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Dewi Krismawati
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Humanities Computer Science & IT Economics, Econometrics & Finance Social Sciences

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Kondisi Perekonomian Nusa Tenggara Barat pada Gelaran MotoGP Mandalika dengan Pendekatan Big Data di Sektor Pariwisata Dewi Krismawati; Satria Bagus Panuntun
Seminar Nasional Official Statistics Vol 2022 No 1 (2022): Seminar Nasional Official Statistics 2022
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1305.245 KB) | DOI: 10.34123/semnasoffstat.v2022i1.1486

Abstract

The COVID-19 pandemic that occurred two years ago was a factor that greatly influenced the economic slowdown, both at the global and national levels. The International Pertamina Grand Prix MotoGP Mandalika was enthusiastically welcomed by the Indonesian people. The existence of the 2022 MotoGP event is an opportunity to encourage economic recovery both at the level of the Province of West Nusa Tenggara (NTB) and nationally. This study aims to see the impact of the Mandalika MotoGP event on the economy, especially the tourism sector in NTB by utilizing Big Data technology. The results of this study indicate a significant increase in community mobility during the event, especially in transit areas and parks. The increase in TPK also occurred quite significantly in March 2022 compared to February 2022. The number of flights to Lombok International Airport increased sharply from 18 to 21 March 2022. Some of these indicators show that the MotoGP mandalika event is a moment for the revival of the NTB economy.
Klasterisasi Wilayah Rentan Bencana Alam Berupa Gerakan Tanah Dan Gempa Bumi Di Indonesia I Nyoman Setiawan; Dewi Krismawati; Setia Pramana; Erwin Tanur
Seminar Nasional Official Statistics Vol 2022 No 1 (2022): Seminar Nasional Official Statistics 2022
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (437.82 KB) | DOI: 10.34123/semnasoffstat.v2022i1.1538

Abstract

Indonesia is one of the countries prone to natural disasters, such as soil movements and earthquakes. The people of Indonesia have felt various kinds of impacts caused by the disaster, both in the form of losing their jobs, their homes, and even their beloved family members. However, this impact can certainly be minimized with good disaster management. Therefore, the author focuses on the clustering of earthquake-prone areas in Indonesia using Density-based Spatial Clustering of Application with Noise (DBSCAN), Common Nearest Neighbor Clustering (CNN), and K-Medoids. The results of the clustering show that the soil movement-prone cluster formed from the DBSCAN algorithm is centered on the islands of Java and Bali, as well as along the western part of North Sumatra to Lampung, while the earthquake-prone areas formed from the K-Medoids algorithm are spread over the area traversed by the Pacific Ring of Fire.
Co-Authors Erwin Tanur I Nyoman Setiawan Pramana, Setia Satria Bagus Panuntun