The stepwise regression analysis method for estimating sorghum production in Karangmojo

Muazam, A. and Widyayanti, S. and Kristamtini, Kristamtini and Daryono, B.S. (2024) The stepwise regression analysis method for estimating sorghum production in Karangmojo. In: 2nd International Conference on Food and Agricultural Sciences 2023 12/12/2023 - 13/12/2023 Yogyakarta, Indonesia, 2023 12/12/2023 - 13/12/2023, Yogyakarta.

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Abstract

Sorghum is a multifunctional crop that can be utilized as a source of food, feed, and bioenergy. Sorghum is a plant that can adapt to land with optimal conditions, dry land with minimal nutrients and tolerant to pests and diseases. Sorghum has been widely cultivated in Indonesia, one in Gunungkidul, Yogyakarta. Sorghum production is influenced by several agronomic characteristics. The purpose of the study was to determine agronomic variables that affect sorghum production. The research was conducted in Karangmojo, Gunungkidul, Special Region of Yogyakarta, from October 2022 to March 2023. Sorghum varieties were local varieties as well as national superior varieties which are usually planted by local farmers. A total of 10 variables were analysed for their significance level on sorghum yield. The collected data were then processed using a multiple linear regression model (stepwise) using SPSS 16.0. The results showed that of the 10 agronomic variables observed, two variables contributed to the sorghum production, namely panicle weight and days to harvesting. The regression model from stepwise results is y = 8.884 + 0.036x3 - 0.062x10, with R2 = 0.754. This result indicates that the two independent variables are the main variables in determining sorghum production in Karangmojo. © Published under licence by IOP Publishing Ltd.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Cited by: 0; All Open Access, Gold Open Access
Subjects: Biology
Divisions: Faculty of Biology > Doctoral Program in Biology
Depositing User: Rusna Nur Aini Aini
Date Deposited: 23 Sep 2025 07:26
Last Modified: 23 Sep 2025 07:26
URI: https://ir.lib.ugm.ac.id/id/eprint/19588

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