Agricultural insurance with the interantional price is new insurance in Indonesia. The international insurance premium is given if the international prices lower than the determined trigger value. The purpose of this study is to presents the steps needed to determine the premium value of the agricultural insurance. The steps are to search data of the international prices and local prices commodity coffee, calculate the return of both data, calculate descriptive statistic, calculate correlation between international prices of commodity coffee and local prices commodity coffee, estimate the parameter by using Maksimum Likelihood Estimasi(MLE), to do the Monte Carlo simulation by using Mean Reversion with Jump Diffusion, to determine the production cost, normality log test, to determine the trigger indexs, and to count the premium value with put cash-or-nothing option. On this study if international prices lower than the determined trigger value, trigger payments as much as Rp 20.248.282,4/Ha based on trigger index as many Rp 24.900/kg, so amount of premium payment equals Rp 334.000.

The existence and services of mangrove ecosystems in Segara Anakan are threatened by changes in land use on land and global warming, which requires proper and intensive monitoring. The monitoring of mangrove and its trend over large areas can be done using multi-temporal remote sensing technology. However, remote sensing data is often contaminated by cloud cover, and its corresponding shadow resulted in missing data. This study aims to assess the performance of the existed gap-filling techniques, such as, linear, spline, stineman,  data interpolation Empirical Orthogonal Function (dineof) and spatial downscaling strategy employing the Proba-V imagery in 100 m, when being used for estimating the missing data and depicting the trend in NDVI from Landsat 8 OLI by using Mann-Kendall test. Our result suggested that EOF-based interpolation gave better prediction results and more accurate in predicting longer missing data. Linear interpolation, on the other hand, was accurate to predict shorter missing data. Overall, all interpolation results can reconstruct 64 (spline) to 72 % (dineof) of missing data in NDVI with the RMSE of 0.10 (dineof) – 0.13 (spline). A consistent decreasing trend was also found from the four interpolation methods, which showed the consistency of the interpolated values when used for deriving trends with similar patterns of overall decreasing trend and magnitude of changes of -0.0095 to -0.0099 (NDVI unit) over the mangrove areas in 2015. The result demonstrated the potential ability of gap-filling methods for simulating the value of missing data and for deriving trends.

Rice is one of the staple foodstuffs whose availability is very important for public consumption in Indonesia, especially Bali Province. The three regencies that produce the most rice in Bali they are Badung, Gianyar and Tabanan. This study aims to model, predict, and analyze the relationship between rice production in Badung, Gianyar, and Tabanan Regency from January 2018 to December 2019 using vector autoregression (VAR) method. VAR method is a time series method that can be used to model and predict time series with more than one variable simultaneously. The results of this study, namely the VAR model obtained to predict the amount of rice production in Badung, Gianyar, and Tabanan Regencies is third order VAR (VAR (3)). Based on the forecasting criteria for the mean absolute percentage error (MAPE) in this model, a reasonable forecast is obtained for the rice production variables in Badung and Gianyar regencies, and good forecasting for the rice production variables in Tabanan Regency is obtained. Then, based on the granger causality analysis, it is found that the amount of rice production in Gianyar Regency affects the amount of rice production in Badung and Tabanan Regencies, and the amount of rice production in Badung Regency affects the amount of rice production in Gianyar Regency.

This study aims to determine the effect of leadership and workload on employee performance. The sample used in this study were employees of PT. Bank Mandiri (Persero) Tbk. KCP Jakarta Cibubur with a total of 45 people using Nonprobability Sampling, namely type (saturation sampling). The analysis in this study used validity test, reliability test, descriptive statistical test, normality test, multicollinearity test, heteroscedasticity test, multiple linear regression test, coefficient of determination test, F test and t test. Based on the results of the t test of tcount 9.299 ttable 1.681 with a significance value of 0.000 0.05. So, Ha is accepted, meaning that leadership has a partial effect on employee performance. Whereas for workload tcount 2.925 ttable 1.681, with a significance value of 0.006 0.05. So, Ha is accepted, meaning that workload partially affects employee performance. Based on testing the coefficient of determination (R2) of 0.925, it means that leadership and workload are able to explain (92.5%), the rest is influenced by other variables. The results showed that leadership and workload had a positive and significant effect on the performance of employees at PT. Bank Mandiri (Persero) Tbk. KCP Jakarta Cibubur.