Vol. 2, No. 1, Januari, 2021 : Estimasi

Disaster cases need to be analyzed considering that when a disaster occurs it will have an extraordinary impact. The statistical method that can be used to study disaster cases is a simple correspondence analysis. This study aims to map areas with the potential for natural disasters in the province of Central Sulawesi. So, in the analysis, regions are grouped according to row profile values that are greater than the average. The result of simple correspondence analysis obtained flood disaster has the potential to occur in Banggai, Morowali, Donggala, Buol, Parigi Moutong, Tojo Una-una, Sigi, and North Morowali. While the dominant tornado disaster occurred in Banggai Kepulauan, Banggai, Poso, Toli-toli, Parigi Moutong and Sigi. For regional landslides with potential Banggai Islands, Donggala, Toli-toli, Parigi Moutong, and Sigi. Then Banggai Islands and the City of Palu are the dominant regions for earthquake disasters. The results of the grouping can be the basis of government and community focus in tackling the dominant disasters occurring in their respective regions so as to minimize the impact when natural disasters occur.

Coronavirus disease 2019 (COVID-19) is an infectious disease caused by the acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and the transmission can mediate human-to human by enviroment. According to Indonesian Meterological, Climatological, and Geophysical Agency found that weather and climate were supporting factors of COVID-19 outbreak so, research and analysis is carried out regarding the most factor were supporting the spread of COVID-19. In this study, using secondary data obtained from data reported by Indonesian Meterological, Climatological, and Geophysical Agency. According the aims of this study by using Principal Component Analysis (PCA) there are three principal components which represents the most factor were supporting the spread of COVID-19 they are temperature, humidity, and length of sunshine.

Structural Equation Modeling (SEM) is a statistical technique used to build and test the statistical models are usually in the form of causal models. SEM is a combination from factor analysis, path analysis, and regression. This method is a statistical approach that serves to test hypotheses about the relationship between observed variables and latent variables. In this paper, SEM is applied to determine the motivation of the millennial generation for the general election 2019 in Indonesia. Data was obtained by distributing questionnaires online according to procedures which were then analyzed using SEM. Millennial’s motivation is seen from the knowledge of the millennial generation on voting rights commitments in the 2019 general election in Indonesia. Based on the result, millennial generation is committed to using voting rights in the 2019 general election. All indicator variables from this study are significant to the millennial generation’s commitment to use their voting rights

The port has become an important part of people's lives. On certain days there is an increase in the number of ship passengers which can slow down operational activities from the port, thus causing a buildup of passengers at the port. therefore, the port must be prepared to deal with the buildup of passengers at the port. Based on this, the researchers made a prediction or forecasting the number of ship passengers at Makassar Soekarno Hatta Port in the coming period to find out how much the estimated number of passengers at Makassar Soekarno Hatta Port. The results of these studies can be input to the PT. Pelabuhan Indonesia IV (Persero ) Makassar if there will be a surge in passengers in the future period. researchers used the fuzzy method of high order chen time series in forecasting or prediction in this study . The researcher divides the data onto training and testing data . The results of the study using fuzzy time series with the best high order chen are that the second order produces MAPE error size of 0,143 , MSE 13470993,9 and MAE of 9478,52 . The result of prediction of testing data onto one period in the future is 52.608.

Acute respiratory infection (ARI) is an infectious desease cause by bacteria or viruses that attack the respiratory organs. This research aims to determine the best panel data regression model in the case of the factors that influence the number of patients with ARI in East Nusa Tenggara Province from 2014 to 2018. Response variable used is the number of ARI patients. Independent variables were observed among others, low birth weight, malnutrition, immunization, exclusive breastfeeding, and vitamin A in 22 districts or city in East Nusa Tenggara. The results showed that the Random Effect Models eliminate outlier data on response variable is a model that can describe the influence of independent variables on the number of patients with ARI in East Nusa Tenggara Province from 2014 to 2018. Variables that influence of ARI are malnutrition and exclusive breastfeeding with a coefficient of determination (R) of 9,2%.