Clustering Analysis of Kutai Sultanate Tombs: Exploring Design Preference, Symbolism, and Social Hierarchy in East Kalimantan, Indonesia
Abstract
Sultanate tombs are cultural artifacts that record various social, political, and symbolic information about past societies. In the context of the Kutai Kartanegara Sultanate, variations in tomb design and decoration are believed to reflect the hierarchical social structure and cultural values passed down across generations. However, previous studies have tended to be descriptive and visual, and have not developed an objective and systematic classification model. This study addresses this gap by applying an exploratory quantitative approach using a mixed-type clustering algorithm to identify patterns of design preference, symbolism, and social structure in the tomb complexes of the Kutai Kartanegara Sultanate in East Kalimantan, Indonesia. A total of 74 tombs were selected through purposive sampling based on the completeness of the inscriptions and the feasibility of visual data. Each tomb was analyzed based on the physical dimensions of the jirat and headstone, decoration, form, material, and the language of the inscription. The clustering results revealed three main groups: clusters with simple dimensions and ornaments (distant families), clusters with moderate proportions (close families), and clusters with monumental designs and complex ornaments (nuclear families and heads of the sultans). The findings suggest that cemetery architecture functions as an expression of social status and a means of preserving collective memories in Islamic royal societies. This study also offers a data-driven classification model that can be replicated in other digital archaeological research, as well as expanding methodological approaches in the study of death, identity, and power in Southeast Asia.
Fields of Study & Subjects
Architecture and Cultural Influences
Data Mining and Machine Learning Applications
3D Surveying and Cultural Heritage
Publication details
- Journal / source
- Asian Journal of Interdisciplinary Research
- Pages
- 47–63
- Publication date
- 2 March 2026
- Language
- EN