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All Journal International Journal of Electrical and Computer Engineering IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Jurnal Teknologi Informasi dan Ilmu Komputer Journal of ICT Research and Applications Proceeding of the Electrical Engineering Computer Science and Informatics Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Jurnal Sistem Komputer & Kecerdasan Buatan Jurnal Abdi Masyarakat Indonesia
Fitriyah, Hurriyatul
Universitas Brawijaya
Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Public Health

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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.
Sistem Deteksi Gejala Hipoksia Berdasarkan Saturasi Oksigen dan Detak Jantung Menggunakan Metode Fuzzy Berbasis Arduino Dian Bagus Setyo Budi; Rizal Maulana; Hurriyatul Fitriyah
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

The rapid development of intelligent systems is highly developed, one of them in the health or medical fields. In the medical field, a tool is needed to observe the patient's condition in a noninvasive way without injuring the patient. If it is ignored continuously then hypoxia can interfere with the function of the brain, liver, and other organs quickly. So that in this study a hypoxic early symptom detection tool that uses a noninvasive method using the Max30100 sensor that is clipped to the fingertip can be made to determine the results of the initial symptoms of hypoxia. To detect the initial symptoms of hypoxia in this tool, the Sugeno fuzzy method is used so that output is obtained according to the existing rules. Sugeno fuzzy method will process data taken from the Max30100 sensor. There are 3 hardware devices that are on this device, the Arduino microcontroller as the controller, the Max30100 sensor to get the input and Bluetooth for sending data to the smarthphone. Software uses the Arduino IDE to program detection devices and APP inventors to program android applications so they can display data. In this study, the test results were obtained and the results of the test obtained a tool error of 2.96% for oxygen duration and 2.86% for heart rate obtained. From the fuzzy method on 12 data experiments, 100% accuracy was obtained and the Sugeno fuzzy method was able to process the input data properly.
Sistem Penghitung Protein Telur Berdasarkan Volume Menggunakan Komputasi Citra Metode Cakram Berbasis Raspberry Pi Dan Perangkat Android Muhammad Riyyan Royhan; Hurriyatul Fitriyah; Agi Putra Kharisma
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

Inappropriate daily intake of protein can cause various diseases. Information about protein content of a food is very useful because with that information, people can know and regulate the level of proteins that they consume. Therefore, chicken eggs as a cheap and easy source of animal protein are important foods to know about their protein value. Research on eggs that have been widely made makes information about egg protein content can be known from the weight of the egg itself. Egg weight can also be found based on its volume. Egg volume can be calculated from the surface area of the egg using disk method. The surface area, and volume of egg can be known by computing the image of the egg. The Image computation to find egg volume can be done by using Raspberry Pi which is assisted with an Android device as an image taker, and also as a system interface. This research embodies a system that is capable of processing egg images to calculate the value of volume, weight, and protein content of the eggs. The system is tested for its accuracy based on its measurement results of the volume and the weight of the eggs, compared to the measurement results of ordinary measuring instruments. The final results of the test show that the system has an accuracy value of 95.76% for measurement of egg weight and 93.94% for measurement of egg volume.
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.
Alat Pemadam Api Terarah Dalam Ruangan Berdasarkan Warna HSV Berbasis Raspberry Pi Wahyu Hari Suwito; Hurriyatul Fitriyah; Gembong Edhi Setyawan
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

A fire disaster is a catastrophic event that causes a fire, which can cause harm both from property, and casualties. Therefore, a system is needed to minimize the occurrence of fires in the house, in this study will provide a more effective solution in detecting and extinguishing fires to prevent fires. By utilizing image processing on the camera, then pump dc water as a water sprayer. The system uses the Raspberry Pi computer as a data processing center, Logitech c170 camera as the input data provider that processes the image, then there is a Servo mg995 as a water hose guide, and a DC 5v Mini Water Pump as a water pump. Taking Logitech c170 camera images will later be converted into HSV Color Space, selecting Upper & Lower HSV levels. Then mark the fire with a red dot and give a circle using MinEnclosingCircle. Then the system classifies hotspots in several categories of fire position positions. Next the system will send data on the Servo mg995 which will move towards the location of the hotspot, turning on the DC 5v Mini Water Pump as a water sprayer. The level of accuracy of the system in recognizing fire points is 88.9%. While testing in determining the location of fire was 92.3%. And the last is a complete fire extinguishing test of 100%.
Sistem Pendeteksi Kecelakaan Pada Sepeda Motor Berdasarkan Kemiringan Menggunakan Sensor Gyroscope Berbasis Arduino Aries Suprayogi; Hurriyatul Fitriyah; Tibyani Tibyani
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

Motorbikes are transportation that are generally in great demand by citizens of developed countries, especially Indonesia. With the increasing population and enthusiasts of motorbikes, the number of accidents in traffic will increase every year. The lack of handling of motorcycle accident sufferers at the time of the incident resulted in a high mortality rate. By knowing the slope of the motorcycle can be stated as an accident. Namely the slope of 10 ° - 50 ° for the left and the slope of 130 ° - 170 ° for the right. Therefore an accident detection system was built on a motorcycle based on the slope using a sensor gyroscope which was used to read the slope of the motorcycle, then sent a notification in the form of an SMS to the victim's family's cellphone via the GSM SIM900A Module. The MPU6050 sensor which is the reader of the slope value on the system installed on the motorbike will be processed on the Arduino Uno microcontroller. If the slope reading is stated as an accident, the GSM SIM900A Module will send a notification in the form of a help message to the relatives or families of the victims with the number that already exists on the GSM SIM900A module. By doing the slope alternately between left and right is selected with the roll value in the MPU6050 Sensor ranging ± -80.00- ± 50.00 expressed with an angle of 10 ° -50 ° and the slope value ± -20.00- ± 74.00 then expressed at an angle of 130 ° ¬ -170 ° the angles are expressed as the angle of the accident on the system and the boundary conditions are 60 ° -120 ° where the roll value is ± -21.00 - ± 1.00 which is declared as a normal system or does not send messages. The system will read the slope if it does not meet the boundary conditions of the roll angle, the system will immediately send a notification in the form of a message of assistance to relatives or victims' families with 80% accuracy if not constrained by the network / signal on the GSM SIM900A Module.
Sistem Pemantauan Menggunakan Blynk dan Pengendalian Penyiraman Tanaman Jamur Dengan Metode Logika Fuzzy Handi Handi; Hurriyatul Fitriyah; Gembong Edhi Setyawan
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

Monitoring and watering have an important role in managing mushroom plants. However, the measurement used is the use of a thermometer as a manual and watering device. Through these fundamentals, it is conducting monitoring and automation of the fungal watering system with fuzzy logic method. The first process is to get information from the DHT11 sensor to send sensor data to the microcontroller for the process of output and humidity, the results of the data can be seen on the LCD screen. Blynk application is done as a remote monitoring. Fuzzy logic method was chosen to category the problem of input data to output data in conducting clean watering. From the sensor test the results obtained compared to the DHT11 reading sensor had an average error of 4.07%. In the process of watering the control system carried out as many as 10 times with a percentage error of 16.66%. Comparison of test duration has a difference of 45 seconds and the difference in water released by 500 ml. Although there are many more manual resections and long durations, the accuracy of the sensors and controllers with fuzzy logic method is more in line with the conditions needed in the mushroom place.
Sistem Peringatan Kondisi Jalan Berdasarkan Kecepatan dan Guncangan Sepeda Motor Menggunakan Naive Bayes Berbasis Embedded System Herwin Yurianda; Dahnial Syauqy; Hurriyatul Fitriyah
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 developing countries especially Indonesia traffic accidents can result in serious health problems.. Indonesia is a country which ranks fifth in the world in terms of traffic accidents, the data obtained at World Health Organization (WHO). Some of the factors that caused the accident was the road condition, vehicle and rider. However, the riders are often the vehicle outside the limit speed of the spur and the streets are less good is the most dominant factor is the cause of the accident. Based on the issue, it needs to be made to road condition warning system security drive vehicle motorcycle Embedde based System using Naive Bayes method. The sensor used in these systems is the hall effect sensor as the speedometer, and vibration sensors that serve to measure the level of shock two-wheeled vehicle. Will then be classified using Naive Bayes method, with a warning sound output with the use of the buzzer, and the screen display uses LCD, all processed system on an Arduino. Testing conducted include functional testing, system performance and accuracy. From functional testing that has been done, the system has a value of 100% truth, so it can be concluded that this test successfully. For performance testing, the system has a speed of processing time on average by 789.441 p. Whereas on testing Accuracy, the system was tested with test data as much as 43 data and the amount of training data by as much as 86 data and to have the accuracy of 97.76%.
Implementasi Decision Tree pada Penentuan Kondisi Ruang Berasap Menggunakan Multi-Sensor Berbasis Arduino Uno Mimi Hamidah; Hurriyatul Fitriyah; Issa Arwani
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 this day and age many facilities are designed automatically to help human activities in regulating the level of comfort and safety in the room, one of the technologies that has been widely used, namely fire alarms that are used to provide automatic warnings about fires that occur. However, due to several reasons and certain factors, often the fire alarm does not work properly and actually sends a false alarm. In this study there are 3 sensors, namely MQ-2 sensor, DHT22 sensor, and flame sensor that is connected to the Arduino Uno microcontroller. Arduino Uno microcontroller implements the decision tree method as the output decision maker based on the calculation of C4.5. There are 3 processes, namely the process of determining datasets, decision tree formation and rule formation. In this system, there are 3 attributes that are used to detect the status of smoky space conditions, namely temperature, fire intensity and smoke content. From the results of several tests conducted, it is known that the error percentage reading of the DHT22 temperature sensor is 1.58% and the MQ22 gas sensor can read the gas content in the room well, where the sensor reading value is directly proportional to the output voltage which is the higher the smoke level detected the higher the value of the sensor output voltage. From the results of testing the fire sensor YG1006 can perform ADC readings detected by the sensor against the fire source based on the distance of the sensor with the fire source. Furthermore, in testing the system using the Decision Tree method with the amount of training data as many as 800 data and test data as many as 40 data, obtained an accuracy of 97%. The average system execution time is ± 1389.9 ms
Perancangan Bot Pada Discord Untuk Pengendali Aktuator di Raspberry Pi Tatit Kisyaprakasa; Rizal Maulana; Hurriyatul Fitriyah
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

Internet of things (IoT) is a relationship between machines, one of the well-known IoT is bot. In this research, a bot is designed that can be used with Raspberry Pi. Discord application is used and user can give a number of commands to the chat column so that the bot can run. In its implementation, 3 actuators used on bot and has performed all technical functions and every case thats can be done properly and successfully. In time measurement test using Stepper Motor 28BYJ-48, resulted average tambah command execution time is 334,14ms, the gerak command is 0,35ms and the hapus command is 1,04ms. When migrating using the Servo SG-90, it has an average tambah command execution time of 385,55ms, 0,33ms of gerak command, and 1,28ms in hapus command. In testing time using DC Motor the average execution time of the tambah command is 344,49ms, the gerak command is 0,33ms, and the hapus command is 1,22ms. The results of the average movement percentage error using the Stepper Motor 28BYJ-48 are 0,154%, the SG-90 Servo movement has a percentage of 0,991%, and the DC Motor rotation has a percentage of 28,02%.
Co-Authors Abdurrahman Diewa Prakarsa Abimanyu Sri Setyo Achmad Baichuni Zain Aditia Reza Nugraha Aditya Rafly Syahdana Afflatuslloh Adi Salung Agi Putra Kharisma Agif Sasmito Agung Setia Budi Ahmad Fahmi AdamSyah Ahmad Fatchi Machzar Ahmad Haris Wahyudi Ahmad Wildan Farras Mumtaz Alfatehan Arsya Baharin Ali Ilham Ainur Rahman Allif Maulana Ananda Ribelta Andhika Rizky Fariz Andi Dwi Angga Prastya Andy Hartono Aprilo Paskalis Polii Aries Suprayogi Bagus Sawung Timur Barlian Henryranu Prasetio Belsazar Elgiborado Giovani Djoedir Benny Adiwijaya Bilawal Haesri Bimo Dimas Nugraraga Boris Wiyan Pradana Chandra Gusti Nanda Putra Cut Fahrani Dhania Dahnial Syauqy David Isura Dede Satriawan Denis Andi Setiawan Dewi Pusparini Dian Bagus Setyo Budi Diego Yanda Setiawan Dimas Bagus Jatmiko Dimas Dwi Saputra Dimas Firmanda Al Riza Dimas Guntoro Dipatya Sakasana Dody Kristian Manalu Dwi Fitriani Edhi Setyaw, Gembong Eko Ardiansyah Eko Setiawan Eko Setiawan Erdano Sedya Dwiprasajawara Esa Prakasa Fadhilatur Rahmah Fahmi Erza Faizal Andy Susilo Fajra Rizky Falachudin Akbar Fatchullah Wahid Afifi Faza Gustaf Marrera Fikriza Ilham Prasetyo Gembong Edhi Setiawan Gembong Edhi Setyaw Gembong Edhi Setyawan Gunawan Wahyu Andreanto Habib Muhammad Al-Jabbar Hafizh Hamzah Wicaksono Hamdan Zuhdi Dewanul Arifin Hamzah Attamimi Handi Handi Handy Yusuf Herwin Yurianda Ichwanul Muchlis Imam Pratama Setiady Indera Ulung Mahendra Iqbal Koza Irham Manthiqo Noor Issa Arwani Ivana Agustina Julisya Thana Khriswanti Khairul Anwar Komang Candra Brata Lashot Ria Ingrid Melanika Lintang Cahyaning Ratri Luqmanul Halim Zain M Ilham Fadilah Akbar M Nuzulul Marofi M. Fiqhi Hidayatulah Marrisaeka Mawarni Mimi Hamidah Moch Zamroni Mochammad Hannats Hanafi Mochammad Hannats Hanafi Ichsan Mohamad Abyan Naufal Fachly Mohamad Misfaul May Dana Mohammad Isya Alfian Mohammad Lutfi Zulfikri Muh. Syifau Mubarok Muhamad Delta Rudi Priyanto Muhamad Ichwan Sudibyo Muhammad Ammar Hassan Muhammad Daffa Bintang Nugroho Muhammad Fatham Mubina Akbar Muhammad Irfan Reza Muhammad Junifadhil Caesariano Muhammad Raihan Al Hakim Muhammad Rifqi Radifan Masruri Muhammad Riyyan Royhan Muhammad Rizki Chairurrafi Muhammad Rizky Rais Muhammad Rizqi Zamzami Muhlis Agung Saputro Musada Teguh Andi Afandi Nafisa Nafisa Nashir Umam Hasbi Nico Dian Nugraha Nur Aini Afifah Isbindra Nur Syifa Syafaat Okky Nizka Pratama Oktaviany Setyowati Olivia Rumiris Sitanggang Pandy Aldrige Simanungkalit Pramandha Saputra Putra Wijaya Putri Harviana Raden Galih Paramananda Rakhmadhany Primananda Rando Rando Refsi Ilham Cahya Rejeki Puspa Dinasty Rekyan Regasari Mardi Putri, Rekyan Regasari Mardi Retno Damayanti Rian Ari Hardianyah Ricky Zefani Aria Zurendra Rifqi Alvaro Rifqi Imam Ramadhan Rizal Maulana Rizka Ayudya Pratiwi Rizqy Maulana Rosa Mulyanis Chan Sabriansyah Rizqika Akbar Salsabiil Hasanah Samuel Lamhot Ladd Palmer Simarmata Satyaki Kusumayudha Septian Mukti Pratama Shafa Sabilla Zuain Sulthan Ghiffari Awdihansyah Syarief Taufik Hidayatullah Tatit Kisyaprakasa Thomas Oddy Chrisdwianto Tibyani Tibyani Tri Oktavia Mayasari Tunggal Manda Ary Triyono Utaminingrum, Fitri Wahyu Hari Suwito Widasari, Edita Rosana Wijaya Kurniawan Wildo Satrio Wisnumurti Wisnumurti Xavierro Lawrenza Yusuf Hendrawan Zultoni Febriansyah