ARIMA Modeling for Forecasting Indonesia’s Per Capita CO2 Emissions and Literature Study of Photobioreactor-Based Mitigation

  • Henny Syahrani Politeknik Statistika STIS
  • Fadli Ardiansyah Politeknik Statistika STIS
  • Nabila Nur Faiza Politeknik Statistika STIS
  • Samuel Kevin Politeknik Statistika STIS
  • Neli Agustina Politeknik Statistika STIS
Keywords: CO2 Emissions, Forecasting, ARIMA, Microalgae Photobioreactor, Climate Change Mitigation

Abstract

Increasing  CO2 emissions from fossil fuels, industrial activities, and transportation drives climate change. Although Indonesia has committed to reducing emissions by 29% unconditionally and up to 43% with international support by 2030 through its Nationally Determined Contribution, per capita  emissions rise. This study forecasts Indonesia’s per capita CO2 emissions using ARIMA based on data from 1950-2024 from Our World in Data. Data from 1950-2009 served as training and 2010-2024 as testing. The Augmented Dickey-Fuller test indicated non-stationarity at level and stationarity after first differencing. ARIMA(0,1,10) was selected based on the lowest AIC and SC, highest adjusted R², and satisfactory diagnostics. MAPE was 13.19%. Forecasts for 2025-2030 show emissions increasing from 2.95 to 3.75 tons per capita. The study evaluates IMC-PBR, which removes atmospheric  through photosynthesis while generating biomass.

References

Antoniadis, A. (2007). Wavelet methods in statistics: Some recent developments and their applications. Statistics Surveys, 1. https://doi.org/10.1214/07-SS014

Anugrah Putra, M., & Andryana, S. (2025). Perbandingan algoritma ARIMA dan LSTM dalam peramalan tingkat konsentrasi CO2 emisi atmosfer untuk masa mendatang. JATI (Jurnal Mahasiswa Teknik Informatika), 9(3), 4150–4157. https://doi.org/10.36040/jati.v9i3.13511

Bain, L. J., & Engelhardt, M. (1992). Introduction to probability and mathematical statistics (2nd ed.). Duxbury Press.

Box, G. E. P., Jenkins, G. M., Reinsel, G. C., & Ljung, G. M. (2016). Time series analysis: Forecasting and control

(5th ed.). Wiley.

Cahyadi, N. H., Solakhudin, M. R., & Nastiti, V. (2023). MAFLEXTOR (Smart and Flexible Photobioreaktor): Inovasi kultivasi mikroalga dilengkapi panel surya berbasis IoT guna mewujudkan sustainable environment di Indonesia. EnviroUS, 3(2), 104–109. https://doi.org/10.33005/envirous.v3i2.24

Dębowski, M., Krzemieniewski, M., Zieliński, M., & Kazimierowicz, J. (2021). Immobilized microalgae-based photobioreactor for CO2 capture (IMC-CO2PBR): Efficiency estimation, technological parameters, and prototype concept. Atmosphere, 12(8), 1031. https://doi.org/10.3390/atmos12081031

Fardana, M. H., Saputra, W. S. J., & Prami, M. H. (2025). Algoritma hibrida LSTM dan ARIMA. JITET (Jurnal Informatika dan Teknik Elektro Terapan), 13(3).

Giesecke, K. (2004). Credit risk modeling and valuation: An introduction. In Credit risk: Models and management

(Vol. 2). Cornell University.

Hyndman, R. J., & Athanasopoulos, G. (2021). Forecasting: Principles and practice (3rd ed.). OTexts. https://otexts.com/fpp3/

Jannah, N., & Hasanah, A. (2025). Peramalan persentase penduduk miskin (PPM) di Kabupaten Pamekasan menggunakan model statistik time series dengan metode Autoregressive Integrated Moving Average (ARIMA). Alpha Epsilon Journal (AEJ), 1(2), 10–18.

Khikmah, K. N., & Sofro, A. (2025). Perbandingan kinerja model ARIMA dan LSTM untuk peramalan curah hujan di Kalimantan Tengah. Jurnal Riset dan Aplikasi Matematika (JRAM), 9(2), 199–207. https://journal.unesa.ac.id/index.php/jram/article/view/42301

Musiela, M., & Rutkowski, M. (2004). Martingale methods in financial modelling (Stochastic Modelling and Applied Probability) (2nd ed.). Springer.

Pramita, A., Kholisoh, N., & Lusia, R. A. (2023). Prediksi emisi gas rumah kaca pada sektor energi di Indonesia menggunakan model ARIMA. Jurnal Fraction, 3(2), 63–70.

Rahardjo, S. (2003). Panduan investasi obligasi. PT Gramedia Pustaka Utama. Ross, S. M. (1997). Introduction to probability models (6th ed.). Academic Press.

Ubaidillah, M. F., Prasetya, S., & Reviansyah, A. F. (2025). Otomasi fotobioreaktor mikroalga berbasis mikrokontroler untuk fiksasi emisi vent stack amine regenerator, 649–657.

Walpole, R. E., & Myers, R. H. (1995). Ilmu peluang dan statistika untuk insinyur dan ilmuwan (R. K. Sembiring, Terj.). Penerbit ITB.

Published
2026-09-27
How to Cite
Syahrani, H., Ardiansyah, F., Faiza, N. N., Kevin, S., & Agustina, N. (2026). ARIMA Modeling for Forecasting Indonesia’s Per Capita CO2 Emissions and Literature Study of Photobioreactor-Based Mitigation. VARIANSI: Journal of Statistics and Its Application on Teaching and Research, 8(02), 188-197. https://doi.org/10.35580/variansiunm650
Section
Articles