Factors Affecting White Pepper Production in Puncak Village, South Sinjai District, Sinjai Regency

Authors

  • Fadilah Nurdin Agribusiness Study Program, Faculty of Agriculture, Muhammadiyah University of Sinjai
  • Nurhalyza Nurhalyza Agribusiness Study Program, Faculty of Agriculture, Muhammadiyah University of Sinjai
  • Nilmalasari Nilmalasari Agribusiness Study Program, Faculty of Agriculture, Muhammadiyah University of Sinjai
  • Asdar Asdar Agribusiness Study Program, Faculty of Agriculture, Muhammadiyah University of Sinjai
  • Salsabila Salsabila Agribusiness Study Program, Faculty of Agriculture, Muhammadiyah University of Sinjai
  • Anisa Fahira Asma Agribusiness Study Program, Faculty of Agriculture, Muhammadiyah University of Sinjai

DOI:

https://doi.org/10.33005/sar.v2i1.36

Keywords:

Production, White Pepper, Production Factors, Multiple Linear Regression

Abstract

This study aims to analyze farmer characteristics and the factors affecting white pepper production in Puncak Village, South Sinjai District, Sinjai Regency. This research employed a quantitative approach using a survey method. A total of 30 farmers were selected using a saturated sampling technique. Data were collected through interviews, observations, and documentation, and analyzed using multiple linear regression. The results show that partially, seed quality (X1), land area (X2), and price (X3) have a significant effect on white pepper production with significance values < 0.05. Seed quality and price have a positive effect, while land area has a negative effect on production. Simultaneously, all variables significantly affect production. The coefficient of determination (R²) is 0.411, indicating that 41.1% of the variation in production is explained by the model, while the rest is influenced by other factors outside the study. In conclusion, Farmers are encouraged to use high-quality seeds and optimize land management to boost white pepper productivity, particularly on large-scale plots, to prevent a decline in production efficiency. The government and agricultural extension officers should provide guidance and training on efficient white pepper cultivation techniques and proper land management to increase farmers’ yields.

Downloads

Download data is not yet available.

References

Assuncao, J. J., & Braido, L. H. B. (2007). Testing household-specific explanations for the inverse productivity relationship. American Journal of Agricultural Economics, 89(4), 980-990. https://doi.org/10.1111/j.1467-8276.2007.01032.x

Barrett, C. B., Bellemare, M. F., & Hou, J. Y. (2010). Reconsidering conventional explanations of the inverse productivity-size relationship. World Development, 38(1), 88-97. https://doi.org/10.1016/j.worlddev.2009.06.002

Carletto, C., Savastano, S., & Zezza, A. (2013). Fact or artifact: The impact of measurement errors on the farm size-productivity relationship. Journal of Development Economics, 103, 254-261. https://doi.org/10.1016/j.jdeveco.2013.03.004

Chavas, J.-P., & Holt, M. T. (1990). Acreage decisions under risk: The case of corn and soybeans. American Journal of Agricultural Economics, 72(3), 529-538. https://doi.org/10.2307/1243021

Deolalikar, A. B. (1981). The inverse relationship between productivity and farm size: A test using regional data from India. American Journal of Agricultural Economics, 63(2), 275-279. https://doi.org/10.2307/1239565

Desiere, S., & Jolliffe, D. (2018). Land productivity and plot size: Is measurement error driving the inverse relationship? Journal of Development Economics, 130, 84-98. https://doi.org/10.1016/j.jdeveco.2017.10.002

Haile, M. G., Kalkuhl, M., & von Braun, J. (2016). Worldwide acreage and yield response to international price change and volatility: A dynamic panel data analysis for wheat, rice, corn, and soybeans. American Journal of Agricultural Economics, 98(1), 172-190. https://doi.org/10.1093/ajae/aav013

Kassie, M., Shiferaw, B., & Muricho, G. (2011). Agricultural technology, crop income, and poverty alleviation in Uganda. World Development, 39(10), 1784-1795. https://doi.org/10.1016/j.worlddev.2011.04.023

Kelley, K., Clark, B., Brown, V., & Sitzia, J. (2003). Good practice in the conduct and reporting of survey research. International Journal for Quality in Health Care, 15(3), 261-266. https://doi.org/10.1093/intqhc/mzg031

Mendola, M. (2007). Agricultural technology adoption and poverty reduction: A propensity-score matching analysis for rural Bangladesh. Food Policy, 32(3), 372-393. https://doi.org/10.1016/j.foodpol.2006.07.003

O'Brien, R. M. (2007). A caution regarding rules of thumb for variance inflation factors. Quality & Quantity, 41, 673-690. https://doi.org/10.1007/s11135-006-9018-6

Shiferaw, B., Kassie, M., Jaleta, M., & Yirga, C. (2014). Adoption of improved wheat varieties and impacts on household food security in Ethiopia. Food Policy, 44, 272-284. https://doi.org/10.1016/j.foodpol.2013.09.012

Sitorus, R., Harianto, Suharno, & Syaukat, Y. (2020). The application of Good Agricultural Practices of white pepper and factors affecting farmer participation. AGRIEKONOMIKA, 9(2), 132-145. https://doi.org/10.21107/agriekonomika.v9i2.6824.g5180

White, H. (1980). A heteroskedasticity-consistent covariance matrix estimator and a direct test for heteroskedasticity. Econometrica, 48(4), 817-838. https://doi.org/10.2307/1912934

Yulia, Y., Bahtera, N. I., & Saputra, H. M. (2019). Karakteristik dan keragaman input produksi usahatani lada putih (Muntok White Pepper) di Provinsi Kepulauan Bangka Belitung. AGROMIX, 10(2), 67-84. https://doi.org/10.35891/agx.v10i2.1609.

Downloads

Published

31-05-2026

How to Cite

Nurdin, F., Nurhalyza, N., Nilmalasari, N., Asdar, A., Salsabila, S., & Asma, A. F. (2026). Factors Affecting White Pepper Production in Puncak Village, South Sinjai District, Sinjai Regency. Sustainable Agribusiness Review, 2(1), 25–31. https://doi.org/10.33005/sar.v2i1.36

Issue

Section

Articles

Most read articles by the same author(s)

Similar Articles

You may also start an advanced similarity search for this article.