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All Journal Jurnal Neutrino : jurnal fisika dan aplikasinya TELKOMNIKA (Telecommunication Computing Electronics and Control) Jurnal Teknologi Informasi dan Ilmu Komputer Journal of Information Technology and Computer Science Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Tri Dharma Mandiri: Diseminasi dan Hilirisasi Riset Kepada Masyarakat (Jurnal Pengabdian Kepada Masyarakat)
Barlian Henryranu Prasetio
Fakultas Ilmu Komputer, Universitas Brawijaya
Biochemistry, Genetics & Molecular Biology Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering Health Professions Physics Public Health Social Sciences

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Sistem Klasifikasi Kualitas Jenis-Jenis Madu berdasarkan Warna, Kecerahan, dan pH menggunakan Metode JST Backpropagation Muhammad Habib Jufah Alhamdani; Dahnial Syauqy; Barlian Henryranu Prasetio
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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Honey is a food substance that has sweet taste and thick structure produced by bees. Honey can be distinguished by observing the color and clarity of honey, but it is quite difficult due to lack of knowledge and each type of honey has almost the same color and level of clarity. Based on these problems, this study designed a system to classify the type and authenticity of honey. The sensors used are the TCS3200 sensor, the LDR sensor, and the pH sensor. The TCS3200 sensor and LDR sensor are placed on the back side and on the front side of the sample glass an LED light is added, while the pH sensor is at the top of the glass and the pH sensor eye is immersed in the solution in an upright position so that the sensor can optimally determine each characteristic of the honey sample. The backpropagation ANN algorithm in this study is processed using Arduino Nano with a network structure of 3 inputs, 1 hidden layer containing 24 perceptrons, and 1 output which is divided into 6 classes. The structure design process uses 900 datasets, the learning rate is 0.001, the epochs are 28.451 and the training process is 2 hours 23 minutes 14 seconds. From the testing process the backpropagation neural network algorithm is proven to be able to classify each honey class well and the NN algorithm accuracy reaches 94.45%, with an average computation time of 0.80076 seconds.
Sistem Deteksi Penyakit Flu menggunakan Suara Batuk menggunakan MFCC dan KNN pada Raspberry Pi Aldi Jayadi; Barlian Henryranu Prasetio; Sabriansyah Rizqika Akbar
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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Dipublikasikan di ICSINTESA
Sistem Pengenalan Suara Batuk menggunakan BFCC dan KNN pada Raspberry Pi untuk Deteksi Dini Penyakit Bronchitis Septiyo Budi Perkasa; Barlian Henryranu Prasetio; Eko Setiawan
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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Dipublikasikan di IoTAIS
Klasifikasi Kualitas Air Tebu berdasarkan PH dan Warna menggunakan Metode Jaringan Syaraf Tiruan berbasis Arduino Hafidz Abdillah Masruri; Dahnial Syauqy; Barlian Henryranu Prasetio
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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Sugarcane juice (sugar cane juice) is a product of the sugarcane plant (Saccharum officinarum) which can be used as a basic ingredient for making brown sugar, medicine, food, or alcohol. Good sugarcane juice has a pH of 7 to 5 and has a green, brown, yellow color. Sugarcane water have a decrease in quality due to contamination. Decreasing the quality has many impacts such as consumer impacts, benefits impacts, losses, and even be toxic. The parameters that are often used by farmers to determine the quality are color, scent, and taste which sometimes the point of view of a person will be different to determine a fixed standard that can be used. Therefore, the researcher wants to create a system that can fixed parameters, namely the sugarcane water quality classification system with 3 classes: best quality, quality suitable for consumption, and quality not suitable for consumption according to the parameters of sugarcane processing Wajak, Malang City. The system uses a 4502C pH sensor and a TCS3200 color sensor to detect the color and pH of sugarcane juice, then utilizes Arduino UNO as a microcontroller and utilizes PROGMEM syntax so that the memory capacity used can be lighter, the classification process uses the backpropagation artificial neural network method, then the results system is displayed via a 16x2 I2C LCD. Based on the test results, the PROGMEM syntax system was able to get 19% lighter results than without using it and testing 10 samples got 90% accuracy because 9/ 10 tests were successful.
Implementasi FIR Filter pada Sistem Monitoring Suara Jantung dan Paru-Paru Nadi Rahmat Endrawan; Barlian Henryranu Prasetio; Rizal Maulana
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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Dipublikasikan di SIET 2022
Klasifikasi Kualitas Beras berdasarkan Nilai Data Larik Sensor Gas MQ menggunakan Metode Jaringan Syaraf Tiruan berbasis Arduino Defri Alif Raihan; Dahnial Syauqy; Barlian Henryranu Prasetio
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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Rice is the result of the rice plant which is separated from the husks, every year the need of rice for indonesian people continues to increase, the abundant rice yields make rice have different types and qualities, in general the components that make up the smell of rice consist of several compounds it will produce a different smell of rice. Indonesian people still use conventional methods to classify quality in terms of taste and aroma, this makes the quality classification inaccurate and produces inappropriate quality, that makes many people commit fraud by circulating unsuitable types of rice and make bad quality which causes losses to various parties due to inappropriate prices and quality. With the development of technology, a tool that can classify based on quality is made using input from the array of MQ gas sensor by utilizing the Arduino UNO R3 microcontroller as a data processor from the gas sensor and utilizing a computational time code which make the system can classify quickly, the classification process uses the artificial neural network method and the classification results will be displayed on a 16x2 I2C LCD. the system is able to classify the quality with an average execution time of 54 milliseconds. From 11 test, the system is able to complete 9 times the output according to the detected sample which makes the accuracy of the system more than 80% and in accordance with which is expected.
Sistem Kontrol dan Monitoring Kualitas Air pada Kolam Ikan Air Tawar menggunakan Logika Fuzzy berbasis Arduino Yosia Nindra Kristiantya; Eko Setiawan; Barlian Henryranu Prasetio
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 7 (2022): Juli 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Control on the water quality of freshwater fish ponds is the main thing that must be considered, whether consuming freshwater fish or ornamental freshwater fish. Fish pond water quality parameters that can be controlled for example are temperature and ammonia as parameters that can affect the survival and lifestyle of fish. To overcome this, a water quality control and monitoring system is needed in freshwater fish ponds that can help with these problems. This system receives the results of sensor readings which will later be processed in the microcontroller using the fuzzy method to determine the output of the system. The temperature sensor used is the ds18b20 sensor. Based on the tests that have been carried out in this study, the average value of the reading error from the ds18b20 sensor is 0.95%. The ammonia sensor used is the mq-135 sensor, based on the tests that have been carried out in this study, the average error value of the mq-135 sensor reading is 0%. The Sugeno model fuzzy method used in this study after testing the value with an average error of 3.92%. The system is able to run computations from fuzzy method calculations with an average time of 1.4 seconds
Implementasi Sistem Pendeteksi Premature Atrial Contraction (PAC) menggunakan Metode Naive Bayes Classifier Rosyana Lencie Mampioper; Rizal Maulana; Barlian Henryranu Prasetio
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 7 (2022): Juli 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Heart disease or cardiovascular disease is one of leading causes of death worldwide. In Indonesia there are more than two million cases per year. Premature Atrial Contraction (PAC) is a heart disease in the atrium section where this heart rhythm disturbance occurs with symptoms of a faster or slower and irregular heartbeat. Currently, Premature Atrial Contraction (PAC) examination is performed by cardiologists with patients undergoing ECG tests. However, the cost of ECG examination is quite expensive and also the pandemic conditions caused restrictions to public places and hospitals. Therefore, a solution is offered in this study to identify early PAC heart rhythm disorders. This study makes a prototype using several devices such as Arduino Nano as Microcontroller, AD8232 Sensor and Electrodes to get ECG signal and also LCD to display the heart information output either “normal” or “PAC”. The main features in this system are RR intervals and QRS complex and apply classification using Naive Bayes Classifier. The results of the naive bayes classification in this study achieved an accuracy value of 91,67% using 24 training data and 12 testing data with an average computation time of 3,35 milisecond.
Rancang Bangun Sistem Tracking Matahari berdasarkan Cahaya dan Arus pada Sel Surya menggunakan Logika Fuzzy Model Sugeno Yunan Alamsyah Nasution; Dahnial Syauqy; Barlian Henryranu Prasetio
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 7 (2022): Juli 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Electricity is one of the most demand energy nowadays, demand for electricity has come greater year by year. With the increasing demand for electrical energy, the need for fulfillment of enviromentally friendly energy. One way is to use solar panels. However, the effectiveness of solar panels will be reduced if their position is not perpendicular to the direction of the sun's rays. Based on the problem, writer want to make a system that can increase solar panels effectivity with detecting where sun ray come with LDR sensors, and the system can move the solar panel in the direction of sun ray comes with servo motor. Data gathered from each sensors will be processed in the Arduino Uno with Fuzzy Logic and then Arduino Uno will send a signal to servo motor to move according to calculations that has been done before. Based on testing, after solar fuzzy system installed on the solar panel, the effectiveness of solar panels increased by 13,427%.
Rancang Bangun Sistem Klasifikasi Kualitas Minyak Goreng berdasarkan Warna dan Kejernihan menggunakan Metode Naive Bayes berbasis Arduino Uno Joan Chandra Kustijono; Fitri Utaminingrum; Barlian Henryranu Prasetio
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 8 (2022): Agustus 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Cooking oil is one of the basic needs of the Indonesian people for food processing ingredients, especially for frying process. Palm cooking oil is commonly used by Indonesian people because it matches the Indonesian people's taste. In its use, cooking oil is often used repeatedly for savings which is known as used cooking oil. The use of used cooking oil can increase the risk of several diseases for the body, such as carcinoma and diarrhea caused by the accumulation of peroxide values, as well as changes in the color and clarity of the oil. To determine the quality of the oil, the method used today is to test the peroxide number in the laboratory. However, this method takes more time and is not cheap. So that a system was created that can detect the quality of cooking oil based on color and clarity using the Naive Bayes method to shorten the time at a lower price. This study uses a TCS3200 sensor to detect color changes, and an LDR sensor to detect oil clarity. There are 2 classes used, namely the Eligible class to declare that the oil is still suitable for use and the Inappropriate class to declare that the oil is not suitable for use. In the research results, the accuracy of the TCS3200 sensor is 95.15%, the accuracy of the Naive Bayes method is 87,5%, and the overall system accuracy is 87.5%.
Co-Authors Achmad Ridok Adharul Muttaqin Adi Setiawan Adven Edo Prasetya Adven Edo Prasetya, Adven Edo Agra Firmansyah Ahmad Afif Supianto Aldi Jayadi Ali, Zidane Allaam, Fakhrul Arief Kurniawan Aryo Pinandito Ash-Shadiq, Aqsath Muhammad Aswin Suharsono, Aswin Atmojo Pamungkas, Handoko Bagus Ayu Astina Sari, Ni Made Baariu, Rahagi Abdu Bagus Priyo Pangestu Brylliano Maza Putra Budi Darma Setiawan Budy Prakoso, Khrisna Shane Chatarina Umbul Wahyuni Dahnial Syauqy Dayat, Fauzi Syarifulloh Defri Alif Raihan Denny Sagita Rusdianto Dhimas Arfian Lazzuardhy Dini Eka Ristanti Dini Ismawati Dwiki Ilham Bagaskara Dwinanda Romolo Edita Rosana Widasari Edita Rosana Widasari, Edita Rosana Eko Setiawan Eko Setiawan Eko Setiawan Fabiana, Ryzaldi Ananda Fachry Ananta Fadhilah, Khairian Fadhillah, Muhammad Galih Faisal Natanael Lubis Faviansyah Arianda Pallas Faza Gustaf Marrera Fitra Abdurrachman Bachtiar Fitriyah, Hurriyatul Gembong Edhi Setiawan Gembong Edhi Setyawan Ghifari, Ahmad Hafidz Abdillah Masruri Hanifa Maulani Ramadhan Haqyah, Saprina Hani Heru Nurwarsito Hilal Imtiyaz I Wayan Boby Astagina Naghi Imam Cholissodin Iqbal Maulana Susanto Irfan Muzakky Nurrizqy Irwanda Adhi Firmantara Isnandar, Muhammad Fawwaz Dynoeputra Iwasawa, Takeru Jevandika Joan Chandra Kustijono Julisya Thana Khriswanti Kamal, Attar Syifa Kusuma, Lindhu Parang La Ode Adriyan Hazmar Lavanna Indanus Ramadhan M. Hannats Hanafi Ichsan M. Ihsan An-Nashir Mahardika, Aryanta Seta Mochammad Hannats Hanafi Mochammad Hannats Hanafi Ichsan Muchlas Mughniy Muflih, Aufada Muhammad Fatikh Hidayat Muhammad Ghifari, Muhammad Muhammad Habib Jufah Alhamdani Muhammad Nabil Aljufri Muhammad Rizki Chairurrafi Nadi Rahmat Endrawan Nashrullah, Ega Rasendriya Naviaddin, Arsal Wildan Ngulandoro, Mochammad Giri Wiwaha Nobel Edgar Novaria Elsari Ryzkiansyah Novea, Leisha Nur, Farhan Marwandi Nurrizqy, Irfan Muzakky Nurul Hidayat Ovriawan Aldo Pribadi Putra Paleva, Haidar Rheza Panggabean, Riki Boy Parja, Mujianto Anda Perkasa, Septiyo Budi Permana, Galih Pierl Kritzenger Sinaga Prawironegoro, Abdul Harris Putera, Thariq Andhita Putra Pamungkas, Dimas Resha Putra, Brylliano Maza Putra, Ravelino Adhianto Surya Raden Galih Paramananda Rahmawan, Muhammad Fuad Rajasa, Mohammad Fariq Rakhmadhany Primananda, Rakhmadhany Ramadhan, Dimas Ramadhan, Muhammad Fitrah Randy Cahya Wihandika Rekyan Regasari Mardi Putri, Rekyan Regasari Mardi Reza Hastuti Riyad Febrian Rizal Maulana Rizal Maulana, Rizal Rosyana Lencie Mampioper Ryan Anggito Priono Sabriansyah Rizkiqa Akbar Sabriansyah Rizqika Akbar Sabriansyah Rizqika Akbar Septiyo Budi Perkasa Sifaunnufus Ms, Fi Imanur Sigit Priyo Jatmiko Subianto, Aflah Fadhlurrahman Syahrul Chilmi, Syahrul Tampubolon, Jeremya Tiara Mahardika Tibyani Tibyani Utaminingrum, Fitri Valensiyah Rozika Widasari, Edita Rosana Wijaya Kurniawan Wijaya Kurniawan Yosia Nindra Kristiantya Yudhistira, Gevan Putra Yunan Alamsyah Nasution Yusril Dewantara Yusuf, Delfi Olivia