ANALYSIS OF INDONESIA’S OIL PRODUCTION AND CONSUMPTION USING LAGRANGE POLYNOMIAL INTERPOLATION WITH MATLAB

Annisa Nur Azizah; Luluk Dwi Anggraini; Ari Wibowo

doi:10.36987/jpms.v12i2.9214

ANALYSIS OF INDONESIA’S OIL PRODUCTION AND CONSUMPTION USING LAGRANGE POLYNOMIAL INTERPOLATION WITH MATLAB

Annisa Nur Azizah, Luluk Dwi Anggraini, Ari Wibowo

Abstract

This study aims to examine patterns of oil production and consumption in Indonesia using the Lagrange polynomial interpolation method with the assistance of MATLAB R2025b software. The data used consists of secondary data on Indonesia’s oil production and consumption from Worldometer, covering the period 2016–2024. This study employs a quantitative approach using interpolation analysis techniques to estimate values at time points not available in the original data, thereby providing a more continuous picture of the data dynamics. The results show that the Lagrange polynomial interpolation method is capable of producing a smooth, continuous curve that passes through all observation points, thus providing a good level of approximation and closely matching actual values. The analysis shows that oil production in Indonesia tends to decline despite fluctuations in certain periods, specifically from 940,999 barrels per day in 2016 to 840,868 barrels per day in 2024 (a decrease of approximately 10.6%), while oil consumption shows an upward trend, rising from 1,527,215 barrels per day in 2016 to 1,626,878 barrels per day in 2024 (an increase of approximately 6.5%). Furthermore, oil consumption has consistently exceeded production, with the gap ranging from 517,691 barrels per day (2020) to 800,657 barrels per day (2018), indicating a gap between national energy needs and domestic production capacity. These findings indicate that the Lagrange polynomial interpolation method is effective in modeling numerical data and capable of providing an overview of the national energy situation, thereby serving as an analytical tool to support planning and policymaking in the energy sector.

Full Text:

PDF

References

S. Maarip, A. Hermansyah, S. N. Hadraeni, S. Miqdad, A. D. Nuryadin, and S. Yuliyanti, “Prediction of Life Expectancy in Indonesia by Implementing Website-Based Lagrange Polynomial Interpolation,” Int. J. Appl. Sci. Smart Technol., vol. 6, no. 2, pp. 393–406, 2024, doi: 10.24071/ijasst.v6i2.9167.

A. F. Sa’adah, A. Fauzi, and B. Juanda, “Peramalan Penyediaan dan Konsumsi Bahan Bakar Minyak Indonesia dengan Model Sistem Dinamik,” J. Ekon. dan Pembang. Indones., vol. 17, no. 2, pp. 118–137, 2017, doi: 10.21002/jepi.v17i2.02.

Worldometer, “Oil Product by Country (2024).” Accessed: Apr. 20, 2026. [Online]. Available: https://www.worldometers.info/oil/oil-production-by-country/

Worldometer, “Minyak Indonesia.” Accessed: Mar. 27, 2026. [Online]. Available: https://www.worldometers.info/id/minyak/minyak-indonesia/

O. of the P. E. Countries, “Indonesia Minyak Mentah: Impor,” CEIC Data. Accessed: Apr. 20, 2026. [Online]. Available: https://www.ceicdata.com/id/indicator/indonesia/crude-oil-imports

B. Ashar, “Analisis Perlambatan Produksi Minyak Bumi di Indonesia,” vol. IX, no. 2, pp. 414–429, 2026.

U.S. Energy Information Administration, “Country Analysis Brief: Indonesia,” Washington, 2025. [Online]. Available: https://www.eia.gov/beta/international/analysis_includes/countries_long/United_Arab_Emirates/uae.pdf

D. Darwin, I. M. J. A. Dwipatna, M. F. Ngoyo, A. Rahman, and H. Sumarwadji, “Implikasi Ekonomi dari Penurunan Produksi Minyak Mentah terhadap Kebutuhan Impor dan Defisit Energi (Analisis tren produksi dan ekspor-impor BBM),” J. Econ. Bussiness Manag. Issues, vol. 2, no. 4, pp. 415–426, 2025, doi: 10.47134/jebmi.v2i4.875.

Y. Furqaansyah, F. Fauziah, A. Gunaryati, and I. Fitri, “Perbandingan Metode Interpolasi Newton dan Lagrange dengan Bahasa Pemrograman C++,” J. JTIK (Jurnal Teknol. Inf. dan Komunikasi), vol. 6, no. 3, pp. 411–416, 2022, doi: 10.35870/jtik.v6i3.457.

I. K. S. Blegur, “Kajian Interpolasi Dua Dimensi dalam Tabel Nilai Kritik Sebaran F Berbantuan Program Matlab,” Fraktal J. Mat. dan Pendidik. Mat., vol. 2, no. 1, pp. 64–79, 2021, [Online]. Available: https://ejurnal.undana.ac.id/fraktal

M. Julian, L. Ambarwati, and Y. Mahatma, “Penentuan Derajat Optimum Interpolasi pada Metode Mengestimasi Kasus Pasien Sembuh dari Covid-19 di,” JMT (Jurnal Mat. dan Ter., vol. 4, no. 1, pp. 11–18, 2022.

M. Dolly Sianturi, M. Christyn Lubis, G. Triyunita Sinaga, and J. Nicholas Manihuruk, “Prediksi Pertumbuhan Jumlah Penduduk Indonesia Menggunakan Interpolasi Polinomial Lagrange,” J. Cendekia Ilm., vol. 4, no. 2, pp. 1315–1321, 2025.

D. Triana, A. Putri, A. Faradhilah, and Y. A. Sitorus, “Application of Lagrange Interpolation Method in Predicting the Number of HVS Orders in Printing,” Holist. Sci., vol. 4, no. 3, pp. 433–437, 2024, doi: 10.56495/hs.v4i3.791.

Santa Falare Sitanggang, Mikolis Etimanta Ginting, Valen Silvana Hasibuan, and Agnes Miranda Sitanggang, “Penerapan Metode Interpolasi Lagrange Untuk Meramalkan Jumlah Pelanggan Listrik Bulanan di PT PLN Tasikmalaya,” Konstanta J. Mat. dan Ilmu Pengetah. Alam, vol. 3, no. 1, pp. 127–136, 2025, doi: 10.59581/konstanta.v3i1.4856.

Ilmanita and H. Aimon, “Analisis Keseimbangan Jangka Pendek Dan Jangka Panjang Konsumsi Energi Di Indonesia,” J. Kaji. Ekon. dan Pembang., vol. 1, no. 3, p. 807, 2019, doi: 10.24036/jkep.v1i3.7708.

L. Zakaria and U. Muharramah, Pengantar Metode Numerik, Pertama. Lampung: CV. Anugrah Utama Raharja, 2023.

T. N. Hidayah, A. K. Nisa, and A. Wibowo, “Implementasi Polinomial Lagrange dalam Prediksi Jumlah Kelahiran di Indonesia Menggunakan Microsoft Excel,” Fermat J. Pendidik. Mat., vol. 8, no. 1, pp. 35–43, 2025.

N. N. Mansyur, Arman, L. Gubu, W. Somayasa, and Aswani, “Penerapan Metode Interpolasi Lagrange dalam Meramalkan Jumlah Pendapatan pada Percetakan (Studi Kasus: Gevira Advertising),” J. Mat. Komputasi dan Stat., vol. 4, no. April, pp. 540–546, 2024.

P. S. A. Soko, R. Renata, A. Ilhamzah, R. E. Standsyah, and D. Savitri, “Prediksi Tingkat Pengangguran Terbuka di Indonesia Menggunakan Metode Numerik Ekstrapolasi Berbasis Python,” J. Unitomo, vol. 14, no. 1, pp. 95–110, 2026.

Roziqin, “Post-reform oil sector management in indonesia: analysis of public welfare concept,” J. Tata Kelola Akuntabilitas Keuang. Negara, vol. 1, no. 2, pp. 128–140, 2015.

M. F. Aprizal, B. Juanda, A. Ratnawati, and A. Muin, “Indonesian Upstream Oil & Gas Governance for Sustainable Innovation,” J. Manaj. dan Organ., vol. 13, no. 1, pp. 48–60, 2022, doi: 10.29244/jmo.v13i1.40427.

H. Wahyudi, “Peramalan Konsumsi dan Produksi Minyak Menggunakan Model ARIMA di Indonesia,” J. Ekon. Pembang., vol. 19, no. 1, pp. 44–56, 2023.

B. P. Putra and B. F. T. Kiono, “Mengenal Enhanced Oil Recovery (EOR) Sebagai Solusi Meningkatkan Produksi Minyak Indonesia,” J. Energi Baru dan Terbarukan, vol. 2, no. 2, pp. 84–100, 2021, doi: 10.14710/jebt.2021.11152.

B. P.Manohara and T. Suprajogo, “Implementasi Kebijakan Transisi Energi di Indonesia , Tantangan dan Strategi Menuju NZE 2060,” J. Sos. Hum. dan Pendidik., vol. 5, no. 1, pp. 5582–596, 2026.

DOI: https://doi.org/10.36987/jpms.v12i2.9214