Contribution Analysis of “Suroboyo Bus” in Waste Management Based on Two Form of Complete Fourier Series Estimator
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.
Central Bureau of Statistic Indonesia and Ministry of Environment Indonesia, Environment Statistics of Indonesia, Jakarta: Central Bureau of Statistic, 2018
Kurniawan, A.A., & Prabawati, I, Implementasi Suroboyo Bus di Dinas Perhubungan Kota Surabaya. Publika Jurnal Ilmu Administrasi Negara, vol. 6, no. 9, 2018
Haqie, Z.A, Nadiah, R.E, Ariyani, O.P, Inovasi Pelayanan Publik Suroboyo Bis Di Kota Surabaya, Journal of Public Sector Innovations, Vol. 5, no. 1, pp.23-30, 2020
Eubank, R.L, Nonparametric Regression and Spline Smoothing 2nd Edition, New York: Marcel Dekker, 1998
Takezawa, K, Introduction to Nonparametric Regression. John Wiley and Sons Inc. New Jersey, United State of America, 2006
Hardle, W, Applied Nonparametric Regression, New York: Cambridge University Press, 1990
Mardianto, M.F.F., Kartiko, S.H., & Utami, H, Forecasting Trend-Seasonal Data Using Nonparametric Regression with Kernel and Fourier series Approach, Proceedings of the Third International Conference on Computing, Mathematics and Statistics (iCMS2017), pp. 343-349, 2019
Suslov, S.K, An Introduction to Basic Fourier Series, Arizona: Springer Science, 2003
Biedermann, S., Dette, H., & Hoffmann, P, “Constrained Optimal Discrimination Designs for Fourier Regression Models”, Ann Inst Stat Math Journal, vol. 61, no. 2, pp. 143-157, 2009
Bilodeau, M, “Fourier Smoother and Additive Models”. Canadian Journal of Statistics, vol. 20, no. 3, pp. 257-269, 1992
Mardianto, M.F.F., Kartiko, S.H, Utami, H, Regression for Trend-Seasonal Longitudinal Data Pattern: Linear and Fourier Series Estimator, International Conference on Mathematics and Islam, vol. 1, pp. 350-356, 2018
Mardianto, M.F.F., Kartiko, S.H, Utami, H, Prediction the Number of Students in Indonesia who Study in Tutoring Agency and Their Motivations based on Fourier Series Estimator and Structural Equation Modelling, International Journal of Innovation, Creativity, and Change (IJICC), vol. 5, no. 3, pp. 708-731, 2019
Ulyah, S.M, Mardianto, M.F.F., Sediono, Comparing the Performance of Seasonal ARIMAX Model and Nonparametric Regression Model in Predicting Claim Reserve of Education Insurance. Journal of Physics: Conference Series 1397 012074, pp. 1-13, 2019
Mardianto, M.F.F., Tjahjono, E, Rifada, M, Statistical Modelling for Prediction of Rice Production in Indonesia Using Semiparametric Regression Based on Three Forms of Fourier Series Estimator, ARPN Journal of Engineering and Applied Science, vol. 14, pp. 2763-70, 2019
Mardianto, M.F.F., Tjahjono, E, Rifada, M, Semiparametric Regression Based On Three Forms Of Trigonometric Function In Fourier Series Estimator, Journal of Physics: Conference Series 1277 012052 pp. 1-10, 2019
Mardianto, M.F.F., Tjahjono, E, Syarifah, L, Andirani, P, Prediction of the Number of Foreign Tourist Arrival in Indonesia Halal Tourism Entrance using Simultaneously Fourier Series Estimator, KnE Social Sciences, pp. 1093-1104, 2019
Mardianto, M.F.F, Semiparametric Regression Based On Fourier Series For Longitudinal Data With Weighted Least Square (WLS) Optimization, Journal of Physics: Conference Series 1836 012038, pp. 1-10, 2021
Mardianto, M.F.F., Tjahjono, E, Rifada, M, Herawanto, A, Putra, A.L, Utama, K.A, The Prediction of Rice Production in Indonesia Provinces for Developing Sustainable Agriculture, Proceeding of the International Conference on Food and Agriculture,Vol.1.pp. 325-333, 2018
Mardianto, M.F.F., Kartiko, H.S., & Utami, H, The Fourier Series Estimator To Predict The Number Of Dengue And Malaria Sufferers In Indonesia, AIP Conference Proceedings 2329 060002, 2021
Mardianto, M.F.F., Sediono, Safitri, S.A.D, Afifah, N, Syahzaqi, I, The Prediction of Indonesia Strategic Commodity Prices during the COVID-19 Pandemic based on a Simultaneous Comparison of Kernel and Fourier Series Estimator, Journal of Southwest Jiaotong University, Vol. 55, no. 6, pp.325-333, 2020
Copyright (c) 2021 M. Fariz Fadillah Mardianto, Reynaldy Aries Ariyanto, Raka Andriawan, Devayanti Anugerahing Husada
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work