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All Journal Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Abdimas: Jurnal Pengabdian Masyarakat Universitas Merdeka Malang Bubungan Tinggi: Jurnal Pengabdian Masyarakat Jurnal Sistem Informasi, Teknologi Informasi, dan Edukasi Sistem Informasi (JUST-SI) Jurnal Nasional Teknik Elektro dan Teknologi Informasi
Issa Arwani
Fakultas Ilmu Komputer Universitas Brawijaya
Humanities Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Energy Engineering Social Sciences Other

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Pembangunan Aplikasi Informasi Kesehatan Masyarakat Kota Malang Berbasis Mobile Native Android Ferdy Wahyurianto; Issa Arwani; Arief Andy Soebroto
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 1 (2019): Januari 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

The population of the society will continue to evolve over time, this makes process of logging society's health data will be more difficult to do. The problem is becoming a foundation in developing technology to ease the process of logging society's health quickly. The society's health information used by the Government in serving and improving the welfare of the society. The society's health information technology at Malang present day is based with website which requires a static place and low mobility. The solution to this problem is by developing a mobile app that is more practical and much sought present day, because it gives convenience to access information and high mobility support. Solutions offered the author is building a society's health information system based on mobile native app using the android platform because the majority of 89.75% of society use android operating system. System development method using the waterfall method that supports development in accordance with the needs of users who are clearly defined at the beginning. This Application can process and projecting the amount of society's health data distribution into Google Maps. The system is tested by doing unit testing, validation testing, as well as the compatibility testing. The results of the testing analysis on this system meets the needs of users as well as being able to support the system's performance and high mobility.
Sistem Klasifikasi Aktivitas Manusia Menggunakan Sensor Accelerometer dan Gyroscope dengan Metode K-Nearest Neighbor Berbasis Arduino Fadhilatur Rahmah; Hurriyatul Fitriyah; Issa Arwani
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 1 (2019): Januari 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Human activity recognition technology allows a system to detect simple activities by humans, such as standing, sitting, lying, walking, running and others using a camera or sensor. The camera-based human activity recognition system has a lack of adaptability to light so that the accuracy obtained is not good, while wearable sensor-based systems that use multiple sensors cause discomfort when used and battery life problems. In this study a system can be made that can classify simple activities carried out by humans using the MPU6050 sensor which has an accelerometer and gyroscope sensor and uses the k-Nearest Neighbor classification method. Input from this system is the value of the accelerometer and gyroscope sensor readings sent using the NRF24L01 wireless communication module to Arduino Mega as a device that classifies and displays the classification results in Serial Monitor Arduino IDE. In this study the test was carried out using one sensor and two sensors. From the results of the tests performed, obtained the highest accuracy results of 93.75% for systems that use one sensor with sensor placement on the thighs and 96.25% for systems that use two sensors with sensor placement on the thighs and waist. For testing the computation time of the k-Nearest Neighbor method in classifying human activities, the average time taken was 173.6 milliseconds for classification using one sensor and 353.2 milliseconds for classification using two sensors.
Sistem Pembacaan Nada Trumpet dengan Metode Fast Fourier Transform (FFT) Berbasis Embedded System A. Baihaqi Mubarok; Dahnial Syauqy; Issa Arwani
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

Marching bands are an art group that half of the composition is brass players. However, in Indonesia some trumpet players in the marching band did not understand the C D E F A B C tone theory, including the method for tuning tools. In this study a tuning system for trumpet with FFT (fast fourier transform) algorithm was developed. The system developed uses a USB microphone as a sensor, data processing is done with Raspberry Pi 3. FFT processing uses the Numpy library, in which there are several subprocesses, from taking signal samples to windowing. After the window is obtained, the FFT can be calculated, and then the results of the FFT will be converted into a frequency domain and then converted to pronunciation notation (do, re, mi, fa, sol, la, si, do). The output of this process is the frequency and notation displayed on the 16 x 2 LCD. The test results on the sensor can capture various sounds, and the test results on the system can capture chromatic tones between octaves 3 to 4, with an average the difference in frequency is 1.85 Hz. In testing the computation time, the average results were 0.28 seconds.
Implementasi K-Nearest Neighbor untuk Klasifikasi Ekspresi Wajah Berdasarkan Data Muscle Sensor dan Berbasis Arduino Aprilo Paskalis Polii; Hurriyatul Fitriyah; Issa Arwani
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

Human facial expressions are formed by face muscles. Therefore, as an interest to develop Human-computer interaction, the system of human facial expression classification based on face muscles' movement is made for those reasons. The output from facial muscles is obtained by the muscle sensor. The classification in this research has been done by using K-Nearest Neighbor Algorithm system. The Muscle sensor is connected to the face by using electrodes. Then, the sensor's output is processed in Arduino and shows the result on LCD Monitor as an output. By the testing of sensor's functionality, it is found that the sensor responds according to the muscle performance. The sensor's value is increased along with the number of gained loads. Besides that, by the testing of LCD monitor's functionality, the result is obtained that LCD Monitor works well by displaying the output in accordance with the command. Then by the accuracy testing, the best the result is from K equals to 3 with 81% of accuracy level. By the computation time testing, the result of taking the output from sensor, processing, and display the classification takes 1.68 seconds as the average time.
Sistem Penghitung Jumlah Orang Melewati Pintu Menggunakan Metode Background Subtraction Berbasis Raspberry Pi Diego Yanda Setiawan; Hurriyatul Fitriyah; Issa Arwani
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 center state of the crowd such as shopping centers, libraries and so on are the places that many people visit. This data is very important because it can be used as interest indicator. In this research is needed a system which can provide an information about the number of visitor so manager can do monitoring of the place. Possible technologies in making this system is to uses digital image processing and computer vision. Background Subtraction Method useful to detect moving objects. From the test results, the Background Subtraction method can detect moving objects very well, opening and closing can improve image results. The success rate when one person enter is 87,5% and exit is 87,5%, The Accuracy when two persons enter at the same time is 87,5% and exit is 100%. Overall the Average accuracy obtained by this system with a certain angle camera when one person enter is 75% and exit is 78.75%, The Accuracy when two persons enter and exit at the same time is 71% and 71%. Also the best camera angle while capture images when one person pass is 70°,80°, 90°. when two person pass at the same time 50°, 70°.
Implementasi Sistem Kendali Kecepatan Kursi Roda Elektrik Menggunakan Kendali Proporsional Pada Kondisi Jalan Menanjak Dan Menurun Achmad Fanani Kurniawan Saputra; Dahnial Syauqy; Issa Arwani
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

Health is one of important thing, because an awful lot of diseases that can causing difficulties when moving, so we need tools like a wheelchair. wheelchairs have an awful lot of development, one of which namely electric wheelchairs. The application of electric wheelchair still not have a feature to adjust the speed while on the uphill and downhill road conditions so that safety and comfort will be reduced. Speed control system using proportional control while on the condition of the streets uphill and downhill works by checking the condition of the slope sensor path with GY-521 MPU6050 whose value will be used as the parameters change speed maximum. the speed read by the Encoder FC-03 was calculated using proportional control which will produce output to set the speed of the motor and will always check if it's value has reached set point is expected. on the uphill road conditions the system will add speed to the value of RPM can match the set point, whereas at the moment the road conditions decreased system will lower the speed so the RPM value can be fixed in accordance with the set point. The testing results of this system show the percentage success system when uphill road condition of 78.5% and when downhill road condition is 85.61%.
Face Recognition Untuk Sistem Pengaman Rumah Menggunakan Metode HOG dan KNN Berbasis Embedded Bagus Septian Aditya Wijayanto; Fitri Utaminingrum; Issa Arwani
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 home security system is one of the features that must be owned and considered for every homeowner who wants to have a home that is safe from theft and avoid other unwanted security disturbances. So we need a support system that is able to increase home security. In this study, the system created uses the face as security data. This system uses a webcam as a face image taker and is integrated with the Raspberry Pi. This system will apply the buzzer, LED, solenoid door lock and SIM800L modules as outputs of the system. This system uses HaarClassifier to detect faces, then Histogram of Oriented Gradient and k-Nearest Neighbor for face recognition. First the system will take the image captured by the webcam, then use face image detection with Haar-Classifier, then the facial image will be extracted using the HOG feature. After the face feature value is obtained, it will then be classified using the k-Nearest Neighbor algorithm. From the results of testing the accuracy of face detection is the best accuracy of 100% at a distance of 40cm. The results of the accuracy of face recognition at a distance of 40cm in total are equal to 87.5%. For testing the accuracy of integration between software and hardware produces an accuracy rate of 100%. The average time needed for the face recognition process is 13,28839 seconds.
Pengembangan Permainan Edukasi Pengenalan Chord Gitar Berbasis Virtual Reality Dengan Menggunakan Myo Armband Aditya Yudha Agung N; Tri Afirianto; 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 learning the guitar, it is necessary to know the basic chords that can be learned through books or the internet. However, the use of print media does not provide real experience to students. Therefore we need an interactive learning media that can provide real experiences to students. By using virtual reality and Myo Armband this research combines the two technologies into interactive learning games so they can provide real experiences to their students. The system built using the MDA Framework, describing the mechanics, dynamics and aesthetics that exist in the game system. The system is tested using the System Usability Scale (SUS) and Task Completion Rate to test User Experience (UX) of the system, Black Box testing to validate functions in the system and pre-test - post-test testing to test the influence of the game on increasing understanding of material. The results showed that the value of the SUS test was 67.5%, which number did not meet the SUS standard of 68%. The black box testing test results get a 100% valid result which indicates that the functional system of the game has been running correctly. The results of task completion testing give an average yield of 91.43% with a standard task completion of 78% which indicates that this system is good in terms of its effectiveness. The pre-test and post-test tests get an average result for the pre-test of 70 and a post-test of 90. From the two values, there are 20 equalizations which indicate that there is an increase in player understanding in other words the game has succeeded as an interactive learning media.
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
Sistem Pengecek Kelayakan Pakai Oli Motor Matic Berdasarkan Parameter Warna dan Viskositas Menggunakan Metode Bayes Mustajib Furqon Haqiqi; Dahnial Syauqy; 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

Lubricating oil on engine motorcycle is an important component of a vehicle as a means of transport. When oil is replaced, then the late effect on performance and condition of the machine motor. And most of the community if you want to check the condition of his motorcycle oil has to come to the repair shop if you want to check or replace the oil in the motor. The use of oil lubrication parameters as objects of research,. study on the parameters used to perform the comparison level of lubricant lubricant oil is color and viscosity on the oil of motorcycle. The use of lubricating oil parameter as an object of research due to the condition of the lubricant oil is very influential on the condition of the machine that is on the motor. The process of determining eligibility levels oil through color and viscosity of the oil obtained from the reading of the result value of the color sensor TCS3200 sensor and Water Flow YF-S201 by microcontroller, Arduino Uno with Naive Bayes method. Naive Bayes method is selected as one of the techniques for decision making types of lubricating oil eligibility levels, because this method was one method of classification is good enough where classes classification of types of eligibility levels have been known from the beginning. From the results of some tests done known percentage error reading sensor TCS3200 is color of 2.22% and the value of the correlation of readings the sensors Water flow YF-S201 by function it works can differentiate liquid based on the kind of lumpy. Next on the testing system using Naive Bayes method with the amount of training data by as much as 35 data and test data as much as 18 data, obtained accuracy of 94.44% with average computing time over the 1.68 seconds.
Co-Authors A. Baihaqi Mubarok Abi Dwijo Sukma Abidin Adi Prasetyo Abimanyu Prayuda I. H. Alfianto Ach Fauzan Achmad Fanani Kurniawan Saputra Adithia Risma Rara Putri Aditya Yudha Agung N Adlan Husein Malahella Agi Putra Kharisma Ahmad Yazid Bastomi Alfa Fadlilah Alfin Noor Afyuddin Alfredo Juan Pratama Almira Kalyana Ammar Gunya Pratomo Andrew Adi Nugraha Andyan Bina Ardhana Anisa Dwi Novita Rika Annisa Hestiningtyas Aprilo Paskalis Polii Arief Andy Soebroto Asroru Maula Romadlon Aulia Rizki Ananda Azzahra Princessa Shekina Wijaya Bagas Rayi Prabowo Bagus Septian Aditya Wijayanto Bayu Rahayudi Bella Krisanda Easterita Bima Tri Atmaja Bondan Sapta Prakoso Buce Trias Hanggara Budi Darma Setiawan Chandra Wira Hadikusuma Christian Doxa Hamasiah Dahnial Syauqy Denny Sagita Rusdianto Diah Priharsari Dian Eka Ratnawati Diego Yanda Setiawan Dimas Setyo Utomo Djoko Pramono Dwi Rama Malawat Dwija Wisnu Brata Eki Yusandhi Iskandar Elfa Fatimah Eriq M. Adams Jonemaro Eriq Muh. Adams Jonemaro Eriq Muhammad Adams Jonemaro Ernani Hadiyati Ervin Winardo Toepak Fadhilatur Rahmah Fahmi Aquinas Faizatul Amalia Fajar Nur Rohmat Fauzan Jaya Aziz Fajar Pradana Fajar Rizki Kristiono Farandi Angesti Farhah Annisa Jamal Firdaus Farhan Fadhillah Djabari Fariz Sokhinda Hamza Fathin Al Ghifari Fatwa Ramdani, Fatwa Ferdy Wahyurianto Fitra Abdurrachman Bachtiar Fitria Adi Sulistiya Rini Fitriyah, Hurriyatul Galih Muhammad Gede Satria Harinamanata Gembong Edhi Setyawan Gladys Wahyu Khairunnisa Gunadi Hana Chyntia Morama Handoko Handoko Hanif Nabila Muflih Hanifah Muslimah Az-Zahra Hariz Farisi Hendro Dwi Prasetyo Herdianto Tri Setyaji Herlambang Yudha Prasetya Herman Tolle Hermawan Wijaya I Gede Merta Ariantara I Kadek Yoga Darma Putra I Made Setia Baruna Ians Adji Adhitama Ihza Aulya Nanda Ikhsanul Isra Yunelfi Ikrar Amalia Sholekhah Ilham Dwi Muchlison Insan Nurzaman Bangga Adi Pratama Irwan Kurniawan Juan Michel Hesekiel Kevin Aditya Firmansyah Putra Kevin Renjiro Khairi Ubaidah Luqman Rizky Dharmawan Lutfi Fanani Luthfi Irfan Hakim Praditya Marji Marji Micahel Yulius Munthe Mimi Hamidah Mochammad Hannats Hanafi Mochammad Hannats Hanafi Ichsan Moh. Izza Auladina Latansya Mohamad Faisal Amir Mohammad Arkan Ridhwan Razan Muhamad Maulana Zuhad Aditya Muhamad Rizky Prahesa Putra Muhammad Aminul Akbar Muhammad Fikri Fadlurrahman Muhammad Indra Harjunada Muhammad Rouvan Amiruddin Muhammad Tanzil Furqon Muhammad Wildan Aldiansyah Muhammad Yaqub Muhammad Zaki Nabil Muhibbuddin Al Haqqi Mustajib Furqon Haqiqi Nabila Fairuz Zahra Nafisa Nafisa Nana Amalia Mulia Nur Aini Nurul Qomariah Oceandra Audrey Priyambadha, Bayu Qonita Nur Farhana Radea Zulindra Ardisukma Raja Farhan Ramadha Pohan Rangga Noviansyah Nuur Aziiz Ratih Kartika Dewi Reinata Devi Nindya Tirzasari Renaldi Muhammad Rivan Haposan Rizal Maulana Rizky Edyatna Putra Rofy Firmansyah Rachmandany Rosikhan Maulana Yusuf Ryan Bayu Permadi Ryan Leonardo Sabriansyah Rizqika Akbar Safitri Herdian Rachmawati Safria Isnibaiti Satrio Agung Wicaksono Satrio Hadi Wijoyo Sausan Zahrah Shafira Margaretta Sherryl Sugiono Sindarto Sobakhul Munir Siroj Sultan Saladdin Syarief Noor Permadi Taufiqurrachman Ilham Thifal Fadiyah Basar Tibyani Tibyani Tio Allin Subiantoro Tri Afirianto Unggar Salsabila HSS Utaminingrum, Fitri Welly Purnomo Wibisono Sukmo Wardhono Widhy Hayuhardhika Nugraha Putra Wiku Galindra Wardhana Wildan Afif Abidullah Ya'qub Al-Kindi Yuliana Anggreini Budiman Yusi Tyroni Mursityo Zain Fikri Hanastyono