The Automatic Identification System (AIS) is a maritime identification and tracking system that must be implemented on certain vessels in accordance with the regulations of the International Maritime Organization (IMO). One of the ways to enhance maritime safety on ships is by utilizing AIS. This research aims to develop a low-cost AIS intended for use on small vessels such as fishing boats. This study utilizes hardware components such as the GPS M8N, Arduino Nano, and LoRa RA-02 module. The LoRa module is chosen for its ability to transmit data over long distances with low power consumption, making it ideal for maritime applications. The Arduino microcontroller is responsible for controlling the entire system, while the GPS M8N is highly effective in achieving accurate positioning within meter-level precision. The Arduino Nano serves as the main component for receiving and processing data from the GPS M8N and LoRa RA-02, then transmitting the data to the receiver. The methodology and system design in this research follow an experimental approach, where at least one variable is manipulated to study cause-and-effect relationships. The test results of the AIS transmitter device indicate that it can successfully transmit call sign, latitude, and longitude data, with a maximum transmission range of 15 meters on land and 13 meters at sea.

The Unmanned ships have become a primary focus in maritime technology development to enhance efficiency and navigational safety in waters. In this research, a unmanned ship utilizing ESP32CAM as its core system is designed to detect navigation lights of other vessels and avoid potential collisions. The initial response of the ESP32CAM camera reads the colors of lights approaching the unmanned ship within a distance of less than 100cm. The ESP32CAM reads and identifies colors through image processing. When the ESP32CAM detects green and red lights, it commands the buzzer to sound. The color detection system works such that when the ESP32CAM detects a red light, it sends a signal to the servo motor to move left, and when it detects a green light, it sends a signal to the servo motor to move right. The servo motor functions as the ship's rudder. Testing of the navigation light system with ESP32CAM camera to prevent ship collisions is conducted with predetermined scenarios, including testing with red LEDs, green LEDs, and overall system testing. The results show that the navigation light system with ESP32CAM camera functions well. The ESP32CAM camera can optimally identify light colors at a distance of 100cm. Based on the conducted research, the ESP32CAM camera is capable of reading both the distance and colors of lights as specified at a distance of 100cm.

The phenomenon that occurs in the load lifting system is the need for an efficient and reliable mechanism to move the crane hoist pulley vertically and horizontally. This study aims to design and test a crane hoist system that uses a DC motor and a stepper motor controlled by an L293D motor driver, and to develop an application based on MIT App Inventor to control the movement of the motor. The research method used is integrated hardware and software design, followed by testing the performance of the motor, driver, and the application developed. Testing was carried out under limited load conditions, to measure the motor speed, voltage, and current used at loads of 10 to 100 grams. The results of the study showed that the system can function well at varying speeds, and the motor is able to lift a maximum load of up to 100 grams with a speed that decreases according to the weight of the load. The MIT App Inventor application successfully controls the motor effectively via a WiFi connection with a maximum distance of 10 meters, and loads the operation of the crane vertically and horizontally. This study proves that the designed system is able to work optimally in lifting and moving loads, and the application developed provides easy and efficient control.