Indoor Positioning System (IPS) is a system that aims to track the coordinate positions of users or objects indoors. IPS is important to develop in order to complement the shortcomings of the Global Positioning System (GPS), which is based on satellite signals. Satellite signals are blocked by buildings so that the GPS position indoors cannot be relied on. The potential applications of IPS are very diverse, such as indoor navigation in large buildings such as shopping malls, offices, airports, etc. In addition, IPS can also be used to track the location of equipment, monitor employee movements, and support security monitoring. This system was developed to support various Location-Based Service (LBS) applications, which are very useful for tracking, monitoring, navigation, and targeted advertising in indoor environments. In general, the way IPS works is similar to GPS in predicting positions. However, the role of GPS satellites is replaced by the Bluetooth Low Energy (BLE) devices as radio signal transceivers. By using the Deep Learning algorithm, we predict the target positions based on the information of the received signal strength indication (RSSI) from the BLE devices.