Mengisi Gap Informasi Persentase Penduduk Miskin di Jawa Timur dengan Google Trend Index - Ajiwasesa Harumeka; Tasmilah Tasmilah (Politeknik Statistika STIS, 2022)
The first goal of the Sustainable Development Goals (SDGs) is to end poverty in all its forms everywhere. One of the important aspects for alleviating poverty is the availability of good poverty data. Good poverty data can be used to evaluate government poverty alleviation programs, and can be compared over time. The Central Statistics Agency (BPS) calculates the poverty rate twice a year, in March and September. This creates an “information gap”, namely the unavailability of data between the times of the calculation. The Google Trend Index (GTI) as a type of big data can be utilized by the National Statistics Offices (NSO) to fill this “information gap”. This study used GTI to predict the monthly percentage of poor people in East Java. The method used was Feed Forward Neural Network (FFNN). The best FFNN model produced a Root Mean Square Error (RMSE) of 0.1279 with 1 hidden layer and 1 neuron in the hidden layer. The best model was used to predict the percentage of poor people from January to December 2021.