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Journal : Jurnal Informatika

Expert System of Error Tracking Automated Weather Observing System Using Certainty Factor Method Based on Android Application M Djibran, Halis; Purba, Joshua; Saadia, Aprilia Ode; Restele, La Ode; Hasria, Hasria
Jurnal Informatika Vol 12, No 1 (2025): April
Publisher : Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/inf.v12i1.22536

Abstract

The limited number of technicians at several BMKG UPT (Task Implementation Units) in Indonesia is the main background of this research. Especially in the field of Aviation Meteorology, which has a significant safety risk for equipment data users. This can be made easier with an expert system. The fault tracking expert system aims to provide information about the symptoms of damage that occur in the Automated Weather Observing System (AWOS) so that it can make it easier for BMKG technicians to repair and handle the equipment. This research stage begins with collecting information data through experts and literature sources regarding AWOS equipment, then calculating the certainty value of the information using the certainty factor method, and produce information that will be displayed through the application. The system uses a Certainty Factor calculation method that presents the calculation of the certainty value of information based on the percentage of information delivery by the source, this method is used in accordance with the type of research that utilizes information from sources or experts in the AWOS field. The resulting system is an android application consisting of several knowledge bases stored in the MySQL database on the server. The results of the data analysis show that the resulting system can be used on the user's smartphone, and users can consult AWOS equipment damage properly. In addition, users can also view the consultation history and damage list. The application user satisfaction questionnaire shows the system has worked and fulfilled the function for users by showing a value of 33.3% Very Good and 66.7% Good.