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<![CDATA[perancangan robot lengan pemilah objek sesuai warna berbasis arduino mega 2560 ]]>
<![CDATA[Erwin Ramadhani]]>;
<![CDATA[Sujono Sujono]]>
<![CDATA[ MAESTRO Vol 2 No 2 (2019): Edisi Oktober 2019 ]]>
Publisher : <![CDATA[FAKULTAS TEKNIK UNIVERSITAS BUDI LUHUR ]]>
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<![CDATA[ABSTRACT In this paper designing the robot arm objects according to color. The system consists of Arduino mega 2560, Servo motor, CMUcam5 Pixy, ultrasonic sensor, and DC motor. The objects used are limas, cube and tubes, the colors used are red, yellow and blue. Using an ultrasonic sensor to detect the existence of an object, DC motors are used to drive the conveyor, the camera is used to detect the color of the object, then the data is processed by Arduino Mega 2560 using the programming algorithm. The results obtained on this robot when the active robot conveyor carries the object through the camera CMUcam5 to detect the color of the object and the conveyor will stop when the ultrasonic sensor detects the distance of < 15cm on the object, then the Pencapit robot arm will Work fetching objects and moving them to places according to their colors. So on until the object above the conveyor moves all to the respective container.]]>
<![CDATA[SISTEM KONTROL POSISI DAN EKSPANSI MEKANIK ROBOT PENJAGA GAWANG UNTUK MENGHADANG BOLA ]]>
<![CDATA[Sony Alfian]]>;
<![CDATA[Sujono Sujono]]>
<![CDATA[ MAESTRO Vol 3 No 1 (2020): Edisi April 2020 ]]>
Publisher : <![CDATA[FAKULTAS TEKNIK UNIVERSITAS BUDI LUHUR ]]>
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<![CDATA[Pada tugas akhir ini dirancang sistem kontrol posisi dan ekspansi mekanik pada robot penjaga gawang untuk menghadang bola. Sensor yang digunakan adalah Kamera Pixy CMUcam5 yang digunakan sebagai pendeteksi objek dalam hal ini berupa bola berwarna oranye. Sensor ultrasonik sebagai pendeteksi jarak antara robot dengan tiang gawang. Sensor Proximity sebagai pendeteksi ada atau tidaknya bola ke arah robot. Pneumatik sebagai penggerak ekspansi mekanik robot, dan Arduino Mega 2560 digunakan sebagai kontroler. Robot akan melacak bola dan mengikuti arah pergerakan bola dengan cara bergeser ke kanan atau kiri pada lintasan garis gawang, untuk menjaga posisi robot agar tetap tegak lurus terhadap bola. Setelah sensor proximity mendeteksi adanya bola, maka ekspansi akan dilakukan. Dari data pengujian pergeseran bola kekanan dan pergeseran bola kekiri, robot hanya mampu bergeser pada sudut akhir 5,1° terhadap bola dengan jarak pergeseran robot 29 cm pada sudut awal robot terhadap bola 30°. Dari data pengujian robot penjaga gawang pada posisi kanan gawang dan kiri gawang, robot hanya mampu bergeser pada sudut akhir 5,2° terhadap bola dengan jarak pergeseran robot 106,6 cm pada sudut awal robot terhadap bola 45°. Sedangkan dari data pengujian ekspansi robot, robot hanya mampu mendeteksi bola diposisi acak pada jarak 10 cm sampai 40 cm dengan sudut bola terhadap robot hanya -50O , -40O dan 40O , 50O.]]>
<![CDATA[PERANCANGAN MAXIMUM POWER POINT TRACKING PADA WINDBELT GENERATOR DENGAN ALGORITMA PERTURB & OBSERVE ]]>
<![CDATA[Aulia Rakhman]]>;
<![CDATA[Sujono Sujono]]>;
<![CDATA[Eka Purwa Laksana]]>
<![CDATA[ MAESTRO Vol 5 No 1 (2022): Jurnal Maestro Vol.5 No.1. April 2022 ]]>
Publisher : <![CDATA[FAKULTAS TEKNIK UNIVERSITAS BUDI LUHUR ]]>
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<![CDATA[Renewable energy is energy that comes from natural elements and its availability will not run out because it is formed from sustainable natural processes. Renewable energy is an alternative energy to replace fossil energy because it is environmentally friendly and does not produce carbon emissions. Renewable energy sources come from sunlight, wind, water flow, geothermal, etc. One of the renewable energy potentials in Indonesia is wind energy with a total potential of 60.6 GW. Utilization of wind energy can be done by using wind turbines and windbelts to convert wind energy into electrical energy. Windbelt is a device consisting of a permanent magnet, coil and tape to produce electrical energy. When the oscillating band is blown by the wind, the magnet produces a change in magnetic flux, then the magnetic flux captured by the coil produces induced emf at both ends of the coil. In order for the power generated by the windbelt to remain at its maximum point even though the wind speed fluctuates, a Maximum Power Point Tracking (MPPT) system is needed. Therefore, in this study, an MPPT system was designed using the Perturb & Observe (P&O) algorithm by controlling the length and tension of the band based on the windbelt output voltage. The optimal voltage generated by the windbelt is 8.93 Volts without using the MPPT system, while when using the MPPT system the optimal voltage is 5.05 Volts. In testing the MPPT system using a load (condition 2), the output voltage has decreased drastically because the current generated by the windbelt is so small that it cannot pass through the load.]]>
<![CDATA[OTIMISASI DAYA PEMBANGKIT PADA WINDBELT GENEARTOR DENGAN METODE PERTURB & OBSERVE (P&O) ]]>
<![CDATA[Achmad Rizky]]>;
<![CDATA[Sujono Sujono]]>;
<![CDATA[Nifty Fath]]>;
<![CDATA[Nazori AZ]]>;
<![CDATA[Suwasti Broto]]>
<![CDATA[ MAESTRO Vol 5 No 2 (2022): Jurnal Maestro Vol.5 No.2. Oktober 2022 ]]>
Publisher : <![CDATA[FAKULTAS TEKNIK UNIVERSITAS BUDI LUHUR ]]>
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<![CDATA[Energi Baru Terbarukan (EBT) menjadi energi alternatif pengganti energi fosil karena ramah lingkungan dan tidak menghasilkan emisi karbon. Energi baru terbarukan merupakan energi yang berasal dari alam yang tersedia di bumi dalam jumlah yang besar, salah satu contoh pemanfaatan energi angin. Perlu dikembangkan energi angin menjadi energi listrik. Generator sabuk angin merupakan salah satu yang dapat memanfaatkan energi angin menjadi energi listrik. Sabuk angin dapat memanfaatkan gerak atau getaran pita yang tertiup oleh angin kemudian menggerakan magnet yang berada di dekat kumparan dan menginduksi kumparan tersebut sehingga menghasilkan arus listrik.Beberapa faktor yang memperngaruhi induksi GGL terbaik dari sebuha windbelt generator yaitu : ukuran pita, ukuran magnet, jumlah lilitan kumparan, dan keceptan angin. Agar daya yang dihasilakan sabuk angin tetap berada pada titik maksimum meskipun dengan kecepatan angin yang berubah-ubah maka diperlukan sebuah sistem Maksimum Power Point Tracking (MPPT). Oleh karena itu penelitian ini merancang sebuah sistem MPPT dengan menggunakan metode Perturb & Observe (P&O) dengan cara mengendalikan (tension) pita berdasarkan tegangan keluaran windbelt. Nilai rata-rata yang dihasilkan oleh windbelt generator sebesar 1,67 Volt pada pengujian sistem tanpa beban.Pada pengujian sistem menggunakan beban tegangan keluaran dari generator windbelt mengalami penuruan yang drstis karena arus yang dihasilkan sangan kecil sehingga tidak mampu melewati beban. Oleh karena itu penelitian ini merancang sebuah sistem MPPT dengan menggunakan metode Perturb & Observe (P&O) dengan cara mengendalikan (tension) pita berdasarkan tegangan keluaran windbelt. Nilai rata-rata yang dihasilkan oleh windbelt generator sebesar 1,67 Volt pada pengujian sistem tanpa beban. Pada pengujian sistem menggunakan beban tegangan keluaran dari generator windbelt mengalami penuruan yang drstis karena arus yang dihasilkan sangan kecil sehingga tidak mampu melewati beban.Oleh karena itu penelitian ini merancang sebuah sistem MPPT dengan menggunakan metode Perturb & Observe (P&O) dengan cara mengendalikan (tension) pita berdasarkan tegangan keluaran windbelt. Nilai rata-rata yang dihasilkan oleh windbelt generator sebesar 1,67 Volt pada pengujian sistem tanpa beban. Pada pengujian sistem menggunakan beban tegangan keluaran dari generator windbelt mengalami penuruan yang drstis karena arus yang dihasilkan sangan kecil sehingga tidak mampu melewati beban.]]>
<![CDATA[PEMETAAN LINGKUNGAN KERJA ROBOT BERODA DENGAN METODE SLAM GMAPPING MENGGUNAKAN SENSOR LIDAR ]]>
<![CDATA[Noeroes Shobie Ahfan]]>;
<![CDATA[Peby Wahyu Purnawan]]>;
<![CDATA[Sujono Sujono]]>;
<![CDATA[Akhmad Musafa]]>;
<![CDATA[Indra Riyanto]]>
<![CDATA[ MAESTRO Vol 5 No 2 (2022): Jurnal Maestro Vol.5 No.2. Oktober 2022 ]]>
Publisher : <![CDATA[FAKULTAS TEKNIK UNIVERSITAS BUDI LUHUR ]]>
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<![CDATA[The wheeled robot used to deliver documents between rooms must be able to move according to the environmental conditions of the work area. For this reason, the robot must have knowledge of the conditions of the work environment to be passed. In this final project, the work area environment mapping on the wheeled robot is carried out. Mapping was done using the Simultaneous Localization and Mapping (SLAM) method. The equipment used in the mapping is a lidar sensor. The robot system consists of a raspberry Pi 4 which is used as the main controller of the robot. The robot has two sensors. The first sensor is a lidar sensor, which is used to detect the distance of the object in front of the robot. Then the IMU sensor is used to detect the robot's orientation and position changes. In the robot there is a motor driver which is used as a robot control signal processor to drive a DC motor. Map making is done by means of a lidar sensor reading the robot's working area environment. The lidar sensor output signal is processed using the SLAM gmapping method. In this test, to determine the environment of the robot's work area, using a laser scanner to produce a two-dimensional (2D) map, while estimating the position of the robot on the map using a particle filter. This simultaneous mapping uses the Simultaneous Localization and Mapping (SLAM) mapping algorithm based on Raspberry Pi 4. The results obtained are maps in grayscale. In addition to SLAM gmapping, this article also shows that there are one to three robot position 2D testing arenas.]]>
<![CDATA[PERANCANGAN SISTEM PENDETEKSIAN OBYEK BOLA DENGAN METODE FRAMEWORK YOLOv4 ]]>
<![CDATA[Jalu Nuralim]]>;
<![CDATA[Nifty Fath]]>;
<![CDATA[Akhmad Musafa]]>;
<![CDATA[Sujono Sujono]]>;
<![CDATA[Suwasti Broto]]>
<![CDATA[ MAESTRO Vol 5 No 2 (2022): Jurnal Maestro Vol.5 No.2. Oktober 2022 ]]>
Publisher : <![CDATA[FAKULTAS TEKNIK UNIVERSITAS BUDI LUHUR ]]>
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<![CDATA[In this final project, a spherical object detection system has been designed in which the final result will display the class name according to the detected object and a bounding box on the object indicating the object is detected accordingly. What will be done from having a dataset of 202 images and divided into 70% training data, 20% validation data, 10% test data. By using the YOLOv4 method, it is hoped that the detection of spherical objects will be more efficient in detecting an object that is needed, the final result of the implementation of this spherical object detection system will display a bounding box and the accuracy of objects detected on the laptop screen for testing and analysis results of the YOLOv4 method performance system. done by confusion matrix which calculates the results of accuracy, recall, precision and there are several tests to find out with different conditions the system can detect an object. In the first test, the ball was detected by being blocked by another object in the percentage value of 50%, 60%, 70% of the system being able to detect a ball object that was blocked by another object, then with an obstacle value of 80%, 90%, 100% the system could not detect a ball object.]]>
<![CDATA[PERANCANGAN SISTEM OTOMASI PENGUNCI PINTU MENGGUNAKAN E-KTP BERBASIS IOT SMARTPHONE ]]>
<![CDATA[Ichsan Maulana]]>;
<![CDATA[Sujono Sujono]]>;
<![CDATA[Peby Wahyu Purnawan]]>
<![CDATA[ MAESTRO Vol 6 No No 2 (2023): Vol.6 No. 2. Oktober 2023 ]]>
Publisher : <![CDATA[FAKULTAS TEKNIK UNIVERSITAS BUDI LUHUR ]]>
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<![CDATA[This paper discusses a door lock automation system using IoT-based e-KTP that will be monitored using a smartphone. The system consists of HC-SR04 ultrasonic sensor, Radio Frequency Identification (RFID), and EasyVR 3. HC-SR04 ultrasonic is used to detect the presence of door access users. The RFID sensor is a medium for entering the access code in the form of Unique Identification (UID), and the EasyVR 3 sensor is used to detect passwords in the form of voice signals from access users. To record the real-time of door access users, Real Time Clock DS3231 is used. The microcontroller used to manage the system's work is Arduino Mega 2560. NodeMCU ESP 8266 sends data to a smartphone as a monitoring device. MG90S servo is used to drive the door opening/closing mechanical system. To get access, users must register by entering e-KTP UID data and passwords as sound signals. Testing is carried out to evaluate the performance of the system that has been made. The test scenarios consist of door access from the inside and door access from the outside, each for users who have access and those who do not have access. The test results show that the system can secure door access only for users with access. Monitoring the system using a smartphone can work well where every instance of access use can be monitored user data and access time. However, there are still weaknesses in the mechanical part of opening / closing the door where the servo fails to open and close.]]>
<![CDATA[TRACKER SYSTEM SINGLE AXIS SOLAR CONCENTRATOR IN 2 W SUN HEAT POWER PLANT ]]>
<![CDATA[Ananda Eddy Irvine]]>;
<![CDATA[Sujono Sujono]]>;
<![CDATA[Akhmad Musafa]]>
<![CDATA[ MAESTRO Vol 6 No No 2 (2023): Vol.6 No. 2. Oktober 2023 ]]>
Publisher : <![CDATA[FAKULTAS TEKNIK UNIVERSITAS BUDI LUHUR ]]>
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<![CDATA[This paper discusses the single-axis solar concentrator tracker system for solar thermal power plants. This system concentrates the harvesting of heat from solar radiation to increase the electrical power generated from the solar thermal conversion process. The solar concentrator is designed as a parabola and can adjust the direction following the sun's motion. The overall system work is regulated by Arduino Mega 2560. A 24-volt DC motor and BTS7690 driver are used to drive the parabola. RTC DS3231 is used to provide real-time data. ACS712 sensor is used to measure the current and voltage generated. The conversion of solar heat into electrical energy is done using Peltier SP1848. All generated data is recorded to the SD Card module, which will later be used to analyze the overall system performance. The tracker system is designed to move following the sun’s position, starting from 08:00 at position 19O to 17:00 at position 139O. Update the position or direction of the parabola to 15O, done every hour. The effectiveness of the tracker is assessed by comparing the solar concentrator system that is not equipped with a tracker. From the tests conducted for two consecutive days, the tracker-equipped solar concentrator system produced an average percent increase in electrical power of 4.86% on the first day and 5.26% on the second day. The average percent increase in power for two days was 5.06%. The results show that the application of the tracker is able to increase the productivity of the solar thermal power generation system. This opens up opportunities for larger-scale deployment in solar concentrator farms.]]>
<![CDATA[Rancang Bangun Sistem Pendeteksian Objek Halang Dan Pengereman Otomatis Pada Robot Forklift ]]>
<![CDATA[Lutfi Wahyu Aryanto]]>;
<![CDATA[Sujono Sujono]]>;
<![CDATA[Akhmad Musafa]]>
<![CDATA[ MAESTRO Vol 6 No No 2 (2023): Vol.6 No. 2. Oktober 2023 ]]>
Publisher : <![CDATA[FAKULTAS TEKNIK UNIVERSITAS BUDI LUHUR ]]>
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<![CDATA[Forklifts are tools to move large and large items to the place you want to go, forklifts are widely used in the warehousing section in running forklifts an operator is needed. The problems that occur include forklifts crashing into goods in the warehouse, forklifts crashing into forklifts because of the problems that occur, a prototype of an obstacle object detection system and automatic braking on a forklift robot is made. The parts of the forklift robot are the obstacle detection system in the form of (ultrasonic sensor and pixy camera) and the automatic braking system, namely (motor driver and dc motor). ). The working principle of the forklift robot is that the forklift follows the line that has been made if the detection system can detect an obstacle object, the braking system will automatically brake with a robot distance of 20 cm from the obstacle object, after that the buzzer will turn on and provide notification if an obstacle object is detected, if the obstacle object is moved, the robot will move again until the finish. In the overall robot testing scheme, the robot will be given several objects in the form of blue block-shaped objects, red block-shaped objects and green triangular objects, the forklift robot testing scheme is carried out 6 times with objects placed in different positions. The result of testing the forklift robot is that the robot can detect obstacle objects in the form of red and blue blocks and green triangles if the position of the object is in front of the forklift robot The conclusion is that the forklift robot can detect obstacles if the object is in front of the forklift robot.]]>
<![CDATA[Rancang Bangun Robot Berkaki Enam Menggunakan Pola Gerak Tripod Gait ]]>
<![CDATA[Dhia Farhan]]>;
<![CDATA[Sujono Sujono]]>;
<![CDATA[Nazori AZ]]>
<![CDATA[ MAESTRO Vol 6 No No 2 (2023): Vol.6 No. 2. Oktober 2023 ]]>
Publisher : <![CDATA[FAKULTAS TEKNIK UNIVERSITAS BUDI LUHUR ]]>
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<![CDATA[In this study, a six-legged robot (hexapod) was designed to detect the presence of a victim by interpreting the shape of an orange cube and passing through various obstacles such as a broken road, a downhill road with rocks, a flat road with rocks, a muddy road with marshes and a stair climb using the Gait Tripod movement pattern. The hexapod is designed to have a size of 31.8 cm x 27.4 cm x 18 cm. The robot consists of 18 servo motors that each foot uses 3 servos, 2 HC-SR04 ultrasonic sensors right and left as the sensor of the distance between the robot and the wall, the TCS230 color sensor as the detection of victims and the Arduino Mega2560 as the microcontroller that regulates the work of the system on the robot. When the robot finds the victim, the LED lights up to indicate the victim has been found. On obstacles a straight path without obstacles and boundary walls up to 120 cm can move forward at a speed of 18.6 seconds with a deviation of 3.6 cm, at a distance of 80 cm has a speed of 12.8 seconds with a deviation of 11.9 cm, and at a distance of 40 cm has a speed of 7.1 seconds with a deviation of 15.9 cm. On broken road obstacles the robot can pass with a speed of 20.7 seconds, on downhill road obstacles with rocks it can pass with a speed of 20.3 seconds, on flat road obstacles with rocks it can pass with a speed of 19.3 seconds, on muddy road obstacles with muddy media it can pass with a speed of 17.5 seconds, but on stair climbing obstacles the robot fails to pass the obstacles.]]>
