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All Journal Gravity : Jurnal Ilmiah Penelitian dan Pembelajaran Fisika Journal of Physics and Its Applications TELKA - Telekomunikasi, Elektronika, Komputasi dan Kontrol MASALIQ: Jurnal Pendidikan dan Sains
Annas, Muhamad Azwar
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Religion Astronomy Computer Science & IT Control & Systems Engineering Earth & Planetary Sciences Education Electrical & Electronics Engineering Materials Science & Nanotechnology Physics Social Sciences

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Effectiveness of Noise Barriers Based on Waste Materials in Case Study of Residential Noise Due to Double-Track Railways Febrianti, Denisa Eka; Agus Salim, Alfi Tranggono; Rezika, Wida Yuliar; Annas, Muhamad Azwar; Suyatno, Suyatno
Journal of Physics and Its Applications Vol 6, No 1 (2023): November 2023
Publisher : Diponegoro University Semarang Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jpa.v6i1.19992

Abstract

The noise pollution in residential areas adjacent to double-track railways can significantly disturb the comfort and well-being of residents. The noise originates from passing trains on these double-track railways. The research problem aims to compare the noise levels in the residential area with the standard noise threshold and evaluate the effectiveness of a noise barriers based on waste material called sustainable noise barrier. The effectiveness of reducing noise levels for communities residing near the dual railway lines. The sustainable noise barrier is constructed using waste cardboard and sawdust as sound absorbers for reducing noise from passing trains. The objective of the research is to analyze the noise levels in the residential areas near the dual railway lines, referring to the noise threshold value specified in Kep.MenLH No.48 of 1996, which is 55 dBA. Additionally, the research aims to assess the effectiveness of the sustainable noise barrier in mitigating noise pollution in these residential areas. The research employs a quantitative experimental method, following the SNI 8427 of 2017 standard for measuring residential noise pollution and determining the sustainable noise barrier's effectiveness using Insertion Loss (IL) and Sound Transmission Loss (STL) measurements in both laboratory-scale and existing conditions (alongside the double-track railways). The research findings indicate that the noise levels in residential areas adjacent to dual railway lines exceed the threshold value, reaching 78.08 dBA. However, the sustainable noise barrier proves to be effective in reducing noise pollution by 27 dB at a frequency of 1,000 Hz in the residential areas neighboring the double-track railways. This research suggests that limiting noise disturbances in residental areas bordering railway lines is one solution with noise barriers.
Karakterisasi Sensor Cahaya Light Dependent Resistor (LDR) Annas, Muhamad Azwar; Widodo, Aris; Aisiyah, Muktamar Cholifah; Ningrum, Izza Eka; Makrufah, Dini
MASALIQ Vol 2 No 4 (2022): JULI
Publisher : Lembaga Yasin AlSys

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (544.343 KB) | DOI: 10.58578/masaliq.v2i4.516

Abstract

Research on the Characterization of the Light Dependent Resistor (LDR) Light Sensor has been carried out with the aim of understanding the characteristics of the LDR light sensor, for processing changes in the LDR resistance value as a measurement of light intensity and for accessing an 8-bit resolution ADC by entering the LDR light sensor voltage result. The value of the resistance on the LDR depends on the size of the light received by the LDR itself. In addition, the greater the intensity of light hitting the LDR surface, the smaller the resistivity. On the other hand, the smaller the intensity of light hitting the LDR, the greater the resistance value. The basic principle used in the use of LDR resistors as components of this sensor is the change in the resistance value and the amount of current flowing in the circuit. In this experiment, the distance variations of 0cm, 3cm, 6cm, 9cm, 12cm, 15cm, 18cm, 21cm, 24cm, 27cm and 30cm were used. LDR characteristics are slow response in identifying light intensity, the greater the light intensity the smaller the resistivity, LDR can be used to read changes in light intensity and data retrieval can be done with an op-amp and a microcontroller.
Pengukuran Konduktifitas Termal pada Bahan Kayu, Kapur, dan Besi Annas, Muhamad Azwar; Chasanah, Uswatun; Sandi, Aris
MASALIQ Vol 3 No 4 (2023): JULI
Publisher : Lembaga Yasin AlSys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/masaliq.v3i4.1528

Abstract

Measurement Of Thermal Conductivity In Wood, Lime And Iron have been carried out with the aim of determining the termal conductivity of a material and knowing the factors that affect the termal conductivity of a material. The tools and materials in this experiment were two metal cylinder conductors, the test material (in the form of a cylinder) in the form of cotton wool, iron and wood, an electric stove, a pyrometer, water, clamps and a stopwatch with the stove working steps turned on, piling up the test material placed in the middle of the metal conductor, heated for 10 minutes, the temperature was measured with a pyrometer on the bottom surface, the metal surface below the test material, the metal surface above the test material, and the top surface. Note, the test material and metal conductors are cooled with water and repeated for the other test materials. The working principle used is termal convection termal conduction, temperature measurement. The results of the experiment showed that the value of the termal conductivity was 27.13 W/m°C for wood, 18.6 W/m°C for lime, and 60.6 W/m°C for iron. As for the conductivity is influenced by the temperature difference of each surface of the material, the type of material, the cross-sectional area.
Characterization of the cough monitoring device for TB patients based on the MAX9814 sound sensor Musfiana, Masria; Widodo, Aris; Annas, Muhamad Azwar
Gravity : Jurnal Ilmiah Penelitian dan Pembelajaran Fisika Vol 10, No 2 (2024)
Publisher : Universitas Sultan Ageng Tirtayasa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30870/gravity.v10i2.28340

Abstract

Mycobacterium tuberculosis is the cause of tuberculosis (TBC), one of the deadliest diseases in the world that affects the respiratory system. One of the nations having the highest number of tuberculosis cases worldwide is Indonesia. Health professionals must improve patient monitoring as one way to address this issue. This work aims to compile and describe monitoring instruments. The monitoring sensor is intended to help medical professionals treat patients and raise the quality of life for TB patients. Using advancements in technology, specifically the Internet of Things (IoT) to remotely operate electronic equipment, the Arduino Cloud Web serves as a platform for transmitting and storing patient cough data, enabling medical professionals to Recognize the intensity of the cough at any moment and act accordingly. Data on the sensor's accuracy and error values, sensitivity, repeatability, precision, and resolution are gathered as part of this monitoring sensor characterisation process. The instrument was calibrated using an Audiosensor with a 1000Hz audio generator and an SLM (Sound Level Meter) calibrator prior to data collection. The investigation yielded excellent results, with an accuracy rating of 96,14% and an error of 3,86%. This figure is reasonably close to the estimated value of 5% that has been calculated for the Gaussian distribution. The SLM with a sensor has an average value of 0.05, whereas the audiotool has a sensor value of 0.02. 50% is the repeatability value, 0.01% is the precision value, and 0.0125 is the sensor resolution.
Deteksi Intensitas Suara Batuk pasien Infeksi Saluran Pernafasan Akut (ISPA) Menggunakan Edge Impulse Machine Learning berbasis Model Mel Frequency Cepstral Coefficients (MFCC) Widodo, Aris; Annas, Muhamad Azwar
TELKA - Telekomunikasi Elektronika Komputasi dan Kontrol Vol 10, No 1 (2024): TELKA
Publisher : Jurusan Teknik Elektro UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/telka.v10n1.12-21

Abstract

Batuk merupakan salah satu indikator kondisi pasien pengidap penyakit infeksi saluran pernafasan akut (ISPA). Teknologi terkini memiliki banyak metode untuk mendeteksi batuk diantaranya analisis gelombang suara batuk langsung, penggunaan Frequency-Modulated Continuous Wave radar (FMCW) atau jaringan saraf tepi konvolusi dan sebagainya sebagai acuan deteksi suara batuk namun masih belum pada tingkatan pengukuran beruntun dalam bentuk intensitas deteksi batuk tiap waktu. Pada penelitian ini telah dilakukan uji coba alternatif deteksi intensitas menggunakan Mel Frequency Cepstral Coefficients (MFCC) pada platform Edge Impulse untuk mengetahui nilai akurasi deteksi intensitas batuk ISPA. Penelitian ini dilakukan dengan membuat dataset batuk ISPA, membuat pemodelan MFCC pada design Impulse dan pengembangan library mikrokontroler. Library ini diunggah pada mikrokontroler untuk dilakukan uji langsung deteksi batuk beruntun dengan variasi tanpa jeda, jeda 5 detik dan 10 detik dari kompilasi 50 suara batuk. Hasil deteksi diakumulasi dengan nilai confidence level di atas 50% dianggap sebagai batuk dan dihitung nilai akurasi dari rasio jumlah batuk yang terukur. Pada penelitian ini dihasilkan akurasi pengukuran suara batuk tanpa jeda, jeda 5 detik dan 10 detik sebesar 18%, 34% dan 62%. Cough is an indicator of the condition of patients with acute respiratory infections (ARI). Latest technology has many methods for detecting cough, such as analysis of direct cough sound waves, use of frequency-modulated continuous wave radar (FMCW), convolutional peripheral nerve networks, etc., as a reference for cough detection, but still not at the continuous measurement level in the form of cough detection intensity each time. In this study, an alternative intensity detection test will be tested using the Mel Frequency Cepstral Coefficients (MFCC) on the Edge Impulse platform to determine the accuracy of the intensity detection of ARI cough intensity. This research was carried out by creating an ISPA cough dataset, doing MFCC modeling on the Impulse design, and developing a microcontroller library. This library is uploaded to the microcontroller for a direct test of continuous cough detection with variations without pause of 5 seconds and 10 seconds from a compilation of 50 coughing sounds. The detection results accumulated a confidence level value above 50%, which was considered a cough, and the accuracy value was calculated from the ratio of the number of coughs measured. In this study, the accuracy of cough sound measurement without pauses, pause of 5 seconds, and 10 seconds was 18%, 34%, and 62%, respectively.
Design and Construction of a Bipolar Disorder Detection Device Based on Anomalies in the Frequency of Conversational Sound Waves Using the Max9814 Sensor Badiyah, Rohmatul; Chasanah, Uswatun; Makrufah, Asmaul Lutfi; Widodo, Aris; Annas, Muhamad Azwar
Gravity : Jurnal Ilmiah Penelitian dan Pembelajaran Fisika Vol 11, No 2 (2025)
Publisher : Universitas Sultan Ageng Tirtayasa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62870/gravity.v11i2.34826

Abstract

Bipolar disorder is a mental health condition that causes extremely dramatic mood swings, from very high (mania) to very low (depression). Physically, mood changes can be identified from variations in sound frequency. However, early detection of individuals suspected of having bipolar disorder remains a challenge due to the limited availability of tools and healthcare facilities. This research aims to design a bipolar disorder detection tool based on anomalies in the frequency of conversational sound waves using the MAX9814 sensor as a preventive measure for bipolar disorder, with the novelty of the research being its connection to IoT, enabling real-time monitoring of bipolar patients' emotional conditions. The system design uses Arduino Nano as the data processor, and ESP8266 module for IoT connectivity, with testing method conducted on ten respondents with five variations of emotion combinations. The testing method was performed on  10 people (5 men and 5 women) aged 20–40 years, who recited sentences combining variations of depression and mania. The research results show that the device is able to detect changes in voice frequency with an average error of 5% and an accuracy of 95%. The range of sound frequencies indicative of bipolar disorder is 190–355 Hz, with the following patterns: anger < 320 Hz, happiness < 300 Hz, sadness and fear > 240 Hz, especially if negative sounds are the highest. In individuals with bipolar disorder, voice frequencies can change suddenly by more than ±50 Hz within a single sentence. These findings prove that the developed tool has high sensitivity in detecting emotional changes based on voice frequency and can be used as a supporting instrument in the early detection of bipolar disorder efficiently and sustainably.
Co-Authors Agus Salim, Alfi Tranggono Aris Widodo Aris Widodo Badiyah, Rohmatul Febrianti, Denisa Eka Makrufah, Asmaul Lutfi Makrufah, Dini Muktamar Cholifah Aisiyah Musfiana, Masria Ningrum, Izza Eka Sandi, Aris Suyatno Suyatno Uswatun Chasanah Wida Yuliar Rezika, Wida Yuliar