The Fourier series estimator to predict the number of dengue and malaria sufferers in Indonesia

Mardianto, M. Fariz Fadillah; Kartiko, Sri Haryatmi; Utami, Herni

doi:10.1063/5.0042115

Cited by 7 publications

(8 citation statements)

References 13 publications

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“…Untuk memperoleh parameter osilasi optimal dapat dilihat dari nilai GCV yang paling minimum. Metode GCV secara umum didefinisikan sebagai berikut [8].…”

Section: E Pemilihan Parameter Osilasiunclassified

“…Dalam hal ini, proses prediksi harga ekspor non migas dapat dilakukan dengan membandingkan metode time series klasik dan modern. Pada analisis time series klasik, metode prediksi yang dapat digunakan adalah estimator deret Fourier yang termasuk dalam metode nonparameterik [8]. Metode estimator deret Fourier dipilih karena memiliki fleksibilitas dalam memodelkan pola data yang bentuk osilasinya tidak diketahui [8].…”

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“…Pada analisis time series klasik, metode prediksi yang dapat digunakan adalah estimator deret Fourier yang termasuk dalam metode nonparameterik [8]. Metode estimator deret Fourier dipilih karena memiliki fleksibilitas dalam memodelkan pola data yang bentuk osilasinya tidak diketahui [8]. Pada analisis time series modern, metode prediksi yang digunakan adalah Support Vector Regression (SVR).…”

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Prediksi Harga Ekspor Non Migas di Indonesia Berdasarkan Metode Estimator Deret Fourier dan Support Vector Regression

et al. 2023

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Pertumbuhan ekonomi merupakan salah satu indikator dalam Sustainable Development Goals (SDGs) pada peningkatan kegiatan ekonomi. Salah satu kegiatan yang menopang berjalannya perekonomian adalah perdagangan antar negara, seperti ekspor. Di Indonesia, ekspor non migas memegang peranan penting dalam total ekspor beberapa tahun terakhir, diantaranya ekspor batu bara menjadi ekspor utama. Oleh karena itu, prediksi harga ekspor non migas Indonesia menjadi sangat penting sebagai bahan evaluasi kebijakan untuk mendorong pertumbuhan ekonomi. Hal tersebut menjadi fokus utama dari penelitian ini. Dalam studi ini, prakiraan harga ekspor non migas dibuat dengan mempertimbangkan isu-isu terkini seperti pandemi COVID-19 dan perang Rusia-Ukraina. Keakuratan model yang diperoleh dari estimator deret Fourier dan Support Vector Regression (SVR) diselidiki dengan membandingkan nilai Mean Absolute Percentage Error (MAPE) untuk memprediksi harga ekspor non migas Indonesia. Hasil penelitian menunjukkan bahwa masalah pandemi COVID-19 dan perang Rusia-Ukraina berdampak signifikan terhadap harga ekspor non migas. Model SVR dengan kernel Radial Basis Function (RBF) menunjukkan akurasi yang lebih baik daripada model estimator deret Fourier fungsi cos sin, dengan masing-masing nilai MAPE sebesar 9,29 dan 15,26% untuk setiap data uji. Oleh karena itu, kajian ini diharapkan dapat menjadi dasar untuk merumuskan kebijakan terkait pengaturan proses ekspor non migas untuk mendukung pertumbuhan ekonomi di Indonesia. Kata kunci⎯ ekspor, non migas, estimator deret Fourier, support vector regression, radial basis function.ABSTRACT ⎯ Economic growth is one of the indicators in the Sustainable Development Goals (SDGs) on increasing economic activity. One of the activities that supports the running of the economy is trade between countries, such as exports. In Indonesia, non-oil and gas exports have played an important role in total exports in recent years, including coal exports being the main export. Therefore, price predictions for Indonesia's non-oil and gas exports are very important as material for evaluating policies to encourage economic growth. This is the main focus of this research. In this study, non-oil and gas export price forecasts are made taking into account current issues such as the COVID-19 pandemic and the Russia-Ukraine war. The accuracy of the model obtained from the Fourier series estimator and Support Vector Regression (SVR) is investigated by comparing the Mean Absolute Percentage Error (MAPE) value to predict Indonesia's non-oil and gas export prices. The results of the study show that the COVID-19 pandemic and the Russia-Ukraine war have had a significant impact on non-oil and gas export prices. The SVR model with the Radial Basis Function (RBF) kernel shows better accuracy than the Fourier series estimator model of the cos sin function, with MAPE values of 9.29 and 15.26% for each test data, respectively. Therefore, this study is expected to be the basis for formulating policies related to regulating non-oil and gas export p...

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“…Untuk memperoleh parameter osilasi optimal dapat dilihat dari nilai GCV yang paling minimum. Metode GCV secara umum didefinisikan sebagai berikut [8].…”

Section: E Pemilihan Parameter Osilasiunclassified

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Prediksi Harga Ekspor Non Migas di Indonesia Berdasarkan Metode Estimator Deret Fourier dan Support Vector Regression

et al. 2023

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“…The goodness of model also can be measured by the determination coefficient (R 2 ). The determination coefficients determine how much influence between independent variable and dependent variable [19]. Formula of R 2 can be written…”

Section: Measure Of Goodness Of Modelmentioning

confidence: 99%

“…The procedure in data analysis that is related to estimation contribution of Suroboyo bus with nonparametric regression used complete Fourier series estimator for both models from equation (7), and equation (19) was given as follows: a. Study literature related to the contribution of Suroboyo bus and its relationship to the related predictor variables.…”

Section: Data Analysis Proceduresmentioning

confidence: 99%

Contribution Analysis of “Suroboyo Bus” in Waste Management Based on Two Form of Complete Fourier Series Estimator

et al. 2021

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Plastic waste is a problem that almost exists in all countries. This problem arises because of the lack of facilities that can handle the plastic waste. Suroboyo Bus is an innovation for this problem because Suroboyo Bus uses plastic bottles as payment. The purpose of this research is to predict the percentage contribution of Suroboyo Bus in handling plastic waste. The Fourier series estimator performs well for data modeling with seasonal trend patterns. This paper examines two approaches to the Fourier series. The difference between the approaches is the inclusion of the phi (π) function in the model. The result shows the goodness of fit criterion model with π function are for and 0,08% for MAPE whereas the fit criterion model without π function is 100% for and 0,07% for MAPE. In conclusion, the Fourier series model without the π function is better because the Fourier series model without the π function is more satisfy the goodness of fit criteria than the Fourier series model with the π.

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Modelling and forecasting high-frequency data with jumps based on a hybrid nonparametric regression and LSTM model

Song,

Cai,

et al. 2024

Expert Systems with Applications

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The Fourier series estimator to predict the number of dengue and malaria sufferers in Indonesia

Cited by 7 publications

References 13 publications

Prediksi Harga Ekspor Non Migas di Indonesia Berdasarkan Metode Estimator Deret Fourier dan Support Vector Regression

Prediksi Harga Ekspor Non Migas di Indonesia Berdasarkan Metode Estimator Deret Fourier dan Support Vector Regression

Contribution Analysis of “Suroboyo Bus” in Waste Management Based on Two Form of Complete Fourier Series Estimator

Modelling and forecasting high-frequency data with jumps based on a hybrid nonparametric regression and LSTM model

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