Implementation of Autoregressive Integrated Moving Average for Tourism Recommendation in Pamijahan Area Based on Internet of Things

Abstract

Pamijahan is one of the sub-districts located in Bogor regency, West Java. Pamijahan has a variety of tourist destinations, one of which is the Cigamea waterfall, Cikuluwung waterfall, and the Seribu watering problem when visiting tourists, one of them is the weather factor such as rainy weather where Bogor has a highland area so very big influence on the variation of rain there and visitors have difficulty in choosing tourist sites with sunny conditions, the solution to the problem above is to predict the weather during rainy weather in the tourist areas of Cigamea waterfall, Cikuluwung waterfall, and Seribu waterfall using the Autoreggressive Integrated Moving Average method as weather prediction process uses Time Series data with the help of the Internet of Things tool in data retrieval, the weather prediction testing process uses the Autoreggressive Integrated Moving Average method by calculating the value of MSE (Mean Square Error) and MAPE (Mean Absolute Presentage Error) as minimum as possible to see the level of accuracy of the weather prediction process at each designated tourist site. The results of this study indicate that weather forecasting in Cigamea, Cikuluwung and Seribu waterfalls shows the smallest MSE (Mean Square Error) value, the waterfall that has the smallest MSE value, the Seribu waterfall with the Mean Square Error value of the temperature sensor 0.06, Air Humidity 0.59, and Light Intensity 13.30, so that tourist attractions that can be used as tourist attractions for visitors are the Seribu Waterfall.