Weather information has an important role in human life in various fields, such as agriculture, marine, and aviation. The accurate weather forecasts are needed in order to improve the performance of various fields. In this study, use artificial neural network method with backpropagation learning algorithm to create a model of weather forecasting in the area of ??South Bali. The aim of this study is to determine the effect of the number of neurons in the hidden layer and to determine the level of accuracy of the method of artificial neural network with backpropagation learning algorithm in weather forecast models. Weather forecast models in this study use input of the factors that influence the weather, namely air temperature, dew point, wind speed, visibility, and barometric pressure.The results of testing the network with a different number of neurons in the hidden layer of artificial neural network method with backpropagation learning algorithms show that the increase in the number of neurons in the hidden layer is not directly proportional to the value of the accuracy of the weather forecasts, the increase in the number of neurons in the hidden layer does not necessarily increase or decrease value accuracy of weather forecasts we obtain the best accuracy rate of 51.6129% on a network model with three neurons in the hidden layer.

No abstract

Life insurance products consist of a single life insurance and joint life insurance. Joint life is a state where the rule die life is a combination of two or more factors, such as the husband-wife, parent-child. The research is to obtain the formula of the annual premium of joint life insurance with the age of x, y, and z. By using formula and constants Helligmann-Pollard will be determined value of mortality tables, life annuity and single premium to get the formula annual premium joint life insurance for three persons. In addition, this study also aims to get the number of annual premium joint life insurance for a household of three consisting of a married couple and one son with the ages of 50, 45, dan 15 years old, with the interest rate of 5% used. For the contract terms of one and two years, the annual premium of joint life for two persons respectively and greater than the joint life insurance of three persons. While for three to ten years contract, the annual premium of joint life insurance three person is bigger than the joint life insurance for two persons.

Survival analysis is a statistical method that accommodates the collection of censored data. One of popular method in survival analysis is the Cox Proportional Hazard Regression. The Cox Proportional Hazard Regression can be used to see old looking for work where data may contain censored data. This article aims investigate the characteristics of job seekers and the variables that affect old looking for work. To establish the best model using Stepwise Selection method. Prior to that the assumption of Cox Proportional Hazards Regression is tested using log minus log curve. The results obtained from Cox Proportional Hazards Regression model is as follows

Black-Scholes model suggests that volatility is constant or fixed during the life time of the option certainly known. However, this does not fit with what happen in the real market. Therefore, the volatility has to be estimated. Implied Volatility is the etimated volatility from a market mechanism that is considered as a reasonable way to assess the volatility's value. This study was aimed to compare the Newton-Raphson, Secant, and Bisection method, in estimating the stock volatility value of PT Telkom Indonesia Tbk (TLK). It found that the three methods have the same Implied Volatilities, where Newton-Raphson method gained roots more rapidly than the two others, and it has the smallest relative error greater than Secant and Bisection methods.