Analysis of Life Expectancy (LE) in Indonesia Using the K-Means Clustering Algorithm Method for 2020-2023

Deni Luvi Jayanto (Universitas Tadulako)
Prakasit Poonwong (Praboromrajchanok Institute Thailand)
Vicky Bin Djusmin (Universitas Cokroaminoto Palopo, Sulawesi Selatan)
Mohamed Fal Mohamed Fadel (Al Akhawayn University, Morocco)
Nimatu Zuliana (Institut Ilmu Kesehatan Bhakti Wiyata)
Ninda Mulya Ike Ardila (Institut Ilmu Kesehatan Bhakti Wiyata)
Mia Ashari Kurniasari (Institut Ilmu Kesehatan Bhakti Wiyata)

Journal Health Information Management Indonesian
Vol. 4 No. 3 (2025): Desember (Journal Health Information Management Indonesian)

Life Expectancy (LE) is one of the key indicators in assessing the quality of health in a region. This study aims to analyze the distribution patterns of LE in Indonesia from 2020 to 2023 using the K-Means Clustering algorithm. The data used includes LE from all provinces in Indonesia during this period, sourced from secondary data provided by the Central Bureau of Statistics (BPS). This research adopts a quantitative descriptive approach with a population comprising all provinces in Indonesia for the years 2020-2023. The analysis results indicate that provinces can be grouped into three clusters based on LE levels: high LE cluster (C1), moderate LE cluster (C2), and low LE cluster (C3). High LE clusters, such as DKI Jakarta and Bali, demonstrate good healthcare infrastructure, high education levels, and effective government programs. Conversely, low LE clusters, such as Central Kalimantan and North Sumatra, face challenges such as limited access to healthcare services, low education levels, and high poverty rates. This study recommends the development of healthcare infrastructure, equitable distribution of healthcare resources, and the enhancement of health education programs in low LE regions to reduce disparities across regions.