Stocks are one of the many investments that are favored by all groups because they promise high returns. But in addition to promising high returns, stocks can also provide a high risk of loss, which makes ordinary people afraid to start investing in the stock market. To prevent losses in buying stocks is to choose stocks with good fundamentals. To support this, we need an analysis that can help make decisions in choosing the best stocks in the technology sector. The saw method analysis will be used in this study, where the saw method is able to select alternatives based on predetermined categories. This study will rank the best stocks based on company fundamentals, namely EPS, PER, PBV, ROE, DER and Dividend Yield. The results of this study are EDGE stocks as the best stocks in the technology sector with the highest value of 0.88. The purpose of this research is to help investors choose stocks before investing in technology companies.

In this research, an image classification model was developed to distinguish hand objects pointing at rock, paper, and scissors using one of the popular image classification methods, namely the Probabilistic Neural Network. Probabilistic Neural Network is a method in an artificial neural network that is used to classify a category based on the results of calculating the distance between the density function and the probability. PNN has 4 stages of processing, namely Input Layer, Pattern Layer, Summation Layer, and Output Layer. Tests in the study were carried out with a total of 60 testing data from three object classes from the dataset. Then the results of the classification of Batu, Scissors, and Paper hand images using the application of the PNN algorithm in this research test obtained an average accuracy value of 90%

This study discusses the problem, namely the process of determining the type of anesthesia for patients before carrying out surgery. In determining the appropriate type of anesthesia based on the conditions experienced by the patient, generally anesthesiologists or anesthesiologists still use the common method, namely by conducting interviews related to the symptoms experienced by patients before anesthesia is carried out on patients who will be operated on. Then the anesthesiologist will write down the results of the interview in the form of a written report and will adjust the results of the interview related to the symptoms experienced with the existing anesthesia guidelines. And this will certainly take more time in adjusting the results of the patient's symptoms to the type of anesthesia that will be given. Along with the rapid development of technology, determining the type of anesthesia that will be given to the patient before it is carried out can be overcome by building an information system that is able to adopt the process and way of thinking of humans, namely Artificial Intelligence or artificial intelligence which is often called the Expert System. In this case, a smart application in determining the type of anesthesia in android-based patients is designed using the Bayes Theorem calculation method, and it is possible for an anesthesiologist and anesthesiologist to administer anesthesia to a patient before a patient steps into the operation stage. Thus, it can also cause work productivity to increase and the time used to complete the work is getting shorter

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