This study aims to develop an automatic detection system to improve lift safety through early detection and rapid response to sling failure. The research method uses an experimental approach by designing a 3-story lift prototype that integrates a Raspberry Pi Pico microcontroller as the main processing unit, an HC-SR04 ultrasonic sensor to detect lift position, a limit switch to detect sling failure, and a mechanical braking system using a servo motor. The system is equipped with an I2C LCD for real-time display, Telegram notifications for remote monitoring, and a buzzer alarm as an early warning. The test results show that the ultrasonic sensor has a high accuracy of 97.58% with an average error of 2.42%. The system successfully detects sling failure and activates mechanical braking automatically, preventing the basket from falling freely and allowing it to stop on the nearest floor. All control functions such as navigation buttons, motor rotation direction, and limit switch accuracy work well. This system provides an innovative solution to improve elevator safety through the integration of automatic detection technology, real-time monitoring, and direct physical response that can be applied to the development of future elevator safety technology.

Query is the ability to display and or request data that is used to access data in the database system by using certain commands. Where a data obtained from one or more tables in the database according to what the user needs. The data can also interact with other data or tables with the aim of making it easier for the user to use it. The query response time is one of the considerations for testing databases. This journal will discuss two types of databases, namely MySQL (SQL) and MongoDB (NoSQL). Due to the increasing demand for data, data processors are competing to provide the right database with the best performance for applications or data processing. Then this journal provides a comparison analysis of MySQL and MongoDB databases in response time performance. This study uses the Query Runtime comparison execution test method between these databases. By using basic commands or DML queries, namely CRUD (Create, Read, Update, Delete). Several stages will be carried out, namely the determination of the dataset, implementation and testing, and analysis of the test results. In this study, trials were conducted on the insert, select, update, and delete processes with the data being tested were 100, 1000, 10000. After experimenting with MongoDB (NoSQL) and MySQL(SQL) databases. The MongoDB database has a faster query response time in the insert and delete process, for the query response time update and delete the MySQL database has a faster response time. Then it can be obtained that in query response time, the MongoDB database is superior in the update and delete processes with a runtime difference of 0.005 seconds and 0.017 seconds. MySQL database is superior in insert and select process with a difference of 4.137 seconds and 0.006 seconds.

Rafka Baby Convection is an industrial business that produces baby clothes that has been established since 22 years ago. Sales data collection at the Rafka Baby Convection is still done manually. This study aims to find out what are the needs and problems in sales data collection and to design a sales database in developing the Rafka Baby Convection business. The method used in this study is the method of data collection by interview and literature study, as well as the system design method, which means the author designs a new database system based on the results of data collection. The results show that sales at Rafka Baby Convection are still manual in the sense that sales are made without a database system regarding the goods sold, buyers, payments, and transactions. Therefore, a database design was made to help collect data on the Rafka Baby Convection. The database created is designed using a MySQL database and is managed in the PhpMyAdmin application. This database design is expected to be able to provide convenience in collecting sales data at Rafka Baby Convection.

In writing this study aims to review the implementation of tree data structures on web blogs as learning media, starting from a discussion of the implementation of data structures. After that, it was continued with the use of blogs as an applied learning medium. The use of tree data structures is one of the most common data structures used in the development of a web. One of the efforts to streamline and provide a variation in the realm of learning media is to create a web blog, especially in the era of globalization, everyone who lives in that era should at least know about one of the results of technological and communication advances. This study will see how the description or description of the application of tree data structures on blogs as learning media. The making of this research uses a qualitative descriptive method in which the data is obtained from observation and documentation of matters relating to the topic under study. The core discussion of this research is the implementation of data structures on blogs as learning media.