Analysis of temperature patterns in Pekanbaru City using fractals and artificial neural networks based on monthly temperature data

Reynal Nur Razzaq, Defrianto Defrianto

Abstract


Climate and global warming play a crucial role in the lives of living organisms on Earth. Temperature, varying in each region, is a vital aspect in climate observation. This study analyzed temperature fluctuations in Pekanbaru from 2016 to 2022 using fractal analysis and Backpropagation artificial neural networks. The research findings revealed that temperature prediction with Backpropagation artificial neural networks was quite accurate. However, errors during testing or validation could impact the comparison with the target values. Fractal analysis indicated a persistence tendency in temperature fluctuations in Pekanbaru, with a Hurst exponent of 0.7993 and a fractal dimension of 1.2007. Nevertheless, temperature fluctuations were also influenced by other factors, leading to varying levels of stability over certain periods. Thus, temperature in Pekanbaru can be considered a complex system with diverse fluctuation patterns and varying levels of complexity.


Keywords


Artificial Neural Network; Backpropagation; Exponent Hurst; Fluctuation; Fractal Dimension; Temperature

References


Ance Gunarsih Kartasapoetra. 2017. Klimatologi: pengaruh iklim terhadap tanah dan tanaman. Jakarta: Bumi Aksara.

Bakhrun, A. 2013. Perbandingan Metode Adaline dan Backpropagation untuk Prediksi Jumlah Pencari Kerja di Jawa Barat. Diploma thesis, Universitas Komputer Indonesia.

Barnsley, Michael F. 1993. Fractal Everywhere. Academic Press Proffesional. United States of America.

Barbulescu, A., Serban, C., Maflei, C. 2007. Evaluation of exponent for precipitation time series, latest trend on computers. 2:590-595.

Boer, Rizaldi dan Perdinan. 2008. Adaptation to climate variability and climate change: Its socio-economic aspect. Paper presented at the

EEPSEA Conference on Climate Change: Impacts, Adaptation, And Policy In South East Asia With A Focus On Economics, Socio-Economics And Institutional Aspects. Bali.

BöHm, R., Auera,I.,Brunettib,M., Maugeric, M., Nannib, T., and Schoner,W., 2001,Regional Temperature Variability In The European Alps: 1760–1998 From Homogenized Instrumental Time Series,International Journal Of Climatology, Vol.21, Hal : 1779–1801.

Chen, Y., Li, Y., & Mao, L. 2022. Combining the Effects of Global Warming, Land Use Change and Dispersal Limitations to Predict the Future Distributions of East Asian Cerris Oaks (Quercus Section Cerris, Fagaceae) in China, Environmental Science, Forests.

Barbulescu, A., Serban, C., Maflei, C. 2007. Evaluation of exponent for precipitation time series, latest trend on computers.

Cahyono, B. 2013. Penggunaan Software Matrix Laboratory (Matlab) dalam Pembelajaran Aljabar Linier.

Diyah Puspitaningrum. 2006. Pengantar Jaringan Syaraf Tiruan. Yogyakarta: Andi.

Dwi Efri Rufiyanti, 2015. Implementasi Jaringan Syaraf Tiruan Backpropagation Dengan Input Model Arima Untuk Peramalan Harga Saham, Universitas Negeri Semarang.

Hermawan, E., 2010, Pengelompokkan Pola Curah Hujan Yang Terjadi Di Beberapa Kawasan P. Sumatera Berbasis Hasil Analisis Teknik Spektral, Jurnal Meteorologi Dan Geofisika, Vol.11, No.2, Hal: 75 –84.

Hidayat, U.A., Prasetyo, S., Donni Haryanto, Y., & Florida Riama, N. 2022, Pengaruh ENSO Terhadap Curah Hujan dan Kelembapan Relatif serta Suhu Permukaan Laut di Sulawesi. Buletin GAW Bariri.

Koutsoyiannis, D. (2021). Rethinking Climate, Climate Change, and Their Relationship with Water. Water.

Lakitan, 2002. Pengukuran Kadar Gas Pencemar Nitrogen Dioksida (NO2) di Udara Sekitar Kawasan Industri Medan. Medan: Universitas Sumatera Utara.

Mandelbrot, B. 1983. The Fractal Geometry of Nature. New York: W. H Freeman and Company.

Prawaka F., Zakaria A., Tugiono S. 2016. Analisis Data Curah Hujan yang Hilang dengan Menggunakan Metode Normal Ratio, Inversed Square Distance, dan Rata-Rata Aljabar (Studi Kasus Curah Hujan Beberapa Stasiun Hujan Daerah Bandar Lampung). JRSDD

Priyanta, I.B., & Astawa, I.N. 2014. Penerapan Jaringan Syaraf Tiruan Dalam Prakiraan Hujan Harian di Daerah Kuta Selatan Provinsi Bali.

Rangarajan, G., dan Sant, D. 2004. A climate predictability index and its application. Geophysical reseach letter. 24:1239-1242.

Rosalina 2012. Keterkaitan Perubahan Iklim dan Produksi Pangan Strategis. Telaah Kebijakan Independen Bidang Perdagangan dan Pembangunan Oleh Kemitraan/Partnership Indonesia. Seameo Biotrop. Bogor

Sekawati, L. 2013. Teknik Penggambaran dan Cinta Alamiah Berbasis Dimensi Fraktal. Makalah IF2120 Matematika Diskrit-sem 1 2012/2013. Bandung: Institut Teknologi Bandung.

Selvi, S., Tamil., selvaraj, R., Samuel. 2011. Fractal dimension analysis of northeast monsoon of tamil nadu. Universitas journal of environtmental research and technology. 1(2):219-221.

Tamarin-Brodsky, T., Hodges, K.I., Hoskins, B.J., & Shepherd, T.G. ,2019. A Dynamical Perspective on Atmospheric Temperature Variability and Its Response to Climate Change. Journal of Climate.

Tjasyono, B. H. K dan Harijono, S. W. B. 2006.Meteorologi Indonesia 2: Awan dan Hujan Monsun, Badan Meteorologi Klimatologi dan Geofisika, Jakarta.

Tyagi, H. 2016. Weather-Temperature Pattern Prediction and Anomaly Identification using Artificial Neural Network. In International Journal of Computer Applications (Vol. 140, Issue 3).

Vos, J. A., dkk. 1985. Raising surface water levels in peat areas with dairy farming upscaling hydrological, agronomical, and economic effects from farm-scale to local scale. Agricultural water management 97:1887-1897.

Wirjomiharjo dan Swarinoto. 2007. Evaluasi Kehandalan Simulasi

Informasi Prakiraan Iklim Musiman Menggunakan Metode ROC. Jakarta: Bidang Klimatologi Badan Meteorologi Klimatologi dan Geofisika (BMKG)

.

Yunita., 2015. Prediksi Cuaca Menggunakan Metode Neural Nerwork.Vol. 12.




DOI: http://dx.doi.org/10.31258/jkfi.21.1.%25p

Refbacks

  • There are currently no refbacks.


Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

Indexing by:

  

 

Image