ANALISIS CLUSTERING DAERAH PRODUKTIVITAS PADI DI KABUPATEN DELI SERDANG MENGGUNAKAN ALGORITMA ISOLATION FOREST - Ardi Wirya Indarto; Asrianda; Sujacka Retno (Prodi Teknologi Informasi UIN Ar-Raniry Bekerjasama dengan Pusat Penelitian dan Penerbitan LP2M Universitas Islam Negeri Ar-Raniry Banda Aceh, 2026)
Rice is a major food commodity that plays a vital role in national food security. However, differences in rice productivity levels between regions pose a challenge in formulating targeted agricultural policies. This study aims to analyze and cluster rice productivity areas in Deli Serdang Regency using the Isolation Forest algorithm. The data used are rice productivity data from all sub-districts in Deli Serdang Regency for the period 2020–2024, with variables of planted area, harvested area, production volume, and rice productivity. The analysis process is carried out through a web-based system using the Python programming language with the Streamlit framework. The Isolation Forest algorithm is used for clustering and anomaly detection, while cluster quality is evaluated using the Silhouette Score. The results of the 2024 data analysis show that 22 sub-districts in Deli Serdang Regency are divided into four clusters: a high-productivity cluster of 7 sub-districts (31.82%) with an average productivity above 6.2 tons/ha, a medium-productivity cluster of 4 sub-districts (18.18%) with a productivity of 6.0–6.1 tons/ha, a low-productivity cluster of 7 sub-districts (31.82%) with a productivity of around 5.9–6.0 tons/ha, and an anomalous cluster of 4 sub-districts (18.18%). The results of this clustering are expected to assist local governments in determining policies to increase rice productivity more effectively and based on data.