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Fithri Selva Jumeilah
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KLASTERISASI PENDUDUK LANJUT USIA SUMATERA SELATAN MENGGUNAKAN ALGORITMA K-MODES Fithri Selva Jumeilah; Dicky Pratama
Jurnal TAM (Technology Acceptance Model) Vol 8, No 2 (2017): Jurnal TAM (Technology Acceptance Model)
Publisher : LPPM STMIK Pringsewu

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (240.41 KB)

Abstract

Currently, Indonesia is included in a country with a population of old structures because of its advanced population of more than 7% of the total population and 2% comes from southern Sumatra. The large number of elderly citizens required a special government policy to formulate policies and special programs the population can use to alleviate the community. To help local government of South Sumatera government to determine the policy and program hence needed clustering elderly population by using K-mode algorithm existing in R-Studio. This study uses population census data of South Sumatera in 2010 obtained from Bapan Pusat Statistik with 47,358 data sample. From the results of this study made 4 clusters: K1 16244 people, K2 6061 people, K3 18681 people, and K4 6372 people. K1 is an elderly group of mostly men who live in the village and still work in agriculture and plantations. K2 is a cluster of women who still work and live in the village. The third K3 cluster is an elderly unemployed group that mostly lives in the city and 25% lives alone. The last K4 is a cluster of women who do not work anymore, live in the village and 73% illiterate. With the cluster the government can determine what is most appropriate for each cluster.
KLASTERISASI PENDUDUK LANJUT USIA SUMATERA SELATAN MENGGUNAKAN ALGORITMA K-MODES Fithri Selva Jumeilah; Dicky Pratama
Jurnal TAM (Technology Acceptance Model) Vol 8, No 2 (2017): Jurnal TAM (Technology Acceptance Model)
Publisher : LPPM STMIK Pringsewu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56327/jurnaltam.v8i2.535

Abstract

Currently, Indonesia is included in a country with a population of old structures because of its advanced population of more than 7% of the total population and 2% comes from southern Sumatra. The large number of elderly citizens required a special government policy to formulate policies and special programs the population can use to alleviate the community. To help local government of South Sumatera government to determine the policy and program hence needed clustering elderly population by using K-mode algorithm existing in R-Studio. This study uses population census data of South Sumatera in 2010 obtained from Bapan Pusat Statistik with 47,358 data sample. From the results of this study made 4 clusters: K1 16244 people, K2 6061 people, K3 18681 people, and K4 6372 people. K1 is an elderly group of mostly men who live in the village and still work in agriculture and plantations. K2 is a cluster of women who still work and live in the village. The third K3 cluster is an elderly unemployed group that mostly lives in the city and 25% lives alone. The last K4 is a cluster of women who do not work anymore, live in the village and 73% illiterate. With the cluster the government can determine what is most appropriate for each cluster.
Co-Authors Dicky Pratama