, dan pengendalian bagi para peneliti, praktisi, dan perencana penggunaan lahan, sehingga kerugian (finansial) yang cukup besar tidak terjadi nantinya. Program komputer dengan menggunakan Jaringan Syaraf Tiruan (JST) metode Learning Vector Quantization (LVQ) dapat digunakan sebagai alat yang tepat dalam memberikan informasi tanaman yang cocok ditanam dengan mudah, cepat, dan akurat. Data pelatihan didapat dari kombinasi nilai karakteristik lahan yang termasuk dalam kelas kesesuaian S1 dan S2. Hasil pengujian menunjukkan bahwa nilai Eps (error minimum yang diharapkan) = 0.005, nilai ?? ?? = 0.05, nilai maksimum epoh = 10, dan nilai pengurangan learning rate sebesar 0.1*?? ?? merupakan nilai-nilai yang cukup efektif dan efisien dalam melakukan prediksi jenis tanaman pangan yang sesuai ditanam pada lahan tertentu karena tingkat ketepatan prediksinya adalah 100%.
The Prediction of Medical Decision Post Operative of the Major Operation using Neural Networks Anifudin Azis; Nur Rokhman; Praretno Wibowo
IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 1, No 1 (2006): January
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijccs.20

Abstract

The exact handling to the postoperative inpatient of the major operation in the restoration period, became one of the factors that very important for the success of the process of medical treatment on the whole. By paying attention to the development of signs and vital signs from the patient, could be made medical by one decision took the form of the further action for the handling of the patient. Using backpropagation neural networks, could be made by a system that could carry out the prediction (forecast) the medical decision that will be taken to the postoperative patient the major's operation. After trining, by accepting sign input and the vital sign of the patient, the system could determine the action that will be carried out against the patient. From results of the test of the application program showed that the backpropagation neural networks could do the prediction of the medical decision with the success to 80%. Therefore, output from the system could be used as consideration of the doctor to decide the further action for the patient.
Co-Authors Bambang Hendro sunarminto Nur Rokhman Praretno Wibowo