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All Journal BAREKENG: Jurnal Ilmu Matematika dan Terapan Contemporary Mathematics and Applications (ConMathA) Jurnal Statistika dan Komputasi (STATKOM)
Fitri, Marfa Audilla
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Energy Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Social Sciences Transportation

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Pemodelan Indeks Kualitas Lingkungan Hidup di Indonesia dengan Spline Truncated dan MARS Fitri, Marfa Audilla; Suliyanto, Suliyanto; Mardianto, M Fariz Fadillah; Ana, Elly
Jurnal Statistika dan Komputasi Vol. 4 No. 1 (2025): Jurnal Statistika dan Komputasi
Publisher : Universitas Nahdlatul Ulama Sunan Giri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32665/statkom.v4i1.4394

Abstract

Background: Indonesia, endowed with abundant natural resources, faces substantial challenges in maintaining environmental quality amid rapid urbanization and economic growth. The 2022 Environmental Performance Index ranked Indonesia 164th out of 180 countries with a score of 28.2. Regionally, Indonesia ranked 22nd among 25 Asia-Pacific countries. The Environmental Quality Index (EQI), crucial for achieving the Sustainable Development Goals (SDGs), was recorded at 72.42 in 2022, classified as "fair." This condition underscores the need for in-depth analysis of key factors influencing environmental quality. Objective: This study aims to examine significant factors affecting the Environmental Quality Index (EQI) across Indonesian provinces using appropriate nonparametric statistical methods. Methods: A nonparametric regression approach, specifically the Multivariate Adaptive Regression Spline (MARS) and the truncated spline multipredictor model, was applied. Predictor variables included the Human Development Index (HDI), population density, access to proper sanitation, poverty rate, and Gross Regional Domestic Product (GRDP). Secondary data for 34 provinces in 2022 were sourced from the Central Bureau of Statistics and the Ministry of Environment. Results: The truncated spline model demonstrated superior performance, achieving a minimal MSE of 5.63308, minimal GCV of 10.42, and R2  of 82.63%, outperforming MARS, which yielded a minimal MSE of 7.685, GCV of 16.014, and R2 of 79.3%. All predictor variables significantly influenced EQI. Conclusion: Social and economic factors were found to significantly affect environmental quality. The truncated spline approach offers an effective modeling alternative, providing critical insights to support environmental policy development at the provincial level.
MODELING LONGITUDINAL FLOOD DATA IN WEST SUMATRA USING THE GENERALIZED ESTIMATING EQUATION (GEE) APPROACH Nitasari, Alfi Nur; Sa'idah, Andini; Faizun, Nurin; Darmawan, Kezia Eunike; Fitri, Marfa Audilla; Chamidah, Nur
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 4 (2024): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol18iss4pp2181-2190

Abstract

Flooding is one of the many natural disasters that often hit Indonesia. In July 2023, three areas in West Sumatra experienced floods and landslides which caused damages and even 2 missing victims. Since November 16th, 2023, 8 hamlets in Meranti Village, Landak District, West Sumatra have been inundated by floods which affected families and many public facilities. This research uses data from West Sumatra Province Central Statistics Agency. The data used is 2014, 2018 and 2021. The response variable used is the number of villages/sub-districts experiencing natural disasters according to district/city ( ). The predictor variables used are regional topography , the number of water channels such as rivers, reservoirs, etc. , the number of fields cleared through burning , the number of villages/sub-districts in C excavation area , and the number of dumpsters . This research uses Negative Binomial Regression with the Generalized Estimating Equation (GEE) approach. In the Poisson regression test, the QIC value based on Independent Working Correlation Structure (WCS) is with deviance value of , degree of freedom of , and dispersion score of 4,6144. Because the dispersion value is greater than 1, it can be concluded that there is overdispersion. Because there is more than one overdispersion, it is overcome by using negative binomial. The results of parameter estimation using negative binomial regression based on Independent WCS showed that only one variable was significant, which is the number of fields cleared through burning with deviance value of , degrees of freedom of and a QIC of . Negative Binomial regression model that was formed is ). From the two regression models used, namely Poisson and negative binomial, it was found that the negative binomial regression model was the best model because it had the lowest QIC value of .
Prediksi Inflasi, Tingkat Suku Bunga, dan Nilai Ekspor dengan Vector Autoregressive dan Estimator Deret Fourier Simultan Lu'lu'a, Na'imatul; Haq, Affan Fayzul; Fitri, Marfa Audilla; Mardianto, M. Fariz Fadillah; Pusporani, Elly
Contemporary Mathematics and Applications (ConMathA) Vol. 6 No. 1 (2024)
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/conmatha.v6i1.54128

Abstract

In the face of global economic uncertainty, predictions of the value of inflation, interest rates, and the value of exports are becoming increasingly crucial. This is also closely related to the SDGs in goals 8 and 9, namely on Decent Work and Economic Growth as well as Industry, Innovation, and Infrastructure. This study discusses the use of Vector Autoregressive (VAR) methods and Fourier series estimators to improve the accuracy of predictions of these economic variables. The data used are the inflation, export value, and BI Rate sourced from Bank Indonesia and Badan Pusat Statistik with a monthly period and starting from the beginning of 2010 to September 2023. After analysis, the best method was obtained, namely the Fourier series estimator which included cosine and sine components with oscillation parameters 6 with MAPE 1.51% on the inflation value, 1.65% on the interest rate, and 3.03% on the export value. By considering the interaction between economic variables, the prediction results are expected to provide deeper understanding, support decision-making at the macroeconomic level, and assist governments, central banks, and market participants in identifying risks and planning export strategies.
Co-Authors Darmawan, Kezia Eunike Elly Ana Elly Pusporani Faizun, Nurin Haq, Affan Fayzul Lu'lu'a, Na'imatul M. Fariz Fadillah Mardianto Nitasari, Alfi Nur Nur Chamidah Sa'idah, Andini Suliyanto Suliyanto