Prediksi Hasil Produksi Beras di Kabupaten Lamongan Menggunakan Stochastic Frontier Analysis (SFA)

Authors

  • Imelda Widya Ningrum Sains Data, Fakultas Ilmu Komputer, Universitas Pembangunan Nasional "Veteran" Jawa Timur https://orcid.org/0009-0005-7681-1437
  • Dwi Arman Prasetya Sains Data, Fakultas Ilmu Komputer, Universitas Pembangunan Nasional "Veteran" Jawa Timur https://orcid.org/0000-0003-0281-9928
  • Trimono Sains Data, Fakultas Ilmu Komputer, Universitas Pembangunan Nasional "Veteran" Jawa Timur

DOI:

https://doi.org/10.26905/jasiek.v7i1.15556

Keywords:

Efisiensi Teknis, Pertanian, Prediksi, Produksi Beras, Stochastic Frontier Analysis

Abstract

The agricultural sector plays a crucial role in the Indonesian economy, especially in maintaining food estate and economic stability. This study aims to identify and improve the technical efficiency of rice production in Indonesia using Stochastic Frontier Analysis (SFA). Agricultural data were analyzed through validation, cleaning, feature selection, and modeling with a log-linear Cobb-Douglas production function estimated using Maximum Likelihood Estimation (MLE). Model performance was evaluated on training and test data using Log-likelihood, R-squared, and Mean Absolute Percentage Error (MAPE). The results showed good model prediction performance on test data (R-squared = 0.6658 and MAPE = 14.34%). Technical inefficiency analysis indicated that the level of inefficiency among farmers in Lamongan Regency was relatively low and homogeneous. However, the efficiency frontier analysis identified significant opportunities to increase rice yields through more efficient management of production factors and reduction of inefficiencies

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Author Biographies

Dwi Arman Prasetya, Sains Data, Fakultas Ilmu Komputer, Universitas Pembangunan Nasional "Veteran" Jawa Timur

Dosen dan peneliti di Departemen Sains Data, UPN "Veteran" Jawa Timur, dengan minat riset di bidang robotics, Artificial Intelligence, Internet of Things

Trimono, Sains Data, Fakultas Ilmu Komputer, Universitas Pembangunan Nasional "Veteran" Jawa Timur

Dosen dan peneliti di Departemen Studi Sains Data, UPN "Veteran" Jawa Timur, dengan minat riset di bidang manajemen risiko, time series modellingprobability statistics

References

D. A. Prasetya, A. Sanusi, G. Chandrarin, E. Roikhah, I. Mujahidin, and R. Arifuddin, “Small and Medium Enterprises Problem and Potential Solutions for Waste Management,” J. Southwest Jiaotong Univ., vol. 54, no. 6, 2019.

D. A. Prasetya and E. F. Armay, “Resolving the Shortest Path Problem using the Haversine Algorithm,” J. Ilm. Teknol. dan Rekayasa, vol. 26, no. 1, pp. 73–80, 2021.

D. A. Prasetya, A. P. Sari, M. Idhom, and A. Lisanthoni, “Optimizing Clustering Analysis to Identify High-Potential Markets for Indonesian Tuber Exports,” Indones. J. Electron., Electromed. Eng. Med. Inform., vol. 7, no. 1, pp. 113–122, 2025.

A. Lisanthoni and D. A. Prasetya, “Optimizing Clustering Analysis to Identify High-Potential Markets for Indonesian Tuber Exports,” Indones. J. Electron., Electromed. Eng. Med. Inform., vol. 7, no. 1, pp. 113–122, 2025.

A. Muhaimin, “Implementasi MySQL untuk pengelolaan data besar dalam sistem informasi pertanian,” J. Teknol. Inf. dan Komput., vol. 7, no. 3, pp. 115–121, 2021.

S. S. M. Wara, “Predictive Analysis of Government Application Comment on Playstore with Clustered Support Vector Machine,” in Proc. IEEE 10th Inf. Technol. Int. Semin. (ITIS), 2024.

P. A. Riyantoko, “Optimizing User-PC Computing System with Multicore CPU Utilization through Parallel Computing Jobs Distributions,” in Proc. Semin. Nas. Teknol. Komput. dan Informatika (SENATIK), vol. 1, no. 1, pp. 101–106, 2023.

P. Damaliana, “Evaluasi model regresi menggunakan R-squared dan log-likelihood dalam analisis efisiensi produksi,” J. Ekon. Pertan., vol. 1, pp. 10–18, 2020.

M. Nasrudin, “Application of VAR-GARCH for Modeling the Causal Relationship of Stock Prices in the Mining Sub-sector,” J. Varian, vol. 8, no. 1, pp. 90–97, 2024.

A. Fakhri, “Penerapan Metode Variance Inflation Factor (VIF) untuk Mengatasi Multikolinearitas dalam Model Regresi,” J. Stat. dan Apl., vol. 4, no. 1, pp. 15–22, 2020.

M. Awangga and S. Adinugroho, “Evaluasi Kinerja Model Prediksi Harga Saham dengan Proporsi Data Latih dan Uji yang Berbeda,” J. Ilmu Komput. dan Agri-Informatika, vol. 5, no. 1, pp. 37–44, 2024.

S. Fitriani and A. Kurniawan, “Estimasi Parameter Model Regresi Logistik dengan Metode Maximum Likelihood Estimation (MLE),” J. Mat. dan Aplikasinya, vol. 7, no. 1, pp. 45–52, 2021.

R. Purnamasari and B. Kusuma, “Analisis Efisiensi Teknis Usahatani Padi Sawah di Kabupaten Subang Menggunakan Metode SFA,” J. Apl. Sist. Inf. dan Komput. (JASIEK), vol. 3, no. 2, pp. 112–121, 2022.

D. F. C. Kusuma, D. A. Prasetya, F. Kholid, and I. Mujahidin, “Evaluasi Database Senjata Untuk Sistem Keamanan Menggunakan Fuzzy Logic,” JASIEK, vol. 1, no. 2, 2019.

K. M. Hindrayani, “Penerapan Dashboard System (Pendapatan Asli Daerah (PAD) Sektor Pariwisata pada Kabupaten Mojokerto Menggunakan Tableau,” J. Comput. Sci. Technol. (JCS-TECH), vol. 4, no. 1, pp. 14–18, 2024.

A. Pramono, T. J. L. Tama, and T. Waluyo, “Analisis Arus Tiga Fasa Daya 197 KVA dengan Menggunakan Metode Uji Normalitas Kolmogorov-Smirnov,” J. RESISTOR (Rek. Sist. Komput.), vol. 4, no. 2, 2021.

E. P. Budiana, D. A. Himawanto, D. D. D. P. T., P. J. Widodo, and B. Suhardi, “Uji impak mesin heated die screw extruder pada pembriketan limbah pertanian,” INOTEKS: J. Inov. Ilmu Pengetah., Teknol., dan Seni, 2022.

V. Glinskiy et al., “Modifications to the Jarque–Bera Test,” Mathematics, vol. 12, 2024.

A. Fakhri, “Penerapan Metode Variance Inflation Factor (VIF) untuk Mengatasi Multikolinearitas dalam Model Regresi,” J. Stat. dan Apl., vol. 4, no. 1, pp. 15–22, 2020.

D. S. Nugroho and E. Prasetyo, “Analisis Efisiensi Teknis Produksi Jagung di Provinsi Jawa Tengah dengan Pendekatan Stochastic Frontier Analysis,” J. Ekon. Pertan. dan Agribisnis, vol. 6, no. 2, pp. 101–112, 2022.

I. G. Sedana and N. M. Yuliarmi, “Pengaruh Faktor-Faktor Produksi Terhadap Efisiensi Teknis Usahatani Cabai Merah di Bali: Aplikasi Stochastic Frontier Analysis,” J. Agribisnis dan Agrowisata, vol. 9, no. 1, pp. 1–10, 2020.

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Published

2025-06-30

How to Cite

[1]
I. W. Ningrum, Dwi Arman Prasetya, and Trimono, “Prediksi Hasil Produksi Beras di Kabupaten Lamongan Menggunakan Stochastic Frontier Analysis (SFA)”, JASIEK, vol. 7, no. 1, pp. 116–126, Jun. 2025.

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