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All Journal IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Jurnal Mahasiswa TEUB Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer
Widasari, Edita Rosana
Fakultas Ilmu Komputer, Universitas Brawijaya
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering

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Implementasi Alat Monitoring Kesuburan Lahan Pertanian Ketela Pohon berbasis Web Fathul Abdillah Khosin; Mochammad Hannats Hanafi Ichsan; Edita Rosana Widasari
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 9 (2022): September 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Cassava is a plant that can be used as a substitute for the daily staple food. Many farmers encounter obstacles at the time of post-harvest cassava, which is not suitable for harvesting for consumption. Most farmers do not know the fertility of the land to be planted. Implementing a monitoring tool on the system for observing the fertility of cassava agricultural land can be a solution. The method used is the Telemetry method. Where Telemetry is the process of measuring the parameters of an object (objects, space, natural conditions) whose measurement results are sent to other places via cables or without using cables (wireless). Telemetry is expected to provide convenience in measurement, monitoring and reduce barriers to obtaining information. Sensors are connected to components, then these components will be connected to each other through communication in the sensor network. From the implementation of the test, the results obtained from the test were that the tool worked properly where the monitoring tool could retrieve data from the research place where the sensor was installed. Then the monitoring tool can also send data to the webserver and the webserver successfully receives data from the monitoring tool and then saves it to the database on phpMyAdmin and displays it on the web pc or cellphone. Performance is obtained based on throughput, packet loss and delay with the result that the throughput is 8,567 kbps. The packet loss of is 0.1%. The total delay is 4.449 s and the average delay is 1.6322 ms.
Perancangan Sistem Pengamanan Ganda pada Brankas menggunakan Convolutional Neural Network berbasis Raspberry Pi Muhamad Fauzan Alfiandi; Fitri Utaminingrum; Edita Rosana Widasari
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 9 (2022): September 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

In human life, one of the most important things is security. Security works to prevent, protect assets, physical or digital items that we own from theft and lost items. According to the data from Indonesian National Police Yogyakarta Region, the number of theft cases in 2021 has reached 1219 cases, and that's why a protection system is necessary as an effort to guard against any thief. The commonly used protection system for physical items is a safety box. Technological advancements especially hardware, encourage people to help, simplify and solve problems. Microcontroller technology is currently evolving. Microcontroller serves a digital processing purpose and certain program and instruction can be made according to what we want. Technological advancements can be associated with the security field such as biometric face recognition. This face recognition system can recognize a person's face. To construct a protection system preventing theft, this research uses double security on a safety box, PIN and face detection. Applying the deep learning Convolutional Neural Network for face detection so the system can detect the safety box owner's and not the owner's face. PIN number combination must be inputted to lock the safety box using a solenoid lock. The purpose of this research is to construct a double security safety box without risking losing a key. According to the test results, the system can detect the owner's face object with 83% accuracy, 81% precision, 86% recall with 8.19 seconds of computing time, 100% success rate of PIN input, face detection and keypad integration to solenoid lock test results with a 100% success rate.
Implementasi Wearable Device untuk Sistem Pendeteksi Stres pada Manusia berdasarkan Suhu Tubuh dan Detak Jantung Izzati Firsta Wijayanti; Edita Rosana Widasari; Barlian Henryanu Prasetio
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 9 (2022): September 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Stress is the result of an unusual situation, with factors such as good or bad events, frustration, pressure, and environmental conditions causing stress. Stress can affect the condition of the body, and if a person experiences it, the body's reactions include excessive sweating, shaking, an increase in heart rate, rapid breathing, and headaches. Stress will be detected earlier and treated more effectively. As a result, we require a practical stress detector that is simple to use and can determine a person's condition based on his heart rate and body temperature. This stress detector uses two parameters: heart rate, which is detected by the MAX30102 sensor, and body temperature, which is measured by the MLX90614 sensor and processed by the Arduino Nano. The outcome of developing a tool with both sensors detecting via the fingers displayed on the OLED 0.96 inch and the accurarcy of the measurement between MLX90614 and thermometer is 98.51%, the measurement between MAX30102 and pulse oximeter got 92.43% accuracy and the overall test of the tool that has mad comparisons with DASS 42 stress scale got 70% accuracy using 10 subjects. The average computations time when a person detected as stress is 0.359 seconds.
Implementasi Analisis Perbandingan Filter Kalman, Moving Average dan Eksponensial pada Alat Pengukur Kadar Kolesterol berbasis Non-Invasif Hafid Ilmanu Romadhoni; Rizal Maulana; Edita Rosana Widasari
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 9 (2022): September 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Stroke is a dangerous disease and can occur at any time. High cholesterol is one of the causes of stroke. Cholesterol measurements are generally carried out on an invasive basis, namely taking blood samples. Invasive-based cholesterol measurements can damage the skin tissue of the patient by using a needle to remove blood from the body. There is a way that is safer than the risk of injury that is based on non-invasive. There are several non-invasive methods, one of which utilizes infrared light that penetrates the skin so that it can measure what is flowing in the blood. Non-invasive measurements have been carried out in the measurement of cholesterol, but there is no filter program in it. Filters are needed to improve sensor accuracy. Kalman, Moving Average, and exponential filters can be applied to reduce errors. This study has aim to examine the role of filters in non-invasive cholesterol measurement. The parameter measured is the BPM value from the sensor. The sensor from the research has an accuracy of 99.86%. Kalman, Moving Average, and exponential filters have been tested for accuracy compared to invasive cholesterol measuring tools. On the measuring instrument with the addition of a kalman filter, an accuracy of 92.595% was obtained. For measuring instruments with the addition of a Moving Average filter, an accuracy of 95.189% is obtained. In measuring instruments with the addition of an exponential filter, an accuracy of 93.682% is obtained.
Analisis Perbandingan Filter Finite Impulse Response, Infinite Impulse Response, dan Discrete Wavelet Transform pada Kondisi Kelelahan Mental berbasis Sinyal Electroenchephalography Dwinanda Romolo; Edita Rosana Widasari; Barlian Henryranu Prasetio
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 9 (2022): September 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

The brain is one of the vital organs owned by living things. The brain will work optimally if it gets enough oxygen from the blood. If not, the work of the brain will decrease and will affect human performance in daily activities. One of the reasons for the decreased supply of oxygen to the brain is fatigue. According to the International Labor Organization in 2013, as many as two million workers experienced work accidents due to fatigue caused by mental factors. One way to find out whether humans experience mental fatigue or not is by recording brain wave signal activity or Electroenchephalography (EEG) and analyzing it. To analyze the EEG signal must use digital filters which are very numerous. This study will analyze the EEG signal using three filters, namely Finite Impulse Response (FIR), Infinite Impulse Response (IIR), and Discrate Wavelet Transform (DWT). Then the filtering results from these three filters will be compared to find which filter has the highest efficiency level by looking at the Signal to Noise Ratio (SNR) value and the resulting computational time. The result is that the FIR filter is the most efficient than the other filters, resulting in an average SNR value of 27.89975 dB. While the average value of the resulting computation time is 0.131 s
Sistem Pendeteksi Sleep-disordered Breathing berdasarkan High dan Low Frequency menggunakan Metode Naive Bayes Achmad Ghifari; Edita Rosana Widasari
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 7 No 13 (2023): Publikasi Khusus Tahun 2023
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Rancang Bangun Sistem Deteksi Hipoksia berdasarkan Detak Jantung dan Saturasi Oksigen menggunakan Low Power Mode dengan Metode Naive Bayes Ahmad Haris Wahyudi; Edita Rosana Widasari; Hurriyatul Fitriyah
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 11 (2022): November 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Hypoxia is a condition when the tissues in the body lack oxygen so that their functionality is disrupted and can be fatal, such as organ damage and even death. One of the causes of hypoxia is environmental factors such as being at high altitudes with minimal oxygen. Therefore, hypoxia is also a frightening specter for mountain climbers, where there are minimal medical facilities to check the condition of climbers. Therefore, in this study designed a portable system to detect hypoxia in climbers. Hypoxia detection was carried out using heart rate (BPM) and blood oxygen saturation (SpO2) parameters whose data were acquired using the MAX30102 sensor. After that, the data was processed and classified using the naive Bayes method on the Arduino Mega 2560 microcontroller. This system uses a battery for its power source so that it is more portable and can still be used in mountain areas where there is no power source. Due to very limited battery power, a low-power mode is implemented in the form of sleep mode so that it can save battery power consumption. In testing the BPM and SpO2 readings with the MAX30102 sensor, an accuracy of 98.03% and 97.62% was obtained. In the naive Bayes classification test results obtained an accuracy of 93.33% with a computation time of 829.2 µs. As well as for power efficiency with low power mode, a decrease in current consumption reaches 70.13%.
Rancang Bangun Alat Deteksi Hipotermia berdasarkan Detak Jantung dan Suhu Tubuh dengan Metode Fuzzy Tsukamoto Henry Trenggana; Edita Rosana Widasari; Mochammad Hannats Hanafi Ichsan
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 12 (2022): Desember 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Hypothermia is a condition where the body temperature is below average and the body does not have the ability to produce heat properly due to a weakened heart rate and common in climbers who climb mountain. Hypothermia can be dangerous if not treated immediately because people with hypothermia usually don't know that they have hypothermia. In this study, a tool was designed to detect hypothermia with classfication method using the Fuzzy Logic Tsukamoto Method. Fuzzy input come from the MAX30102 sensor to calculate the number of heartbeats, and the DS18B20 sensor to calculate body temperature. Because the tool will be used in climbing areas that have limited power sources, the tool requires a mechanism to save its power. In this study, the low power mode mechanism is used which is applied to the ATmega328P. When the tool is not in use, the system goes into sleep mode and will return to wake mode if the trigger made of a push button is pressed. This system has 2 components that function as output, the 128x32 OLED used to display sensor readings and classification results and a buzzer that will emit a sound if the user is detected to have hypothermia. This study obtained an accuracy of 96.45% on the MAX30102 sensor in the heart rate reading test. In testing the temperature readings, this study obtained an accuracy of 99.41%. In testing the accuracy of the Fuzzy Tsukamoto Method, a value of 100% was obtained with an average computation time of 395.6 µs. As well as the low power mode mechanism which has managed to reduce the average current usage by up to 72.2%.
Implementasi Metode Neural Network pada Sistem Monitoring Pendeteksi Sleep-Disordered Breathing berdasarkan Low dan High Frequency Muhammad Nur Arssy; Edita Rosana Widasari
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 7 No 13 (2023): Publikasi Khusus Tahun 2023
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Implementasi Algoritme Learning Vector Quantization untuk Deteksi Kelelahan Mental berbasis Sinyal Electroencephalography Syifa' Hukma Shabiyya; Edita Rosana Widasari
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 7 No 13 (2023): Publikasi Khusus Tahun 2023
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Co-Authors Achmad Ghifari Adharul Muttaqin Adhitya Bhawiyuga Agung Setia Budi Ahmad Haris Wahyudi Andhika Nino Pratama Andre Adikusuma Andrika Wahyu Wicaksono Andy Hartono Anethasia Putri Prasetyowati Angger Dimas Bayu Sadewo Ariyan Jazmi Aulia Zhafran Auliya Firdaus Barlian Henryanu Prasetio Barlian Henryranu Prasetio Batara Dolly Nababan Cut Fahrani Dhania Dahnial Syauqy Denis Reza Ramdani Desy Marinda Oktavia Sitinjak Dody Kristian Manalu Dwinanda Romolo Dzakwan Daffa Ramdhana Eko Setiawan Elisabeth Agustina Fathul Abdillah Khosin Fatkhurrozi Fatkhurrozi Fitriyah, Hurriyatul Graciella Fiona Br. Panjaitan Hafid Ilmanu Romadhoni Harry Mulya Henry Trenggana Hery Julianto Situmorang Izzati Firsta Wijayanti M. Yunior Dwi Ashari Moch Rizki Cahyadi Mochammad Hannats Hanafi Ichsan Mohammad Fauzin Amin Mohammad Hafidh Wildan Maulana Muhamad Fauzan Alfiandi Muhammad Ammar Hassan Muhammad Fadhil Sadeli Muhammad Fauzan Edy Purnomo Muhammad Nur Arssy Muhammad Risyat Nashrullah Muhlis Agung Saputro Noveriko Noveriko Nur Syifa Syafaat Onky Soerya Nugroho Utomo Putri Laras Rinjani Qonita Luthfiyani Rakhmadhany Primananda Rejeki Puspa Dinasty Reza Hastuti Rifki Pinto Hidayat Rifqi Imam Ramadhan Rizal Maulana Rosa Mulyanis Chan Sabriansyah Rizqika Akbar Salsabila Salsabila Sasmita Eko Raharjo Selina Kusmiawati Syifa' Hukma Shabiyya Thomas Oddy Chrisdwianto Tri Oktavia Mayasari Utaminingrum, Fitri Zhafran Wadiansyah Zhuliand Rachman Zonnete Bryllian Dheo