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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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Implementasi Tingkat Keasinan Telur Asin menggunakan Metode K-Nearest Neighbor dengan Sensor TCS3200 berbasis Arduino Mega Rian Ari Hardianyah; Hurriyatul Fitriyah; Agung Setia Budi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 12 (2021): Desember 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Salted eggs are one of the foods made from eggs that are preserved by salting. Most use duck eggs for preservation and it is possible to use other eggs. Salted eggs have different kinds such as boiled salted eggs, baked salted eggs, smoked salted eggs and grilled salted eggs. In detecting eggs that have been mashed and not mashed, the conventional method is still used. To distinguish between fried eggs and unmarried eggs, to determine the level of saltiness of salted eggs, the TCS3200 sensor will be used to detect the white and yolk colors. For the Arduino Mega Microcontroller, it is used for the proces implemented by the K-NN method to calculate the RGB result value. The results of the first TCS3200 obtained an average value of 4.05% while second TCS3200 obtained an average value of 8.34%. As for the accuracy of K-NN, the value is 66.67% where the difference is not too prominent so it is classified as good..
Sistem Kendali Pitch, Roll dan Ketinggian Quadcopter dengan Isyarat Tangan menggunakan Kalman Filter Muhammad Junifadhil Caesariano; Eko Setiawan; Hurriyatul Fitriyah
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 1 (2022): Januari 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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UAV (Unmanned Aerial Vehicle) is an aircraft that can be controlled remotely either by humans or programmed automatically. UAV control requires a joystick controller. However, the use of a joystick as a UAV controller requires special skills in its use. Therefore, the author created a hand position-based controller that is easier to understand by people who are not familiar with the use of joysticks. However, the sensor readings are often inaccurate, therefore the Kalman Filter is used as a solution to reduce the inaccuracy. The test results show that the use of kalman filter increases the accuracy of sensor readings by using the calculation of the Root Mean Square Error. Based on testing the suitability of control using hand gestures on the movement of the UAV, the accuracy rate of control success is 85% for pitch and roll movements and 70% control success for altitude control
Rancang Bangun Sistem Klasifikasi Ukuran Baju berdasarkan Ukuran Tubuh dengan Metode K-Nearest Neighbor berbasis Arduino Xavierro Lawrenza; Hurriyatul Fitriyah; Dahnial Syauqy
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 1 (2022): Januari 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Technological developments that are currently growing rapidly indicate the emergence of several new innovations that make work activities more practical and efficient because at this time time efficiency is an added value in the success factor in work, one of the fields of work is clothing measurement activities. Currently, the activity of measuring clothing sizes in order to get clothes of the right size requires an innovation to create efficiency and comfort. The purpose of this research is to create a system that can overcome the problems of efficiency and convenience. In this thesis research, the system was created using two ultrasonic sensors HC-SR04 as a measuring tool for body height and width as a parameter for determining the size of clothes and pants and a 16X2 LCD as the output of the size results obtained so that they are more efficient in terms of measurement and speed of time. Arduino Uno is used as a microcontroller in this study because it is hoped that its smaller size can overcome efficiency problems. The sizes that will be included as a classification include sizes S, M, L and XL. Parameters for determining the size include body height and body width. K-nearest neighbor is a classification calculation method by determining the closest distance from the test data to the training data, the number of training data for the nearest neighbor or referred to as K has been determined previously by the researcher. The calculation speed of each test data is about 10 seconds at the latest. Determination of the size using the k-nearest neighbor method because after testing and analysis this method has a high level of accuracy where the calculation results on average almost all get 100% accuracy results.
Implementasi Sistem Pendeteksi Premature Atrial Contraction berbasis Mikrokontroler Arduino Uno berdasarkan Interval QTc dan Durasi Gelombang T menggunakan Metode Support Vector Machine Dipatya Sakasana; Rizal Maulana; Hurriyatul Fitriyah
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 13 (2022): Publikasi Khusus Tahun 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Untuk dipublikasikan ke Jurnal Teknologi Informasi dan Ilmu Komputer (JTIIK)
Sistem Klasifikasi Saus Cabai mengandung Formalin dengan Sensor TCS3200 dan Sensor Groove-HCHO menggunakan Metode K-Nearest Neighbor berbasis Arduino Hamzah Attamimi; Dahnial Syauqy; Hurriyatul Fitriyah
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 1 (2022): Januari 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Chili sauce is a sauce made using the main ingredient chili, which is processed by adding spices and permitted food ingredients, or without the addition of other foods. However, in Indonesia, the term fake sauce is often used to define sauces that contain ingredients that are harmful to the health of the body, one of the dangerous ingredients used is formalin. In checking chili sauce containing formalin carried out by experts by mixing a sample of sauce into a test tube and mixing it with a special formalin reagent, the results of the examination also require a long time. Based on these needs, it is necessary to design a system that can facilitate the checking of chili sauce containing formalin, and does not take much time in the inspection process. In this study, the detection system for chili sauce containing formalin used color parameters and formaldehyde gas content in the sauce sample. Arduino Mega microcontroller is used as a data processor on the system. The system will classify the Non-formalin and Contain Formalin data with the K-Nearest Neighbor method. In this study, 20 test data were applied in 60 training data used to determine the level of classification accuracy from the use of the K-Nearest Neighbor method with a value of K=3 of 85%, K=5 of 85%, and K=7 of 80%. Meanwhile, the average computation time obtained from 10 tests is 1807.3ms.
Analisa Akurasi dari Pendeteksian Berjalan pada Variasi Peletakan Sensor IMU, Filter Kalman dan FIR, serta Klasifikasi KNN dan Naive Bayes David Isura; Hurriyatul Fitriyah; Rakhmadhany Primananda
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 1 (2022): Januari 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Development of research in footsteps has been carried out, especially by using IMU sensor. IMU sensor is a system that can detect changes in speed, orientation of the gravitational force. However, the accuracy in measuring "footsteps" using IMU sensor is not yet accurate, due to inconsistent human footsteps, different body shapes, stepping models and so on. In this research, researchers used MPU6050 sensor where the sensor produces two types of sensors, namely accelerometer sensors and gyroscope sensors. Sensor placement points are located on the wrist, calf and thigh. Sensor used will produce three axis, where each axis is filtered using a Kalman Filter and a Finite Impulse Response (FIR) Filter. After the data is filtered, then data will be classified with the data has been sorted (training data). The classification used is K-NN and Naive Bayes. The use of the best filter is owned by the Kalman filter, which has the lowest average ratio compared to the FIR filter, which is 0.378. Accuracy results obtained from research that has been carried out are 92.5%, where the accuracy has a combination of the use of gyroscope sensors, sensor placement in the calves, the use of Kalman filters and the Naive Bayes classification algorithm. The resulting computation time is 0.23 seconds.
Sistem Kendali Level dan Suhu Air pada Hidroponik menggunakan Sensor Ultrasonik, Sensor Suhu, dan Arduino dengan Metode Regresi Linier Muhammad Rizki Chairurrafi; Hurriyatul Fitriyah; Barlian Henryranu Prasetio
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 1 (2022): Januari 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Hydroponics is a method of farming in which the growing media does not use soil but uses nutrient water needed by plants. There are several factors for the quality of the plants grown hydroponically are fresh and healthy. By controlling the height and temperature of the nutrient water in the hydroponic tub. The control process uses Arduino Uno ATMega328, the for the water level reading system using ultrasonic sensor HC-SR04 and reading the water temperature using a water temperature sensor DS18B20. The output for the water level is a water pump and for the water temperature is a cooling system using Peltier TEC1-12706 as the water cooling component. This research uses a simple linear regression method that functions to predict the duration of the system. The result of this study for the water level feature have a set point of 2,8 cm and the linear regression equation y = 9.71756x - 56.0144 then for the MAPE value is 6.097%. For the water temperature feature have a set point of 28°C and the linear regression equation y - 712.56386 - 19746.65866 then for the MAPE value is 6.3134%. And the computational value to get the duration or y value for the two features obtained from each simple linear regression equation is 1081 mx or 1.081 seconds.
Implementasi Quick Response Code dan Filter Unsharp dalam Deteksi Objek untuk Pemindahan Benda dengan Integrasi Database SQL menggunakan Robot Manipulator Refsi Ilham Cahya; Rizal Maulana; Hurriyatul Fitriyah
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 1 (2022): Januari 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

The increase in the number of E-commerce retail users is currently growing very rapidly coupled with the effects of the covid-19 outbreak which has made the number of users increase. Therefore, an automation system is needed to help support the improvement of the E-commerce business that can perform tasks efficiently without the need to increase production costs. This system will use the camera to identify objects with images but this image will have noise that affects the identification process. The results of taking pictures of the object will be processed by the Raspberry Pi4 with an Unsharp filter to eliminate noise, then the process of identifying information data from the QR code on the object and determining the initial coordinates of the object will be carried out. The results of this data will later be forwarded to OpenCM to move the manipulator robot using the Inverse Kinematics function. In addition, this system will also send information data to the database for data storage. The use of the Unsharp Filter and QR Code methods in this system produces an accuracy value of 100% with a computation time of 801 ms in 40 times of object reading testing. As for the inverse method, this system has an error of 9.12% to reach the coordinates in 10 times of testing. And to move an object the system requires a computation time of 11 seconds for each type of object for scanning, moving, and storing information from the object.
Sistem Klasifikasi Kesegaran Daging Ikan Gurami berdasarkan Warna dan Gas Amonia menggunakan K-Nearest Neighbor (KNN) berbasis Arduino M. Fiqhi Hidayatulah; Hurriyatul Fitriyah; Fitri Utaminingrum
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 2 (2022): Februari 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Gouramy in some areas is one of the mainstay of agriculture. Gouramy meat is one of the sources of food that contains lots of good nutrition for humans. The protein content in gouramy is 19%, more than other fish that are often consumed by humans, such as catfish which has (18.2%) protein content, tilapia which has (16%) protein content, and carp which has ( 16%) protein content. The protein found in fish has more benefits than other animal meat. The characteristics of fresh fish are that it has a smooth texture but is still quite chewy and dense. All parts of the meat seemed to stick tightly to the bone. Gouramy has a weakness after the fish dies, that is, it quickly declines in quality, the speed of decline in fish quality can be influenced by internal factors that depend on the type of fish itself and externally related to human handling. gouramy meat that is not fresh or rotten with fresh gourami meat. So it will be very dangerous if the meat is not fresh or in a rotten state to be consumed by consumers. In this study, a classification system was created that can detect the level of freshness of gouramy meat with the characteristics of quality deterioration found in gouramy meat. With the MQ137 sensor to calculate the NH3 odor parameter and the TCS3200 sensor to calculate the color value of gouramy meat with an output of 3 classes, namely Rotten, Less and Fresh which is displayed on lCD16x2. With the classification results obtained on 180 training data and 30 test data, it produces an accuracy of up to 80% with an average computation time of 8.0667 ms..
Klasifikasi Minyak Nabati Menggunakan Sensor Warna dan Sensor Cahaya dengan Metode K Nearest Neighbor (KNN) berbasis Arduino Nur Aini Afifah Isbindra; Hurriyatul Fitriyah; Dahnial Syauqy
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 4 (2022): April 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Vegetable oil is one of a product from plants and is often used as the main ingredient in food processing. Each plant that is used as a source of this oil produces different vegetable oils in terms of nutritional content. Oils that have high health benefits for the body are usually sold at high prices in the market. The similarity of the characteristics of the oil in terms of its physical make some producers deliberately sell vegetable oil that is not in accordance with the original plant source. To minimize this incident, in this study a system was created to distinguish vegetable oils based on plants directly and quickly. RGB parameters as well as turbidity are used as features in the classification. RGB data is acquired by the TCS34725 color sensor, while the turbidity data will be obtained by the LDR light sensor. The classification method itself uses the K-NN (K-Nearest Neighbor) algorithm. The K-NN method uses training data as a classification system training to calculate the distance from the test data which is the new data that is entered into the system. Then the results of the distance calculation will be sorted from the closest and the results will be determined based on the most selected class in the voting as many as K. Based on the accuracy test of the classification method, an accuracy of 87.5% was obtained from K=3 and K=5. Then the average computational speed of the classification is 103.6 ms.
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