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All Journal PROSIDING CSGTEIS 2013 CIRCUIT: Jurnal Ilmiah Pendidikan Teknik Elektro Masyarakat Berdaya dan Inovasi
Indra Jaya
Sekolah Tinggi Ilmu Kesehatan Muhammadiyah Aceh
Humanities Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Law, Crime, Criminology & Criminal Justice Library & Information Science Nursing Social Sciences Other

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Simulasi Alat Photoplethysmograph (PPG) Indra Jaya; Wisma Wisma
CIRCUIT: Jurnal Ilmiah Pendidikan Teknik Elektro Vol 1, No 2 (2017)
Publisher : PTE FTK UIN Ar-Raniry

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22373/crc.v1i2.2081

Abstract

Heart is a vital organ in the human body. The heart functions circulated the blood throughout the body. The volume of blood in a body organ will vary due to blood pumping by the heart. Photoplethysmograph (PPG) is a device that can detect changes in blood volume using optical sensors. The purpose of this research is to make Photoplethysmograph monitoring system online. That is a device to monitor blood volume changes and display the change graph. Fluctuations in blood volume changes are influenced by the rhythm of blood pumping by the heart. Each peak on the PPG signal is correlated with one heartbeat. Photoplethysmograph charts can be used to determine the condition and abnormalities of a person's heart. Photoplethysmograph system online is realized in the form of sensors, amplifiers, LPF, ADC, and microcontroller as a serial interface, wiz610wi module, and web applications as online PPG graph viewer. Sensors composed of red LED and photoresistor (LDR) are placed on the fingers. The rays emitted by the LEDs are received by the LDR. The signals received by the LDR vary according to the volume of blood changes. The sensor output signal is then amplified and filtered. Incoming filter output signal ADC, serial interface by AT89C2051 then by wiz610wi module transmitted for display and monitored. Obtained Devices and apps created have worked well. The signal shown is pretty good, clean of noise. Transmission distance measured up to 70 m with delay less than 200 ms. The average heart rate calculation was in error 3%
Pemodelan ARIMA untuk Kanal Frekuensi Tinggi (High Frequency) Link Banda Aceh-Surabaya Indra Jaya
PROSIDING CSGTEIS 2013 CSGTEIS 2013
Publisher : PROSIDING CSGTEIS 2013

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Abstrak—Pada era globalisasi saat ini teknologi telekomunikasi berkembang dengan sangat pesat. Begitu juga dalam bidang broadcasting. Sehingga sangat memungkinkan meningkatnya kebutuhan terhadap kanal frekuensi yang baru. Sistem komunikasi radio HF mempunyai kelebihan dalam propagasi yaitu dapat menjangkau jarak lintasan yang jauh, mudah diimplementasikan dan lebih murah dibandingkan dengan sistem komuniksi satelit.Para peneliti telah banyak melakukan pemodelan terhadap kanal HF dengan berbagai macam model, umumnya pemodelan kanal statistik dirancang dan diterapkan dengan menggunakan simulator kanal. Salah satu model yang dapat diterapkan adalah dengan model ARIMA. Karena Model ARIMA memiliki karakteristik yang paling sesuai dengan karakteristik data yang didapat dari pengukuran redaman kanal HF yaitu time series. Dengan pemodelan ARIMA, perlu dipertimbangkan sifat tak stasioner dalam dimensi waktu, agar didapat keakuratan yang tinggi, sehingga sangat cocok untuk data yang mempunyai sifat tak stasioner. Pemodelan ARIMA untuk kanal HF saat ini belum banyak diteliti, akan tetapi pemodelan ARIMA dalam bidang telekomunikasi lainnya sudah banyak sekali dilakukan.Dari hasil pemodelan diperoleh dua belas model ARIMA yaitu Model ARIMA (0,1,1), (1,0,0), (1,0,1),(1,0,2),(1,0,3), (1,0,4), (0,0,5), (2,0,1), (2,0,2), (2,0,0), (2,0,5), dan (3,0,3). Model ARIMA yang paling dominan yaitu model ARIMA (1,0,2) dengan jumlah event sebanyak 30,67 %, model ARIMA (2,0,2) dengan jumlah event sebesar 20 %, model ARIMA (2,0,1) yaitu sebanyak 14,67 %, model ARIMA (1,0,3) sebesar 9,33%, model ARIMA (1,0,1) 6,67%, ARIMA(3,0,3) sebesar 5,33%, model ARIMA (0,1,1) 4%, ARIMA (1,0,0) 4%, (0,0,5), (2,0,0), (2,0,5), dan (1,0,4) masing-masing sebesar 1,33%. Dan hanya dua model yang paling mendekati dengan model pembangkitan yaitu model ARIMA (1,0,0) dan Model (1,0,2).Dari seluruh model ARIMA yang diperoleh dipilih salah satu model ARIMA terbaik dengan mempertimbangkan kriteria AIC yang paling kecil. Model ARIMA terbaik yaitu model ARIMA (1,0,2).Kata Kunci—Frekuensi tinggi (HF); Maximum Usable Frequency (MUF); Redaman kanal HF.
Perancangan Alat Pengaduk Magnetik Berbasis Arduino Uno Atmega 328p Indra Jaya; Di Ikhwal
Circuit: Jurnal Ilmiah Pendidikan Teknik Elektro Vol 7, No 1 (2023)
Publisher : PTE FTK UIN Ar-Raniry

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22373/crc.v7i1.14915

Abstract

To stir and homogenize chemical solutions and other liquid substances, a magnetic stirrer is required. This study aims to create a magnetic stirrer device with three speed levels based on the Arduino Uno microcontroller. This stirrer tool is made up of a DC motor, a Microcontroller with the IC ATmega 328P, a speed control circuit, a buzzer, and an LCD display. The IC controller will initialize commands to the LCD circuit and the speed control circuit when the device is turned on, according to the tool's working principle. When the set timer button is pressed, the speed set menu appears; on the speed set menu, press the high, low, and normal buttons to select the speed.The motor's speed is controlled using the PWM principle, which involves setting the duty cycle to 25% (Low) for low speeds where the voltage supply to the DC motor is 1.25 volts, 60% for medium speed (Normal) where the voltage supply is 3 volts, and 100% for high speed (High) where the voltage supply is 5 volts. Then press the Start button to begin stirring. If the motor is turned on, the tool will run for a predetermined time ranging from 1 to 15 minutes. Then, press the required speed start button. Then, press the start button to begin stirring; if the motor runs, the stirrer tool will run for the duration specified. To determine the speed of a DC motor at low speeds. Low speed DC motor speed measurements yielded a speed of 2673 rpm, normal speed yielded a speed of 3294 rpm, and high speed yielded a speed of 4438 rpm. The buzzer will sound when the stirring process is complete.
Inspeksi dan Pemeliharaan Peralatan Dental Unit di Puskesmas dalam Masa Pandemi Covid-19 jaya, indra; Muhsen, Irma; yanti, Fitri; Mulyani, Sri; Azmi, Zul
Masyarakat Berdaya dan Inovasi Vol. 4 No. 2 (2023)
Publisher : Research and Social Study Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33292/mayadani.v4i2.111

Abstract

Covid-19 is a virus that can spread through the mouth, and attack the lungs so that the patient will experience respiratory problems. The effect caused by the virus is the thickening of the fluid in the lungs, causing the sufferer to experience difficulty in breathing. The purpose of this service is to socialize, inspect and maintain dental unit equipment as a medical support tool at the Kuta Alam Health Center in Banda Aceh City. This activity was carried out during the Covid-19 pandemic. This is done so that dental unit equipment as medical support can be used properly and avoid the spread of the Covid-19 virus. The method used is to provide material to medical staff, to carry out inspections and maintenance of dental unit equipment in the dental and oral service room. The results obtained are an increasing understanding of the covid-19 virus, and understanding the functions and benefits of dental unit devices for efficiency of maintenance cost. The material presented was in great demand by the public and hoped that there would be a continuation with other topics.
Arima Modeling for High-Frequency Channel Response in Equatorial Region Jaya, Indra; Nawawi, Muhammad; Handoko, Lukman; Alfiah, Agry
Circuit: Jurnal Ilmiah Pendidikan Teknik Elektro Vol. 9 No. 2 (2025)
Publisher : PTE FTK UIN Ar-Raniry

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22373/5yvm4332

Abstract

Indonesia, an archipelagic country located along the equator, is highly vulnerable to natural disasters. At the same time, its geographical conditions require reliable telecommunications to strengthen connectivity across its many islands. One effective solution is the utilization of High-Frequency (HF) communication technology, which enables long-distance communication and supports broadcasting-based telecommunications. This approach can expand available frequency channels, making HF radio communication an important tool for disaster-prone regions like Indonesia. To optimize HF communication, researchers have developed various models of HF channel radio systems, often represented statistically and implemented through channel simulators. Among these approaches, the Auto Regressive Integrated Moving Average (ARIMA) model has been identified as particularly suitable. This is because ARIMA can handle the non-stationary characteristics of time-series data, such as those found in HF channel attenuation measurements. In the modeling process, several ARIMA configurations were tested, including ARIMA (0,1,1), (0,0,5), (1,0,0), (1,0,1), (1,0,2), and (0,0,4). From these options, two models—ARIMA (1,0,0) and ARIMA (1,0,2)—showed the closest fit to the observed data. The final selection was made using the Akaike Information Criterion (AIC), where the ARIMA (1,0,2) model emerged as the best. This model provides the most accurate representation for predicting HF channel attenuation, supporting more reliable telecommunications systems for Indonesia.
Co-Authors Alfiah, Agry Azmi, Zul Di Ikhwal Fitri Yanti Irma Irma Lukman Handoko Muhammad Nawawi Sri Mulyani Wisma Wisma