<![CDATA[Text preprocessing in Indonesian applications commonly relied on external libraries such as Sastrawi. However, performing this task outside the database layer often introduced significant latency due to data communication overhead between the application and the server. This study proposed and evaluated a native stemming mechanism utilizing the Nazief and Adriani algorithm implemented directly within an Oracle PL/SQL environment. The primary objective was to determine whether in-database processing could offer better performance than the standard application-layer approach. The assessment compared the PL/SQL implementation against the Python-based Sastrawi library using a comprehensive dataset of 54,715 words sourced from the Kamus Besar Bahasa Indonesia (KBBI). Performance metrics focused on stemming accuracy and total execution time. The empirical results revealed that the proposed PL/SQL method achieved an accuracy of 96.82%, which proved slightly superior to the 96.58% accuracy obtained by Sastrawi. Furthermore, the stored procedure implementation demonstrated significant efficiency, completing the process in 602.22 seconds, whereas the baseline method required 1,259.28 seconds. It was concluded that migrating the stemming logic into the database layer effectively reduced execution time by approximately 52.18% while maintaining high precision. These findings suggested that native database implementation provided a more robust solution for systems requiring high-performance text processing.]]>
