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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 Telur Ayam Fertil dan Infertil Menggunakan Fitur Tekstur Dan Metode K-Nearest Neighbor Berbasis Raspberry Pandy Aldrige Simanungkalit; Hurriyatul Fitriyah; Eko Setiawan
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

Fertile chicken eggs are eggs that fertilized by a male and have potential to hatch while infertile eggs are eggs that not fertilized by a male. In chicken hatching management infertile eggs need to be removed from hatching machine so that they do not rot and explode in hatching machine. The removing process of infertile eggs from hatching machine doing by candling the eggs using a flashlight or lamp placed behind the eggs. In hatching industry with a large capacity doing this process is very tiring for the eyes because it requires high concentration and accuracy so this affects the consistency and accuracy of the observation results, therefor a system that classify fertile and infertile eggs constantly is needed. This study design classification system for fertile and infertile eggs based on Computer Vision with texture feature extracted using Gray Level Co-Occurrence Matrix method and classified using K-Nearest Neighbor method. To support the memory requirements for image processing the system is run on a raspberry pi device. The results of analysis and testing using K-Fold Cross Validation of Gray Level Co-Occurrence Matrix feature extraction show that the best feature combination is dissimilarity-correlation and Classification results using K-Nearest Neighbor show an accuracy rate of 93,33% on the number of neighbor K=7 and 9.
Implementasi Sistem Pendeteksi Obstructive Sleep Apnea berdasarkan Parameter Interval QT dan Interval PR menggunakan Metode Naive Bayes Iqbal Koza; Rizal Maulana; Hurriyatul Fitriyah
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

Obstructive Sleep Apnea is a condition in which breathing stops momentarily during sleep and repeats several times. If this disorder is not treated further, it can cause complications in the form of lack of sleep, fatigue and eye problems. For now, sleep apnea examination can only be checked in a hospital and is expensive. Therefore, in this study a system for detecting obstructive sleep apnea was created which did not require too much money. The tools to be used are the Arduino Uno microcontroller as a place for the system program, the ECG AD8232 sensor to detect electrical activity in the heart which is attached to the chest using 3 electrodes, and a 16x2 LCD to display the final result. This study uses the Naive Bayes classification in classifying the electrical activity of the heart. The features in the classification of the naive Bayes method are the QT Interval and the PR Interval, the results of which will be displayed on the LCD in the form of "Normal" or "Sleep Apnea". There were 24 test data taken and 48 training data used in the Naive Bayes classification test. The results of the accuracy test using Naive Bayes were 87.5%. And the results of computational time testing were carried out 24 times with an average value of 1,044.2083 ms.
Kendali Antena UAV menggunakan Kontrol PID untuk mendapatkan Gain Maksimum Okky Nizka Pratama; Eko Setiawan; Hurriyatul Fitriyah
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

Antenna tracker is a mechanism used to control the direction of the antenna, the system controls the horizontal servo to the right and left, while the vertical servo is up and down. The author made a tracker antenna so that it can follow a UAV that is equipped with PID control to reduce servo movement errors. In general, the system consists of UAVs for sending GPS data, GCS as data receivers, horizontal and vertical servo. PID control testing is carried out to determine the type of controller that is good for the system, disturbance testing to determine the steady state of the system, accuracy testing to determine errors in servo movement, and signal testing to determine the obtained rssi. In the PID control test, it was found that the proportional controller has the best performance with a value of 2 on the horizontal servo and 6.5 on the vertical servo. In the disturbance test, the settling time for the horizontal servo was 0.72 seconds and the vertical servo was 0.8 seconds when the disturbance was given. In the accuracy test, the average horizontal servo accuracy was 89.98% with an average error of 5.33 degrees. Meanwhile, the vertical servo obtained an average accuracy of 96.54% with an average error of 1.34. In the signal strength test, it was found that the rssi when using an antenna is better than without an antenna. At a distance of ± 20 meters, the rsssi is -35 dbm when using an antenna and -58 dbm when not using an antenna.
Sistem Identifikasi Jenis Makanan dan Perhitungan Kalori berdasarkan Warna HSV dan Sensor Loadcell menggunakan Metode K-NN berbasis Raspberry Pi Muhammad Rizqi Zamzami; Dahnial Syauqy; Hurriyatul Fitriyah
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 3 (2021): Maret 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Overweight and obesity are still common diseases in this world, which is caused by an unhealthy lifestyle, one of which is consuming excessive food. This excessive food consumption is caused by several factors, namely emotional problems, environmental and social conditions and certain physical conditions. If food consumption is not controlled and is not balanced with a lot of body activity, it will cause calorie accumulation in the body, resulting in obesity and obesity and a risk of disease. One way to overcome this is by controlling yourself in consuming food by measuring the number of calories that will be consumed. From these problems, a system is made to measure food calories by identifying the type of food and measuring the weight of the food. The identification of these foods uses the k-Nearest Neighbor method and the Loadcell sensor to read the weight of the food being measured. The system will capture images and read the weight of the food measured through the camera module and loadcell sensor. The image is then processed on the Raspberry Pi 3 B to extract the color value from the mean HSV. Furthermore, the extraction results are used as a feature to identify the type of food which is used to measure food calories based on the identification and measurement results of the Loadcell sensor. The results of the system will be displayed on the 16 × 2 LCD screen. The system test uses 5 samples for each type of food. From the test results, the accuracy at k = 3 is 96%, at k = 5 is 92% and at k = 7 is 92%.
Pengembangan Sistem Pengenalan Bahasa Isyarat dengan Sensor Akselerometer menggunakan Metode Naive Bayes Gunawan Wahyu Andreanto; Dahnial Syauqy; Hurriyatul Fitriyah
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 3 (2021): Maret 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Communication is the process of delivering information in social life. However, people with hearing impairments have difficulty exchanging information because of their limitations. The Indonesian Government's solution to this problem is the standardization of the Indonesian Sign Language System (SIBI). Previous research has been carried out related to SIBI alphabet sign recognition with flex sensor and MPU6050 using the Naive Bayes method. However, from 130 tests, the research only produced an accuracy about 43.85%. The problem is due to the limitations of the flex sensor orientation reading accuracy. From these, development research was carried out to improve the accuracy of SIBI sign recognition. From these, development research was carried out to improve the accuracy of SIBI sign recognition. In this study, there were 6 units of MPU6050 that functioned as finger and opisthenar orientation readers. Sign recognition using the Naive Bayes method based on the sensor orientation reading. The research produces data suitability between the controller and the Android application is 100% that the application can be used as a data media representation, Mean Absolute Percentage Error (MAPE) of the sensor readings at 1,471% from 24 tests, classification accuracy rate at 92.31% from 78 tests, and the average processing time at 20 ms from 20 tests.
Sistem Pengendalian Gerak Sendok Menggunakan Sensor Mpu6050 Dan Metode Pid Berbasis Arduino Ahmad Fahmi AdamSyah; Hurriyatul Fitriyah; Rizal Maulana
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 3 (2021): Maret 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Difficulty eating is a condition in which a person is unable to eat normally or comfortably. Researchers want to propose a spoon system that can be controlled its stability. The system of this research is the movement of the spoon to be read using the MPU6050 sensor. The value obtained from the sensor will be forwarded to the Arduino Nano processing unit for calculations using the PID controller method where the Kp, Ki, and Kd variables are searched using the trial and error tuning method. The results of these calculations will be used as a spoon mover. Based on the tests that have been carried out, there are conclusions on the test results, first on testing the accuracy of the sensor angle, it can be seen that from 7 experiments from an angle of 0 ° to 180 ° with a multiple of 30 ° on both axes, namely pitch and roll, the percentage error is 0. 59% or less than 1%. The second test of the accuracy of the servo angle based on the setpoint is done, it can be seen that from 7 experiments from an angle of 0 ° to 180 ° with a multiple of 30 ° on both axes, namely roll and pitch, the percentage error is 0.8. Finally, the system speed test has reached stable or commonly called the settling time that has been carried out, it can be seen that from 10 experiments, the initial speed of the system reaches the settling time, which is the average time of both axes, namely 0.99 seconds or under 1 second.
Alat Pendeteksi Uang untuk Tunanetra menggunakan Metode Histogram of Oriented Gradients dan K-Nearest Neighbor Nico Dian Nugraha; Fitri Utaminingrum; Hurriyatul Fitriyah
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 4 (2021): April 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Banknotes that distributed by scammers would causes restlessness in society, including blind people. With impairment vision, blind people would hard to distinguish between genuine and fake money. From that problem there would be a research about nominal and authenticity detection system for blind people. The detection system consists of camera as a sensor device to detect picture from the banknote, followed by ultraviolet lamp to tell about the genuine banknote, and speaker as the output from this system. Output would generate voice as the nominations and tell if it is genuine or fake banknote. Code program on this system were written in Pyhton language with Raspberry Pi hardware, Webcam sensor camera, and ultraviolet lamp. Detecting banknotes would use Histogram of Oriented Gradients method and using K-Nearest Neighbour method to classify banknote. Around 3370 data training were used to detect about authenticity of the banknotes and the detections were tried for 56 times. implementation of K-Nearest Neighbor method using k=3 obtained an accuracy result of 98.21% with an average compute time of 3608 ms.
Sistem Klasifikasi Kesegaran Daging Sapi berdasarkan Citra menggunakan Metode Naive Bayes berbasis Raspberry Pi Habib Muhammad Al-Jabbar; Hurriyatul Fitriyah; Rizal Maulana
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 4 (2021): April 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Beef is one of the commodities that has contributed to the improvement of public nutrition, particularly the need for animal protein. Fresh beef is meat that is fresh red in color, starting from being cut up to 10 hours. So far, evaluation of freshness and identification of meat composition has been done manually by means of human visual observations. Due to human limitations, there are often different perceptions of each observer. On this basis, as an effort to obtain beef freshness accurately, this research has made a tool that can detect the freshness of beef with the help of digital image computing. By using the Raspberry Pi as a mini computer, a camera as a sensor and image processing which is then classified by Naive Bayes, this system can work properly, it can be proven by the output of the accurate classification of beef freshness. The choice of the naive Bayes method is based on the fact that this method is a very good classification method in which the class of freshness types is known from the start. This method can also work even though it only uses a little training data. When there is a slight change in training data, the naive Bayes method also adapts quite well. The results of the beef color conversion process are then classified at the color level based on SNI standards. From 40 training data and 20 tested data, an accuracy of 95% and an average computation rate of 0.009094 seconds.
Sistem Klasifikasi Langit Cerah dan Berawan menggunakan Gray Level Co-Occurrence Matrix dan K-Nearest Neighbor berbasis Raspberry Pi Marrisaeka Mawarni; Hurriyatul Fitriyah; Rizal Maulana
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 6 (2021): Juni 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Weather is a condition in the atmosphere that occurs in an area in a short time. Weather can be predicted by observing weather elements, such as clouds. This research will perform a weather classification based on sky and clouds conditions in the form of sunny and cloudy weather. Sunny weather occurs when the sun shines brights, and there are no clouds in the sky. Cloudy weather occurs when sunlight is covered by clouds that contain water vapor in the atmosphere. The system used fisheye images so that we have a wider field of view images than panoramic images. The classification process for clear and cloudy skies uses the Gray Level Co-occurrence Matrices (GLCM) method to extract the texture features. The features for the classification of sky conditions in the GLCM method are energy, contrast, correlation, homogeneity, and dissimilarity with four angular variations, namely 0,45,90, and 135. The sky classification process is using the K-Nearest Neighbor method with k = 3,5,7, and 9. The Raspberry Pi 4 is used for the whole data processing, and then the classification results are displayed on the LCD. the Accuracy testing was carried out using k-fold with 5 fold, obtaining an average accuracy result of 100% and an average computation time of 2.3516 seconds.
Sistem Rute Terpendek Pencarian Buku Di Perpustakaan Menggunakan Algoritme Dijkstra Muh. Syifau Mubarok; Dahnial Syauqy; Hurriyatul Fitriyah
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 6 (2021): Juni 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

The library is considered as a convenient place to read, because the library provides a collection of books and other publications services that are provided to the general public or certain groups. Lots of information can be obtained from the library includes scientific, recreational, religious and entertainment that are human needs. However, according to a survey conducted by UNESCO in 2015 stated that the reading interest of Indonesian society is very low. The lack of interest in reading the community can be affected by several factors such as, the minimal number of libraries and the lack of decent facilities in the library. For example, the more extensive a library, the more variations of book categories and certainly directly proportional to the large number of shelves arranged. Doing a random search manually is the way that most often done, so it will wasting time, especially if the library visitors are visiting the library for the first time and don't know the location of the shelves and the arrangement of the book placement. With the research located on the white label room of the central library of Brawijaya University, the writer made an Arduino-based system which was planted in a book basket, which in the system contained a list of book categories in the library as well as the shelf location where the books were stored. The visitors only need to select the category of books that they want to borrow then the system will process it. The resulting output is the shortest bookshelf route through the LCD on the system by first mapping the existing bookshelves in the library by calculating the shortest distance of the book sought on the nearest shelves from the starting point. With the research located on the white label room of the central library of Universitas Brawijaya, the results from 10 random route search samples the system succeeded in determining the right route with an accuracy value of 100%. It is proven that the system works well besides of that the kind system is an embedded system that is installed in a book basket, so it will make it easier for the visitors if they want to borrow a lot of books in large quantities. On another test was done by testing the execution time required by the system to find the shortest route, the results of 10 tests using random samples only require a very short time with an average of 4.2 milliseconds.
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