Abstract: The accuracy of indoor positioning based on wireless local area network (WLAN) fingerprints depends on the algorithms used. Choice of which algorithm to use in positioning is a challenge. This study aims to compare the Euclidian distance (deterministic algorithm) and probability density function (probabilistic algorithm) in their accuracy. The signal samples were collected from the modelled study area using android mobile phone. Then, the samples were analyzed to compare their performance in a specific environment. Comparisons were made with respect to the number of access points, number of reference points and number of samples. The experimental results show that, the probabilistic method has higher accuracy when adopting the signal relation than deterministic algorithm.