The purpose of our research is to predict the short-term of confirmed cases of in Spain by using SutteARIMA method. Covid-19 Spanish confirmed data obtained from Worldometer and Spain Stock Market data (IBEX 35) data obtained from Yahoo Finance. Data starts from 12 IBEX). In this study, the SutteARIMA method will be used. For the evaluation of the forecasting methods we applied forecasting accuracy measures, mean absolute percentage error (MAPE). Based on the results of ARIMA and SutteARIMA forecasting methods, we conclude that the SutteARIMA method is most suitable than ARIMA to calculate the daily forecasts of confirmed cases of Covid-19 and IBEX in Spain. The MAPE value of 0.1905 (smaller than 0.04 compared to MAPE value of ARIMA) for confirmed cases of Covid-19 in Spain and 0,0202 for IBEX stock. At the end of the analysis, using the SutteARIMA method, we calculate daily forecasts of confirmed cases of Covid-

The purpose of this study was to develop Android-based teaching materials, which have qualities (valid, practical and effective) that can help to improve the quality of student learning outcomes and to motivate students to learn. The process of developing this material used the Plomp development model, which consists of a preliminary investigation phase, a design phase, a realisation/construction phase, a test, evaluation and revision phase and an implementation phase. To assess the quality of the learning device, the validity of the validator of experts was, then, tested in order to ensure that the teaching material is valid, practical and effective.

This study was conducted with the aim to the clustering of provinces in Indonesia of the risk of the COVID-19 pandemic based on coronavirus disease 2019 (COVID-19) data. This clustering was based on the data obtained from the Indonesian COVID-19 Task Force (SATGAS COVID-19) on 19 April 2020. Provinces in Indonesia were grouped based on the data of confirmed, death, and recovered cases of COVID-19. This was performed using the K-Means Clustering method. Clustering generated 3 provincial groups. The results of the provincial clustering are expected to provide input to the government in making policies related to restrictions on community activities or other policies in overcoming the spread of COVID-19. Provincial Clustering based on the COVID-19 cases in Indonesia is an attempt to determine the closeness or similarity of a province based on confirmed, recovered, and death cases. Based on the results of this study, there are 3 clusters of provinces.