{"title":"乡村环境中机电链Saing传动指示器的确认和分类","authors":"Analisa Konfirmasi, Dan Klasifikasi, Indikator Penggerak, Daya Saing, Rantai Pasok, Umkm di, Pedesaan Sumarsono, Andhika Mayasari, Fatma Ayu, Nuning Farida Afiatna","doi":"10.25105/jti.v12i3.15647","DOIUrl":null,"url":null,"abstract":"Abstract— Supply chain driver (SCD) sebagai pendorong daya saing UMKM Pedesaan, menjadi topik yang perlu dikaji. Penelitian ini bertujuan untuk mengkonfirmasi dan mengklasifikasikan SCD daya saing UMKM Pedesaan. Desain penelitian kuantitatif menggunakan kuesioner dengan metode purpose sampling. Metode Analisis data menggunakan Confirmatory Factor Analysis (CFA) untuk mendapatkan model konfirmasi. Selanjutnya, metode Machine Learning untuk menemukan model klasifikasi. Hasil penelitian disimpulkan bahwa faktor inventori menjadi penggerak daya saing terbesar di UMKM pedesaan. Kemudian secara berurutan yaitu faktor transportasi, sourcing, informasi, fasilitas, dan harga. Hasil selanjutnya disimpulkan 5 indikator teratas dari klasifikasi level daya saing High, Middle, Low. Implikasinya untuk pengembangan daya saing UMKM pedesaan, yakni dengan menerapkan strategi bauran dari 5 indikator tersebut. Yang meliputi route of transportation, lead time of supplier, variation of inventories, utility of facility, dan purchase quantity of supplier. \nAbstract— Supply chain drivers (SCD) as a driver of the competitiveness of Rural MSMEs, is a topic that needs to be studied. This study aims to confirm and classify the SCD of Rural MSME competitiveness. Quantitative research design using a questionnaire with a purposive sampling method. Data analysis method uses Confirmatory Factor Analysis (CFA) to obtain a confirmation model. Next, the Machine Learning method for finding a classification model. The results of the study concluded that the inventory factor is the biggest driver of competitiveness in rural SMEs. Then sequentially namely transportation factors, sourcing, information, facilities, and prices. The next result concludes the top 5 indicators from the classification level of competitiveness High, Middle, Low. The implication for developing the competitiveness of rural MSMEs is by implementing a mix strategy of the 5 indicators. Which includes routes of transportation, lead time of suppliers, variation of inventories, utility of facilities, and purchase quantity of suppliers.","PeriodicalId":32828,"journal":{"name":"Jurnal Teknik Industri","volume":"6 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Analisa Konfirmasi dan Klasifikasi Indikator Penggerak Daya Saing Rantai Pasok UMKM di Pedesaan\",\"authors\":\"Analisa Konfirmasi, Dan Klasifikasi, Indikator Penggerak, Daya Saing, Rantai Pasok, Umkm di, Pedesaan Sumarsono, Andhika Mayasari, Fatma Ayu, Nuning Farida Afiatna\",\"doi\":\"10.25105/jti.v12i3.15647\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract— Supply chain driver (SCD) sebagai pendorong daya saing UMKM Pedesaan, menjadi topik yang perlu dikaji. Penelitian ini bertujuan untuk mengkonfirmasi dan mengklasifikasikan SCD daya saing UMKM Pedesaan. Desain penelitian kuantitatif menggunakan kuesioner dengan metode purpose sampling. Metode Analisis data menggunakan Confirmatory Factor Analysis (CFA) untuk mendapatkan model konfirmasi. Selanjutnya, metode Machine Learning untuk menemukan model klasifikasi. Hasil penelitian disimpulkan bahwa faktor inventori menjadi penggerak daya saing terbesar di UMKM pedesaan. Kemudian secara berurutan yaitu faktor transportasi, sourcing, informasi, fasilitas, dan harga. Hasil selanjutnya disimpulkan 5 indikator teratas dari klasifikasi level daya saing High, Middle, Low. Implikasinya untuk pengembangan daya saing UMKM pedesaan, yakni dengan menerapkan strategi bauran dari 5 indikator tersebut. Yang meliputi route of transportation, lead time of supplier, variation of inventories, utility of facility, dan purchase quantity of supplier. \\nAbstract— Supply chain drivers (SCD) as a driver of the competitiveness of Rural MSMEs, is a topic that needs to be studied. This study aims to confirm and classify the SCD of Rural MSME competitiveness. Quantitative research design using a questionnaire with a purposive sampling method. Data analysis method uses Confirmatory Factor Analysis (CFA) to obtain a confirmation model. Next, the Machine Learning method for finding a classification model. The results of the study concluded that the inventory factor is the biggest driver of competitiveness in rural SMEs. Then sequentially namely transportation factors, sourcing, information, facilities, and prices. The next result concludes the top 5 indicators from the classification level of competitiveness High, Middle, Low. The implication for developing the competitiveness of rural MSMEs is by implementing a mix strategy of the 5 indicators. Which includes routes of transportation, lead time of suppliers, variation of inventories, utility of facilities, and purchase quantity of suppliers.\",\"PeriodicalId\":32828,\"journal\":{\"name\":\"Jurnal Teknik Industri\",\"volume\":\"6 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-12-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Jurnal Teknik Industri\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.25105/jti.v12i3.15647\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Jurnal Teknik Industri","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.25105/jti.v12i3.15647","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Analisa Konfirmasi dan Klasifikasi Indikator Penggerak Daya Saing Rantai Pasok UMKM di Pedesaan
Abstract— Supply chain driver (SCD) sebagai pendorong daya saing UMKM Pedesaan, menjadi topik yang perlu dikaji. Penelitian ini bertujuan untuk mengkonfirmasi dan mengklasifikasikan SCD daya saing UMKM Pedesaan. Desain penelitian kuantitatif menggunakan kuesioner dengan metode purpose sampling. Metode Analisis data menggunakan Confirmatory Factor Analysis (CFA) untuk mendapatkan model konfirmasi. Selanjutnya, metode Machine Learning untuk menemukan model klasifikasi. Hasil penelitian disimpulkan bahwa faktor inventori menjadi penggerak daya saing terbesar di UMKM pedesaan. Kemudian secara berurutan yaitu faktor transportasi, sourcing, informasi, fasilitas, dan harga. Hasil selanjutnya disimpulkan 5 indikator teratas dari klasifikasi level daya saing High, Middle, Low. Implikasinya untuk pengembangan daya saing UMKM pedesaan, yakni dengan menerapkan strategi bauran dari 5 indikator tersebut. Yang meliputi route of transportation, lead time of supplier, variation of inventories, utility of facility, dan purchase quantity of supplier.
Abstract— Supply chain drivers (SCD) as a driver of the competitiveness of Rural MSMEs, is a topic that needs to be studied. This study aims to confirm and classify the SCD of Rural MSME competitiveness. Quantitative research design using a questionnaire with a purposive sampling method. Data analysis method uses Confirmatory Factor Analysis (CFA) to obtain a confirmation model. Next, the Machine Learning method for finding a classification model. The results of the study concluded that the inventory factor is the biggest driver of competitiveness in rural SMEs. Then sequentially namely transportation factors, sourcing, information, facilities, and prices. The next result concludes the top 5 indicators from the classification level of competitiveness High, Middle, Low. The implication for developing the competitiveness of rural MSMEs is by implementing a mix strategy of the 5 indicators. Which includes routes of transportation, lead time of suppliers, variation of inventories, utility of facilities, and purchase quantity of suppliers.