Palm oil is one of the largest agricultural products in Indonesia and has a high economic value and can improve the welfare of oil palm farmers. The amount of oil palm fruit production is not always stable or increasing, but increases up and down which is influenced by many factors. This study aims to estimate the average amount of oil palm fruit production every year and prepare anticipatory steps in the event of a decrease in oil palm fruit production. The image processed in this study was the production of palm fruit in a few years which was generated from the results of oil palm plantations. Furthermore, data is processed using the Single Moving Avarage method. This method is a method of forecasting or predictions using a number of actual data to generate predictive values ​​in the future. The results of testing on the single moving average method can be seen forecasts of oil palm fruit production in 2021 using Moving Averge 3 of 200.749 tons with Mean Absolute Deviation 19.604, Mean Squared Error  456.963.281  and Mean Absolute Percent Error 10,0%. Moving Averge 4 was  206.771 tons with the Mean Absolute Deviation  27.333, Mean Squared Error  752.202.579 and Mean Absolute Percent Error 14,2%. Moving Averge 5 was  210.908 tons with Mean Absolute Deviation  26.890, Mean Squared Error  723.072.100 and Mean Absolute Percent Error 14.1%. The test results using the Single Moving Average method can be concluded that forecasting using Moving Average 3 can be used because the relative error level is smaller than Moving Average 4 and 5, with the value of the Mean Absolute Percent error of 10.0% and Mean Absolute Deviation 19.604.

The common method used to secure a MySQL database is in access control. The technique is the use of a password. To better secure the data sent cryptographic techniques need to be done. This study uses the Elgamal method in conducting cryptography. The results of this study generate MySQL databases in random form during safer delivery and can only be accessed by parties who have a password. So this research can further improve MySQL data security

Lungs are a very importand part of the human organ, which functions as a place for oxygen  exchange. This organ that is located under the ribs has a very heavy task, as well as the pollution of the air we breathe everyday which will cause various diseases in the lungs. Lung disease is a disease that is common to everyone, and there are still many who are less concemed with lung healty, so that is causes many indications of lung diseas. Expert  system is a system that uses human knowledge recorded in a computer to solve a problem. The purpose og this study was to datermine the accuracy of disease identification in the lungs using the Certainty Factor method. The date obtained is datae about the symptoms that prove wherher a person has lung disease or not and conduct an analysis of the date, so that later conclusions can be abtained from the facts found using an expert system of the Certianty Factor method. The date obtained is date about the sympyoms thet prove whethera person has lung as a problem solving metric which is a parameter value to show the amount of trust. The result of the research from an expert system on pulmonary disease with pulmonary  tuberkolosis (TBC) with a certainty level  og 68%. Expert system on lung disease using the Certainty Factor method can make it easien for sufferes to know and handle prevention and handling