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Clustering the micro, small and medium enterprises (MSMEs) in Yogyakarta City based on technology readiness index 2.0 using K-Means method
MSMEs as one of the economic drivers and have important role in local economic growth. As pandemic condition that came in 2019, technology become an essential part of activities. If pandemic condition is continuing, MSMEs have to adopt the technology. In Yogyakarta city, there are many MSMEs that ca...
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creator | Astuti, Amalia Yuli Adzaningtyas, Riri Dwi Akbar, Nurul |
description | MSMEs as one of the economic drivers and have important role in local economic growth. As pandemic condition that came in 2019, technology become an essential part of activities. If pandemic condition is continuing, MSMEs have to adopt the technology. In Yogyakarta city, there are many MSMEs that came from various backgrounds. But the segmentation of MSMEs’ technology readiness has not been examined. This research took sample of the MSMEs in the Yogyakarta city. The purpose of this research was to clustering the MSMEs with Technology Readiness Index (TRI) 2.0. The methodology used is a survey of 180 MSMEs in the fields of food processing and clothing convections. The clustering was computed with K-Means algorithm in R software. The cluster of MSMEs based on five groups (explorers, pioneers, skeptics, paranoids, and laggards) from TRI's user segmentations. The results of the clustering were found only two groups from the sample and the groups were pioneers and skeptics. The number sample in the pioneers group was 59% and the skeptics was 41%. The pioneers have positive and little negative perceptions about using technology. The skeptics didn't oppose technology but have low enthusiasm. |
doi_str_mv | 10.1063/5.0104939 |
format | conference_proceeding |
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As pandemic condition that came in 2019, technology become an essential part of activities. If pandemic condition is continuing, MSMEs have to adopt the technology. In Yogyakarta city, there are many MSMEs that came from various backgrounds. But the segmentation of MSMEs’ technology readiness has not been examined. This research took sample of the MSMEs in the Yogyakarta city. The purpose of this research was to clustering the MSMEs with Technology Readiness Index (TRI) 2.0. The methodology used is a survey of 180 MSMEs in the fields of food processing and clothing convections. The clustering was computed with K-Means algorithm in R software. The cluster of MSMEs based on five groups (explorers, pioneers, skeptics, paranoids, and laggards) from TRI's user segmentations. The results of the clustering were found only two groups from the sample and the groups were pioneers and skeptics. The number sample in the pioneers group was 59% and the skeptics was 41%. 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The skeptics didn't oppose technology but have low enthusiasm.</description><subject>Algorithms</subject><subject>Clustering</subject><subject>Economic development</subject><subject>Food processing</subject><subject>Pandemics</subject><subject>Pioneers</subject><subject>Small & medium sized enterprises-SME</subject><subject>Technology utilization</subject><issn>0094-243X</issn><issn>1551-7616</issn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2023</creationdate><recordtype>conference_proceeding</recordtype><recordid>eNotkMtOwzAQRS0EEqWw4A8ssQFEih0_4ixRVB6iFQu6gFXk1E7rktjFdiT6C3w1Ru1qFnNmju4F4BKjCUac3LMJwoiWpDwCI8wYzgqO-TEYIVTSLKfk4xSchbBBKC-LQozAb9UNIWpv7ArGtYa9WXp3B0Mvuw5Kq2CvlRl6qG2Ctt4EHeD1_H0-DTfQWPjpVjv5JX2UsDJxBxsZtILOwqiXa-u6tIZeS2WsDiEdKP0D8wmCQ_gXvmZzLW1Ijrh26hyctLIL-uIwx2DxOF1Uz9ns7emlephl25KjjImmFZQ2RHCFCs5SvJZTrjDPUUl4Q5uyVSRftlw2SuGWUCo0ExQTolQpKRmDq_3brXffgw6x3rjB22Ssc0ELRhgRRaJu91RYmiijcbZO6XvpdzVG9X_VNasPVZM_d9NwNg</recordid><startdate>20230808</startdate><enddate>20230808</enddate><creator>Astuti, Amalia Yuli</creator><creator>Adzaningtyas, Riri Dwi</creator><creator>Akbar, Nurul</creator><general>American Institute of Physics</general><scope>8FD</scope><scope>H8D</scope><scope>L7M</scope></search><sort><creationdate>20230808</creationdate><title>Clustering the micro, small and medium enterprises (MSMEs) in Yogyakarta City based on technology readiness index 2.0 using K-Means method</title><author>Astuti, Amalia Yuli ; Adzaningtyas, Riri Dwi ; Akbar, Nurul</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-p960-58bf844b386d0765616f646d1620936b4b9fd32cf6abdd1f3448e584133dd9a43</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Algorithms</topic><topic>Clustering</topic><topic>Economic development</topic><topic>Food processing</topic><topic>Pandemics</topic><topic>Pioneers</topic><topic>Small & medium sized enterprises-SME</topic><topic>Technology utilization</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Astuti, Amalia Yuli</creatorcontrib><creatorcontrib>Adzaningtyas, Riri Dwi</creatorcontrib><creatorcontrib>Akbar, Nurul</creatorcontrib><collection>Technology Research Database</collection><collection>Aerospace Database</collection><collection>Advanced Technologies Database with Aerospace</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Astuti, Amalia Yuli</au><au>Adzaningtyas, Riri Dwi</au><au>Akbar, Nurul</au><au>Septiani, Winnie</au><au>Wahyukaton, Wahyukaton</au><au>Ningtyas, Desinta Rahayu</au><au>Maulidya, Rahmi</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Clustering the micro, small and medium enterprises (MSMEs) in Yogyakarta City based on technology readiness index 2.0 using K-Means method</atitle><btitle>AIP conference proceedings</btitle><date>2023-08-08</date><risdate>2023</risdate><volume>2485</volume><issue>1</issue><issn>0094-243X</issn><eissn>1551-7616</eissn><coden>APCPCS</coden><abstract>MSMEs as one of the economic drivers and have important role in local economic growth. As pandemic condition that came in 2019, technology become an essential part of activities. If pandemic condition is continuing, MSMEs have to adopt the technology. In Yogyakarta city, there are many MSMEs that came from various backgrounds. But the segmentation of MSMEs’ technology readiness has not been examined. This research took sample of the MSMEs in the Yogyakarta city. The purpose of this research was to clustering the MSMEs with Technology Readiness Index (TRI) 2.0. The methodology used is a survey of 180 MSMEs in the fields of food processing and clothing convections. The clustering was computed with K-Means algorithm in R software. The cluster of MSMEs based on five groups (explorers, pioneers, skeptics, paranoids, and laggards) from TRI's user segmentations. The results of the clustering were found only two groups from the sample and the groups were pioneers and skeptics. The number sample in the pioneers group was 59% and the skeptics was 41%. The pioneers have positive and little negative perceptions about using technology. The skeptics didn't oppose technology but have low enthusiasm.</abstract><cop>Melville</cop><pub>American Institute of Physics</pub><doi>10.1063/5.0104939</doi><tpages>6</tpages></addata></record> |
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source | American Institute of Physics:Jisc Collections:Transitional Journals Agreement 2021-23 (Reading list) |
subjects | Algorithms Clustering Economic development Food processing Pandemics Pioneers Small & medium sized enterprises-SME Technology utilization |
title | Clustering the micro, small and medium enterprises (MSMEs) in Yogyakarta City based on technology readiness index 2.0 using K-Means method |
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