Reviews of a service, especially hotel services, have an important role to play in consumer decisions. Tripadvisor is a guide and reference platform for travelers in finding information about the hotel services in various countries. There are many reviews about hotels on the platform so that readers are difficult to make decisions so it is necessary to conduct a sentiment analysis that aims to dig up information from existing reviews. The initial stage is by labeling (positive, neutral, negative) to the review. Then the preprocessing stage so that the review can be easily processed, then from that stage continued weighting using Term Frequency - Inverse Document Frequency (TF-IDF) using the best parameters, after weighting the data, then the next is the distribution of data into training data, validation and test. The data are entered into the machine learning process using Support Vector Machine (SVM) and obtained the accuracy of the model by 85%. For testing scenarios if not using slang handling get F1-Score by 80% and if not using stopword get F1-Score by 82%. On the evaluation of the performance of the model using K-Fold obtained the best results on the Fold-7 with a precision value of 87%, recall 86%, F1-score 86%, and accuracy of 87%.

MSMEs in Indonesia are MSMEs with a business scale level of 98.7% are micro-enterprises and this MSME-scale assessment category was assessed or researched 10 years ago, the results are still the same as the previous assessment, due to the average MSMEs in Indonesia not having a way or the right innovation in developing its business, especially in terms of the products produced and other things, an example of MSMEs experiencing this is MSME Foodendez, which causes these MSMEs to not have significant sales progress. Therefore, to improve the quality and progress of the Foodendez MSME business, the current sales data is used to recapitulate and evaluate the Foodendez MSME market segmentation. By using the a priori algorithm, the sales data can be used to find out predictive information on consumer interest based on age, gender, and sales location criteria. The application of business intelligence uses an a priori algorithm so that it can help provide predictive information on consumer interest in a product and can clearly know its market segmentation by collecting data through product sales in the marketplace it can be seen which products are most interested in by consumers, then data on the amount followers, comments, and likes in every post on social media in order to determine engagement (promotional strategies through social media). In this research, testing is carried out based on the location of sales at Foodendez SMEs so as to produce market segmentation data. The conclusion from the temporary test results, the frequency of sales in the marketplace is the highest at 52%, then the lowest frequency of sales is 12% in sales through exhibition bazaars.

Technological development is growing rapidly among with the increasing of human needs especially in mobile technology where the technology that often be used is android. The existence of this android facilitates the user in access of information. This android can be used for healthy needs, for example is detecting dental disease. One of the branches of computer science that can help society in detecting dental disease is expert system. In this research, making expert system to diagnosis dental disease by using certainty factor method. Dental disease diagnosis application can diagnose the patient based on griping of the patient about dental disease so it can be obtained diseases possibility of the patient itself. This application is an expert system application that operates on android platform. Furthermore, in the measurement accuracy of the system test performed by 20 patients, there were 19 cases of corresponding and 1 cases that do not fit. So, from system testing performed by 20 patients resulted in a 95% accuracy rate.

The software development process has gone through significant change in the recent years. Now delivering a system that merely satisfies functional requirements is no longer enough. Companies want their systems to be easily maintained, scalable, fault tolerant, available, integrated, and other attributes. The microservice architecture was designed to create such a robust system where a big monolith system is broken down into multiple small services that communicate each other to fulfill the requirements. One area of functional requirements that exist and needed in almost all kind of companies is the logistic part. This paper will discuss how microservices architecture can be designed and implemented to support logistic functionality that can be reused in a lot of companies as the base system.

To be able to have mastery of various sciences that are useful for experience in the world of work, students are encouraged through the MBKM program. Most students of the Informatics Study Program will choose an internship scheme and independent study in applying for the MBKM. However, the increasing number of students' interest in this program requires the Informatics Study Program to be more selective in analyzing the eligibility of students to take part in the MBKM program it has chosen. For this reason, a decision support system is needed that can assist the study program in determining and assessing the eligibility of these students. This study created a DSS modeling using the Analytical Hierarchy Process (AHP) method and the Technique For Order Preference by Similarity to Ideal Solution (TOPSIS) using 8 criteria.