<p class="Abstract">The quadcopter represents one of the emerging research areas in unmanned aerial vehicle (UAV) technology. One of its advantages lies in its simple mechanism and smaller propeller size compared to helicopters, while maintaining the same lifting capacity. The quadcopter employs inner and outer control schemes, where the inner control manages attitude roll, pitch, yaw, and altitude, thereby affecting the motion of the quadcopter. Meanwhile, the outer control governs the direction of the quadcopter's movement. This condition underscores the significance of inner control, ensuring the quadcopter's maneuverability. Consequently, there is a need to design an attitude, pitch, and roll control using the PID method. This experiment focuses on roll and pitch control under hover conditions. The PID control experiment yielded optimal results with parameters K_P = 60, K_I = 22, and K_D = 14, exhibiting rapid response, absence of oscillation, deviations smaller than 20^o in both roll and pitch controls, and the ability to return the attitude to the initial setpoint position when disturbances occur.</p><p>                                                                                                 </p><p class="IndexTerms"><strong>Keywords</strong>: Attitude, hovering, PID controller, quadcopter.</p><p> </p><p class="Abstract" align="center"><strong>ABSTRAK</strong></p><p class="Abstract">Quadcopter merupakan salah satu bidang riset yang baru dalam teknologi unmanned aerial vehicle (UAV). Salah satu keunggulan pada Quadcopter adalah mekanisme yang sederhana dan ukuran pada baling-baling yang lebih kecil dibandingkan dengan helicopter dengan daya angkat yang sama. Quadcopter memiliki skema kendali inner dan kendali outer, dimana kendali inner mengendalikan attitude roll, pitch, yaw, dan altitude yang berimplikasi pada gerak quadcopter. Sedangkan kendali outer mengendalikan arah gerak quadcopter. Kondisi ini menjadikan kendali inner sangat penting sehingga mampu menjaga quadcopter dapat bergerak. Untuk itu perlu dirancang suatu kendali attitude pitch dan roll dengan metode PID. Eksperimen ini focus pada kendali roll dan pitch di kondisi hover. Hasil eksperimen kendali PID pada roll dan pitch didapatkan hasil terbaik pada parameter K_P=60, K_I=22, dan K_D=14 yang memiliki respon cepat, tidak terjadi osilasi, lonjakan lebih kecil dari 20^o baik pada kendali roll maupun pitch, dan mampu mengembalikan attitude pada posisi setpoint awal apabila diberi gangguan.</p><div id="gtx-trans" style="position: absolute; left: -26px; top: 21px;"> </div>

<p><em>Internet of Thing</em><em> </em><em>(IoT</em><em>) technology is able to manage devices to collect and exchange data over the internet network. IoT is one of the keys to implementing Industry 4.0 in various sectors such as manufacturing, transportation and even education. IoT can be utilized for laboratory device management. The Production Systems Laboratory, Faculty of Engineering, Dian Nuswantoro University has CNC-based machines such as a CNC router machine with the G-Eike brand type WK1212. Through the implementation of IoT, user data, operational time, and electricity such as voltage and current while the CNC machine is operating can be sent and stored on a database server. Furthermore, analysis of the data is carried out for various purposes such as predicting machine maintenance schedules. The results of the research that has been carried out regarding the design of user authentication systems and electrical monitoring of the CNC machine have been tested with good results in extracting the required data via IoT to then be used in predicting machine maintenance. It is known from the test results that the user (student) authentication system can be carried out by inputting a username and password based on student data registered by the laboratory assistant. Electrical data (voltage, current, power, energy, frequency and power factor) is successfully sent from the control panel periodically every 10 seconds to the broker. The broker managed to save the data received into the MySQL database.</em> </p><p> </p><p class="IndexTerms"><strong>Keywords</strong>: Internet of Thing, CNC Router, G-Weike WK1212, Autentikasi, Monitoring.</p><p> </p><p class="Abstract" align="center"><strong>ABSTRAK  </strong></p><p class="Abstract">Teknologi Internet of Thing (IoT) mampu mengelola perangkat untuk mengumpulkan serta bertukar data melalui jaringan internet. IoT menjadi salah satu kunci dalam penerapan industri 4.0 di berbagai sektor seperti manufaktur, transportasi, dan bahkan pendidikan. IoT dapat dimanfaatkan untuk manajemen perangkat laboratorium. Laboratorium Sistem Produksi Fakultas Teknik Universitas Dian Nuswantoro memiliki mesin-mesin berbasis CNC seperti mesin CNC router dengan Merk G-Eike tipe WK1212. Melalui penerapan IoT maka data pengguna, waktu operasional, dan kelistrikan seperti tegangan dan arus selama mesin CNC beroperasi dapat dikirim dan disimpan pada server basis data. Selanjutnya, analisis terhadap data tersebut dilakukan untuk berbagai keperluan seperti memprediksikan jadwal pemeliharaan mesin. Hasil dari penelitian yang telah dilakukan terkait perancangan sistem autentikasi pengguna dan monitoring kelistrikan mesin CNC tersebut telah diuji dengan hasil yang baik dalam menarik data-data yang dibutuhkan melalui IoT untuk kemudian dapat dimanfaatkan dalam prediksi pemeliharaan mesin. Diketahui dari hasil uji tersebut sistem autentikasi pengguna (mahasiswa) mampu dilakukan melalui input username dan password berdasarkan data mahasiswa yang didaftarkan oleh asisten laboratorium. Data kelistrikan (tegangan, arus, power, energi, frekuensi dan power factor) berhasil dikirim dari kontrol panel secara periodik tiap 10 detik ke broker. Broker berhasil menyimpan data yang diterima ke dalam database MySQL.</p>

<p><em>Self driving cars are an interesting topic to discuss due to the high level of traffic accidents that occur due to human error. Self driving cars are vehicles that can find out about the environment with minimal human intervention. Self driving itself has many development methods such as Light Detection and Ranging (LIDAR), cameras, radars, or a combination of these sensors. This study made a prototype self-driving car using a camera as a sensor and a neural network algorithm for pattern recognition. The pattern recognition in question is the image recognition of the path taken. The data that has been taken will later be converted into a matrix with dimensions of 320x120 according to the image resolution. Then the data will be trained to recognize the path pattern with the proportion of 7: 3 for training accuracy and validation accuracy. The resulting prediction has an accuracy of 76.86% for training accuracy and 75.24% for validation accuracy.</em></p>