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ANALISA PENGARUH RANGSANGAN AROMATERAPI LAVENDER DAN KAYU CENDANA TERHADAP KUALITAS TIDUR BERBASISKAN GELOMBANG EEG Alyani Durrah Fauzan; Nushrotul Lailiyya; Dwi Esti Kusumandari; Fiky Yosef Suratman
TEKTRIKA Vol 4 No 1 (2019): TEKTRIKA Vol.4 No.1 2019
Publisher : Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25124/tektrika.v4i1.1608

Abstract

Abstrak Tidur merupakan aktivitas yang penting bagi tubuh. Aktivitas tidur membantu tubuh untuk menyembuhkan sel-sel yang rusak dan meningkatkan sistem kekebalan tubuh. Tetapi banyak dari kita yang tidak mendapatkan kualitas tidur yang baik untuk menerima manfaat tersebut. Demi meningkatkan kualitas tidur, sebagian besar masyarakat percaya bahwa penggunaan aromaterapi dapat membuat tubuh lebih rileks dan membantu penggunanya tidur lebih lelap. Paper ini melakukan studi mengenai ada tidaknya pengaruh aromaterapi terhadap kualitas tidur dengan memanfaatkan sinyal biopotensial pada otak, yaitu electroencephalogram (Sinyal EEG). Sinyal EEG didapatkan dari proses akuisisi menggunakan Mitsar-EEG-202 dan Software WinEEG. Selanjutnya, sinyal EEG akan dibaca secara visual berdasarkan bentuk, frekuensi, amplitudo, dan lokasi. Proses pembacaan sinyal akan menghasilkan nilai latensi tidur, durasi fase tidur (NREM dan REM), dan WASO. Data-data tersebut akan diuji secara manual (menghitung efisiensi tidur) per individu dan statistik (uji kesamaan dua rata-rata dan uji kesamaan dua varians). Hasil analisis secara statistik menunjukkan bahwa tidak adanya pengaruh yang signifikan antara subjek yang diberi stimulus aromaterapi terhadap subjek tanpa stimulus. Sedangkan pada analisis per individu, kualitas tidur dengan stimulus aromaterapi lebih baik dibandingkan tanpa stimulus pada beberapa subjek. Jika dihitung secara rata-rata, stimulus aromaterapi lavender dan kayu cendana dapat menaikkan efisiensi tidur, namun tidak signifikan.
ANALISIS PENGARUH MUSIK KLASIK DAN MUSIK ALAM TERHADAP KUALITAS TIDUR BERDASARKAN SINYAL ELECTROENCEPHALOGRAM Adriani Rizka Amalia; Fiky Yosef Suratman; Dwi Esti Kusumandari; Nusharatul Lailiyya
TEKTRIKA Vol 3 No 1 (2018): TEKTRIKA Vol.3 No.1 2018
Publisher : Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25124/tektrika.v3i1.2204

Abstract

Tidur merupakan kebutuhan dasar bagi setiap individu. Kondisi seseorang bisa dipengaruhi oleh kualitas tidurnya. Menjaga kualitas tidur penting untuk dilakukan karena dapat membantu menurunkan stress, meningkatkan mood dan fokus. Sebagian besar masyarakat meyakini bahwa pemberian stimulus musik dapat menambah kenyamanan tidur. Rangsangan suara merupakan salah satu variabel yang dapat mempengaruhi kehadiran gelombang listrik di otak, serta dapat membantu seseorang untuk merasa lebih rileks. Penelitian ini mempelajari pengaruh musik klasik dan musik alam terhadap kualitas tidur dari sinyal electroencephalogram (EEG). Sinyal EEG adalah salah satu cara untuk dapat mengetahui kualitas tidur seseorang. Kualitas tidur dipelajari melalui sinyal EEG, dengan memberikan rangsangan musik yang secara bertahap kepada individu, berdasarkan total waktu di setiap tahapan tidur, sleep latency dan efisiensi tidur. Masukan sistem merupakan sinyal yang didapat dari perekaman sinyal menggunakan sensor Mitsar EEG-202, yang pada penerapannya akan diletakkan pada 19 titik (multi channel) sesuai dengan sistem internasional 10-20. Tahap awal penelitian pengaruh stimulus musik berdasarkan sinyal EEG ini adalah akuisisi data, kemudian pembacaan data dilakukan secara visual dan telah diverifikasi oleh dokter spesialis syaraf. Setelah itu penentuan kualitas tidur ditentukan dengan melihat adanya pengaruh musik dengan metode statistik uji kesamaan dua rata-rata dan F-test. Hasil analisis dari 9 subjek dengan menggunakan uji kesamaan dua rata-rata menunjukkan bahwa adanya pengaruh pada Non Rapid Eye Movement (NREM). tahap 3 dengan musik klasik. Analisis F-test menunjukkan adanya perbedaan yang signifikan pada NREM tahap 1 dengan musik klasik maupun musik alam.
Automatic Warning System for Weather Station Power Supply Mumtazanisa Fairuzen; Angga Rusdinar; Fiky Yosef Suratman; Denny Darlis
Ultima Computing : Jurnal Sistem Komputer Vol 13 No 2 (2021): Ultima Computing : Jurnal Sistem Komputer
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/sk.v13i2.2261

Abstract

Weather observation is one of the important factors in agriculture. Data from weather observations can be used for various things, including to predict future risks due to these weather conditions. An Automatic Weather Station (AWS) is needed to read weather conditions continuously. Some of the devices that will be built for the AWS system are data communication, sensors, and power supply. AWS is usually installed in certain areas where there is no power source. Hence, it takes a power supply system that can stand alone and has a security system that can monitor the components connected to the system in real-time. This research successfully designed a power supply system for a weather station that is equipped with current and voltage measurement features for its load as well as a warning system feature in case of interference on GSM SIM900-based Weather Station. Based on the results of the study the system using solar cell modules has an efficiency of 14,1% and is supported with the help of batteries that can be recharged through solar energy. Using the INA219 sensor to measure the voltage and load current connected to devices that have an error percentage value of less than 1%, the data is then uploaded to Thingspeak. Testing of warning systems at the Weather Station is conducted using Magnetic reed sensors capable of detecting changes when the separation distance between the sensor and other magnets is more than 3cm.
Electrocardiogram feature selection and performance improvement of sleep stages classification using grid search Lyra Vega Ugi; Fiky Yosef Suratman; Unang Sunarya
Bulletin of Electrical Engineering and Informatics Vol 11, No 4: August 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i4.3529

Abstract

Sleep analysis is often used to identify sleep-related human health. In many cases, sleep disorders could cause a particular disease. One of the approaches to detect sleep disorders is by investigating human sleep stages. However, the selection of the proper electrocardiogram (ECG) features is still considered challenging and becomes an issue to achieve the performance of the algorithm used. Therefore, it is necessary to investigate which ECG features are very significant to the performance of the algorithm. In this study, the support vector machine (SVM) method has been utilized to classify sleep stages into two classes namely awake and sleep. In order to improve the classification performances, an optimization method of grid search was used to find the best parameters of the SVM. Feature selection of information gain was then used to find the most significant ECG features. To validate the performance results, one leave-subject out cross-validation has been conducted during the implementation. There were ten subjects involved in this implementation. The ECG signals from those ten subjects were used to differentiate awake from sleep state. Based on the results, our method obtained an average accuracy of 85.46% a precision of 84.05% and a recall of 85.44% respectively.
Spectrum Sensing in Cognitive Radio Using Combined Sequential Energy Detector and Cyclostationary Feature Detector Santosh Poudel; Heroe Wijanto; Fiky Y. Suratman
JMECS (Journal of Measurements, Electronics, Communications, and Systems) Vol 2 No 1 (2016): JMECS
Publisher : Universitas Telkom

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25124/jmecs.v2i1.1487

Abstract

In the following research, we derive a detector which is based on sequential probability ratio test (SPRT) and it uses Energy Detector (ED) which is followed by Cyclostationary Feature Detector (CFD). ED is a blind sensing technique and it is easy to implement while conceptually simple. However, it is highly affected by interference and noise uncertainties. Therefore, CFD is applied for fine sensing as research has shown that Cyclostationary Feature Detector is more suitable than the energy detection when noise uncertainties are unknown. Our method is novel in trying to derive a sequential Energy Detector and combine it with Cyclostationary Feature Detector for low SNR region where average sample number (ASN) as a random variable may take very high value to achieve a desired performance level for sequential Energy Detector. For this sequential Energy Detector is terminated after it reaches certain cut-off sample number, making it truncated sequential Energy Detector.
Design and Implementation Pulse Compression for S-Band Surveillance Radar Kalfika Yani; Fiky Y Suratman; Koredianto Usman
JMECS (Journal of Measurements, Electronics, Communications, and Systems) Vol 7 No 1 (2020): JMECS
Publisher : Universitas Telkom

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25124/jmecs.v7i1.2631

Abstract

The radar air surveillance system consists of 4 main parts, there are antenna, RF front-end, radar signal processing, and radar data processing. Radar signal processing starts from the baseband to IF section. The radar waveform consists of two types of signal, there are continuous wave (CW) radar, and pulse compression radar [1]. Range resolution for a given radar can be significantly improved by using very short pulses. Pulse compression allows us to achieve the average transmitted power of a relatively long pulse, while obtaining the range resolution corresponding to a short pulse. Pulse compression have compression gain. With the same power, pulse compression radar can transmit signal further than CW radar. In the modern radar, waveform is implemented in digital platform. With digital platform, the radar waveform can optimize without develop the new hardware platform. Field Programmable Gate Array (FPGA) is the best platform to implemented radar signal processing, because FPGA have ability to work in high speed data rate and parallel processing. In this research, we design radar signal processing from baseband to IF using Xilinx ML-605 Virtex-6 platform which combined with FMC-150 high speed ADC/DAC.
Robust Modified MVDR Scheme Using Chirp Signal for Direction of Arrival Estimation Kalfika Yani; Koredianto Usman; Fiky Y Suratman
JMECS (Journal of Measurements, Electronics, Communications, and Systems) Vol 6 No 1 (2020): JMECS
Publisher : Universitas Telkom

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25124/jmecs.v6i1.2630

Abstract

This research is about an effort to increase the robustness of the Minimum Variance Distortionless Response (MVDR) algorithm to noise by using a chirp signal for direction of arrival estimation (DoA). DoA is a part of radar capability to estimate the angle of arrival on the object under observation. The conventional MVDR as proposed by J. Capon, was designed to work with the monochromatic sinusoidal signal. Even though the conventional MVDR work on low SNR up to 0 dB, however, the conventional method does not work well if chirp signal is used instead of monochromatic sinusoidal signal. The usage of MVDR chirp signal is essential in the case of a very low SNR environment such as in long distance object detection, which is typically more than 10 km. The problem to be solved in this research is how to modify the MVDR algorithm so that it can work well on chirp signal. In this research we offer a modified MVDR algorithm by adding the matched filter and the phase detector components before the MVDR algorithm is applied. Matched filter is responsible for the timing of the chirp signal detection, and the phase detector is to estimate the time delay estimation of each chirp signal from each antenna with a reference signal, which correspond to the phases. Based on the phase estimation, sinusoidal signal is generated and fed to the MVDR algorithm. On the technical aspect, the chirp signal is sent intermittently with a duration of 100 ?s and repeated in time interval of 1 ms. The antenna sensor using an array of Uniform Linear Array (ULA) which consist of N-elements. Computer simulation shows that the modified MVDR using the chirp signal improve the robustness of the algorithm up to -30 dB, while on the other hand the classical MVDR works only up to 0 dB SNR. -30 dB of SNR is the minimum requirement of 3D Radar existing.
Ultra Wideband Radar for Respiratory Monitoring on Sleep Position Nurul Qashri Mahardika T; Erfansyah Ali; Fiky Yosef Suratman
JMECS (Journal of Measurements, Electronics, Communications, and Systems) Vol 8 No 1 (2021): JMECS
Publisher : Universitas Telkom

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25124/jmecs.v8i1.2873

Abstract

Sleep apnea is a sleep disorder that has a relation with respiratory system during sleep.One of the sleep apnea characteristic is suddenly stop breathing during sleep. Peoplehave the dierent of respiratory rate (RR) which is affected by sleep positions andbody mass index (BMI).There are four sleep positions aecting the respiratory rate(RR). Polysomnography (PSG) is conventionally used to analysis the sleep apnea. Thistechnique requires body contact that might be uncomfortable for the patient. In thisstudy, the Xethru X4M200 radar sensor is proposed as non-contact tool to detect the RRby implementing the Doppler effect. Furthermore, the relation between RR with the sleepposition and the BMI are discused. For that purpose, 20 participants (10 males and 10females) with dierent BMIs and sleep positions are examined by monitoring their chestmovement. This method is able to detect the indication of bradypnoea or tachypnoea.Futher systematic study and more participants are required to confirm our results andprovide better non-contact technique for RR measurement.
Deteksi Radar Terhadap Multi-Object Bergerak Dengan Pemrosesan Doppler Reyhan Fahmirakhman Abdullah; Dharu Arseno; Fiky Yosef Suratman
Proceedings Series on Physical & Formal Sciences Vol. 1 (2021): Proceedings of Smart Advancement on Engineering and Applied Science
Publisher : UM Purwokerto Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1096.668 KB) | DOI: 10.30595/pspfs.v1i.128

Abstract

In general, Radar or Radio Detection and Ranging is an electromagnetic wave system that is useful to measure distance and answer and make maps of surrounding objects. Radar has an advantage compared to other navigation tools, which is that radar does not require a transmitter station as a transmitter. Radar has an electronic wave emission principle that emits short radio wave pulses emitted in a narrow beam by a directional antenna. In this study, a multi-object radar detection simulation was carried out using Dopler processing both MTI and PDP, which later on the radar will detect related objects. Multi-object here is a condition that is achieved when a navigation radar detects more than one object. The result of this research is a multi-object detection process using the MTI and PDP methods and the matched-filter obtained from the predetermined data. So Doppler processing aims to mitigate the clutter signal to improve the detection performance of moving targets even though there is a dominance of signals originating from stationary clutter.
An Image Processing Method to Convert RGB Image into Binary Ratri Dwi Atmaja; Muhammad Ary Murti; Junartho Halomoan; Fiky Yosef Suratman
Indonesian Journal of Electrical Engineering and Computer Science Vol 3, No 2: August 2016
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v3.i2.pp377-382

Abstract

It is important in image processing to extract objects from their background into binary image. Binary image is used as input to feature extraction process and have an important role in generating unique feature to distinguish several classes in pattern recognition. This paper propose an image processing algorithm to obtain a binary image from RGB. The results showed that the binary image of the proposed algorithm contained the desired object.
Co-Authors -, Sugihartono A. A. Pramudita Achmad Rizal Adinda Mutiara Hakim Adriani Rizka Amalia Agung Chrisyancandra Mobonguni Ali Muayyadi Ali, Erfansyah Aloysius Adya Pramudita Alyani Durrah Fauzan Andika Pradana Arif Wicaksono Angga Rusdinar Angga Wijaya Anhar Ari Widodo Aptadarya, Harwin Arentaka, Fiendo Mahendra Argaloka, Aditya Adni Arif Abdul Aziz Arifyandy, Rachmat Ario Wicaksono ARIS HARTAMAN Aurelia, Felicia Bunga Azhar Sukarna Putra Azhar Yunda Ramadhan Azizah Yusrina Bambang Hidayat Bambang Setia Nugroho Budi Permana Dami Mahardiwana Daud, Pamungkas De Fitrah, Figo Azzam Denny Darlis Dharu Arseno Dhiky Wahyu Santoso Dias Daffa Wiwaha Dien Rahmawati Dimas Mustaqim Dwi Esti Kusumandari Ekki Kurniawan Erwin Susanto Estananto Fadhli Rahman Faishal Adli Fani Fauziah, Fani Farhan Ramadhan FARIED IZZANTAMA NUGRAHA HARSWA Figo Azzam De Fitrah Fikry Lazuardi Fitrah, Figo Azzam De Giashinta Larashati Grace Bobby GRACE BOBBY, GRACE Hana Pratiwi Hasbian Fauzi Perdana Heni Pujiastuti Heroe Wijanto Hidayat, Mujib R. HIDAYAT, MUJIB RAMADAN Hurianti Vidyaningtyas I Wayan Oka Krismawan Putra Ig. Prasetya Dwi Wibawa Imam Darmawan Istiqomah Istiqomah istiqomah istiqomah Jody H, Amadeus Evan Junartho Halomoan Juse Wisman Oktabri Kalfika Yani Khalisa Khairuna Khilda Afifah Kirana, Tsania Puspa Koredianto Usman Krisna Muhammad Luthfi Kurniawan, Bella K. Lyra Vega Ugi M. Reza Raihan N.R MAARIF, AHMAD FATHAN Made Indra Wira Pramana Marchellyn, Ferryn Mochammad Haldi Widianto Mohamad Ramdhani Muhamad Ridwan Widyantara Muhamad Riswan Nurfadilah Muhammad Adi Nurhidayat Muhammad Ary Murti Muhammad Hablul Barri Muhammad Hegi Rinaldi Muhammad Nashih Rabbani Muhammad Zakiyullah Romdlony Mujib R. Hidayat Mumtazanisa Fairuzen Nasrullah Armi Neina Oktavia Sariningsih Nelson, Garry Nina Mardiana (F01108057) Nurhidayat, Muhammad Adi Nurul Qashri Mahardika T Nusharatul Lailiyya Nushrotul Lailiyya Patriananda, Teguh Porman Pangaribuan Pramudita, A. A. Pramudita, Aloysius A. PRATIWI, HANA Qolbiyah, Nada Syifa Rachmita Hasni.H1 Radika Gitatama Rahmad Rahmad Ramadhan, Azhar Yunda Ramdhan Nugraha Ratri Dwi Atmaja Rebecca Chittra Widyaparamitha Reyhan Fahmirakhman Abdullah Reynaldo Sandy Montolalu Reza Nurul Fajri Rheza Faurizki Rahayu Rifqy Miftahul Hidayat Rissa Rahmania Rizal Akhlaqul Rizki Ardianto Priramadhi Rizkia Dwi Auliannisa Rizky Ardianto Priramadhi Salwa Nur Rohmah Santosh Poudel Saputri, Desti M. Sari, Nurlina Satyawan , Arief Suryadi Satyawan, Arief Suryadi Seno Nugroho Siburian, Sebastian Edward Slamet Widodo Slamet Widodo Sony Sumaryo Sugihartono - Suputra , Mahesa Wisnu Suryo Adhi Wibowo Unang Sunarya Widyantara, Muhamad Ridwan Y. R, Azhar Yohana Jayanti Aruan Yudha Purwanto Yudha Setyawan, Raden Rofiq Zahwa Rizzi Ani