<![CDATA[The ability to identify earthquake events that are consistent, efficient and accurate is increasingly needed along with the increase in the amount of data analyzed. In this paper a filter picker algorithm is implemented to identify aftershock events and determination of arrival time automatically, especially for the P wave phase. Here modifications are made in determining the uncertainty of arrival time and there are additional criteria in determining the time of arrival used. The additional criteria are that in a certain time span, there are at least 5 stations determined by the time the filter picker arrives. This is done to minimize identification errors due to local noise and other practical reasons, namely the minimum number of stations to determine the location and other seismological analysis. To test the filter picker algorithm, aftershock data from the Lombok earthquake occurred on July 29 (M 6.4), August 5 (M 7), and August 19 (M 6.3 and M 6.9) 2018. The aftershock data were used for 30 days, from August 4, 2018 to September 4, 2018 using local seismic station in Lombok Island. The results of the filter picker algorithm were evaluated by comparing the number of earthquake events detected and the accuracy of determining the P wave arrival time automatically to the results of manually arriving time. In addition, a comparison of the results obtained from a broadband type seismometer with a short period is used to find out how much influence the type of tool has on its performance results. The results of the comparison with the manual arrival time show that more than 85 percent of the results of the automatic arrival time have a difference below 0.2 seconds. Therefore, it can be said that the filter picker algorithm is quite effective for identifying events and determining the arrival time of P waves. In this paper it is also shown that this algorithm can be used for broad band and short period seismometer sensor, even without the prior correction of instruments.]]>
