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All Journal International Journal of Electrical and Computer Engineering International Journal of Reconfigurable and Embedded Systems (IJRES) ComEngApp : Computer Engineering and Applications Journal TELKOMNIKA (Telecommunication Computing Electronics and Control) Jurnal Teknologi Informasi dan Ilmu Komputer Register: Jurnal Ilmiah Teknologi Sistem Informasi Journal of Information Technology and Computer Science Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi Dinamisia: Jurnal Pengabdian Kepada Masyarakat
Dahnial Syauqy
Fakultas Ilmu Komputer, Universitas Brawijaya
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Social Sciences Other

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Deteksi Tangga Naik dan Turunan untuk Notifikasi Keamanan pada Tunanetra menggunakan YOLO Versi 4 berbasis Jetson Nano B01 Muhammad Nazrenda Ramadhan; Fitri Utaminingrum; 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

Blind people currently use The White Cane to help with their daily activities. However, The White Cane has a drawback where its detection range is limited to the length of the cane. In addition, The White Cane cannot distinguish objects that are in front of blind people. This study aims to develop a Jetson Nano B01-based system that can detect floors and stairs, both going up and down to assist the activities of blind people. With the help of artificial intelligence, this system is expected to be able to notify blind people that there is a stair in front of them by activate a buzzer. Then, to be able to produce the right stair detection, pattern recognition is needed with the You Only Look Once (YOLO) method which has a fast detection speed. When the stairs are identified, the system will give a notification in the form of a buzzer sound to notify that there is a stair ahead. The tests carried out, obtained the results of the classification accuracy of object detection (Floor, Upstairs, and Downstairs) of 90%, the average computation time of 0.177s, and the integration accuracy of YOLOv4 detection with a buzzer of 100%.
Rancang Bangun Perangkat Wearable "Clever-Mask" untuk Pemantauan Pola Pernapasan sebagai Penanganan Pertama pada Pasien Terdampak Covid-19 secara Kontinyu Moch. Alvin Yasyfa Salsabil; Dahnial Syauqy; Agung Setia Budi
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

Big Pandemic Covid-19, In ​​Indonesia Deaths due to the Covid-19 virus up to 144,000 thousand people. One of the causes of the high number of deaths due to Covid-19 cases is the lack of prompt treatment for patients affected by Covid-19 in the cytokine storm phase. Cytokine Storm is a condition in which the release of mal-adaptive cytokines is “out of control” in response to infection and stimuli. Cytokine storms attack lung tissue and blood vessels. In this study, a system consisting of several components was used, namely, Arduino Mega 2560 Rev 3 as a microcontroller board, NTC Thermistor Sensor as a breathing signal generator mounted on an oxygen mask and an OLED display to display the output in the form of "Normal" or "Abnormal". This system uses the Min, Max, Amplitude, Interval and Breath Rate features per 4 cycles of 4 cycles which are then classified using the Support Vector Machine. In system testing related to testing the accuracy of the classification results using the Support Vector Machine, it was carried out 12 times to find the class of the test data obtained and the accuracy level of the classification results with SVM was 91.66. In the computational testing of the system, the classification was carried out 12 times to get the class classification results from the test data and the average computation time was 29.29 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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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.
Pengembangan Smart Trash sebagai Media Monitoring Lingkungan Hidup Larva Lalat Tentara Hitam (Hermetia Illucens) menggunakan Metode Gaussian Naive Bayes Mukhamad Angga Setiawan; Dahnial Syauqy; Mochammad Hannats Hanafi Ichsan
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

Indonesia is one of the country with the most waste in the worlds. Most of the waste come from organic waste. One way to reduce the organic waste is using help from microorganism such as black soldier fly larvae (Hermetia Illucens). The living environment of the black soldier fly larvae greatly influences the amount of organic waste consumption, such as temperature, height of the media, humidity, and water content of organic waste. Using smart trash can help to monitoring the environment of the larvae so the condition of black soldier fly larvae is maintained well. This system using DS18B0 as temperature sensor, VL53L0X as height sensor, DHT-22 as humidity sensor, and YL-69 as moisture content are connected to the nodeMCU microcontroller. The data from system is continuous data so it must implement gaussian naive bayes first before implementing naive bayes. There are three classes of system output classification, namely “Optimal”, “Medium”, and “Bad”. Sensors data and classification result are sent through the firebase server which is then sent it to the android application and displayed on the lcd screen. By using 32 training data and 17 test data, the accuracy of the gaussian naive bayes classification is 82,3%. The average computional speed of gaussian naive bayes classification is 5,2 ms by performing 10 times tests. Meanwhile, the accuracy of sending data to the firebase is 100%.
Adaptasi Pergerakan pada Robot Beroda terhadap Jalan Halang Rintang dengan Metode Fuzzy Billy Gusparentaqi; Eko Setiawan; 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

In this study, the aim of this research is to design the adaptation of the movement of the wheeled robot using the fuzzy method. In this wheeled robot, there are 3 ultrasonic sensors input and 2 DC motor output. These inputs and outputs will be used as variables for the fuzzy method. This input variable consists of sensor (left), sensor (front) and sensor (right), each of which has 2 sets of membership functions, namely near and far. This output variable consists of a DC motor (right) and a DC motor (left), each of which has 2 sets of membership functions, namely slow and fast. The number of if-then rules in the fuzzy method used is 8 rules. The test was carried out as many as 3 experiments on the movement of the wheeled robot, namely moving straight, moving to turn right and moving to turn left. This test succeeded in proving that the fuzzy method can control the movement of the wheeled robot.
Sistem Monitoring Postur Tubuh Lansia berbasis Wearable Embedded System dan Metode Klasifikasi Naive Bayes Cahyanita Qolby Rahmarta Rizaputri; Dahnial Syauqy; Rizal Maulana
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 5 (2022): Mei 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Posture is a movement made by humans, either standing, walking, face down, sitting or lyiing down. Movement of the body is also a process that requires complex integration of the limbs. Walkiing is the same as moving and both require balance control in the body. Posture will change with age and several factors are considered. The older you get, the more prone your body will be to injury. The Elderly Posture Monitoring System Based on the Wearable Embedded System and the Naive Bayes Classification Method was created to monitor the movement of an elderly person, usiing several determined axis points. The goal is to get a value from the angle of the body at the top and bottom. The installation of the point axis is at the top of the right and left calves and on the back as the main axis. This system uses the Naive Bayes classification method with 65 training data taken from 5 people and divided into 5 classes. In the test, it has obtained an error percentage of 10% to 20% and got an overall success with an accuracy percentage of 90% which was tested 10 times. The system will also send an Alert to the telegram bot if it occurs due to rapid changes from one class to another with a time frame that is limited to 10 seconds
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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Abstract

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 Monitoring Multiruang Lokasi Lansia dengan Teknologi Indoor Positioning System (IPS) berbasis Wi-Fi dan Algoritma Random Forest Dading Firwandhi Sukma; Dahnial Syauqy; Sabriansyah Rizqika Akbar
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

Elderly is a person aged more than or equal to 55 years. The elderly experience aging in their bodies which makes them vulnerable when they fall so that the elderly need intensive supervision to stay safe. In this study, a system was built that can monitor the elderly in six different rooms using Wi-Fi as an indicator of the Indoor Positioning System (IPS) technology.The system is built in two stages, namely the training stage and the testing stage. At the training stage, the system scans the Received Signal Strength Indication (RSSI) value from each room. From the data obtained, using the Random Forest Algorithm, a model is made that will be used on the microcontroller to predict the location of the elderly based on the scanned RSSI. In the testing phase, a wearable device was built that was attached to the waist of the elderly. Wearable devices will predict the position of the elderly and will send the prediction results to the database and displayed on the smartphone application. Tests are carried out to test the accuracy of the system that has been built. The results of the test obtained an average accuracy of all rooms of 82.85%.
Implementasi Real Time Operating System (RTOS) pada Mikrokontroler Arduino Uno untuk Menghitung Benih Lele Bayu Santoso; Dahnial Syauqy; Agung Setia Budi
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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Abstract

Dipublikasikan di JITeCS
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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Abstract

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.
Co-Authors A. Ashar Ashari A. Baihaqi Mubarok Abdul Aziz, Muhammad Rafi Abdul Rahman Halim Abdussalam, Ghifarie Sa'id Achmad Basuki Achmad Fanani Kurniawan Saputra Achmad Rizal Zakaria Addin Miftachul Firdaus Adharul Muttaqin Adhisuwignjo, Supriatna Adhitya Bhawiyuga, Adhitya Adi Setiyawan Adinugroho, Sigit Adit Ilmawan Adryan Chiko Pratama Afdy Clinton Afflatuslloh Adi Salung Agastya Bramanta Sanjaya Aghnadiin, Radifan Muhammad Agi Putra Kharisma Agra Firmansyah Agung Bachtiar Sukmaarta Agung Leona Suparlin Agung Prasetyo Agung Setia Budi Agung Setia Budi, Agung Setia Agung Widya Gumelar Agung Wismawan Rochmatullah Ahmad Mustafidul Ibad Ahmad Rizqi Pratama Ahmad Wildan Ahmad Yazid Bastomi AJI, IBRAHIM Akbar, Muhammad Daffa Pradipta Akbar, Muhammad Faithur Adel Patria Alfian Reza Pahlevi Alrynto Alrynto Althaf Banafsaj Yudhistira Andhika Nino Pratama Anggi Diatma Styandi Angsar, Mohamad Rinaldi Anisa Awalia Rizky Anjasmoro, Reza Ardiansyah Ardiansyah Arief Kurniawan Arief Wahyu Wicaksono Aulady, Fadhli Aulia Zhafran Barlian Henryranu Prasetio Bayu Rahayudi Bayu Santoso Belsazar Elgiborado Giovani Djoedir Billy Gusparentaqi Bima Muridianto, Muhammad Bimo Dimas Nugraraga Buce Trias Hanggara Bukhori Darmawan Bunga Boru Hasian Siahaan Cahyanita Qolby Rahmarta Rizaputri Cipto Bagus Jati Kusumo Constantius Leonardo Pratama Dading Firwandhi Sukma Daffa, Ali Zhafran Dedi Siswanto Defri Alif Raihan Denis Reza Ramdani Devo Harwan Pradiansyah Dimas Rizqi Firmansyah Dini Eka Ristanti Dini Ismawati Duwi Hariyanto Dwi Arini, Talitha Dwi Firmansyah Dwiki Ilham Bagaskara Dyas Restu Palupi Edita Edita Rosana Widasari Edita Rosana Widasari, Edita Rosana Eka Nanda Sugianto Eko Ardiansyah Eko Hilmi Firmansyah Eko Setiawan Eko Setiawan Elisabeth Agustina Era Imanningtyas Ezra Maherian Fachry Ananta Fahmi Gymnastiar Gozali, Muhammad Faizal Ardiansyah FAQIH, ABDULLAH Farras Nabil Fatur Rahman, Mohammad Fauzi Ali Farhi Fauzi Rivani Fikri Fauzan Firdy Yantama Firmanda, Dwi Ady Firza Zamzani, Muhammad Fitriyah, Hurriyatul Fungki Pandu Fantara Ganda Wibawa Putra Gembong Edhi Setyawan Ghazy Timor Prihanda Govinda Dwi Kurnia Sandi Graciella Fiona Br. Panjaitan Grafidi, Alif Akbar Gunawan Wahyu Andreanto Hafidz Abdillah Masruri Hafiz Nul Hakim Hamdan Bagus Firmansyah Hamzah Attamimi Hanggara, Buce Trias Hannats Hanafi Ichsan Haqiqi, Farih Akmal Harahap, Syazwandy Hazal Kurniawan Putra Hazbiy Shaffan, Nur Henryranu Prasetio, Barlian Herenda Madi, Matius Herwin Yurianda Hurriyatul Fitriyah Hurriyatul Fitriyah Hurriyatul Fitriyah, Hurriyatul Idang Wahyuddin Septiawan Ihsanurrahim Ihsanurrahim Ikhwan Zulfy Imam Cholissodin Irfan Pratomo Putra Irvan Ramadan Issa Arwani Ivan Kasogi Izaaz Waskito Widyarto Izza Febria Nurhayati Jeffry Atur Firdaus Jevandika Jezriel Lukas Lumbantobing Johannes Archika Waysaka Khairul Anwar Khairul Anwar Kresna Wiska Kafila Kurnia, Yudisthira Dwi Kurniawan, Rizaldy Ariobimo Kurwniawan, Wijaya La Ode Muh. Fadlun Akbar Lase, Nicolash Jeremy Onoma Latief Nurrohman Alfansuri Lavanna Indanus Ramadhan Lb Novendita Ariadana Lutfi Anang Makruf M Nuzulul Marofi M. Adib Fauzi Rahmana M. Ali Fauzi Mahendra, I Gusti Putu Krisna Suaba Malik, Hifdzul Megananda, Muhammad Rifqi Mela Tri Audina Merry Hassani, Fadila Muqtadaro Mhd. Idham Khalif Moch. Alfian Zainullah Moch. Alvin Yasyfa Salsabil Mochamad Iswandaru Mochammad Hannats Hanafi Mochammad Hannats Hanafi Ichsan Moh. Saifud Daulah Moh. Zainur Rodhi Mohammad Ali Muhsin Mohammad Faizal Ajizi Muchamad Rafi Dharmawan Muchammad Cholilulloh Muh. Syifau Mubarok Muhajir Ikhsanushabri Muhammad Alif Alfajra, Andi Muhammad Aminul Akbar Muhammad Daffa Bintang Nugroho Muhammad Eraz Zarkasih Muhammad Fadhil Sadeli Muhammad Fajaruddin Akbar Muhammad Habib Jufah Alhamdani Muhammad Hanif Haikal Muhammad Hannats Hanafi Ichsan Muhammad Irvine Fidellio Maiza Muhammad Jibriel Bachtiar Muhammad Kholash Fadhilah Muhammad Naufal Muhammad Nazrenda Ramadhan Muhammad Rizqi Zamzami Muhammad Wingga Woggiasworo Muhammad Yusuf Ramadan Mukhamad Angga Setiawan Mukhamad Roni Mukmin Mukmin Munif Cleveriandy, Ahmad Musharrif, Mohammad Faiz Mustajib Furqon Haqiqi Mutiara Pramesti Utami Muzayyin, Asep Nabila Eka Putri, Alisya Nadhifa, Nadaa Nanda Epriliana Asmara Putri Navayo, Bagja Nicho Ferdiansyah Kusna Nikmatus Soleha Niko Aji Nugroho Noveriko Noveriko Nur Aini Afifah Isbindra Nur Fuady, Muhammad Sholahuddin Nurul Ikhsan Nyoman Wira Prasetya Oggy Setiawan Parja, Mujianto Anda Perkasa, Septiyo Budi Prakoso, Aldo Hani Pramandha Saputra Prasetya, Nyoman Wira Prasetyo, Budi Eko Prasojo, Satya Haryo Pricillia, Lidya Ruth Purnomo, Welly Putra Pandu Adikara Putra Pandu Adikara Putra, Brylliano Maza Raga Jiwanda Raharja, Kahfi May Rahayu, Vina Trisnawati Rahman, Edy Raka Bagas Perdana Rakhamadhany Primananda Rakhmadhany Primananda Rakhmadhany Primananda, Rakhmadhany Randy Cahya Wihandika Rekyan Regasari Mardi Putri, Rekyan Regasari Mardi Renal Prahardis Reza Budi Pratikto Rezak Andri Purnomo Rifqi Anshari Ringga Aulia Primahayu Rint Zata Amani Rioadam Sayyid Abidin Riza Irfan, Muhammad Rizal Maulana Rizal Maulana, Rizal Rizal Setya Perdana Rizka Ayudya Pratiwi Rizky Putra Wijaya Rizqi Muh. Muqoffi Ashshidiqi Ronilaya, Ferdian Rudy Agus Santoso Sabrian Rizqika Akbar Sabriansyah Rizkiqa Akbar Sabriansyah Rizqika Akbar Sabriansyah Rizqika Akbar Sabriansyah Rizqika Akbar Safirurrasul Santoso, Mush'ab Safrudin Bendang, Dehleezto Lawanangkara Salman Farizy Nur Samuel Lamhot Ladd Palmer Simarmata Santoso, Bayu Saputro, Mauna Mohammad Wahyu Sari, Sylvia Sentosa, Azy Dwi Putra Septino, Fernando Setiawan , Eko Shaffan, Nur Hazbiy Shelsa Faiqotul Himmah Sigi Syah Wibowo Siradjuddin, Indrazno Sulaiman, Ihsan Susilo, Faizal Andy Sutikno Sutikno Syarief Taufik Hidayatullah Syauqi, Mohd Alfitra Syazwana, Selvia Tibyani Tibyani Tio Haryanto Adi Putra Toar, Mikhael Ryan Tobias Sion Julian Utaminingrum, Fitri Utomo, Satria Wahyudi Vira Muda Tantriburhan Mubarak Virza Audy Ervanda Wahyu Adi Prayitno Welly Purnomo Widasari, Edita Rosana Widhy Hayuhardhika Nugraha Putra Wijaya Kurniawan Wijaya Kurniawan Wijaya Kurniawan Wijaya, Jason Wildo Satrio Wirafadil Nugraha Wisik Dewa Maulana Wisnu Mahendra Xavierro Lawrenza Yanottama Oktabrian Yudhistira, Gevan Putra Yuita Arum Sari Yunan Alamsyah Nasution Yunus, Ahmad Haykal Yurliansyah Hirma Fajar Yusriansyah Shohibul Hamzah Zahra, Inez Bedwina Zakaria, Akhmad Nizar