The impact of the COVID-19 pandemic is very broad, especially in Indonesia. In early 2022, Indonesia entered the early stages of recovering conditions caused by the pandemic. The government has an option for the community to carry out a third dose of vaccination (booster). However, there are a number of pros and cons in the community regarding the booster vaccine. This study aims to conduct sentiment analysis related to public opinion on the COVID-19 booster vaccination in Indonesia with Naive Bayes model. The data source used comes from Twitter. The workflow of this research includes data crawling, labeling, preprocessing, dataset sharing, and model testing and comparison with other models, namely Decision Tree and SVM. The results of this study indicate that the largest AUC score falls to the SVM model (75.40%), but for more accurate precision falls to the Naive Bayes model (83.81%). In addition, there is a confusion matrix which shows that the Naive Bayes model trial is running well.

Agile have been widely used by companies. With using of Agile, the project will be more flexible when compared to the traditional method (Waterfall). However, the use of Agile has many challenges, including its agile nature and iterations. This makes us interested in conducting further investigations regarding risk management practices in Agile following an outsourcing company in Indonesia. The system created is in the form of a job marketplace in which there are job vacancies to support outsourced activities at the company. The purpose of this research is to identify what risks are faced related to development with Agile methods at the company. Related to this, identification will be carried out using risk management combined with Agile development methods. The results of this research indicate that there are four risks that are quite critical in the application of Agile methods, namely human factors, communication factors, changing requirements factors, and schedule factors.

The impact of the COVID-19 pandemic has paralyzed the business sector, resulting in changes in business activities in many companies today. Many companies are competing to digitize their business, PT XYZ is one of them. PT XYZ is a company engaged in outsourcing. Outsourcing companies are one of the many types of companies that have been heavily impacted during the COVID-19 pandemic. In order to restore its business, PT XYZ has an innovation in the form of a job portal. PT XYZ always strives to market its job market. This is the biggest challenge that PT XYZ has on its job portal. Therefore, it is necessary to apply big data to be utilized by PT XYZ. This study reviews the application of big data on the job portal of PT XYZ. The implementation of big data refers to the five characteristics of big data (5V), volume, variety, velocity, veracity, and value. The method used to obtain data in this study is through interviews and observation. The results of this study indicate that the five characteristics meet the criteria for the application of big data. This allows PT XYZ's job portal to apply big data analytics to its marketing strategy.

Public transportation services in Indonesia, especially Jabodetabek, have used social media, especially Twitter, as a way to improve services. Currently, the use of online transportation services is like a need; it is necessary to conduct a sentiment analysis of online transportation to find out how people respond to these online transportation services. This research was made to analyze community responses with data analysis in the form of tweets that filtered with a public transportation-related keyword then classified into positive and negative classes using the Naïve Bayes Classifier method. Based on the system built, the total sentiment results for the percentage of the occurrence of positive words were 0.507843137, and the sentiment results for the percentage of negative word occurrences were 1.4132493. The results show that the level of negative sentiment from public tweets is greater than the level of positive sentiment.

Blind is a condition of a person who has a disturbance in his vision, obstacles in seeing. The blind are divided into two categories, those who are totally blind and those with residual vision. For this problem, we need an assembly tool that is smart, automatic and makes it easier for blind people and can assist in the activities of a blind person in walking and help tell if there is an object in front of him, this tool will emit a loud sound sensor so that the blind person can hear it. The author designed an Ultrasonic Belt to help the Blind Walk with Arduino Uno R3 and the HC-SR04 Module by using a proximity sensor to determine the presence of objects in front of it, the buzzer immediately emits a sound with a minimum or closest distance of 1 cm and the furthest distance of 1.5 meters is still detected if there are objects in the area. in front of him.