Outlier Identification Techniques in Daily Rainfall Data - Sudirman Sudirman; Muhammad Irfan; Supari Supari; Baba Musta; Nurul Dzakiya (AMPLITUDO : Journal of Science and Technology Innovation, 2026)
A quality test was conducted on daily rainfall data in the Sumatra region to select good data. The data used came from 19 observation stations belonging to the Meteorology, Climatology, and Geophysics Agency (BMKG) spread across the Aceh-Lampung provinces from early 1985 to late 2023. The quality test aims to ensure data reliability, consistency, and validity. Daily rainfall data often face issues such as missing data, unrealistic extreme values, and recording discrepancies, which can reduce the accuracy of climate analysis. The quality test examined data completeness and outliers using the interquartile range. The quality test results showed a data completeness level of 93%, thus declaring the data valid. Outliers were identified in small amounts (<1%) for very high rainfall intensity at the Minangkabau meteorological station in West Sumatra (470 mm/day), the Bengkulu climatological station (400 mm/day), the FL Tobing meteorological station in North Sumatra (430 mm/day), the Fatmawati Soekarno meteorological station in Bengkulu (390 mm/day), the West Sumatra climatological station (320 mm/day), the South Sumatra climatological station (230 mm/day), and the Radin Intan II meteorological station in Lampung (265 mm/day). These values ​​were not removed from the analysis because they passed the data quality test and represented meteorologically realistic extreme rainfall events. The results of the evaluation of daily rainfall data in Sumatra during the study were representative and reliable enough to be used in further climatological analysis.