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All Journal International Journal of Electrical and Computer Engineering IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Bulletin of Electrical Engineering and Informatics Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer
Rizal Maulana
Teknik Komputer, Fakultas Ilmu Komputer, Universitas Brawijaya
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering

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Implementasi Protokol UPnP pada Perangkat Smart Home Berbasis ESP8266 Imam Syafi'i Al Ghozaly; Sabriansyah Rizqika Akbar; 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

Before smart home devices can be used by users, their services and capabilities need to be discovered first. However, there are some issues regarding standardization in that process. Standardization is critical to ensure devices' interoperability. This research proposes Universal Plug and Play (UPnP) protocol as the standard to discover and utilize available smart home devices on the network. Devices' services and capabilities can be learned through UPnP discovery and description. Once discovered, smart home devices can be controlled by sending them control messages or regularly monitored by subscribing to event message which will be sent off by smart home devices whenever their state changed. UPnP protocol was implemented on four different ESP8266 microcontrollers, each of which is connected to a PIR motion sensor, magnetic switch door sensor, SCT-013-000 current sensor, or relay module. Users can search, discover and utilize available smart home devices on the network through a control point application runs on Android. Test results showed that the average time for smart home devices to be fully discovered, to respond to a control message, and to send event message are 279.33 ms, 235.79 ms, and 220.49 ms respectively. Another test results showed that the SCT-013-000 current sensor readings' accuracy was 98.48 %.
Implementasi Alexa Voice Command Untuk Pembacaan Informasi Sensor Pada Rumah Pintar Romario Siregar; Sabriansyah Rizqika Akbar; 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

Rapid technological development is needed in facilitating access to technology at this time. Because of the increasing mobility of the people, the higher the level of neglect of small things such as forgetting to turn off electronic equipment such as lights, televisions, air conditioners, and others. Smart home (Smart Home), one of the solutions that can be offered to overcome this problem. Smart Home is a term used for homes that have electronic equipment or security systems that are integrated with each other and can be monitored for use. The developing method in monitoring smart homes is to use sound (Speech Recognition). One of the Amazon voice services that can be used is Alexa Voice Service. In this study, Alexa Voice Service will be implemented to the Raspberry Pi which functions as the speech recognition module and Raspberry Pi can receive sensor data that contains the value of air quality, temperature, and smoke wirelessly which will then be sent to the Alexa Skills Kit through the Alexa Web Service. Then the voice command is entered and sent to the Lambda Amazon Web Service to be modeled in the JSON format. This format will be published to MQTT and MySQL Database so that it can be recognized by the system. The system will subscribe to the command as a reference for what Alexa must say. The level of accuracy and success of the system to be able to read voice command sensor data using 5 different speakers is 70%.
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.
Implementasi Algoritme Mapping Dengan Backtracking Pada Mobile Robot Dalam Maze Fikri Fauzan; Dahnial Syauqy; Rizal Maulana
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

Autonomous Mobile Robot is rife in many researches especially the Maze Wall Follower robot that can find its way out of a very complicated labyrinth. In this study the Robot Maze Wall Follower using Backtracking algorithm is to trace all possible paths in the maze and recognize each node that is passed so as not to repeat the path that has been passed. This prototype is built using several modules of Arduino Nano as its processing, Ultrasonic sensor, Photodiode sensor and L298N Driver Motor. Test results from measurement of wall distance using HC SR04 Ultrasonic sensor which is tested as much as 4 times with different distance obtained by the distance of sensor distance to wall the smaller also the level of accuracy of sensor, line reading done with 3 different color and every color is done 3 times the test result is just a black color that can't reflect light that can be read by the photodiode sensor. Testing the robot control system, the left turn of success reaches 50% at the right turn reaches 70% and when the turnaround only reaches 40%. After mapping the maze using the Backtracking algorithm all paths that have been passed by the robot will be marked, after all the lines have been robot so the robot will stop moving.
Implementasi Arsitektur Publish And Subscribe Pada Alat Monitoring Suhu Dan Kelembaban Kandang Ular Python Regius Menggunakan NodeMCU (ESP8266) Habib Zainal Sarif; Mochammad Hannats Hanafi Ichsan; Rizal Maulana
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

The climatic conditions in the city of Malang, a pretty cool and slightly damp to make some of the pets we have become vulnerable to attack diseases in animals, especially reptiles, especially snakes Pythons regius or commonly known as ball python. In addition to the affected adult Pythons snakes on hormones, decreased appetite the snake can also be influenced by the surrounding temperature and humidity snake cages. For temperature and humidity are ideal for snakes at noon ranged between 27-29 ° C and for the evening temperature ideally is 23-24 ° C. As for the moisture is good for these snakes ranged from 50-60%. Although there have been many successful toosl for measuring temperature and humidity of a room but the rancher still needs a tool capable to move so that it is able to keep an eye on the State of the cages despite not being on the enclosure. Based on the issue be made a snake enclosure monitoring system uses a Publish and Subscribe architecture. Where this system is supported by a communication protocol MQTT and will be shown on a Android applications. This research uses 3 parameters of readout of temperature and humidity from sensors DHT11 and time of DS3231 RTC periodically, as the output form of display on the LCD and also on Android applications. For publish and subscribe architecture or send it was chosen because it has the speed and lower power consumption. So that will create an environment that is good for the life of the snake itself.
Implementasi Raspberry Pi Untuk Mendiagnosis Penyakit Diabetes Melitus Melalui Warna Lidah Menggunakan Metode Otsu's Tresholding Tri Putra Anggara; Rizal Maulana; 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

Misdiagnosis is the cause of treatment and maintenance of the disease to be inappropriate, perhaps even cause of death. Some technological applications are able to overcome misdiagnosis. In general, diagnosis uses technology used images as data to be processed. One disease that can be diagnosed is diabetes mellitus. In this research tongue images used to diagnose diabetes mellitus. The color of the tongue image is a parameter used to diagnose diabetes mellitus. Tongue image obtained from webcam by Raspberry Pi with the Otsu's Thresholding method. The tongue image before processing uses Otsu's Thresholding, image must be converted into grayscale, then Improves the histogram using the Histogram Equalization method. Based on the test results, the company can acquire images, become Grayscale imagery, generalize histograms by histogram equalization method and be able to diagnose diabetes mellitus through tongue color. The result of testing the acquisition image result was obtained on 100 %, testing the system the diagnosis of diseases diabetes mellitus against patients diabetes mellitus obtained accuracy 80 % and testing the system the diagnosis of diseases diabetes mellitus against patients non diabetics mellitus obtained much as 90 % accuracy. The average of the past computing time towards the tongue diabetics mellitus 0.3 seconds and computing the average of the past time towards the tongue non diabetics mellitus 0.4 seconds.
Sistem Otomasi dan Monitoring Tanaman Hidroponik Berbasis Real Time OS Pinandhita Yudhaprakosa; Sabriansyah Rizqika Akbar; Rizal Maulana
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

Wireless Sensor Network (WSN) can be applied to agriculture. But in terms of timeliness required execution in a timely manner in operation, to the maximum so as not to miss the expected time. Problems are often found, namely when scheduling caring for plants that are less regular. Scheduling method is needed called Real Time OS (RTOS). RTOS has scheduling and priority, where it will make the execution of data that has been determined according to its priority. This is called multi-tasking on sensors and actuators in several conditions. In accordance with the problem described above, the author designed a system of automation and monitoring of hydroponic plants based on real time OS, this system is designed to create a system that can monitor and automate the system. The system can automatically control water in hydroponic plants. The microcontroller used is Arduino Uno. For the method used in the system is Scheduling on the DHT11 sensor, Turbidity, Ultrasonic and actuator solenoid valve, mini water pump. DHT11 is used as an input that detects temperature and humidity, Turbidity is used to detect the degree of turbidity of water, Ultrasonic is used to detect water levels. Then the solenoid valve is used to remove water, a mini water pump is used to fill water. In this case, Thingspeak is used as a website to display temperature and humidity. After testing the RTOS successfully with a comparison without RTOS. Data is sent using Nodemcu. Nodemcu itself is a Wi-fi module that is used to send data from Arduino Uno to the Thingspeak website. Then it was also found that the results of the data accuracy test values found for RTOS found an error value of 0.95% and without RTOS 2.25%.
Implementasi Pendeteksi Penyakit Paru-Paru Berdasarkan Warna Kuku dan Suhu Tubuh Berbasis Sensor TCS3200 Dan Sensor LM35 dengan Metode Naive Bayes Dadang Kurniawan; Rizal Maulana; Mochammad Hannats Hanafi Ichsan
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

The human lung is an organ that is susceptible to disease because it is in direct contact with the air inhaled through the nose. Lung medicine is currently using CT scan and sputum tests which are checked manually by sputum experts. Many people still do not know about this treatment system, and finally they are reluctant to check their lung health, because they feel inefficient and besides that the results of the tests can't go out immediately. based on these problems, there is a need for research related to the automation system to detect the severity of lung disease from patients, so when a patient comes to check their lungs, the results can be immediately known. In this study the parameters used to compare the grade level of lung disease are nail color and body temperature of patients using the Naive Bayes method. It is known that the Naive Bayes method has good accuracy and can be used based on class classification at the beginning of the process. Based on several tests carried out on the system generated TCS3200 color sensor reading error of 1.478%, and the LM35 temperature sensor reading error against the thermometer measuring instrument is 1.13%. Furthermore, testing the system using the Naive Bayes method with the number of training data as many as 24 data and test data as much as 12 data, obtained an accuracy of 91.6% with an average computing time of 0.69 seconds.
Sistem Klasifikasi Kualitas Kondisi Toilet Berdasarkan Gas Serta Suhu Berbasis Sensor MQ135 dan DHT11 Menggunakan Metode Naive Bayes Didik Wahyu Saputra; Rizal Maulana; 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

Environmental health is one of the important components that are very influential for human life and health. A clean and healthy environment will make every individual around him comfortable and improve the quality of his life. Toilets are part of an environment that is very important. The poor quality of the toilet facilitates the transmission of bacteria and the development of germs. Based on these problems a system was created that could be used to classify the quality of toilets based on several parameters. In this study the parameters used in comparing the quality of the toilet are odor and temperature on the toilet. Where for odor parameters consists of ammonia gas, carbon dioxide, and carbon monoxide. These gases are gases that are often produced in human activities when on the toilet. The process of determining toilet quality through ammonia, carbon monoxide, carbon dioxide, and temperature is obtained from reading two MQ135 sensors and DHT11 sensors by the Arduino Uno microcontroller using the Naive Bayes method. The use of the Naive Bayes method was chosen as a decision making technique for toilet conditions because it has very good accuracy where the class of toilet type classification has been known from the beginning. From the results of several tests the reading of two MQ135 sensors has a very high correlation with the output voltage. Where for ammonia reading has a correlation of 99.13%, carbon monoxide has a correlation of 99.66%, and carbon dioxide 99.22%. Whereas for the temperature reading of the DHT11 sensor it has a presentation error of 0.502%. Furthermore, in testing the Naive Bayes method system with a total of 55 training data and test data as many as 25 data, obtained an accuracy of 96% with an average computing time of 4.59 seconds.
Rekognisi Wajah Pada Sistem Smart Class Untuk Deteksi Kehadiran Mahasiswa Menggunakan Metode Viola Jones dan Local Binary Patterns Histograms (LBPH) Berbasis Raspberry Pi Fitrahadi Surya Dharma; Fitri Utaminingrum; Rizal Maulana
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

Facial recognition is one of the techniques in computer vision that is able to recognize a person's face from an image. The application of face recognition into the presence system is very important considering that there are still cases of attendance data manipulation by students in the presence system using manual - filling signatures on the attendance sheet. Lack of tight supervision in filling attendance sheets is an event that is vulnerable to cases of manipulating attendance data. Therefore in this study try to present a presence system that uses images to find out the presence of students. The trick is to take pictures using a camera that is placed in front of the class, just above the blackboard facing the student. From the images taken, the system will then detect the faces of students using the Viola Jones method of the OpenCV library combined with YCbCr skin color pixel detection to avoid false detection. And for face recognition students will be using the local binary patterns histograms method from the OpenCV library. Accuracy results obtained by the system showed the level of detection accuracy of 82.33% and recognition accuracy of 50.83% in the morning, 61.11% during the day, and 58.89% at night. The average total computing time for the detection of one student is 0.293 seconds, two students 0.297 seconds, three students 0.317 seconds, four students 0.313 seconds, five students 0.31 seconds and six students 0.307 seconds. While the average total face recognition computing time for one student is 2.17 seconds, two students 2.58 seconds, three students 3.01 seconds, four students 3.38 seconds, five students 3.78 seconds, and six students 4 .12 seconds.
Co-Authors Abdullah Asy Syakur Abdurrahman Arif Kasim Addin Miftachul Firdaus Adhly Hasbi Fadhlillah Adinugroho, Sigit Adit Ilham Nugroho Aditya Rafly Syahdana Agung Setia Budi Ahmad Fahmi AdamSyah Ahmad Rizqi Pratama Alfatehan Arsya Baharin Alfatehan Arsya Baharin Alfaviega Septian Pravangasta Ali Ilham Ainur Rahman Allif Maulana Althaf Banafsaj Yudhistira Amelio Eric Fransisco Amri Yahya Ananda Ribelta Anata Tumonglo Andre Ananda Pratama Anggi Fajar Andana Aras Nizamul Aryo Anwar Ariq Monetra Aufa Nizar Faiz Axel Elcana Duncan Bagas Nur Rahman Bambang Gunawan Tanjung Barlian Henryanu Prasetio Barlian Henryranu Prasetio Boris Wiyan Pradana Bramantyo Ardi Cahyanita Qolby Rahmarta Rizaputri Chandra Gusti Nanda Putra Chikam Muhammad Dadang Kurniawan Dahnial Syauqy Dian Bagus Setyo Budi Didik Wahyu Saputra Dien Nurul Fahmi Dipatya Sakasana Dony Satrio Wibowo Dwi Firmansyah Dwi Fitriani Dwiki Nuridhuha Eko Setiawan Ezra Maherian Fachrur Febriansyah Manangkalangi Fajar Miftakhul Ula Falachudin Akbar Farah Amira Mumtaz Farid Aziz Shafari Fauzan Rivaldi Fauzi Awal Ramadhan Fikri Fauzan Fikriza Ilham Prasetyo Fitrahadi Surya Dharma Fitriyah, Hurriyatul Galang Eiga Prambudi Gembong Edhi Setiawan Gembong Edhi Setyawan Govinda Dwi Kurnia Sandi Gusti Arief Gilang Habib Muhammad Al-Jabbar Habib Zainal Sarif Hafid Ilmanu Romadhoni Hafiz Nul Hakim Hafizhuddin Zul Fahmi Hamdan Zuhdi Dewanul Arifin Handoko Ramadhan Hani Firdhausyah Hanif Yudha Prayoga Hanifa Nur Halimah Hendriawan Dwi Saputro Hurriyatul Fitriyah Ichwanul Muchlis Ihsanurrahim Ihsanurrahim Imam Syafi'i Al Ghozaly Iqbal Koza Irham Manthiqo Noor Issa Arwani Istiqlal Farozi Izza Febria Nurhayati Jodie Putra Kahir Kezia Amelia Putri Kiki M. Rizki Lamidi Lamidi Leina Alimi Zain Lia Safitri M. Ali Fauzi M. Sandy Anshori M. Sifa'un Ni'am Mahesha Bayu Paksi Mario Kitsda M Rumlawang Marrisaeka Mawarni Mhd. Idham Khalif Misran Misran Moch Zamroni Mochamad Hannats Hanafi Ichsan Mochammad Hannats Hanafi Ichsan Mochammad Hannats Hanafi Ichsan Mohamad Abyan Naufal Fachly Mohamad Muhlason Nur Aziz Mohammad Ali Muhsin Muhajir Ikhsanushabri Muhamad Ichwan Sudibyo Muhamad Irfanul Hadi Muhamad Taufiq Firmansyah Muhammad Bilal Muhammad Eko Lutfianto Muhammad Fatikh Hidayat Muhammad Jibriel Bachtiar Muhammad Kholis Fikri Muhammad Prabu Mutawakkil Muhammad Raihan Al Hakim Muhammad Rheza Caesardi Muhammad Yaqub Muhammad Yusuf Hidayat Nadi Rahmat Endrawan Nobel Edgar Nugraha Pangestu Octavian Metta Wisnu Wardhana Octavian Metta Wisnu Wardhana Oktaviany Setyowati Pabela Purwa Wiyoga Pinandhita Yudhaprakosa Priyo Prasetyo Putri Laras Rinjani Rachmat Eko Prasetyo Rahadian Sayogo Rahmat Yusuf Afandi Rakhmadhany Primananda Randy Cahya Wihandika Refsi Ilham Cahya Renita Leluxy Sofiana Ricky Zefani Aria Zurendra Ridzhal Hachim Wahyunanto Rifqi Alvaro Rifqi Anshari Riko Andianto Rimas Oktama Rint Zata Amani Rioadam Sayyid Abidin Riski Kurniawan Rizki Septiansyah Rizky Widya Mahendra Romario Siregar Rosyana Lencie Mampioper Sabitha Wildani Hadi Sabriansyah Rizqika Akbar Salsabiil Hasanah Satyaki Kusumayudha Shafa Sabilla Zuain Sulthan Ghiffari Awdihansyah Sutrisno Sutrisno Syahriel Diovanni Yolanda Tatit Kisyaprakasa Tedy Kurniawan Tezza Rangga Putra Tibyani Tibyani Tio Haryanto Adi Putra Tri Putra Anggara Upik Jamil Shobrina Utaminingrum, Fitri Vatikan Aulia Makkah Widasari, Edita Rosana Wijaya Kurniawan Willy Andika Putra Yanuar Enfika Rafani Yohana Angelina Sitorus Yohana Kristinawati Yurliansyah Hirma Fajar