Medical science is a science that explores the handling of diseases carried out by health workers. The importance of the role of health workers today is based on data from the Ministry of Health, Indonesia still lacks health workers and it is hoped that a new generation will come who have broad knowledge, are intelligent, competitive and useful for public health. Basically, many prospective students who will enter medical education do not yet have knowledge about the use of medical devices, so education on the use of medical and medical devices needs to be carried out to provide insight to prospective health workers in the future. In this study, the author designed an application to provide education about medical devices commonly used in hospitals, both in terms of functions and how to use them for prospective students who are interested in majoring in health and medical sciences. The method in designing this system uses the Computer Assisted Instruction method. In its use, users can learn about medical and medical equipment according to their class, namely hospital health care and treatment, anesthesia equipment, teeth, eyes, ENT, radiology, cardiology, surgery, and several others. The author uses an expert review instrument in testing the validity and testing one to one to determine the practicality of using the application. Based on the results of the Expert Review, this application is declared valid based on the average value of the assessment results of media experts, design experts and evaluation experts with an average score of 4.0 so that this application category is declared valid. Furthermore, the results of the product practicality test through one to one testing were assessed by 3 respondents with an average value of 3.9 with practical criteria.

There are still many unidentified negative comments on social media that have a negative impact on others' mental and physical well-being. Therefore, sentiment analysis is needed to filter and identify such types of comments, especially on social media. This research aims to analyze and classify unidentified negative comments spread across social media. Sentiment analysis and comment classification are performed using 7773 comments in the Indonesian language. The comments are then visualized using an embedding projector, which gives satisfactory results in classifying words in the comments, where words with negative or positive sentiments are clustered closely together. The model employed in this study is the Long Short Term Memory (LSTM) model, which achieved an accuracy rate of 77.70% and a validation accuracy of 85.20%. The trained model is then used for testing purposes, employing directly collected comments from social media, which give satisfactory results

In today's digital era, the use of MikroTik routers is increasingly common in companies, including PT Time Excelindo. However, attacks on MikroTik router logins are a frequent problem, and the company has a need to have a cheap and simple security system. This thesis aims to implement login security techniques using Port-Knocking and brute force firewalls on MikroTik routers at PT Time Excelindo, with the aim of providing solutions that are affordable and easy to implement. This study focuses on identifying the problems faced by PT Time Excelindo, namely repeated attacks against MikroTik router logins. The proposed solution involves implementing a Port- Knocking technique which will hide the login port on the router, so that only legitimate access will be allowed after a series of specific requests are made to certain ports. In addition, the firewall will also be activated to block brute force attacks by limiting the number of failed login attempts