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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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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.
Sistem Pengendali Suhu dan Kelembaban Udara Prototipe Greenhouse pada Tanaman Hidroponik menggunakan Metode Regresi Linier Berganda berbasis Arduino Julisya Thana Khriswanti; Hurriyatul Fitriyah; Barlian Henryranu Prasetio
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

Greenhouses can protect plants from erratic weather and plant pests. One of the optimal planting methods to grow in a greenhouse is wick hydroponics. Hydroponic wick is static because it relies on the principle of capillarity which causes high temperatures and poor dissolved oxygen due to the transfer of oxygen from the solution to the air. However, not necessarily hydroponic wick plants are perfectly protected in a greenhouse. The greenhouse effect is an event where some of the heat that penetrates into the greenhouse is then trapped inside so that the greenhouse air temperature becomes warmer. Warm temperatures affect plant growth because the temperature rises and humidity drops. To create optimal temperature and humidity, this research aims to create a temperature and humidity control system. Multiple linear regression is used to control the system, so that the system can run and adjust according to the time predicted by the multiple linear regression model. The temperature and humidity sensor used is a DHT22 sensor with an error during detecting temperature of 5.47% and humidity of 4.85%. In the system, the mean time of multiple linear regression computation is 111 milliseconds. The multiple linear regression model that used to control the system is very good with an error of 7.34%. The system works well and can lower the temperature and increase the humidity.
Pengendalian Kelembaban dan PH pada Alat Semai Otomatis berdasarkan Sensor Kelembaban, PH, dan Arduino menggunakan Regresi Linier Dody Kristian Manalu; Hurriyatul Fitriyah; Edita Rosana Widasari
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

Humidity and acidity (PH) are essential factors because if rockwool is too acidic not moist or dry the plant growth rate will be slower. A pH that is too acidic or alkaline can result in the deposition of nutrients and inorganic substances in hydroponics so that plant growth is less than optimal. Temperature also plays an important role in plant growth. With this the author will create a system using a Soil Moisture sensor a PH-4502C sensor and a Linear Regression method that is connected to the Arduino Uno and will issue an output that is flowing water through a water pump with the condition that the humidity in the rockwool has not met the set point as well as for the pH will flow PHUP water if the pH conditions on Pakcoy plants are low and will flow PHDOWN if the pH conditions on Pakcoy plants are high. For this system there are 25 training data including 20 data as training data and 5 data as test data. The results obtained from the Linear Regression test are MAPE and RMSE for humidity 5,1% and 0.12 while for PH are 5,2% and 0.17 and the results of Pakcoy seed plants can grow perfectly as expected.
Purwarupa Sistem Monitoring dan Otomatisasi Air Limbah Industri Tekstil dengan Metode Fuzzy Logic Mamdani Imam Pratama Setiady; Mochammad Hannats Hanafi Ichsan; Hurriyatul Fitriyah
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 6 (2022): Juni 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Textile industry is one of national mainstay sectors that contribute significantly to economic progress. High production in textile industry causes damage to environmental because production process produces wastewater which is dumped into river areas. Report from Badan Pusat Statistik (BPS) that quality of river water in Indonesia is in not-good category. To overcome these problems, required systems can carry out monitoring of classification status of wastewater and automation actions. This research implements DS18B20 sensor, pH sensor and turbidity sensor as an input monitoring process controlled by Arduino Mega 2560. Classification and automation process is applied to fuzzy logic Mamdani method for making wastewater status and automation of speed on DC motor R385. Fuzzy logic Mamdani method is applied using fuzzy system designer LabVIEW toolkit to implementation of the fuzzification, inference and defuzzification. All of processes displayed real-time in LabVIEW with form of numbers, indicators and graphs from both the monitoring and fuzzy logic Mamdani results. Accuracy fuzzy logic Mamdani method in system was comparing with system in MATLAB. Results MAPE for water status is 0.49%, disposal is 0.49% and water reservoir is 0.50%. It very good results.
Prediksi Bobot Segar pada Tanaman Hidroponik berdasarkan Kondisi Daun menggunakan Metode Pengolahan Citra Digital dan Jaringan Syaraf Tiruan Mohamad Abyan Naufal Fachly; Hurriyatul Fitriyah; Rizal Maulana
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 6 (2022): Juni 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Based on data from the Central Statistics Agency, the production of mustard plants in Indonesia, especially in East Java Province in 2020 reached 77,176 tons. Where this production increased compared to the production in 2019 which reached 74,395 tons . Mustard plants in Indonesia are cultivated using several techniques, one of the techniques is hydroponics. Hydroponics is a system of cultivating plants using water that contains nutrients and minerals without soil. Plants produced from hydroponics have better quality than conventionally grown plants and also hydroponic plants can prevent plants from pests. Besides having advantages, hydroponic cultivation of mustard plants also has disadvantages such as the amount of electricity used, water discharge, solution concentration, and moss which can affect plant conditions like fresh weight. Fresh weight is one indicator of plant growth, where if the plant growth is good, the fresh weight produced will be high. Therefore, researchers want to predict the condition of hydroponic plants based on their fresh weight using digital image processing methods and artificial neural networks. This system works using a RaspberryPi as hardware that is connected to a webcam. Later the camera will capture the image of the leaves from the hydroponic mustard plant, then provide output in the form of fresh weight information on a 16x2 LCD. Based on the tests carried out on the system using 10 mustard plants to predict the fresh weight of the plant, it resulted in an an average MAPE of 0.67%. In addition , two computational time tests were also carried out , which consisted of the computation time on the system and the computation time for the Artificial Neural Network method . Where the computational time on the system produces an average time of 4.884 seconds and the computation time of the artificial neural network method with an average time of 0.192 seconds.
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