Masa Depan Kakao Indonesia: Pendekatan Integratif untuk Pengembangan Kakao Berkelanjutan

Adi Nugraha, Mahra A. Heryanto, Ganjar Kurnia

Abstrak


Abstrak

Kakao merupakan salah satu komoditas perkebunan strategis Indonesia yang berperan penting dalam perekonomian nasional dan penghidupan petani kecil. Namun, pengembangan kakao nasional menghadapi berbagai tantangan, termasuk penurunan produktivitas, perubahan iklim, fluktuasi harga global, serta tuntutan praktik produksi berkelanjutan dari pasar global. Penelitian ini bertujuan menganalisis dinamika sistem agribisnis kakao Indonesia secara integratif melalui proyeksi kuantitatif jangka panjang dan analisis sistem agribisnis. Pendekatan kualitatif digunakan dengan analisis data sekunder menggunakan model ARIMAX untuk memproyeksikan produksi, produktivitas, dan luas lahan kakao hingga tahun 2045. Hasil proyeksi kemudian diperdalam melalui analisis kualitatif berbasis system dynamics dengan penyusunan Causal Loop Diagram berdasarkan wawancara mendalam dan observasi lapangan di sentra kakao Luwu Utara. Hasil penelitian menunjukkan bahwa produksi kakao Indonesia berpotensi meningkat dalam jangka panjang, terutama melalui peningkatan produktivitas, meskipun tetap dipengaruhi flukutasi pasar dan faktor lingkungan. Analisis sistem menunjukkan bahwa keberlanjutan kakao nasional sangat dipengaruhi oleh interaksi antara produktivitas, kelembagaan petani, industri hilir, kebijakan pemerintah, dan dinamika pasar global. Penguatan sistem perbenihan, percepatan peremajaan, peningkatan kapasitas petani, serta pengembangan industri hilir menjadi faktor kunci dalam mendorong sistem produksi kakao berkelanjutan di Indonesia.

Kata kunci: Kakao berkelanjutan, sistem agribisnis kakao, pembangunan perkebunan, system dynamics.

Abstract

Cocoa is one of Indonesia’s strategic plantation commodities, playing a significant role in the national economy and the livelihoods of smallholder farmers. However, the development of the national cocoa sector faces various challenges, including declining productivity, climate change, global price fluctuations, and increasing demands for sustainable production practices from the international market. This study aims to analyze the dynamics of Indonesia’s cocoa agribusiness system in an integrative manner through long-term quantitative projections and agribusiness system analysis. A qualitative approach was employed, utilizing secondary data analysis with the ARIMAX model to project cocoa production, productivity, and cultivated area through 2045. The projection results were further elaborated through qualitative system dynamics analysis by constructing a Causal Loop Diagram based on in-depth interviews and field observations conducted in the cocoa-producing center of North Luwu. The findings indicate that Indonesia’s cocoa production has the potential to increase in the long term, primarily through improvements in productivity, although it remains influenced by market fluctuations and environmental factors. The system analysis reveals that the sustainability of the national cocoa sector is strongly shaped by the interaction among productivity, farmer institutions, downstream industries, government policies, and global market dynamics. Strengthening the seed system, accelerating replanting programs, enhancing farmers’ capacity, and developing downstream industries are key factors in promoting a sustainable cocoa production system in Indonesia.

Keywords: Sustainable cocoa, cocoa agribusiness system, plantation development, system dynamics.


Teks Lengkap:

697-707

Referensi


Abbott, P. C., Benjamin, T. J., Burniske, G. R., Croft, M. M., Fenton, M., Kelly, C. R., Lundy, M. M., Rodríguez Camayo, F., & Wilcox, M. D. (2018). An analysis of the supply chain of cacao in Colombia. https://cgspace.cgiar.org/bitstreams/ba372618-c959-458b-bfaf-34eb6dc3d12f/download

Baffoe-Asare, R., Danquah, J. A., & Annor-Frempong, F. (2013). Socioeconomic factors influencing adoption of CODAPEC and cocoa high-tech technologies among small holder farmers in Central Region of Ghana.

Beer, J., Muschler, R., Kass, D., & Somarriba, E. (1998). Shade management in coffee and cacao plantations. Agroforestry Systems, 38, 139–164. https://doi.org/10.1023/A:1005956528316

Bernard, H. R. (2017). Research Methods in Anthropology: Qualitative and Quantitative Approaches. Rowman & Littlefield.

Bos, M. M., Steffan-Dewenter, I., & Tscharntke, T. (2007). The contribution of cacao agroforests to the conservation of lower canopy ant and beetle diversity in Indonesia. Biodiversity and Conservation, 16(8), 2429–2444.

Clough, Y., Faust, H., & Tscharntke, T. (2009). Cacao boom and bust: Sustainability of agroforests and opportunities for biodiversity conservation. Conservation Letters, 2(5), 197–205. https://doi.org/10.1111/j.1755-263X.2009.00072.x

Creswell, J. W., & Poth, C. N. (2017). Qualitative inquiry and research design: Choosing among five approaches. Sage publications.

Effendy, Pratama, M. F., Rauf, R. A., Antara, M., Basir-Cyio, M., Mahfudz, & Muhardi. (2019). Factors influencing the efficiency of cocoa farms: A study to increase income in rural Indonesia. PLoS One, 14(4), e0214569.

Forrester, J. W. (2007). System dynamics—The next fifty years. System Dynamics Review: The Journal of the System Dynamics Society, 23(2–3), 359–370.

Guest, G., Bunce, A., & Johnson, L. (2006). How Many Interviews Are Enough?: An Experiment with Data Saturation and Variability. Field Methods, 18(1), 59–82. https://doi.org/10.1177/1525822X05279903

Kelley, L. C. (2018). The politics of uneven smallholder cacao expansion: A critical physical geography of agricultural transformation in Southeast Sulawesi, Indonesia. Geoforum, 97, 22–34. https://doi.org/10.1016/j.geoforum.2018.10.006

Neshat, N., Hadian, H., & Behzad, M. (2018). Nonlinear ARIMAX model for long–term sectoral demand forecasting. Management Science Letters, 8(6), 581–592.

Nugraha, A., Heryanto, M. A., Wulandari, E., & Pardian, P. (2019). Heading towards sustainable cacao agribusiness system (a case study in North Luwu, South Sulawesi, Indonesia). IOP Conference Series: Earth and Environmental Science, 306(1), 012035. https://iopscience.iop.org/article/10.1088/1755-1315/306/1/012035/meta

Paul, R. K., & Sinha, K. (2016). Forecasting crop yield: ARIMAX and NARX model. Rashi, 1(1), 77–85.

Pertanian, K. (2025). Buku Outlook Komoditas Perkebunan Kakao (p. 91). Pusat Data dan Sistem Informasi Pertanian. https://satudata.pertanian.go.id/assets/docs/publikasi/OUTLOOK_KAKAO_2025_sign_rev.pdf

Peter, Ď., & Silvia, P. (2012). ARIMA vs. ARIMAX–which approach is better to analyze and forecast macroeconomic time series. Proceedings of 30th International Conference Mathematical Methods in Economics, 2, 136–140. https://www.academia.edu/download/36551553/024_Durka.pdf

Ugoh, C. I., Uzuke, C. A., & Ugoh, D. O. (2021). Application of ARIMAX Model on forecasting Nigeria’s GDP. American Journal of Theoretical and Applied Statistics, 10(5), 216.

Villacis, A., Alwang, J., & Barrera, V. (2022). Cacao value chains and credence attributes: Lessons from Ecuador. Journal of Agribusiness in Developing and Emerging Economies, 12(4), 549–566.




DOI: https://doi.org/10.24198/agricore.v10i2.69847

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