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All Journal Jurnal Matematika BAREKENG: Jurnal Ilmu Matematika dan Terapan JOURNAL OF APPLIED INFORMATICS AND COMPUTING Jurnal Cahaya Mandalika Innovative: Journal Of Social Science Research International Journal of Health and Medicine
I WAYAN SUMARJAYA
Faculty of Mathematics and Natural Sciences, Udayana University
Humanities Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Energy Engineering Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Mechanical Engineering Medicine & Pharmacology Physics Public Health Transportation Other

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Journal : Jurnal Matematika

 1 
Forecasting Monthly Inflation Rate in Denpasar Using Long Short-Term Memory Sumarjaya, I Wayan; Susilawati, Made
Jurnal Matematika Vol 13 No 1 (2023)
Publisher : Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JMAT.2023.v13.i01.p157

Abstract

One of indicators of economic stability of a country is controlled inflation. In general, inflation provides information about the rise of goods and services in a region within certain period which has strongly related with people’s ability to purchase. The Covid-19 pandemic has affected almost any sectors especially the consumer price in-dex. Bali, as a major tourist destination in Indonesia, has severely affected by the pandemic. Information about future inflation rate plays important role in determining the correct decision regarding economic policy. The aim of this research is to fore-cast inflation rate in Denpasar using deep learning method for time series. Deep learning, a part of machine learning, consists of layers of neurons that are designed to learn complex patterns and is able to make forecasting. In this research we de-ployed a special type of recurrent neural networks called long-short term memory (LSTM) that is suitable for use in time series analysis. We stacked the networks into two, three, and four layers to add capacity and to build deep networks for inflation rate series. A grid search for each layer is conducted to obtain optimal hyperparame-ters setting. We conclude that the optimum architecture for setting for this deep net-work is stacked two LSTM layers. The monthly inflation rate forecasts suggest the in-flation for 2022 fluctuates, but below one percent.
A Comparative Analysis of Deep Autoregressive, Deep State Space, Simple Feed Forward, and Seasonal Naive in Forecasting Indonesia’s Inflation Rate Sumarjaya, I Wayan; Susilawati, Made
Jurnal Matematika Vol 14 No 1 (2024)
Publisher : Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JMAT.2024.v14.i01.p170

Abstract

Information about inflation plays important role in economic policy. The government of the Republic Indonesia has put a great deal of effort to control inflation rate. The aims of this research are to forecast Indonesia’s inflation rate using deep auto-regressive networks and to compare it with other models such as deep state space, simple feed forward, and naïve seasonal. In this study we compare eighteen deep au-toregressive networks. Each model differs only in its hyperparameters settings such as the number of epochs, the number of layers, the number of cells, and the number of batch sizes. In order to check for consistency each model is replicated ten times. In total there are 180 runs for each of configuration including the replication. The results show that the deep autoregressive model with 50 epochs, 4 layers, 40 cells, 32 batch sizes produces the smallest root mean squared error at 0.218565. This root mean squared error also the smallest among the other models such as deep state space (0.28734), simple feed forward (0.350449), and naïve seasonal (0.336056). In conclusion, the median forecasts fluctuates but below 1 percent.
Co-Authors Ali, Fauzi Wardah Candrasuari, Ni Luh Putu Diah Ayu Diva, Made Tresia Pramasta Kartika Sari Kencana, Eka N. Made Susilawati Ni Luh Putu Suciptawati Nilakusmawati, DPE Octavanny, Made Ayu Dwi Pramesti, Ni Kadek Lia Cahyani Putri, Made Ayu Asri Oktarini Srinadi, IGAM Suciptawati, NLP TRESNAWARDANI, NI PANDE LUH Widiastuti, Ratna Sari Wijayakusuma, I Gusti Ngurah Lanang