This study aims to optimize the object identification process, especially identifying trash in the house compound. Most object identification methods cannot distinguish whether the object is a real image (3D) or a photographic image on paper (2D). This is a problem if the detected object is moved from one place to another. If the object is 2D, the robot gripper only clamps empty objects. In this study, the Sequential_Camera_LiDAR (SCL) method is proposed. This method combines a Convolutional Neural Network (CNN) with LiDAR (Light Detection and Ranging), with an accuracy of ±2 mm. After testing 11 types of trash on four CNN architectures (AlexNet, VGG16, GoogleNet, and ResNet18), the accuracy results are 80.5%, 95.6%, 98.3%, and 97.5%. This result is perfect for object identification. However, it needs to be optimized using a LiDAR sensor to determine the object in 3D or 2D. Trash will be ignored if the fast scanning process with the LiDAR sensor detects non-real (2D) trash. If Real (3D), the trash object will be scanned in detail to determine the robot gripper position in lifting the trash object. The time efficiency generated by fast scanning is between 13.33% to 59.26% depending on the object’s size. The larger the object, the greater the time efficiency. In conclusion, optimization using the combination of a CNN and a LiDAR sensor can identify trash objects correctly and determine whether the object is real (3D) or not (2D), so a decision may be made to move the trash object from the detection location.

This study aims to design and create a Digital Prayer Schedule system at Masjid UPI "YPTK" Padang using Arduino as a controller. Prayer schedule data can be taken from the Indonesian Ministry of Religion website and stored on a MicroSD card. Likewise with the lecturer activity schedule data, also stored in the MicroSD. This data is processed by the Arduino module based on the program stored therein. The output is in the form of a prayer times display on Seven Segments and a lecturer activity schedule display on Running Text. The first time the device is activated, it must be set up using the input button. The setting process includes setting the date, time and iqomah pause time settings. After the data is saved, it is automatically displaying the date, time and the prayer times on Seven Segments. The system also automatically displays the names of lecturers who are tasked with reading the Qur'an, sayings Asmaul Husna and praying on the Running Text based on data stored on the MicroSD card. Testing is done by activating the equipment for a week non-stop. The system is tested both in terms of component durability in operation and timeliness in activating the Buzzer when prayer time has entered. After testing the designed equipment, the date, time and prayer times can be displayed properly on Seven Segments and the schedule of lecturer activities also can be displayed well on the Running Text. Thus the system can be used and produced on a larger scale.