Abstrak Salah satu penyumbang pertumbuhan perekonomian Indonesia adalah sektor pariwisata. Menurut asalnya wisatawan dibagi menjadi dua yaitu wisatawan lokal dan mancanegara. Kunjungan wisatawan mancanegara ke Indonesia mengalami fluktuaktif setiap bulannya. Menurut kedatangannya, wisatawan mancanegara yang masuk ke Indonesia melalui jalur udara, laut, dan darat. COVID-19 memberikan dampak terhadap sektor pariwisata. Diduga bahwa COVID-19 mempengaruhi terhadap kedatangan wisatawan mancanegara. Tujuan dari penelitian ini yaitu memodelkan kunjungan wisatawan mancanegara ke Indonesia melalui pintu udara, laut, dan darat dengan melibatkan dampak wabah COVID-19. Model yang digunakan pada penelitian ini yaitu Vector Autoregressive input X (VARX). Hasil dari penelitian ini diperoleh bahwa model yang sesuai yaitu VARX (1,2,5,7). Pemilihan model berdasarkan nilai RMSE in sample paling kecil. Nilai RMSE untuk model kunjungan wisatawan melalui pintu udara yaitu sebesar 72,217, pintu laut sebesar 0,175, dan pintu darat sebesar 0,092. Kata Kunci : Wisatawan, Mancanegara, COVID-19, VARX.   Abstract The tourism sector is one sector of Indonesian economic growth contributor. Tourists are divided into two, namely local and foreign tourists. The number of foreign tourist visits to Indonesia has fluctuated every month. Foreign tourists coming to Indonesia by air, sea and land. COVID-19 has an impact on the tourism sector. It is suspected that COVID-19 affects the arrival of foreign tourists. This study examines the modelling of foreign tourist arrivals number to Indonesia by air, sea and land involving the COVID-19 impact. The model used in this study is Vector Autoregressive input X (VARX). The results of this study indicate that the appropriate model is VARX (1,2,5,7). The RMSE in sample is used to determine the appropriate model. The RMSE value for the model of tourist visits through the air gate is 72.217, the sea gate is 0.175, and the land gate is 0.092. Keywords: Tourists, Foreign, COVID-19, VARX.

Abstrak Tujuan dari penilitian ini yaitu meneliti pengaruh dari hari raya Idul Fitri terhadap inflasi bulanan di Indonesia. Digunakan metode ARIMAX (Variasi Kalender) untuk mengetahui besar pengaruh dari Idul Fitri terhadap inflasi bulanan di Indonesia. Karakteristik inflasi Juli 2008 hingga Juni 2019 memiliki keunikan. Rata-rata inflasi bulanan yaitu 0,39 dan varians inflasi bulanan yaitu 0,26. Berdasarkan model ARIMAX menunjukan bahwa bulan Januari, Mei, Juni, Juli, Agustus, November, Desember, dan hari raya Idul Fitri memberikan pengaruh signifikan terhadap inflasi bulanan Indonesia. Efek yang diberikan hari raya Idhul Fitri yaitu sebesar 0,47. Pada saat bulan Idul Fitri tiba angka inflasinya akan lebih tinggi sebesar 0,47 dibandingkan bulan lainnya.   Kata Kunci : Inflasi, ARIMAX, Idul Fitri.   Abstract The purpose of this study is to calculate the effect of Eid Al-Fitr to Indonesian monthly inflation. The ARIMAX (Calendar Variation) method is used to determine the effect of Eid Al-Fitr on Indonesian monthly inflation. The characteristics of inflation in July 2008 to June 2019 are unique. The average of inflation is 0,39 and the variance of inflation is 0,26. The ARIMAX model shows that January, May, June, July, August, November, December, and Eid Al-Fitr has a significant influence on Indonesian monthly inflation. The effect of the Eid Al-Fitr was 0,47. When the Eid Al-Fitr arrives, the inflation rate will be higher 0,47 than other months. Keywords: Inflation, ARIMAX, Eid al-Fitr.

The purpose of this study is to analyze the effect of GRDP per capita and the labor number on the province tax revenue. Regional tax revenues for each province have different figures. It is suspected that GRDP per capita and number of labor affect local tax revenues. To answer the research hypothesis, multiple linear regression analysis was used. The data used in the study were sourced from the Badan Pusat Statistik in 2020. The dependent variable in this study is local tax revenue, while the independent variables are GRDP per capita and the number of labor. Based on the results of the t-test, it was found that the GRDP per capita and the number of workers had a significant effect on province regional tax revenues. The coefficient value of GRDP per capita and the number of labor is positive. Based on the multiple linear regression model formed, the R2 value is 91.05%. So it can be said that GRDP per capita and the number of labor can explain the province tax revenue of 91.5%, the remaining 8.5% is explained by other independent variables not included in this study.

Stock is one of the instruments that can be used to invest. The factors suspected of influencing the fluctuations in the stock price index are the Jakarta Composite Index (JCI), the rupiah exchange rate, and the Covid-19. The purpose of this study is to analyze the effect of the JCI, the rupiah exchange rate, and the Covid-19 on the Jatim Bank stock price index. To analyze the effect of the JCI, the rupiah exchange rate, and the Covid-19 on the Jatim Bank stock price index, time series regression analysis was used. The results of the analysis show that the JCI, the rupiah exchange rate, and the Covid-19 have a significant effect on the Jatim Bank stock price index. The p-value of the three variables is less than 0.05. The value of the determination coefficient is 65.56%, so that the diversity of the dependent variable that can be explained by the model is 65.56%.

According to SEKI data in 2020, DKI Jakarta is the province that has the highest average monthly value of rupiah loans provided by commercial banks and rural banks. Many factors can affect the size of the value. The amount of rupiah loans provided by commercial banks and rural banks in the previous months can affect the current value. The geographical conditions of an area can have an impact on the surrounding area. Likewise, the number of rupiah loans in DKI Jakarta Province is suspected of having mutual influence with surrounding provinces. The provinces that are directly adjacent to DKI Jakarta are Banten Province and West Java Province. The purpose of this study is to conduct spatio-temporal analysis of the amount of loans provided by commercial banks and rural banks. The data used is the monthly amount of rupiah loans provided by commercial banks and rural banks in DKI Jakarta, West Java, and Banten Provinces in a time period between January 2012 to July 2021. The GSTAR method has been used to analyze the spatio-temporal relationship. The GSTAR model formed is GSTAR(3,6,12) with differencing order of 1. Based on the model formed, it was concluded that the amount of loans provided by commercial banks and rural banks in the three provinces is related to each other spatially and temporally. The RMSE value for each of the models formed is 1.871 for Banten Province, 13.701 for DKI Jakarta, and 2.919 for West Java Province.