Physic Education and Technology (PhET) adalah salah satu media pembelajaran yang diciptakan untuk memberikan pengalaman interaktif bagi peserta didik. Penelitian ini bertujuan untuk meningkatkan pemahaman konsep fisika peserta didik dengan menggunakan PhET Simulation. Penelitian ini dilakukan di MTs AT-Taqwa Maumere, dengan sampel 58 peserta didik. Teknik pengambilan sampel pada penelitian ini adalah dengan cara purposive sampling.Jenis penelitian ini merupakan penelitian kuantitatif. Penelitian ini dilakukan dengan metode Quasi Experimen, dengan bentuk Nonequivalent Control Group Design yang melibatkan dua kelompok belajar yaitu kelas eksperimen dan kelas kontrol dimana sampel kedua kelas ini dipilih tidak secara random. Pengumpulan data dilakukan dengan pemberian soal test kemampuan pemahaman konsep. Teknik analisis data menggunakan uji N-gain. Hasil penelitian dengan mengacu pada perhitungan N-gain menunjukan bahwa kelas eksperimen lebih tinggi dari pada kelas kontrol. Peningkatan pemahaman konsep fisika pada kelas eksperimen sebesar 0,62 sedangkan untuk kelas kontrol sebesar 0,13. Berdasarkan hasil perhitungan n-gain dapat dikatakan bahwa pembelajaran dengan menggunakan PhET Simulation dapat meningkatkan pemahaman konsep fisika peserta didik.

Singular Spectrum Analysis (SSA) is a time series method used to decompose the original time series into a sum of a small number of components that can be interpreted such as trends, oscillatory components, and noise. The purpose of this study is to compare the accuracy of the forecast between the SSA and ARIMA methods to obtain the best method in predicting the number of foreign tourist arrivals to Indonesia. The data used in this study is data on the number of arrival of foreign tourists to Indonesia through the Batam entrance. The forecasting results obtained using the SSA method will be compared with the ARIMA method to assess its superiority. The level of forecasting accuracy generated by each method is measured by the criteria of Mean Absolute Percentage Error (MAPE). The results of the study show that the ARIMA method produces better forecast accuracy than the SSA method for forecasting the number of tourist arrivals through the Batam's entrance. The MAPE value obtained from the results of forecasting using the ARIMA method is 9.83. The MAPE value obtained from the results of forecasting using the SSA method is 10.98.

At this time, almost everyone once to consume instant noodles. The high interest of public on the instant noodles should be balanced with enough knowledge about the noodles and its nutritional content, either on it’s instant noodles which have similar nutrient content and nutrient content that become identifier of each this group of noodles. The method can be used to obtain information on several brands of instant noodles that have similar nutrient content and nutrient content type that become identifier of each group of instant noodles is biplot analysis. Biplot analysis can show mie and nutrient content types simultaneously in a two-dimension plot. So that from a plot shows noodles and nutritional content types simultaneously, so that obtain information about the instant noodle that have similar nutrient content and nutrient content types into identifier of each group of instant noodles. This study was used 33 brands of instant noodles as observed objects with the type of nutrient content were observed there were nine. This study aims to find out some instant noodles that have similar nutrient content and nutrient content type that become identifier of each group of instant noodles. From the biplot analysis, obtained six groups of instant noodles with different identifier variables.

This study aims to determine the effect of flight activity noise intensity on student learning concentration. This study involved 48 students (male = 24 and female = 24) who were randomly selected in the Islamic elementary school Waioti, Maumere. The intensity of flight activity noise during classroom learning activities is measured using a Sound Level Meter (SLM), and students' concentration levels were measured using a 5-level Likert scale learning concentration questionnaire. The effect of flight noise intensity on student learning concentration was determined using linear regression analysis. The results showed that the noise level due to flight activities in the Waioti Islamic Elementary School was 58.92 dB, exceeding the set threshold value. The intensity level of students' learning concentration disorders reached 71.43%, including frequent disturbance. The level of flight activity noise significantly affects student learning concentration with the regression model: Y = 49.972 + 0.834X with R2 of 0.635.

Singular Spectrum Analysis (SSA) is the technique of non-parametric analysis of time series used for forecasting. SSA aims to decompose the original time series into a summation of a small number of components that can be interpreted as the trend, oscillatory components, and noise. The purpose of this research is to understand how the SSA model in forecasting the number of foreign tourist arrivals to Indonesia through four entrances. The result of forecasting obtained by using SSA will be compared with ARIMA method to assess its superiority. The data used in this study are the data of the number of foreign tourist arrivals to Indonesia through four entrances in the period January 1996 to August 2016. Four entrances used in this study are Ngurah Rai Airport, Kualanamu Airport, Soekarno-Hatta Airport, and Juanda Airport. The level of forecasting accuracy generated by each forecasting method is measured using the Mean Absolute Percentage Error (MAPE) criterion. The results showed that SSA method is the best forecasting method for forecasting the number of foreign tourist arrivals through Ngurah Rai Airport with an average MAPE value of 9.6%. Forecasting the number of foreign tourist arrivals through Kualanamu Airport, ARIMA method is the best forecasting method with an average MAPE value of 22.4%. In forecasting the number of foreign tourist arrivals through Soekarno-Hatta Airport, ARIMA method is the best forecasting method with an average MAPE value of 10.5%. In forecasting the number of foreign tourist arrivals through Juanda Airport, ARIMA method is the best forecasting method with an average MAPE value of 9.9%.