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All Journal PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON DATA SCIENCE AND OFFICIAL STATISTICS
Reni Amelia
BPS-Statistics Indonesia
Computer Science & IT

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Agricultural Digitalization: Can This Transformation Increase Farmers' Income In East Java? Reni Amelia; Akhmad Munim
Proceedings of The International Conference on Data Science and Official Statistics Vol. 2023 No. 1 (2023): Proceedings of 2023 International Conference on Data Science and Official St
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/icdsos.v2023i1.412

Abstract

The era of the industrial revolution 4.0 has encouraged various economic sectors to utilize technology and information in their activities, including the agricultural sector. This study provides an overview of the impact of agricultural digitization on farmers' income and examines the characteristics of farmers in East Java who have and have not utilized agricultural digitalization as a first step toward agricultural extension targets. The data comes from the August 2022 National Labor Force Survey in East Java conducted by BPS-Statistics Indonesia with a sample size of 7.852 farmers carrying out agricultural businesses. The t-Student test results show that farmers who utilize agricultural digitization have an average income higher than those who do not utilize it. The binary logistic regression results also show that digitization of agriculture, gender, education, agricultural business field, and business status also affect farmers' income. The results random undersampling analysis and random oversampling classification and regression trees results show that there are two types of characteristics of farmers in East Java who take advantage of agricultural digitization, namely farmers who graduated at least junior high school and farmers who graduated elementary school/equivalent, come from X, Y, or Z generations, and work assisted by permanent workers/paid workers.
Strategic Expansion of Digital Payments in Papua and West Papua: Individual Character Analysis Using Random Over and Under Sampling CART Reni Amelia; Akhmad Mun'im
Joint International Conference 2026: The 2nd Indonesia Forum on Labour and Productivity (IFLP) & The 4th International Conference on Data Science and Official Statistics (ICDSOS) Vol. 2025 No. 1 (2025): Proceedings of 2025 International Conference on Data Science and Official St
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/icdsos.v2025i1.651

Abstract

This study examines the characteristics and influencing factors of digital payment usage among individuals in Papua and West Papua. Understanding these characteristics enables stakeholders to design effective strategies for promotion, socialization, and education to support the expansion of digital payment adoption. The analysis uses data from the March 2023 National Socio-Economic Survey conducted by BPS, involving 52,081 respondents aged 17 years and older. A Classification and Regression Trees (CART) approach was applied with random oversampling and undersampling techniques to handle data imbalance. The results reveal that business fields, types of residential areas, and education levels are key determinants of digital payment usage. Three primary user profiles were identified: (1) individuals aged 17+ working outside the agricultural sector with at least a high school education; (2) individuals aged 17+ working outside agriculture, with junior high school education or below, residing in urban areas; and (3) individuals aged 17+ working in agriculture or unemployed, living in urban areas, and having completed high school or higher. These findings suggest that stakeholders should tailor promotional strategies and educational programs based on individual characteristics to effectively increase digital payment adoption in Papua and West Papua.
Co-Authors Akhmad Mun'im Akhmad Munim