Passport Data Based On Time Series Neural Network Prediction

Khoiriya Latifah, Ika Ayu Amelia Putri

Abstract


Globalization has encouraged changes in people's lifestyles. The rapid flow of globalization between countries increasingly opens opportunities for each country to develop its economy. Level needs begin to shift, from secondary or tertiary needs into primary needs, such as a vacation or a trip, including travel abroad. The mobility of the population abroad for a holiday or business trip is also increasing, this will affect the busyness in the immigration office that has a very important role in terms of public services in the field of immigration. The number of immigration visitors is fluctuating and unpredictable, when will there be spikes that cause problems and high risks. To maintain the credibility and quality of service, the immigration office needs calculations in forecasting the number of passport makers when there is a surge of visitors in order to remain able to provide optimal service to visitors. This study uses the technique of forecasting Backpropagation Neural Network forecasting The superiority of Neural Network as a system is capable human thinking by computational intelligencebased computing in pattern recognition that is useful for modeling, predicting, detecting faults and controlling systems that require a design approach with computational artificial intelligence.

Keyword : Passport, Neural Network Algorithm


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