Implementation of Autoregressive Integrated Moving Average for Tourism Recommendation in Pamijahan Based on Internet of Things
Angga Eka Prasetya (a*), Yaddarabullah (a), Ade Syahputra (b)

a) Program Studi Teknik Informatika, Universitas Trilogi
Jl. TMP Kalibata No.1, Jakarta 12760, Indonesia
* Anggaprasetya[at]trilogi.ac.id

Abstract

Pamijahan is one of the sub-districts located in Bogor, West Java Pamijahan has a variety of tourist destinations, one of which is the Cigamea waterfall, Cikuluwung waterfall, and Seribu waterfall. Weather factors become an obstacle that is often experienced by tourists. Bogor Regency has a complex topography, this causes uneven variations in rainfall so that it is difficult for tourists to choose a sunny tourist location. This study predicts the weather during rainy weather in the tourist areas of Cigamea waterfall, Cikuluwung waterfall, and Seribu waterfall using the Autoregressive 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 Autoregressive Integrated Moving Average method by calculating the value of MSE (Mean Square Error) and MAPE (Mean Absolute Percentage 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 Mean Square Error value. The waterfall that has the smallest Mean Square Errorvalue, the Seribu waterfall with the Mean Square Error value of the temperature sensor 0.06, air humidity 0.59 and light intensity 13.30

Keywords: Autoregressive Integrated Moving Average, destinations, Internet of Things

Topic: Information Engineering