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All Journal JAMBURA JOURNAL OF PROBABILITY AND STATISTICS Prosiding Seminar Nasional Official Statistics
Chisan, Innas Khoirun
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Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Environmental Science Social Sciences

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Forecasting Jumlah Penumpang Pesawat Yogyakarta International Airport dengan Big Data Google Trends dan Variabel Makroekonomi untuk Mendukung Official Statistics Chisan, Innas Khoirun; Wijayanto, Arie Wahyu
Seminar Nasional Official Statistics Vol 2024 No 1 (2024): Seminar Nasional Official Statistics 2024
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/semnasoffstat.v2024i1.2123

Abstract

Aviation is an important element to support human connectivity and mobility so it is important to carry out an analysis of the number of airplane passengers. BPS releases data on the number of airplane passengers with a lag of around thirty days. In addition, the use of search engines is increasingly being used nowadays. This research aims to predict the number of Yogyakarta International Airport (YIA) airplane passengers in 2024 using Google Trends and macroeconomic data. To carry out this forecast, the SARIMA and SARIMAX models will be compared with several combinations of external variables. The research results show that the use of Google Trends Index variables and macroeconomics can increase forecasting accuracy. The best model selected was SARIMAX with external variables Google Trends Index and macroeconomics. The forecast results for the number of airplane passengers in January 2024 are 332 thousand passengers and in February 2024 there are 292 thousand passengers. Accurate predictions can help flight planning so that this research can play a role in improving the quality of official statistics in the field of air transportation.
Pendekatan Metode Partisi, Hierarki, dan Densitas dalam Pengelompokan Provinsi di Indonesia Berdasarkan Indeks Ekonomi Hijau Tahun 2023 Gufron, Fat’hul Mubin; Chisan, Innas Khoirun; Utami, Almira; Prakoso, Nur Yudha Jati; Kartiasih, Fitri
Jambura Journal of Probability and Statistics Vol 6, No 2 (2025): Jambura Journal of Probability and Statistics
Publisher : Department of Mathematics, Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/jjps.v6i2.27734

Abstract

Sustainable economic development that maintains environmental balance is a top priority in Indonesia’s national development planning. One of the key indicators to measure this sustainability is the Green Economy Index (GEI). The Ministry of National Development Planning (Bappenas) assesses green economic development using 15 indicators across three pillars: economic, social, and environmental. This study aims to cluster Indonesian provinces based on the GEI. The clustering methods used include partition-based approaches (K-Means, K-Medoids), hierarchical (\textit{agglomerative clustering}), and density-based (OPTICS), with evaluation based on internal validity and stability. The results show that the hierarchical \textit{average linkage} method provides the most optimal clustering performance, dividing provinces into three main groups. Each cluster reflects different GEI characteristics, highlighting disparities in green development achievements across regions. Cluster 1 consists of one province with high economic scores but very low environmental scores; Cluster 2 includes five provinces strong in environmental performance but weak economically; and Cluster 3 contains 32 provinces with diverse characteristics in green economic practices. These findings are expected to support more targeted and region-specific policy formulation to promote equitable green economic development. 
Co-Authors Arie Wahyu Wijayanto Fitri Kartiasih Gufron, Fat’hul Mubin Prakoso, Nur Yudha Jati Utami, Almira