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All Journal International Journal of Electrical and Computer Engineering International Journal of Reconfigurable and Embedded Systems (IJRES) ComEngApp : Computer Engineering and Applications Journal TELKOMNIKA (Telecommunication Computing Electronics and Control) Jurnal Teknologi Informasi dan Ilmu Komputer Register: Jurnal Ilmiah Teknologi Sistem Informasi Journal of Information Technology and Computer Science Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi Dinamisia: Jurnal Pengabdian Kepada Masyarakat
Dahnial Syauqy
Fakultas Ilmu Komputer, Universitas Brawijaya
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Social Sciences Other

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Sistem Navigasi Waypoint Pada Robot Beroda Berdasarkan Global Positioning System Dan Filter Kalman A. Ashar Ashari; Eko Setiawan; Dahnial Syauqy
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 4 No 7 (2020): Juli 2020
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Wheeled robot is one of the most popular categories of mobile robots in the field of its science development. By its functional aspect, a wheeled robot is expected to be able to assist humans in terms of optimized transportation, unmanned exploration vehicle, and etc. The wheeled robot development will continue to run, and as well as its problem of sensor readings, positioning, and navigation system. Waypoint takes an important part in terms of developing navigation systems. In its application, waypoint navigation systems on a wheeled robot are used for reading a correcting position mistake, from GPS data alongside a sensor capable to pinpoint a heading and acts like a compass that can be able to establish a rotational motion. This research has the aim to improve the accuracy of reading data from the GPS module with or without implementing the Kalman Filter and also establishing rotational motions. The results of the research conducted, it was concluded that the accuracy of the magnetometer sensor is at the limit around 1° - 2 ° at the fault tolerance limit with testing parameters 6.1, 7.1, 8.1, 9.1, and 10.1. From the results of the GPS module, it was found that the level of module accuracy varies but is still within a 10m success radius
Klasifikasi Arah Gerak Diagonal Mata dan Normalisasi Sinyal Electrooculography dengan Metode Diferensiasi Muhajir Ikhsanushabri; Rizal Maulana; Dahnial Syauqy
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 4 No 8 (2020): Agustus 2020
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Communication is very important for people like Amyotrophic Lateral Sclerosis (ALS) patients who are not able to speak and write, but not with eye movements. At present, there are already several techniques that can read eye movements using the method based on video that has a high price that using signal calculations with input of images called image processing. This signal requires a camera that supports images with a high degree of accuracy and consideration factors that cause noises. One of these factors is lighting so that this method will require a very large cost. Therefore, an alternative is needed that can make eye movements using bio-signals in the body that issupported by movements using Electrooculography (EOG) that supports the direction of eye movements. This research discusses the signal normalization use Differentiation Method. The system can classify of eye movement 8 directions sen ton 8 LEDs. Based on the results of accuracy for eye movement direction is about 100% and based on the results of average accuracy the whole system by taking 5 samples of people is about 79.25%.
Implementasi Low Power State Machine pada Sistem Notifikasi Kecelakaan Sepeda Motor Lutfi Anang Makruf; Eko Setiawan; Dahnial Syauqy
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 4 No 9 (2020): September 2020
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

In this modern era a motorcycle is very common means of transportation to use. With the increasing population of motorcycle users, accidents caused by motorbikes cannot be avoided. In general, accidents cannot be predicted when and where accidents occur. By using an accident notification system on a motorcycle, it will be easier to find out the location of the accident. So that the device does not consume excessive power on a motorcycle battery, it must have a low power mechanism to be able to save power. Low power and state machine mechanisms can be implemented in a prototype system that serves to inform that an accident has occurred by sending a short message containing the location of the accident. In testing the accuracy and functional levels of several components obtained results that are as expected. The MPU6050 sensor has an accuracy of 84.43%, the NEO6M module has an accuracy of 99.99% and the functional module SIM800L can send short messages properly. In testing the low power mechanism can reduce the power consumed by 22.2 mA or 18.8%. The device consumes power of 117.7 mA without using a low power mechanism and consumes power of 95.5 using the low power mechanism.
Sistem Kendali Kecepatan Robot Beroda Pada Jalan Menanjak dan Menurun Menggunakan Metode Proportional Integral Derivative Muhammad Hanif Haikal; Dahnial Syauqy; Gembong Edhi Setyawan
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 4 No 10 (2020): Oktober 2020
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Abstract The development of the world of robotics is increasingly rapid, there is a human urge for all problems that arise around it so that it can be resolved quickly and efficiently. These problems are human limitation in processing control and a very long time, so that the more advanced the new technological era is, the more it is founds. For example in controlling speed on wheeled robots in terms of helping humans. The speed control system will be researched and applied to the skidsteering wheeled robot. This robot is equipped with an optocoupler sensor, Arduino UNO microcontroller and Motor Driver Shield L293D. this research method used is the Proportional Integral Derivative (PID). The access used is in the form of uphill and downhill roads on the slope of 10°, 15°,20° with the distance about 2m. From the simulation, the results are able to provide good control system performance criteria which can be seen from the comparison of the controller without using the PID controller and by using the PID control. PID contorl paramaters used to control DC motors are able to provide the most ideal control respone, with values of Kp = 0.2, Ki = 0.12 and Kd = 0.01. And when the robot run in the incline and descent area with an angle of 10°, 15°,20°, it has experienced a significant decrease in speed
Sistem Deteksi Perpindahan Kendaraan Bermotor Berdasarkan Data GPS dan Sensor IMU Menggunakan Naive Bayes Wirafadil Nugraha; Dahnial Syauqy; Agung Setia Budi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 1 (2021): Januari 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

The security system in vehicles is something that must be considered because vehicles are often stolen which results in losses to the vehicle owner. Ease of control and a security system that can be monitored using only one communication device such as a mobile phone that can support a wireless connection is an opportunity to develop a vehicle security system. By designing a vehicle displacement detection system based on GPS data and the IMU sensor, it will become a more accurate tool to determine the condition of vehicles. In order for the system to classify the current situation more accurately, the Naive Bayes algorithm is applied. The use of GPS data in this study uses the NEO-6M module because a vehicle must be closely related or always have a coordinate location as long as it is within satellite coverage. This data is used as input along with data from the IMU sensor used in this study using the GY-61 accelerometer sensor. From this research test, the NE0-6M module has an accuracy value of 99.99%, the GY-61 sensor has an accuracy of 87,68%, and the SIM800 module can functionally run well. In the classification process that using Naive Bayes, an accuracy of 95% is obtained.
Kendali Posisi Robot Beroda Dengan Sistem Global Positioning System (GPS) Menggunakan Proportional, Integral dan Derivative (PID) Berbasis Arduino Mega 2560 Duwi Hariyanto; Eko Setiawan; Dahnial Syauqy
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 1 (2021): Januari 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

A wheeled robot is a technological innovation that makes it easier to mobilize exploration. In carrying out the exploration, the wheeled robot has several obstacles, namely the unstable reading of the robot's position. From this problem, the researcher designed a wheeled robot position control system by adjusting the accuracy of the robot's position. The process of monitoring the position of the robot uses the Ublox Neo-6m GPS module which is controlled by the Arduino Mega2560. Latitude and longitude data obtained from the GPS sensor will be converted into a distance and processed into control. The control used to adjust the position of the robot is PID (Proportional Integral Derivative). For the calculation of PID, this research uses the Zigler-Nichols tuning method in getting to a point. In this study, several tests were carried out for the four controls. The results showed that they had a good response to P and PD controls. Because the two controls achieved set points and had a slight error, where the P control has reached the setpoint in 56.378 seconds with an error = 0.1026 meters with a Kp value of 9.4. Meanwhile, PD control in achieving the target takes 57.384 seconds with an error = 0.1481 meters with a value of Kp = 11.38 and Kd = 11.47.
Pemetaan Ruangan Menggunakan Ar.Drone Dengan Metode LSD-SLAM Yanottama Oktabrian; Eko Setiawan; Dahnial Syauqy
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 1 (2021): Januari 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Quadcopter is an Unmanned Aerial Vehicle or UAV which has four propellers on its four sides. Nowadays quadcopter often used to help enrich human's life. Quadcopters need basic abilities. One of basic ability it needs is moving. To be able to move automatically the prerequisite is positioning. Positioning is used to determine quadcopter position in an environment. In robotics this problem is named Simultaneous Localization and Mapping or SLAM. Robot system usually uses Global Positioning System (GPS) to determine its location. GPS is primary method to determine robot position at outdoor environments. The problem occurs when GPS is being used in an indoor environment. GPS have low accuracy when used in a closed building. This problem made localization and mapping using GPS in an indoor environment rather difficult, thus another device is needed for SLAM processing. One of device that can be used to determine a quadcopter position is camera. In this research, writer will determine quadcopter position in an indoor environment using Large Scale Direct Monocular SLAM (LSD-SLAM) on an Ar.Drone 2.0. LSD-SLAM library will run using Robot Operating System (ROS) in a Ground Control System (GCS) computer. The results show that Ar.Drone can send images to GCS computer very well. System also can determine movement estimation of quadcopter using images that sent from Ar.Drone integrated camera which will be processed by LSD-SLAM library.
Implementasi Algoritme K-Nearest Neighbour Untuk Penentuan Pada Sistem Rekomendasi Pose Menembak Senapan Angin Mochamad Iswandaru; Dahnial Syauqy; Mochammad Hannats Hanafi Ichsan
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 2 (2021): Februari 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Shooting training so important for improve the quality of shooting accuracy, especialy for air rifle. Trainer is the important part when the athlete doing training because they can see and evaluate the training. One of indicator that trainer see when the athlete doing excercise is the movement of the rifle. Not every athlete can have trainer especialy amateur one. Stable movement of the rifle indicating that the position was right. From the problem above, need research that can replace trainer to give evaluation. To read the rifle movement in this research using HMC5883L magneto sensore with Arduino Nano using K-Nearest neighbor Algorithm. KNN methode used to find degree of angle from the rifle movement. From several test from HMC5883L sensore aquired 8,68% error percentage. From testing value of "K" aquired sucsses rate is 96%. From 10 times experiment that tested on user, system can get same value as the evaluation table was made.
Implementasi Sistem Pendeteksi Premature Ventricular Contraction (PVC) Aritmia menggunakan Metode SVM Ahmad Rizqi Pratama; Rizal Maulana; Dahnial Syauqy
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 2 (2021): Februari 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Premature Ventricular Contraction (PVC) Arrhythmia is a condition in which the heart beats irregularly. The PVC condition causes the heart to beat too fast or be too slow than it should be. PVC Arrhythmias appear in the lower part of the heart or commonly called the ventrical (chambers) of the heart. Patients with PVC Arrhythmia have a risk of experiencing heart failure, coronary heart disease, and other heart diseases if the PVC Arrhythmia condition occurs continuously. Currently, PVC Arrhythmia can only be detected in the hospital at a cost that is quite expensive. Therefore, research in detecting PVC Arrhythmias is needed in order to solve the cost problem required. There are several parameters that can be used in detecting PVC Arrhythmias, in this study the QRS Interval, QT Interval, and ST segment were selected as parameters. These parameters are in each cycle of the ECG signal which will be read using the AD8232 sensor. Reading the ECG signal requires 3 electrodes attached to the user's body. The placement of the electrodes is on the chest by attaching 2 electrodes and on the stomach by attaching 1 electrode. The ECG signal obtained by the AD8232 sensor will then be processed on the Arduino Uno to reduce the noise obtained and classified by the Support Vector Machine (SVM) method. The use of training data as much as 46 heart data with 23 types of PVC data and 23 types of normal data will be embedded in the SVM method. SVM classification testing was carried out with 20 cardiac data. Classification test results are in the form of class "Normal" or "PVC". Every 3 SVM classification results will be used to determine the type of heart condition. Types of heart conditions include "Normal", "Bigeminy", and "Trigeminy" which will later be shown on the LCD so that users know the condition of their heart. In testing the SVM accuracy level, it was obtained a value of 85% with 1.79 seconds of average training time and 2.49 seconds of average testing time.
Sistem Deteksi dan Klasifikasi Jenis Kendaraan berbasis Citra dengan menggunakan Metode Faster-RCNN pada Raspberry Pi 4B Mela Tri Audina; Fitri Utaminingrum; Dahnial Syauqy
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 2 (2021): Februari 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Vehicles that exceed road capacity will have a negative impact on their surroundings, one of which causes accidents. Examples of cases of accidents that often occur are vehicles traveling in lanes that are not supposed to be, such as vehicles other than the busway crossing the busway lane and when driving on the Pantura highway which has more than 2 lanes, sometimes drivers find it very difficult to pay attention to the lane on the left, if you want. overtaking the vehicle in front of him. Therefore a system is needed to notify drivers to be more careful when driving. In this system there is a notification if there are numbers and types of vehicles in front. This system uses the Faster Regional Convolutional Neural Network modeling made on Tensorflow by processing it on a mini computer or Raspberry Pi 4B. The accuracy result in this system is 0.9025 or 90.25% with an average computation time in the Raspberry Pi 4B of 7,638 seconds per image.
Co-Authors A. Ashar Ashari A. Baihaqi Mubarok Abdul Aziz, Muhammad Rafi Abdul Rahman Halim Abdussalam, Ghifarie Sa'id Achmad Basuki Achmad Fanani Kurniawan Saputra Achmad Rizal Zakaria Addin Miftachul Firdaus Adharul Muttaqin Adhisuwignjo, Supriatna Adhitya Bhawiyuga, Adhitya Adi Setiyawan Adinugroho, Sigit Adit Ilmawan Adryan Chiko Pratama Afdy Clinton Afflatuslloh Adi Salung Agastya Bramanta Sanjaya Aghnadiin, Radifan Muhammad Agi Putra Kharisma Agra Firmansyah Agung Bachtiar Sukmaarta Agung Leona Suparlin Agung Prasetyo Agung Setia Budi Agung Setia Budi, Agung Setia Agung Widya Gumelar Agung Wismawan Rochmatullah Ahmad Mustafidul Ibad Ahmad Rizqi Pratama Ahmad Wildan Ahmad Yazid Bastomi AJI, IBRAHIM Akbar, Muhammad Daffa Pradipta Akbar, Muhammad Faithur Adel Patria Alfian Reza Pahlevi Alrynto Alrynto Althaf Banafsaj Yudhistira Andhika Nino Pratama Anggi Diatma Styandi Angsar, Mohamad Rinaldi Anisa Awalia Rizky Anjasmoro, Reza Ardiansyah Ardiansyah Arief Kurniawan Arief Wahyu Wicaksono Aulady, Fadhli Aulia Zhafran Barlian Henryranu Prasetio Bayu Rahayudi Bayu Santoso Belsazar Elgiborado Giovani Djoedir Billy Gusparentaqi Bima Muridianto, Muhammad Bimo Dimas Nugraraga Buce Trias Hanggara Bukhori Darmawan Bunga Boru Hasian Siahaan Cahyanita Qolby Rahmarta Rizaputri Cipto Bagus Jati Kusumo Constantius Leonardo Pratama Dading Firwandhi Sukma Daffa, Ali Zhafran Dedi Siswanto Defri Alif Raihan Denis Reza Ramdani Devo Harwan Pradiansyah Dimas Rizqi Firmansyah Dini Eka Ristanti Dini Ismawati Duwi Hariyanto Dwi Arini, Talitha Dwi Firmansyah Dwiki Ilham Bagaskara Dyas Restu Palupi Edita Edita Rosana Widasari Edita Rosana Widasari, Edita Rosana Eka Nanda Sugianto Eko Ardiansyah Eko Hilmi Firmansyah Eko Setiawan Eko Setiawan Elisabeth Agustina Era Imanningtyas Ezra Maherian Fachry Ananta Fahmi Gymnastiar Gozali, Muhammad Faizal Ardiansyah FAQIH, ABDULLAH Farras Nabil Fatur Rahman, Mohammad Fauzi Ali Farhi Fauzi Rivani Fikri Fauzan Firdy Yantama Firmanda, Dwi Ady Firza Zamzani, Muhammad Fitriyah, Hurriyatul Fungki Pandu Fantara Ganda Wibawa Putra Gembong Edhi Setyawan Ghazy Timor Prihanda Govinda Dwi Kurnia Sandi Graciella Fiona Br. Panjaitan Grafidi, Alif Akbar Gunawan Wahyu Andreanto Hafidz Abdillah Masruri Hafiz Nul Hakim Hamdan Bagus Firmansyah Hamzah Attamimi Hanggara, Buce Trias Hannats Hanafi Ichsan Haqiqi, Farih Akmal Harahap, Syazwandy Hazal Kurniawan Putra Hazbiy Shaffan, Nur Henryranu Prasetio, Barlian Herenda Madi, Matius Herwin Yurianda Hurriyatul Fitriyah Hurriyatul Fitriyah Hurriyatul Fitriyah, Hurriyatul Idang Wahyuddin Septiawan Ihsanurrahim Ihsanurrahim Ikhwan Zulfy Imam Cholissodin Irfan Pratomo Putra Irvan Ramadan Issa Arwani Ivan Kasogi Izaaz Waskito Widyarto Izza Febria Nurhayati Jeffry Atur Firdaus Jevandika Jezriel Lukas Lumbantobing Johannes Archika Waysaka Khairul Anwar Khairul Anwar Kresna Wiska Kafila Kurnia, Yudisthira Dwi Kurniawan, Rizaldy Ariobimo Kurwniawan, Wijaya La Ode Muh. Fadlun Akbar Lase, Nicolash Jeremy Onoma Latief Nurrohman Alfansuri Lavanna Indanus Ramadhan Lb Novendita Ariadana Lutfi Anang Makruf M Nuzulul Marofi M. Adib Fauzi Rahmana M. Ali Fauzi Mahendra, I Gusti Putu Krisna Suaba Malik, Hifdzul Megananda, Muhammad Rifqi Mela Tri Audina Merry Hassani, Fadila Muqtadaro Mhd. Idham Khalif Moch. Alfian Zainullah Moch. Alvin Yasyfa Salsabil Mochamad Iswandaru Mochammad Hannats Hanafi Mochammad Hannats Hanafi Ichsan Moh. Saifud Daulah Moh. Zainur Rodhi Mohammad Ali Muhsin Mohammad Faizal Ajizi Muchamad Rafi Dharmawan Muchammad Cholilulloh Muh. Syifau Mubarok Muhajir Ikhsanushabri Muhammad Alif Alfajra, Andi Muhammad Aminul Akbar Muhammad Daffa Bintang Nugroho Muhammad Eraz Zarkasih Muhammad Fadhil Sadeli Muhammad Fajaruddin Akbar Muhammad Habib Jufah Alhamdani Muhammad Hanif Haikal Muhammad Hannats Hanafi Ichsan Muhammad Irvine Fidellio Maiza Muhammad Jibriel Bachtiar Muhammad Kholash Fadhilah Muhammad Naufal Muhammad Nazrenda Ramadhan Muhammad Rizqi Zamzami Muhammad Wingga Woggiasworo Muhammad Yusuf Ramadan Mukhamad Angga Setiawan Mukhamad Roni Mukmin Mukmin Munif Cleveriandy, Ahmad Musharrif, Mohammad Faiz Mustajib Furqon Haqiqi Mutiara Pramesti Utami Muzayyin, Asep Nabila Eka Putri, Alisya Nadhifa, Nadaa Nanda Epriliana Asmara Putri Navayo, Bagja Nicho Ferdiansyah Kusna Nikmatus Soleha Niko Aji Nugroho Noveriko Noveriko Nur Aini Afifah Isbindra Nur Fuady, Muhammad Sholahuddin Nurul Ikhsan Nyoman Wira Prasetya Oggy Setiawan Parja, Mujianto Anda Perkasa, Septiyo Budi Prakoso, Aldo Hani Pramandha Saputra Prasetya, Nyoman Wira Prasetyo, Budi Eko Prasojo, Satya Haryo Pricillia, Lidya Ruth Purnomo, Welly Putra Pandu Adikara Putra Pandu Adikara Putra, Brylliano Maza Raga Jiwanda Raharja, Kahfi May Rahayu, Vina Trisnawati Rahman, Edy Raka Bagas Perdana Rakhamadhany Primananda Rakhmadhany Primananda Rakhmadhany Primananda, Rakhmadhany Randy Cahya Wihandika Rekyan Regasari Mardi Putri, Rekyan Regasari Mardi Renal Prahardis Reza Budi Pratikto Rezak Andri Purnomo Rifqi Anshari Ringga Aulia Primahayu Rint Zata Amani Rioadam Sayyid Abidin Riza Irfan, Muhammad Rizal Maulana Rizal Maulana, Rizal Rizal Setya Perdana Rizka Ayudya Pratiwi Rizky Putra Wijaya Rizqi Muh. Muqoffi Ashshidiqi Ronilaya, Ferdian Rudy Agus Santoso Sabrian Rizqika Akbar Sabriansyah Rizkiqa Akbar Sabriansyah Rizqika Akbar Sabriansyah Rizqika Akbar Sabriansyah Rizqika Akbar Safirurrasul Santoso, Mush'ab Safrudin Bendang, Dehleezto Lawanangkara Salman Farizy Nur Samuel Lamhot Ladd Palmer Simarmata Santoso, Bayu Saputro, Mauna Mohammad Wahyu Sari, Sylvia Sentosa, Azy Dwi Putra Septino, Fernando Setiawan , Eko Shaffan, Nur Hazbiy Shelsa Faiqotul Himmah Sigi Syah Wibowo Siradjuddin, Indrazno Sulaiman, Ihsan Susilo, Faizal Andy Sutikno Sutikno Syarief Taufik Hidayatullah Syauqi, Mohd Alfitra Syazwana, Selvia Tibyani Tibyani Tio Haryanto Adi Putra Toar, Mikhael Ryan Tobias Sion Julian Utaminingrum, Fitri Utomo, Satria Wahyudi Vira Muda Tantriburhan Mubarak Virza Audy Ervanda Wahyu Adi Prayitno Welly Purnomo Widasari, Edita Rosana Widhy Hayuhardhika Nugraha Putra Wijaya Kurniawan Wijaya Kurniawan Wijaya Kurniawan Wijaya, Jason Wildo Satrio Wirafadil Nugraha Wisik Dewa Maulana Wisnu Mahendra Xavierro Lawrenza Yanottama Oktabrian Yudhistira, Gevan Putra Yuita Arum Sari Yunan Alamsyah Nasution Yunus, Ahmad Haykal Yurliansyah Hirma Fajar Yusriansyah Shohibul Hamzah Zahra, Inez Bedwina Zakaria, Akhmad Nizar