Version 1
: Received: 12 January 2024 / Approved: 13 January 2024 / Online: 15 January 2024 (03:13:48 CET)
How to cite:
Hadiarto, A.; Firdaus, M.; Harianto, H.; Novianti, T. Increasing Household Income from Vegetable Farming through Mobile and Smartphones Apps. Preprints2024, 2024011050. https://doi.org/10.20944/preprints202401.1050.v1
Hadiarto, A.; Firdaus, M.; Harianto, H.; Novianti, T. Increasing Household Income from Vegetable Farming through Mobile and Smartphones Apps. Preprints 2024, 2024011050. https://doi.org/10.20944/preprints202401.1050.v1
Hadiarto, A.; Firdaus, M.; Harianto, H.; Novianti, T. Increasing Household Income from Vegetable Farming through Mobile and Smartphones Apps. Preprints2024, 2024011050. https://doi.org/10.20944/preprints202401.1050.v1
APA Style
Hadiarto, A., Firdaus, M., Harianto, H., & Novianti, T. (2024). Increasing Household Income from Vegetable Farming through Mobile and Smartphones Apps. Preprints. https://doi.org/10.20944/preprints202401.1050.v1
Chicago/Turabian Style
Hadiarto, A., Harianto Harianto and Tanti Novianti. 2024 "Increasing Household Income from Vegetable Farming through Mobile and Smartphones Apps" Preprints. https://doi.org/10.20944/preprints202401.1050.v1
Abstract
This study aims to determine the impact of the type of ICT usage on household income from main vegetables, agriculture (including main vegetables), and total income. This study is based on surveys and interviews with vegetable farmers using structured questionnaires conducted in three villages in Indonesia, including Cianjur, Sleman, and Malang in West Java, Yogyakarta, and East Java, respectively. The data were collected from 375 respondents selected in each region from November 2021 to March 2022. An econometric model called the multivariate linear regression (MLR) model is used to assess heterogeneous factors that influence the possibility of increasing the income of vegetable farmers. The study found that variables that use ICT as a primary variable, household, marketing, geographical characteristics, and immediate source information in agriculture have a significant impact on household income (P < 0.01) from primary vegetables, agriculture, and total income, with multiple R squares of 70.5, 72.0, 73.7% and F statistics of 28.48, 30.66, and 33.34, respectively. In summary, this novel study shows that the five categories of information technology used in farming and selling of harvest have a positive impact on household incomes
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
