Typological Analysis of Sultanate Tombs in Sumatra Using K-Means and Random Forest Clustering Methods
Keywords:
Islamic Tombs, K-Means Clustering, Morphometric Analysis, Random Forest, Typology of TombsAbstract
The diversity of the morphological characteristics of Islamic tombs from the Sultanates in Sumatra reflects variations in cultural traditions, construction techniques, and architectural forms. However, the identification of tomb typologies is still dominated by manual observation; therefore, the classification process is relatively subjective. This study aimed to identify the typology of tombs from the Sultanates in Sumatra using the K-Means Clustering algorithm and to determine the most influential classification variables using the Random Forest algorithm. This study analyzed 85 tomb records consisting of four morphometric variables (tombstone height, length, width, and height) and several archaeological attributes. The Elbow method was used to determine the optimal number of clusters, resulting in three clusters with distinct morphometric characteristics. The evaluation of the clustering quality resulted in an average silhouette coefficient of 0.267, indicating a fairly good clustering structure. Furthermore, the Random Forest model achieved an accuracy of 68.75% with a kappa value of 0.521, indicating moderate classification performance. Variable importance analysis revealed that grave material, footstone shape, and tombstone shape were the most influential variables for distinguishing tomb typologies. These findings indicate that the combination of K-Means Clustering and Random Forest provides an effective and objective approach to identifying archaeological tomb typologies based on morphometric and physical attributes.
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Copyright (c) 2026 Titin Agustin Nengsih, Sastia Nabila, Amir Husni, Wahyu Rizki Andhifani, Imam Arifa'illah Syaiful Huda, Benny Agusti Putra
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