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All Journal REKAYASA Prosiding Seminar Nasional Official Statistics
Diarty, Milie
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Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Physics Social Sciences

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Total Factor Productivity Growth (TFPG) dan Determinan Produksi Tebu Indonesia Diarty, Milie; Haryanto, Jasmine ‘Abqoriyah; Izzuddin, Kautsar Hilmi; Manganti, Marella Dea; Rahman, Muhamad Reza; Budiasih, Budiasih
Seminar Nasional Official Statistics Vol 2023 No 1 (2023): Seminar Nasional Official Statistics 2023
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/semnasoffstat.v2023i1.1747

Abstract

The increase in Indonesia's sugar imports was due to production originating from within the country but unable to meet various needs for the domestic region. This shortage of sugar production is of course in line with the production of sugar cane which is the main ingredient and there are eight sugarcane producing centers in the province. Sugarcane production is closely related to the influence of production factors and production technology (TFP). This study aims to analyze the various influences on sugarcane production from land area and labor in eight sugarcane-producing provinces and to analyze the determinants of TFP growth (TFPG) using panel data regression. Where the results were obtained showing that the sugarcane planting area had a significant positive effect and labor had a negative but not significant effect. Foreign investment in agriculture and plantations and Farmers' Exchange Rates of plantation crops have a negative but not significant effect on the TFPG.
Analisis Aspek Ketahanan Pangan Indonesia dengan Hard dan Soft Clustering, 2022 Diarty, Milie; Wijayanto, Arie Wahyu
Rekayasa Vol 17, No 1: April, 2024
Publisher : Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21107/rekayasa.v17i1.21774

Abstract

Food security is crucial all over the world. Even food security is one of the goals in the Sustainable Development Goals (SDGs). Indonesia has also made food security a goal in both short and long term development. As a country with geographical conditions that are coveted by other countries, it is only natural for Indonesia to be able to use existing resources to maximize domestic development, one of which is through food security. Provinces that are spread from Sabang to Merauke make Indonesia must be able to analyze the grouping of its food security by considering various indicators. Food security indicators are integrated into the aspects of food availability, affordability, and utilization. Clustering is a method in machine learning to be able to find out food security groupings in Indonesia. There are many clustering methods. Several methods that are widely used are Hierarchical, K-Means, and Fuzzy C-Means. All three can produce different groupings. In this study, it was found that there was one province that had low food security, namely Papua Province. In addition, some of the provinces that always have high food security are all provinces on the island of Java.
Co-Authors Budiasih Budiasih Haryanto, Jasmine ‘Abqoriyah Izzuddin, Kautsar Hilmi Manganti, Marella Dea Rahman, Muhamad Reza