The growth of the online retail market in Indonesia is an excellent business opportunity. It is predicted that this growth will continue to move upward due to the increasing internet penetration. With greater exposure to brands, products and offerings, consumers become smarter and wiser in their purchasing decisions. Offering goods and services that match the tastes and behavior of consumers is very important to maintain business continuity. So far, the models developed are divided into two major parts, namely the time series approach and machine learning. In this study, segmentation and forecasting of online retail sector sales were carried out using extreme gradient boosting (XGBoost). The data used in this study is an online retail dataset obtained from the UCI repository. The k-means clustering (KMC) method is applied to determine the target or data class. Principal component analysis (PCA) is applied to reduce data dimensions by eliminating irrelevant features. Model evaluation is based on a confusion matrix and macro average ROC curve. Based on the research results, XGBoost can perform retail data classification well, this can be seen through confusion matrix metrics and ROC curves.
Extracurricular activities are educational activities carried out by students outside of the standard curriculum learning hours as an extension of curriculum activities and carried out under the guidance of the school with the aim of developing the personality, talents, interests, and abilities of wider students. Talent is the potential ability of a person to achieve success in the future. Interest is a psychological factor that influences a person's actions. The creation of human resources with knowledge and character, an educator must understand the interests and talents of students. In this study, extracurricular management was carried out based on the interests and talents of students by building an expert system, where the analysis of the facts or hypotheses used the certainty factor method. The aim is to assist teachers in identifying students' talents and interests so that they can place a student in extracurricular activities. With the hope that these students can develop their character and potential so as to produce competent resources. The results show that the expert system built can help teachers in extracurricular management where a student has been identified based on their interests and talents and the expert system recommends that the student can take Marawis extracurricular with a confidence level of 72.5%.
The task of the network administrator is also not easy, this is because an admin must secure his network from an attack that can cause the network router to go down until it is damaged. There are so many ways to prevent a person/company from being able to provide optimal service, one of which is to attack the router using a DDoS attack type. Therefore, network security is needed with the Intrusion Detection System (IDS) method. An intrusion Detection System (IDS) is a method used to detect suspicious activity in a system or network. In this study, IDS is used as a deterrent and sends notifications of DDoS attacks on Mikrotik routers via Telegram bots. The process of testing DDoS attacks in the form of ping flood, SYN Flood and UDP Flood, telegram bot notifications were successfully implemented quite well, where IDS sent notifications via network admin telegram bots.
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