Journal of Advanced Technology and Multidiscipline (JATM) Vol. 02, No. 01, 2023, pp. 27-33 e-ISSN: 2964-6162 27 Abstract—The quality of life for Indonesia's population can be measured from the human development index in each province. People who have a good quality of life indicate a prosperous life. The government has the responsibility to advance the welfare of the nation under the mandate of the constitution. The clustering of the Human Development Index (HDI) in Indonesia is used to determine the distribution of quality of life or the distribution of social welfare. In this study, the K-Means method, which is a popular non-hierarchical clustering method, is used to classify human development in each province based on HDI indicators, namely Life Expectancy at Birth, Expected Years of Schooling, Mean Years of Schooling, and Adjusted Expenditure Per Capita. Provinces in Indonesia are clustered into 4 clusters. These results were also compared with the clustering based on HDI categories determined by Statistics Indonesia based on certain cut-off values. According to the HDI category, provinces in Indonesia fall into the medium, high, and very high categories. The results of the two groupings show that there is a trend toward appropriate characteristics for each group. Thus, K-Means can classify provinces in Indonesia according to the characteristics of the HDI indicators. Keywords— Human development, HDI, K-Means, Quality of life. I. INTRODUCTION eneral welfare is a community right and has been regulated by the Indonesian state constitution. Thus, the Indonesian government is responsible for fulfilling the state's mandate. Country achievements in national development can be seen from various factors. Economic growth and the quality of human resources are several factors that support the success of a country. The human development index (HDI) is one measure to assess the quality of human resources [1]. HDI is a measure of the quality of human life as well as an indicator of development goals [2]. HDI explains how citizens can access development outcomes in terms of income, health, education, and other aspects of life [3]–[5]. United Nations Development Programme (UNDP) has used three dimensions to form HDI, namely long and healthy life, knowledge, and a decent standard of living [2], [6]. Corresponding Author: Indah Fahmiyah Faculty of Advanced Technology and Multidiscipline, Universitas Airlangga, Campus C UNAIR Gedung Kuliah Bersama, Mulyorejo, Surabaya, Indonesia Indonesia is an archipelagic country consisting of 5 large island groups namely Sumatra, Kalimantan, Sulawesi, Java, Bali, Nusa Tenggara, Maluku, and Papua [2]. Each region has a diversity which is a challenge for the government in human development. The value of the human development index can be used as a reference for the government to make budget policies for each region and strategies for achieving national or regional development [2]. Regional grouping based on human development is used to determine the distribution of the quality of life of the population. By knowing this distribution, the government can formulate short-term and long-term development strategies to improve and increase the quality of life of the population. HDI Indonesia has increased from year to year [2]. In Indonesia, HDI is categorized into 4 categories, i.e. low, medium, high, and very high with cutoff points at 60, 70, and 80 [1]. The cutoff point for low HDI that is determined by UNDP is slightly different, namely lower than 55 [6]. Most regencies or cities’ HDI in Indonesia is medium HDI [2]. Lampung Province, Central Sulawesi Province, and Maluku Province changed from medium to high HDI with an HDI growth of 0.79%, 0.70%, and 0.73% in 2022 [2]. If the categorization of human development in an area only uses a composite index, then the consideration of the cutoff point for each category becomes very crucial. Cluster analysis aims to group of observations into clusters depends on the similarities and dissimilarities in the characteristics of the dataset. The K-Means is a frequently used non-hierarchical clustering method [7]–[9]. The form of the K- Means algorithm is to assign each object to the cluster that has the closest centroid. Thus, the objective of K-Means is to obtain minimum between-cluster variation and maximum inter-cluster variation. Much research has been carried out regarding the grouping of human development in Indonesia based on HDI indicators by using cluster analysis, such as hierarchical clustering [5], K- Means [4], [5], [10], K-Medoids [5], and Fuzzy C-Means [10]. The researchers found that the number of clusters is four clusters using K-Means [4], [5], [10] and Fuzzy C-Means [10], but two clusters for hierarchical clustering and five clusters for indah.fahmiyah@ftmm.unair.ac.id Human Development Clustering in Indonesia: Using K-Means Method and Based on Human Development Index Categories Indah Fahmiyah 1 , Ratih Ardiati Ningrum 1 1 Faculty of Advanced Technology and Multidiscipline, Universitas Airlangga, Surabaya, Indonesia G