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All Journal Indonesian Council of Premier Statistical Science Parameter: Jurnal Matematika, Statistika dan Terapannya
Iva Aurellia Khalif
Universitas Muhammadiyah Semarang
Computer Science & IT Economics, Econometrics & Finance Mathematics Public Health Social Sciences

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Analysis of Passenger Flight Distance as an Indicator of Economic Activity Ihsan Fathoni Amri; Suci Izzati; Rendi Andika Putra; Iva Aurellia Khalif; Febryana Dilla Setyaningrum; Isnaini Maulida; M. Al Haris
Parameter: Jurnal Matematika, Statistika dan Terapannya Vol 5 No 1 (2026): Parameter: Jurnal Matematika, Statistika dan Terapannya
Publisher : Jurusan Matematika FMIPA Universitas Pattimura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/parameterv5i1pp111-124

Abstract

Understanding macroeconomic dynamics in the United States requires advanced forecasting techniques capable of capturing both seasonal structures and external shocks. This study investigates the relationship between passenger flight distance and the unemployment rate through the implementation of the Seasonal Autoregressive Integrated Moving Average with Exogenous Variables (SARIMAX) model—an enhancement of the SARIMA framework. While SARIMA accounts for autoregressive, differencing, and moving average components with seasonal integration, SARIMAX further augments this structure by incorporating exogenous predictors, enhancing explanatory and predictive power. Monthly time series data from 2015 to 2024 were utilized, with flight distance as the endogenous variable and the unemployment rate as the exogenous regressor. The modeling procedure involved rigorous stationarity testing via the Augmented Dickey-Fuller (ADF) test, model selection using the Akaike Information Criterion (AIC), and residual diagnostics employing the Box–Ljung and Shapiro–Wilk tests. SARIMAX(0,1,0)(0,1,1)[12] + X emerged as the optimal specification, with all parameters statistically significant and a MAPE of 3.68%, denoting excellent forecast accuracy. Empirical findings reveal a significant and negative association between unemployment and air travel activity, emphasizing the role of labor market dynamics in shaping mobility trends. These results reinforce the utility of SARIMAX as a robust tool in macroeconomic forecasting and evidence-based policy formulation.
Identifying Regional Welfare Patterns in West Java Based on Socioeconomic Indicators Using DBSCAN Iva Aurellia khalif; Suci Izzati; Siti Wulandari; Radiatul Hidayat; M Al Haris; Alwan Fadlurohman
Indonesian Council of Premier Statistical Science Vol. 5 No. 2 (2026): August 2026
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/icopss.v5i2.39949

Abstract

Regional disparities in welfare remain a significant challenge in Indonesia, particularly in West Java Province, where socioeconomic conditions vary across districts and municipalities. This study aims to classify districts and municipalities in West Java based on socioeconomic characteristics using the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm. The variables analyzed consist of Mean Years of Schooling, Number of Poor Population, Poverty Severity Index, Annual Population Growth Rate, and Human Development Index (HDI). Secondary data were obtained from the West Java Provincial Statistics Office (BPS). Prior to clustering, the variables were standardized using the Z-score method and analyzed using Principal Component Analysis (PCA) to reduce dimensionality and address multicollinearity. The first principal component (PC1), which explained approximately 82% of the total variance, was used as the input for DBSCAN clustering. The optimal DBSCAN configuration was determined by evaluating combinations of epsilon (ε) and minimum number of points (MinPts) using the Silhouette Coefficient. The results showed that ε = 0.06 and MinPts = 2 produced the highest Silhouette Coefficient of 0.8879592, resulting in two clusters and three observations classified as noise. Cluster 1 consisted of 22 districts and municipalities and was characterized by a relatively higher average number of poor population and Poverty Severity Index. Cluster 2, consisting of Sukabumi City and Cimahi City, exhibited higher Mean Years of Schooling and HDI, along with a lower Poverty Severity Index. Pangandaran, Cirebon City, and Banjar City were identified as noise due to their distinctive characteristics. These findings demonstrate that DBSCAN can identify heterogeneous socioeconomic patterns among regions in West Java
Co-Authors Alwan Fadlurohman Febryana Dilla Setyaningrum Ihsan Fathoni Amri Isnaini Maulida M Al Haris M. Al Haris Radiatul Hidayat Rendi Andika Putra Siti Wulandari Suci Izzati Suci Izzati