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All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control) Jurnal EECCIS Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer
Wijaya Kurniawan
Fakultas Ilmu Komputer Universitas Brawijaya
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering

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Deteksi dan Pengenalan Wajah sebagai Pendukung Keamanan Menggunakan Algoritme Haar-Classifier dan Eigenface Berbasis Raspberry Pi Hernanda Agung Saputra; Fitri Utaminingrum; Wijaya Kurniawan
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 2 (2019): Februari 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

One of the things that is inseparable from the progress of technology is security. If we only rely on a security system using human power, it is also not so effective because people also have a sense of tired. Therefore a security support system was created such as barcode, rfid card, PIN, password and etc. However, the use of media that has some security flaws namely can be lost, stolen or damaged, and abused by people who are not responsible. One of the alternatives that can be performed i.e. utilize face as data security. On the research of this system are made using Raspberries Pi 3 were integrated with the Logitech webcam C525 as input, as well as the mikrokontroller Arduino Uno as ultrasonic and light sensor processing. For LCD, buzzer, and module SIM800L is used as the output of the system to provide notification in the form of a alarm,visual text, and SMS. This system uses Haar-Classifier to detect face objects in the image captured by the webcam. Next, Eigenface method is used to get weight of face image. After weight of face image obtained, search the smallest difference in weight of face image of new faces with the image of the face on the database where the results determine how the output from the system. From the results of testing the accuracy of face detection, best accuracy is obtained at a distance of 40 cm with 100% accuracy. Overall accuracy of testing the accuracy of face recognition at a distance of 40 cm is 75%. From system integration testing software with hardware obtained percentage error of 0%. The average time of computation in recognizing a face is 0.11536 seconds.
Implementasi Purwarupa Sistem Pemantau Suhu Serta Kelembaban Berbasis XBEE Sensor Network dan Arduino Uno Mario Kitsda M Rumlawang; Wijaya Kurniawan; Rizal Maulana
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 2 (2019): Februari 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Temperature and humidity monitoring based on WSN (Wireless Sensor Network). Monitoring system based on WSN has advantages compared to cable-based in addition to installation, maintenance and repair costs. The use of XBEE-S2 is better used for long-term monitoring than nRF because it only uses a 3.3 v low voltage. Even though it is expensive in terms of cost, if it is calculated for the long term it will be better if you have to replace it regularly. The simple implementation of the temperature and humidity monitoring system in the XBEE sensor network based building can be applied in chicken farms which helps to monitor the incubator temperature remotely and the use of Arduino as a Microcontroller is the right choice because of features that match the XBEE character that requires TX and RX pins and DHT-11 sensors that require a lot of pins. The choice of topology in sending data is also very important to know before installing the system to get maximum results. The node sensor uses Arduino uno and uses the XBEE-S2 module as a medium for sending and receiving data and uses two different Topologies, star topology and tree topology, which tests distance and throughput are displayed directly on the XCTU program. Testing with tree topology has the highest throughput of 0.31 Kbps and the lowest is 0.03 Kbps while the star topology reaches the highest number of 0.59 Kbps and the lowest is 0.51 Kbps. This is due to the delivery of the star topology directly to the Coordinator.
Sistem Pendeteksi Penyakit Diabetes Melitus dan Tingkat Dehidrasi Berdasarkan Kondisi Urin Dengan Metode Jaringan Saraf Tiruan Berbasis Aplikasi Android Lamidi Lamidi; Rizal Maulana; Wijaya Kurniawan
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 2 (2019): Februari 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Diabetes mellitus and dehydration in case serious level illness can cause death. However now a days the detection of diabetes mellitus in general uses examination of blood samples, and for dehydration is only based on the analysis of the health team by some clinical signs that cause dehydration. From these problems, there is a need a research about to automation systems to detect diabetes mellitus and levels of dehydration to reduce the number of people with diabetes mellitus and dehydration that untreated. On this research, the parameters used to compare diabetes mellitus and levels of dehydration are color, ammonia levels and pH of human urine. The reason of using urine as research object is because the condition of urine can reflect health conditions in the human body. Process to determine diabetes mellitus and levels of dehydration from color, ammonia levels and pH in human urine is perform with read data color sensor TCS3200, MQ135 gas sensor, and Liquid pH sensor by the Arduino Uno microcontroller with the Artificial Neural Network method. Applying Artificial Neural Network Architecture which has an input layer of 5 units of neurons, 6 units of neurons in 1 hidden layer, and an output layer with 2 neurons. Data training is carried out on other devices just not looking for weight values, for the main system only predictions are made from sensor readings. The system has accuracy of 80% with an average computing time of 2.03 seconds.
Sistem Klasifikasi Jenis Karat Menggunakan Metode Decision Tree Berbasis Raspberry Pi Denis Andi Setiawan; Hurriyatul Fitriyah; Wijaya Kurniawan
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 2 (2019): Februari 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

A place to collect is one of the management of an object that is no longer used or rusty. At the place of the clumping, the corroded object is sorted. However, rust detection is done manually through pieces with the naked eye. This method is vulnerable to human error. Based on these problems, it is necessary to have a system that can sort out the zinc automatically to facilitate the owner. In making this system, the image taken is zinc which has been corroded. This system takes the image of rust using a webcam. Rust from the image is detected using the thresholding method, then classified into mild rust or heavy rust which results will be displayed via LCD. The percentage limit of the rust classification will be determined by the decision tree method. Testing is done to find the percentage of system accuracy, and it can be concluded that the zinc painted in the rusty section has a percentage difference of 0.02 when compared to original rust, and original rust has class accuracy of 90% compared to the original class that has been determined by experts, and the execution time of this program is around 0.59.
Rancang Bangun GPS Back Track Pada Rekaman Rute Pendakian Menggunakan Sistem Embedded Agung Prasetyo; Dahnial Syauqy; Wijaya Kurniawan
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 2 (2019): Februari 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Mountain climbing is one of nature's exploration activities that requires knowledge in understanding the map and area to be passed. However, not all climbers have knowledge of navigation, its causing the risk of getting lost while climbing. Navigation assistant that exist, only guide climbers only first route to final destination and can't save the route that already passed, until it causes climber difficulty going back to first route when they lost. Because that, in minimizing te risk of lost, be required navigation assistant device that cloud show the route has been passed. Based on these problems in this research created a navigation device assistant technology called GPS back track. This device is built with several components such a, the U-Blox Neo 6 M GPS module that functions in retrieving GPS data in the form of latitude and longitude coordinates, LCD display 800 x 480 TFT function displays information in the recording process running routes, Raspberry pi 2B functions process data input and output during the process of recording the route and the main resources for running the entire system using power bank. GPS back track has a feature that is able to open the recorded file that has been created and displayed on the LCD display. Based on the results of GPS accuracy testing, it is known that the GPS module error percentage at latitude coordinates is 3.77505% and longitude is 3.698758%. While in the testing of device recording, tracks and trackbacks functions can record routes and display them on the LCD in the form of route lines that are passed.
Implementasi Fault Tolerant System dengan N-modular Hardware Redundancy Khurinika Cahyaning Susanty; Wijaya Kurniawan; Gembong Edhi Setyawan
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 2 (2019): Februari 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Fault tolerant is needed because many systems are in conditions such critical systems, prone to damage environment, complex designs, and systems with variety users. The survey results of IT company said 99% of 400 respondents had experienced system failure caused by hardware damage resulting in data loss. To overcome this problem, a fault tolerant system was implemented on the hardware part (hardware redundancy) using N-Modular Redundancy (NMR) method that was applied on intensity and temperature reader system. NMR work by duplicate hardware as N that works together and get the same input and then the output results are determined by voting logic using majority vote. The object of implementation is intensity sensor BH1750 and temperature sensor LM35 as input, Arduino Uno as a sensor reader and voter, and the output will be displayed in the Arduino IDE serial monitor. The redundant hardware is sensor reader, Arduino Uno. The test results showed that the system more reliable because even though one of the redundant modules was damaged, the system still operate properly from the other redundant modules that running normally. The analysis before and after the application of the TMR method, reliability system increased by 9.2% from 83.51% to 92.7%.
Deteksi Kendaraan Roda Empat untuk Mendukung Keamanan Berkendara Menggunakan Histogram Of Oriented Gradients dan Support Vector Machine Berbasis Raspberry Pi Intan Fatmawati; Fitri Utaminingrum; Wijaya Kurniawan
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 2 (2019): Februari 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Driving safety is the most important thing in driving on the highway to avoid accidents. Accidents occur due to several factors including lack of concentration while driving, drowsiness, and so forth. One effort to avoid or reduce the risk of accidents when driving is to maintain the distance of the vehicle with the vehicle in front of it. In this study the theme of image processing is used to achieve the goal of maintaining distance between vehicle by utilizing the Histogram of Oriented Gradients (HOG) method as a way of extracting vehicle features which in this case are cars, then classified by the Vector Support Machine (SVM) method to distinguish between car classes and not cars, the two methods are implemented uses a Raspberry Pi camera mounted on the dashboard to detect the vehicle in front of it. When the distance of the vehicle with the vehicle in front is less than or equal to 15 meters (≤15m), the buzzer will sound as a sign that the vehicle is too close. The accuracy of the system in detecting cars using Support Vector Machine (SVM) that based on the Histogram of Oriented Gradients (HOG) feature by testing at a distance of 10 m, 15 m, 20 m, dan 30 m is 81.3% and the testing accuracy of Hardware and Software integration is 87.5%.
Kendali Kecepatan Putaran Motor Smart Wheelchair untuk Meredam Getaran pada Jalan Bergelombang dengan Metode PID Ganda Wibawa Putra; Dahnial Syauqy; Wijaya Kurniawan
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 2 (2019): Februari 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

A wheelchair is a tool for people who have difficulty walking by foot. There are various types of wheelchairs, one electric wheelchair. In its application, the electric wheelchair users still experiencing inconvenience in the form of vibration is received due to the uncertain road conditions as well as the static motor speed control. Congressional control of the speed of rotation of the Motor the Smart Wheelchair that works by controlling the speed of a DC motor using PID method. Input system of sensors the IMU working as detector uneven road conditions. The results of the readings of the sensors the IMU in the form of the position on the x-axis, y-axis, and z-axis. Input from the sensors the IMU processed on NodeMCU method using the PID to determine the speed of the motor. PID process started off doing the giving the value of the setpoint, and the processing of data from the accelerometer has been transformed into a vector. The input of the sensor will determine the value of the vibration to be processed using the PID. After the output values obtained, electric motors will move in accordance with the magnitude of value of output where the motor can increase the speed up to the highest limit if road conditions. Conversely, if uneven road conditions then the motor will lower the speed up to dampen the shocks. The results of the testing of this system in the form of percentage of IMU sensors sensitivity of 90% and the percentage of the system's success in absorbing the vibrations of 80%.
Implementasi Support Vector Machine Berdasarkan Ciri Histogram of Oriented Gradients Untuk Verifikasi Citra Tanda Tangan Berbasis Raspberry Pi Mohammad Lutfi Zulfikri; Hurriyatul Fitriyah; Wijaya Kurniawan
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 3 (2019): Maret 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Signature is a personal attribute that has long been widely accepted as a tool for verification of personal identity. But signatures are also easy to fake to be misused. To avoid this, a system is created to verify signatures. This system uses the image of the signature captured by the camera as an input triggered by the push button, Raspberry Pi as a digital image processing unit, and LCD 16x2 as the system output. This study uses the Histogram of Oriented Gradients (HOG) feature descriptor with precedence of image preprocessing. The output of the HOG method is a feature vector that represents the signature characteristics of the image, this feature vector which will be classified with the Support Vector Machine (SVM) classifier for data training and data prediction. There are two main parts of system software, the training data section, and the testing data section for signature verification. The implementation results obtained that the system can verify signatures with an accuracy of 87.33%. System requires 1.45 seconds in average to train data on each signatory name and for the verification process, the average system takes 0.238 seconds for the genuine signature and 0.242 seconds for forgery signatures.
Implementasi Sistem Operasi Real-Time pada Arduino Nano dengan media Komunikasi NRF24L01 Untuk Pengukuran Suhu, Kelembaban, dan Intensitas Cahaya Eka Nanda Sugianto; Wijaya Kurniawan; Dahnial Syauqy
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 4 (2019): April 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

In building system node sensor for smart home monitoring needed an operating system so that tasks can be executed simultaneously. By running tasks simultaneously, performance of the system monitoring smart home expected to running properly. If not, then the smart home monitoring system will work improperly such as experiencing a decrease or increase in temperature significantly due to lack of timely processing of data and the delay in making a decision that should not occur in a smart home monitoring system. In addition, the operating system must be in real-time because a smart home monitoring system is expected to be able to make decisions and provide the right information in the actual time. To resolve the above problems, RTOS (Real Time Operating System) is one of the appropriate operating systems in executing tasks simultaneously and it's also real-time. To apply RTOS to the Arduino Nano microcontroller, FreeRTOS library is needed. This sensor node system is divided into 2 node, namely client node and base node. The wireless communication media is using nRF24L01. The client node consists of the Arduino Nano microcontroller, LDR sensor, DHT11 sensor, and nRF24L01. While the base node consists of an Arduino Nano microcontroller and nRF24L01. The number of tasks on the client node is 3 tasks while at the node base is 2 tasks. Implementation for method is using Preemptive Priority Based-Scheduling. From the test results, tasks can run according to the priority given. The vTaskDelay function to set the execution time of each task is running as it should.
Co-Authors Abdul Khafid Abdul Rahman Halim Achmad Rizal Zakaria Afredy Carlo Sembiring Agi Putra Kharisma Agung Prasetyo Agung Setia Budi Ahmad Khalid Azzam Amroy Casro Lumban Gaol Anggi Diatma Styandi Aras Nizamul Aryo Anwar ari kusyanti Arif Nur Agung Laksana Arycca Septian Mulyana Ayu Samura Barlian Henryranu Prasetio Bayu Widyo Harimurti Cindy Lilian Cipto Bagus Jati Kusumo Da'imul Royan Dahnial Syauqy Deddy Aditya Kurniawan Dedy Eka Prasetya Denis Andi Setiawan Devo Harwan Pradiansyah Doni Hadiyansyah Ega Dewa Iswantoro Eka Nanda Sugianto Eko Setiawan Enno Roscitra Oktaria Farid Aziz Shafari Fariz Andri Bachtiar Fauzi Awal Ramadhan Fitriyah, Hurriyatul Galang Eiga Prambudi Ganda Wibawa Putra Gembong Edhi Setyawan Gusti Arief Gilang Hafizh Hamzah Wicaksono Hafizhuddin Zul Fahmi Hanif Yudha Prayoga Haqqi Rizqi Hendra Hendra Hernanda Agung Saputra Heru Nurwasito Indra Dwi Cahyo Intan Fatmawati Iqbal Yuan Avisena Ira Oktavianti Irfan Pratomo Putra Irfani Fadlan Istiqlal Farozi Jodie Putra Kahir Joniar Dimas Wicaksono Khurinika Cahyaning Susanty Kiki M. Rizki Lamidi Lamidi Lintang Cahyaning Ratri Lita Nur Fitriani Loki Sudiarta Mongin M Adinura Julian Habibie Mario Kitsda M Rumlawang Mesra Diana Tamsar Miftahul Huda Mochamad Hannats Hanafi Ichsan Mochammad Hannats Hanafi Ichsan Mohamad Misfaul May Dana Mohammad Lutfi Zulfikri Muhammad Adi Wijaya Muhammad Eraz Zarkasih Muhammad Faza Ramadhana Muhammad Kevin Pratama Muhammad Naufal Muhammad Rasyid Perdana Muhammad Wafi Muhammad Yusuf Hidayat Muliyahati Sutejo Muzammilatul Jamiilah Novaria Elsari Ryzkiansyah Octavian Metta Wisnu Wardhana Oggy Setiawan Pierl Kritzenger Sinaga Prayoga Febriandika Puguh Bahtiar Rafif Nurmanda Ghafurutama Raga Jiwanda Rakhmadhany Primananda Rando Rando Reza Akhmad Najikh Reza Tanjung Ahmad Fauzi Ricky Prasetya Santoso Riski Kurniawan Rizal Maulana Rizal Setya Perdana Sabriansyah Rizqika Akbar Salman Farizy Nur Samkhya Aparigraha Septian Mukti Pratama Shandi Sonna Mahardika Sigit Priyo Jatmiko Syahrul Yoga Pradana Tantri Isworo T. R. P. Tezza Rangga Putra Utaminingrum, Fitri Widhi Yahya Wifki Ato'ur Rochim Yongki Pratama