BPS-Statistics Indonesia has used mobile positioning data for official statistics since October 2016. Mobile positioning data from the largest mobile network operator measures cross-border tourism arrivals across over 3000 km of land border and a vast sea border.

Prior to mobile positioning data use, Indonesia used administrative data (immigration data) to measure visitor arrivals in the border areas. Immigration data has its coverage issues and where there is no immigration checkpoint, cross-border surveys aim to fill the gaps. However, surveys in remote cross-border areas are expensive, and the transportation costs to survey locations are high. The survey is only conducted over a month in selected locations, to estimate the numbers for the whole year for the entire border. So, there was a coverage problem in the tourism data in Indonesia, and mobile positioning data aimed to solve that.

The specific type of mobile positioning data used, signaling data, detects on average 3.47 times more roamers at the border areas than call detail records (CDRs). That ratio differs for each particular area. We found that signaling data overcomes some undercoverage issues of CDRs, while it is also adds noise - statistical and non-statistical - created by special types of roamers such as those flying over the country, crossing the country’s seas and accidentally roaming across the border.

This paper shows how in Indonesia the statistical office measured the error of signaling data and then reduced the error significantly through first creating an estimation formula and then applying appropriate algorithms to reduce the noise in signaling data.

The methods introduced in this paper are now part of regular tourism statistics production in Indonesia released every month. The authors believe the methods can be replicated and adjusted to other countries.