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All Journal International Journal of Electrical and Computer Engineering IJCCS (Indonesian Journal of Computing and Cybernetics Systems) 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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Alat Pengukur Berat Badan dan Tinggi Badan Terkomputerisasi berbasis Wireless, Arduino, Sensor Load Cell, dan Ultrasonic Muhamad Ichwan Sudibyo; Hurriyatul Fitriyah; Rizal Maulana
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 9 (2019): September 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

The measurenment of body weight and height are very common ineveryday life, but there are still many people who do the measurenment manually and separately. When measuring body weight, most people will use digital scales, and for measuring height using a meter. To overcome this problem, the researcher made a system that can measure body weight and height while storing data on body weight and height into the database so that can be seen at anytime. In this system the researcher will use load cell to measurenment of body weight and ultrasonic HC-SR04 censor to measurenment body height. In this study, the data transmission will use a wireless and can store data into the database. From the test result obtained, the data from the reading of weight censor load cell has average data 2.73 kilograms with difference in data of digital scales 0,01 - 0,30 kilograms, and for ultrasonic censor HC-SR04 has average data 0.7 centimeter with difference of meters 0.1 - 0.5 centimeters. Data transmission using the wireless sensor can transmit data to a maximum range of 15 meters. And the data you get can be saved into the database.
Rancang Bangun Pot Cerdas Dengan Mengatur Suhu Ruangan, Kelembapan Tanah, dan Intensitas Cahaya Berbasis Arduino dengan Metode Jaringan Saraf Tiruan Backpropagation Indera Ulung Mahendra; Hurriyatul Fitriyah; Mochammad Hannats Hanafi Ichsan
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 9 (2019): September 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Indonesia is one of the countries where the majority of the population work as farmers. Over time, agricultural land decreases. This encourages people to do farming activities in the home which is often called urban farming. One commodity that is often grown is chili. The growth process of the chili plant itself has several factors that must be considered in order to grow optimally. To support the urban farming activities, an intelligent pot frame was created that could regulate the temperature within the framework, soil moisture in the planting media, and also the intensity of the light in the smart pot frame. All of these functions are supported by using a backpropagation feed-forward neural network classification method. The DHT11 sensor is used to conduct temperature readings with an average reading error rate of 2.57% compared to digital thermometers. YL69 sensor is used to read the soil moisture results from the reading of the soil moisture sensor has a pretty good accuracy compared to the reading from the hygrometer. The LDR sensor is used to read the light intensity with an average error rate of 17.62% compared to digital luxmeter. The reading value of each sensor is then entered into the classification program, where the program takes 548 milliseconds to classify after 20 tests.
Sistem Pengusir Hama Burung pada Sawah dengan Menggunakan Sensor PIR dan Metode Naive Bayes Irham Manthiqo Noor; Hurriyatul Fitriyah; Rizal Maulana
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 9 (2019): September 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

There are various methods in dealing with rice pest attacks. Generally, the method used is less efficient and effective. Research carried out initiated the use of technology, specifically by utilizing the Passive InfraRed Sensor (sensor-PIR) on Arduino-UNO in the eviction of bird pests in the fields. The method using the sensor is able to detect infrared light in the form of heatwaves released by birds. The detection results are then sent to the Arduino UNO next to the servo motor. Utilizing the Naive Bayes method to look for opportunities for success, this study revealed an accuracy percentage of 89.45%. The data computing when the system stops at 1262.5898 milliseconds.
Sistem Deteksi Rem Mendadak dan Tabrakan Pada Motor Menggunakan Sensor Akselerometer Dengan Metode K-Nearest Neighbour Berbasis Arduino Musada Teguh Andi Afandi; Hurriyatul Fitriyah; Gembong Edhi Setyawan
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 10 (2019): Oktober 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Accident is incident that unpredictable both of victim and witness. But, the accident increased for every years. This is caused by increasing of vehicle unit that ciculate especially motor cycle. When accident happen, family of course doesn't know that an accident has occured to their family who drived the vehicle. So it's needed the system that give the information to the victim family in home. System designed used by many components like arduino mega that used for process datas, accelerometer sensor ADXL345 type for takes datas and GSM SIM900A module as sender of message for victim family. The system uses simple regression as fiture that will be used in K-Nearest Neighbour methode (K-NN) and classification methode K-NN to get incident class. Testing process of system by doing acceleration like brake and crashing and will be classified with K-NN methode so it will get value of accuracy 90% when the tragedy is sudden brake and 60% when accident use K value is 3 for both. While use K valueis 5, a precentage is obtained sytem to get right tragedy is 90% when sudden brake and 50% when accident. So as a whole precentage of system to get right tragedy is 83,33% when use K value 3 and 80% when value is 5.
Sistem Klasifikasi Tahu Putih Murni dan Tahu Putih Mengandung Formalin Menggunakan Metode K-Nearest Neighbor Dede Satriawan; Hurriyatul Fitriyah; Agung Setia Budi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 10 (2019): Oktober 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Tofu is a food ingredient made from soybean deposits, and tofu is a type of food that does not last long after it is produced. Therefore, some tofu producers are not responsible for adding formaldehyde chemical to tofu so that tofu is more durable and not easily rot. Food containing formalin if consumed by the body is very dangerous to health in the short to long term. And if the body is exposed for a long period of time, it will cause damage to the kidneys, lymph, pancreas, liver, heart, and accelerate the aging process. To solve this problem it is necessary to design a system for the classification of pure white tofu and white tofu containing formalin using Arduino Mega hardware with input sensor from Grove-HCHO as a gas sensor, TCS3200 as a color sensor and the output will use LCD. And the accuracy of the system will be tested with the results with an average percentage error accuracy obtained from the sensor input is 1.20% for TCS3200 sensors, 4.26% for the Grove-HCHO sensor. For the classification of the K-NN method the percentage accuracy obtained is 83.33%.
Sistem Klasifikasi Bakso yang Mengandung Boraks dengan Sensor Warna Menggunakan Metode K-Nearest Neighbor Berbasis Arduino Dimas Dwi Saputra; Hurriyatul Fitriyah; Eko Setiawan
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 10 (2019): Oktober 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Meatballs are a favorite meal of Indonesian people from various backgrounds, there are various types of meatballs based on the use of meat such as chicken meatballs, beef meatballs, shrimp meatballs or rabbit meatballs. Meatballs are also foods that have a delicious taste and nutritional content, protein, vitamins in meatballs can benefit the body. But many meatballs have been circulating with the content of dangerous chemicals in this case is borax. Borax is a chemical compound for use as a wood preservative, an insect repellent and detergent-making material. The use of borax material in meatballs is intended so that meatballs sold by unscrupulous traders can be more durable and have a good texture and shape, so that people can be interested in buying the meatballs. To overcome these acts of cheating, it is necessary to design a system to classify meatballs containing borax with meatballs that do not contain borkas. In order for the system to be implemented, it requires an Arduino Mega microcontroller to process data as well as classification calculations, a color sensor to distinguish colors from the tested meatball object and a pH sensor to detect pH levels on the meatballs. In order for this system to classify, this system will use the K-Nearest Neighbor classification method by using the K value 3,5,7,9,11,13,15,17. The results of the difference in K values ​​will be compared with other K values ​​to find out which K value has the highest accuracy. From testing on the system, the highest accuracy is obtained at 93.33% by applying the K 5 value to the K-Nearest Neighbor method.
Estimasi Volume dan Berat Buah Belimbing menggunakan Metode Cakram dan Regresi Linear berbasis Kamera pada Raspberry Pi Muhammad Rifqi Radifan Masruri; Hurriyatul Fitriyah; Eko Setiawan
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 11 (2019): November 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Evaluating starfruit by looking at its size can be done using a conventional method. This method requires a lot of human resources and time. To speed up the process, digital image processing technology is used. Starfruit is a fruit that is very popular in Indonesia. Sweet and sour taste in starfruit is very suitable to be made into salad. Starfruit becomes a challenge because it has five sections and does not resemble a solid. There is a modified method for adjusting starfruit characteristics. This study uses volume and weight parameters in evaluating. Digital images are taken using a camera connected to the Raspberry Pi. The image obtained is processed for segmentation. Information from the results of segmentation will be used in a modified cylindrical method to produce a volume. Volume will be used in the linear regression method to produce weight. The accuracy of the volume method obtained was 86.64% and the accuracy of the weight method was 86.43% with an average execution time of 3.45 seconds. This solution can be an example of the image processing technology development.
Sistem Penghitung Jeruk Matang pada Kebun berdasarkan Hue, Saturation dan Chrominance-Red menggunakan Algoritme Watershed berbasis Raspberry Pi Salsabiil Hasanah; Hurriyatul Fitriyah; Rizal Maulana
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 11 (2019): November 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Oranges contain vitamin C and a lot of mineral content. The public will definitely choose an orange fruit whose skin color is orange or the condition is ripe. Therefore, farmers must harvest citrus fruit when the conditions are ripe or when the color of the skin turns orange. In the area of ​​agriculture today there are those who implement modern agriculture. The use of technology applied to agriculture is the use of robots. Currently in Indonesia there is no robot that automatically harvests mature oranges in the garden by detecting which ones are already ripe in the garden and then picking them. The harvest process also requires a counter function of ripe oranges in the garden which can be detected to find out the number of ripe oranges found in the garden. From the problems above, the research conducted by this writer will focus on the detection of mature oranges in the garden and the calculation of mature oranges detected using digital image processing. This system will take pictures of oranges found in the garden. The process of detecting ripe oranges uses the Hue, Saturation and Chrominance-Red color space, whereas for the calculation of ripe oranges detected using a watershed algorithm. In testing the system in the process of calculating ripe oranges using watershed algorithm obtained an accuracy rate of 82.14% with an average computing time of 2652 ms for one calculation process.
Implementasi Sistem Pendeteksi Premature Ventricular Contraction (PVC) Aritmia Menggunakan Metode K-NN Sulthan Ghiffari Awdihansyah; Rizal Maulana; Hurriyatul Fitriyah
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 4 No 2 (2020): Februari 2020
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

The condition when the heart beats early is called the Premature Ventricular Contraction (PVC) Arrhythmia. Arrhythmia PVC conditions occur in the left ventricle of the heart. Almost every human will experience PVC arrhythmia during his lifetime. Arrhythmia PVC conditions that occur in a long time span can increase the risk of heart disease that leads to death. Examination of arrhythmia PVC conditions cannot be done independently and is quite expensive. AD8232 ECG Sensor Module, LCD 16x2, and Arduino Mega Microcontroller are used to detect PVC arrhythmia conditions. The K-NN classification method is used to classify 1 heartbeat cycle signal. The results of the K-NN classification are in 2 classes, namely the "Normal" class and the "PVC" class. The QRS Complex and Gradient R values of 1 heartbeat cycle signal will be used as parameters. heart conditions "Normal", "Bigeminy", "Trigeminy" are the output produced by the system. A total of 46 data were used as training data and as many as 23 data were used as test data in the classification of the K-NN method. The average value of program computation time is obtained by performing 10 times of program computation time testing. An accuracy value of 91.3% was generated from the results of the K-NN method classification accuracy testing. Testing the computational time of the program produces an average value of computing time of 1988.9ms.
Sistem Penghitung Stroberi Matang di Kebun berdasarkan Hue dan Saturation menggunakan Algoritme Watershed berbasis Raspberry Pi Putri Harviana; Hurriyatul Fitriyah; Eko Setiawan
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 4 No 2 (2020): Februari 2020
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Strawberries are fruits that contain many benefits, so strawberries are widely cultivated in Indonesia. In the cultivation, farmers pay attention to the productivity of strawberries in terms of excess quality. Farmers are still counting strawberries conventionally or manually so they ask for a long calculation time. In addition, farmers have never received their harvest now. Therefore, farmers need tools that can help and provide in agriculture known as modern agriculture or modern agriculture. Existing modern agriculture in Indonesia such as rice planting and automatic harvesting equipment, soybean dryers, pesticide sprayers, superior seed sorting machines, and so on. To make a tool that suits the needs of strawberry fruit farmers, researchers developed a mature strawberry counter system in the garden based on hue and saturation values. The hue and saturation values ​​are used because both of these values ​​can overcome the change in light intensity and can be used to detect obsolete strawberries based on the skin color of the fruit. The system uses a watershed algorithm to separate the attached or attached strawberries so that they are counted as different objects. This system is based on Raspberry Pi because it can process images quickly. With this tool it is expected to be used to predict crop yields. The harvest prediction can be used to help the work of farmers in their crops, so farmers can improve the quality of the crop every year. It is hoped that further system development can facilitate farmers to pick strawberries released in the gardens carried out by robots. On the test results obtained by the system, obtained an accuracy rate of 82% with an average calculation time of 7558.1 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 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 Erdano Sedya Dwiprasajawara Esa Prakasa Fadhilatur Rahmah 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