<p><em>Circuit</em><em> </em><em>Board (PCB) is a micro-board containing</em><em> </em><em>various components</em><em> </em><em>electronics used in an automatic circuit. In PCB drilling is usually done</em><em> </em><em>human</em><em> </em><em>which takes a lot}when the hole in the PCB is getting more and more. And it takes precision when the eye</em><em> </em><em>touches the PCB board which gives rise to friction force and can cause</em><em> </em><em>drilling. The purpose of this research was the development of tools in the form of automated drills using computers with BCNC software as face-to-face CNC movements. The engine is driven with stepper motor and dc motor as spindle. In this BCNC software the drilling process is done by entering the codes in the form of gcode which can later be read by CNC. The coordinates of the holes in the layout that have been created are obtained by converting the layout into codes called gcode. The process is carried out using PCB designer software. Thoroughness testing on all six axes found an error </em><em>1,2</em><em>% with ten attempts each. PID implementation on DC motor obtained constant value Kp = 54,</em><em> </em><em>Ki = 38 and Kd = 0.9. As well as before drilling, the installation of drill bits must be precise so that at the time of spinning, the drill bits do not shake.</em></p>

The purpose of this research is to design and realize a pipe leak detection system that can be monitored with an Android application. Water flow sensor is used to determine the flow of water, with water flow rate analysis it is possible to know the leakage area, pipe leakage rate, and the number of leaks in pipe area if there is a water flow rate decrease. The data is processed with an NodeMCU microcontroller based on Internet of Things (IoT). The accuracy of all water flow sensors after calibration is 97,53%. When testing with the determination of each leaked area the results are appropriate. The reading of each water flow rate decrease that occurs has an accuracy of determiningthe leakage rate of 90,2% while the suitability of reading the number of leakage areas depends on the detection of the leakage area and the classification of the leakage rate. The greater the water flow reads on the sensors, the precission level to determine the level of water pipe leakage is getting better, and vice versa, this is due to sensors having variable variations in flow rate readings.