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All Journal (JELIKU) Jurnal Elektronik Ilmu Komputer Udayana
Panji Palguna, I Gusti Agung Ngurah
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Computer Science & IT

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Design and Development of Poultry Disease Classification with Certainty Factor Method Panji Palguna, I Gusti Agung Ngurah; Astuti, Luh Gede
JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 8 No 3 (2020): JELIKU Volume 8 No 3, February 2020
Publisher : Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JLK.2020.v08.i03.p13

Abstract

Expert systems in organizations aimed at adding value, increasing productivity and managerial areas that can draw conclusions quickly. Like with organizations that conduct livestock business that are very promising but necessary high vigilance against disease as well as highly poultry susceptible to various types of diseases caused by viruses or bacteria. To know the disease quickly made a system that is useful for detecting, so breeders can check their poultry without seeing a veterinarian for early detection. Permanent Veterinarian required for further treatment.
Prediction Of The Number Of Tourists To Visit Bali Province Using Backpropagation Artificial Neural Network (Case Study: Data 1990-2016) Panji Palguna, I Gusti Agung Ngurah; Widiartha, I Made
JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 8 No 3 (2020): JELIKU Volume 8 No 3, February 2020
Publisher : Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JLK.2020.v08.i03.p05

Abstract

Bali Island is the most popular tourist destination in Indonesia. The total number of foreign tourists visiting Indonesia through the entrance of Ngurah Rai Airport reached 40% as of October 2016, with the value of Bali's foreign exchange receipts for Indonesia from the tourism sector amounting to 70 Trillion Rupiah. Minister of Tourism (Menpar) Arief Yahya always uses the password "Bali" in promoting destinations throughout the world. Because in tourism, Bali is a gate that is passed by 40 percent of foreign tourists (tourists) to Indonesia. In support of more accurate decision making, the author makes a system of forecasting numbers of foreign tourists visiting Bali Province by taking a sample of Japan. Factors that are used as input to make predictions include the number of tourists visiting before, the population of the country of origin of foreign tourists, Gross Domestic Product, and the Relative Consumer Price Index of the countries of origin of foreign tourists. In this research, optimization of the activation function, hidden neuron, and learning rate parameters is performed. Forecasting results using the backpropagation method produce a pretty good accuracy with an accuracy of Mean Square Error = 0.0050558, and test data accuracy of MSE = 0.031695. ANN architecture in the training process is then used to calculate predictions of visits by foreign tourists in the testing process
Co-Authors I Made Widiartha Luh Gede Astuti