Analisis Pengelompokan Kecamatan Penghasil Daging Sapi di Kabupaten Kebumen Menggunakan Metode Clustering Time Series
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Institusion
Institut Teknologi Telkom Purwokerto
Author
Dewi, Qatrunnada
Subject
TA Engineering (General). Civil engineering (General)
Datestamp
2022-09-01 03:51:05
Abstract :
Beef is one of the most popular food commodities in the world, and it contributes to the production of animal protein which is much needed to support human resource development. The increasing demand for beef every year is increasing, due to an increase in population and increasing public awareness of the balance of nutrition and animal protein. Until now, the demand for beef can only be met by 70% of domestic beef production and 30% through imports. This condition does not support the beef self-sufficiency program that has been planned by the Indonesian government and is not in line with the target of domestic beef supply of 90-95 percent. Based on the results of the MB-IPB study (2012), Central Java Province is an area that has great potential in the development of beef cattle and the second largest producer of beef cattle in Indonesia after East Java and has contributed as a cattle supplier for national meat, especially for the DKI Jakarta area. and West Java, Central Java Province has Kebumen Regency which is one of the local beef cattle producers that can be developed. Kebumen Regency is an area that is a source of Ongole Peranakan (PO) cattle based on the Decree of the Minister of Agriculture of the Republic of Indonesia No.47/Kpts/SR.120/1/2015 on January 16, 2015, based on the decree, made the local cattle of Kebumen Regency a family. local beef cattle to continuously improve their production and reproductive performance. One way to do this is by clustering the sub-districts in Kebumen Regency to find out which sub-districts produce large or small amounts of local beef. Grouping based on the large number of local beef production in the Regency using the time series clustering method, time series clustering is a time series data grouping method that can be used to determine the best grouping results using dynamic time wrapping and multidimensional scaling distance similarity measures. Based on the results of the analysis, five groups or clusters were formed and information was obtained that there were two regions with the highest beef production, namely cluster five and cluster four, and the two lowest beef-producing clusters were obtained. Based on these results, the cluster with the highest beef production can be used as a benchmark against other groups. . Keywords: Dynamic Time Wrapping, Time Series clustering, Hierarchical cluster, Kebumen District
Beef is one of the most popular food commodities in the world, and it contributes to the production of animal protein which is much needed to support human resource development. The increasing demand for beef every year is increasing, due to an increase in population and increasing public awareness of the balance of nutrition and animal protein. Until now, the demand for beef can only be met by 70% of domestic beef production and 30% through imports. This condition does not support the beef self-sufficiency program that has been planned by the Indonesian government and is not in line with the target of domestic beef supply of 90-95 percent. Based on the results of the MB-IPB study (2012), Central Java Province is an area that has great potential in the development of beef cattle and the second largest producer of beef cattle in Indonesia after East Java and has contributed as a cattle supplier for national meat, especially for the DKI Jakarta area. and West Java, Central Java Province has Kebumen Regency which is one of the local beef cattle producers that can be developed. Kebumen Regency is an area that is a source of Ongole Peranakan (PO) cattle based on the Decree of the Minister of Agriculture of the Republic of Indonesia No.47/Kpts/SR.120/1/2015 on January 16, 2015, based on the decree, made the local cattle of Kebumen Regency a family. local beef cattle to continuously improve their production and reproductive performance. One way to do this is by clustering the sub-districts in Kebumen Regency to find out which sub-districts produce large or small amounts of local beef. Grouping based on the large number of local beef production in the Regency using the time series clustering method, time series clustering is a time series data grouping method that can be used to determine the best grouping results using dynamic time wrapping and multidimensional scaling distance similarity measures. Based on the results of the analysis, five groups or clusters were formed and information was obtained that there were two regions with the highest beef production, namely cluster five and cluster four, and the two lowest beef-producing clusters were obtained. Based on these results, the cluster with the highest beef production can be used as a benchmark against other groups. . Keywords: Dynamic Time Wrapping, Time Series clustering, Hierarchical cluster, Kebumen District
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