The aim this study is discussed on the detection and correction of data containing the additive outlier (AO) on the model ARIMA (p, d, q). The process of detection and correction of data using an iterative procedure popularized by Box, Jenkins, and Reinsel (1994). By using this method we obtained an ARIMA models were fit to the data containing AO, this model is added to the original model of ARIMA coefficients obtained from the iteration process using regression methods. In the simulation data is obtained that the data contained AO initial models are ARIMA (2,0,0) with MSE = 36,780, after the detection and correction of data obtained by the iteration of the model ARIMA (2,0,0) with the coefficients obtained from the regression       1 2 1 2 3 0,106 0, 204 0, 401 329 115 35,9 t t t Z Z Z X t X t X t         and MSE = 19,365. This shows that there is an improvement of forecasting error rate data.

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This study is aimed at building and analysing a SIRS model and also simulating the model to predict the number of dengue fever cases. Methods applied for this model are building the SIRS model by modifying the SIR model, analysing the SIRS model using the Lyapunov function to prove three theorems (the existence, the free disease, and the endemic status of dengue fever), and simulating the SIRS model using the number of dengue case data in South Sulawesi by Maple. The results obtained are the SIRS model of dengue fever transmission, stability analysis, global stability, and the value of the basic reproduction number R 0 . The simulation done for the dengue fever case in South Sulawesi found the basic reproduction number R 0 = 26.47609 > 1 ; it means that South Sulawesi is in the endemic stage of transmission for dengue fever disease. Simulation of the SIRS model for dengue fever can predict the number of dengue cases in South Sulawesi that could be a recommendation for the government in an effort to prevent the number of dengue fever cases.

Abstrak: Opsi adalah suatu kontrak yang memberikan hak (bukan kewajiban) kepada pemegang kontrak (option buyer) untuk membeli atau menjual suatu aset tertentu suatu perusahaan kepada penulis opsi (option writer). Apabila pada saat jatuh tempo (expiration date) pemegang opsi tidak menggunakan haknya, maka hak tersebut akan hilang dengan sendirinya. Dengan demikian opsi yang dimiliki tidak akan mempunyai nilai lagi. Monte Carlo adalah suatu metode yang menghendaki model simulasi yang mengikutsertakan bilangan acak dan sampel yang berbasis pada komputer. Prosedur simulasi melibatkan pembangkit bilangan acak dengan memberikan kepadatan probabilitas dan menggunakan hukum bilangan besar untuk mendapatkan rata-rata dari nilainya sebagai penaksir dari nilai harapan variabel acak. Penelitian ini bertujuan untuk memprediksi harga opsi saham pada periode kedepannya dan sebagai bahan pertimbangan bagi pelaku perdagangan saham untuk mengambul keputusan untuk menjual atau membali opsi suatu saham dengan menggunakan software Matlab. Jenis penelitian yang digunakan adalah penelitian terapan menggunakan metode Monte Carlo untuk mensimulasikan data saham. Hasil menunjukkan bahwa semakin banyak iterasi yang dilakukan maka nilai prediksi juga semakin baik dan konvergen ke suatu nilai. Nilai prediksi stabil pada iterasi ke-60000 dengan nilai error dari MAPE kurang dari 20% sehingga nilai prediksi dapat dikatakan baik.Kata Kunci: Opsi Asia, Monte Carlo, Black-Scholes, Matlab, MAPE.Abstract: Option is a contract that gives rights (not obligations) to the contract holder (option buyer) to buy or sell a certain asset of a company to the option writer (option writer). Monte Carlo is a method that requires a simulation model that includes random numbers and samples based on computers. The simulation procedure involves generating random numbers by providing a probability density and using the law of large numbers to get the average of its values as an estimator of the expected value of the random variable. This study aims to predict stock option prices in the future and as a material consideration for stock trading players to make a decision to sell or buy options for a stock using Matlab software. The type of research used is applied research using the Monte Carlo method to simulate stock data. The results show that the more iterations are carried out, the predictive value is also getting better and converging to a value. The predictive value is stable at the 60000th iteration with an error value of MAPE of less than 20% so that the predicted value can be said to be good.Keywords: Asia Option, Monte Carlo, Black-Scholes, Matlab, MAPE.

Objective: Fast-disintegrating tablets are a pharmaceutical preparation that is rapidly being developed because they can dissolve in the oral cavity without chewing and without additional water support. The type of dissolver is a crucial component in fast-disintegrating tablets. Maltodextrin and pregelatinized cassava starch (PPS) are excipients that can be used as dissolvers. This study aimed to formulate fast-disintegrating tablets using a combination of maltodextrin dextrose equivalent (DE) 10-15 and PPS in various concentrations as excipients. Methods:The cassava starch classified as PPS was obtained. PPS was then mixed with maltodextrin DE 10-15 to create fast-disintegrating tablets using the wet granulation method.Results: Tablet evaluation showed that formula F containing 40% maltodextrin DE 10-15 and 10% PPS was the most effective of the proposed fastdisintegrating tablets.Conclusions: Formula F has a hardness of 3.39 kp, 0.74% friability, a wetting time of 7.87 seconds, and a dissolve time of 38.55 seconds.