Missing data refers to a condition where part of the dataset is unavailable due to unrecorded information during the data collection process. Missing data problems must be addressed because they can affect the accuracy of the analysis. This study aims to evaluate the performance of univariate imputation methods, namely Kalman Smoothing and STL Decomposition, on time series data obtained from a …