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All Journal Gravity : Jurnal Ilmiah Penelitian dan Pembelajaran Fisika Journal of Physics and Its Applications Martabe : Jurnal Pengabdian Kepada Masyarakat Abdimas Umtas : Jurnal Pengabdian kepada Masyarakat TELKA - Telekomunikasi, Elektronika, Komputasi dan Kontrol Tsaqofah: Jurnal Penelitian Guru Indonesia YASIN: Jurnal Pendidikan dan Sosial Budaya MASALIQ: Jurnal Pendidikan dan Sains Karunia: Jurnal Hasil Pengabdian Masyarakat Indonesia BULETIN FISIKA
AZWAR ANNAS, MUHAMAD
Universitas Muhammadiyah Lamongan
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy Computer Science & IT Control & Systems Engineering Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Health Professions Materials Science & Nanotechnology Medicine & Pharmacology Physics Social Sciences Other

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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.
Empowerment of Karang Taruna Jelakcatur Kalitengah Village, Lamongan Regency, Through an Integrated IoT Early Warning System in an Effort to Increase Independence in Flood Disaster Emergency Response Uswatun Chasanah; Muhamad Azwar Annas; Henny Dwi Bhakti
ABDIMAS: Jurnal Pengabdian Masyarakat Vol. 7 No. 4 (2024): ABDIMAS UMTAS: Jurnal Pengabdian Kepada Masyarakat
Publisher : LPPM Universitas Muhammadiyah Tasikmalaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35568/abdimas.v7i4.5442

Abstract

Jelakcatur Village is a village located in Kalitengah District, where the district has a basin contour or what is called Bonorowo and is included in the River Basin Area (DAS), which is prone to flooding, so that every year it is always affected by flood disasters. Based on the results of discussions with partners, the problems faced related to flooding are: Low knowledge of youth in Karang Taruna regarding flood mitigation has implications for low community preparedness for flood disasters; The unavailability of physical infrastructure for handling floods, namely EWS, which is able to provide up-to-date information about flood disasters; The unavailability of flood disaster hazard maps, safe zones, and evacuation routes. The purpose of this activity is to provide solutions in the form of: increasing the knowledge of youth in Karang Taruna regarding preparedness in facing flood disasters through counseling and education about floods to Karang Taruna in order to increase understanding, concern, and the role of youth in their environment; Making an IoT-integrated EWS so that it can provide early warning information for flood disasters to the Jelakcatur Village community in real time; Making disaster hazard maps in a participatory manner, namely safe zone maps and evacuation routes, to provide the community with an understanding of environmental conditions related to flood disasters. This participatory flood disaster evacuation route map-making training activity is a supplement to increase the capacity of Karang Taruna cadres in non-structural disaster mitigation carried out at the pre-disaster stage, as well as to improve the soft skills of Karang Taruna cadres so that they can increase their role in the local village.
Comprehensive characterization of the Lidar TF Mini sensor for its potential use in early breast cancer detection, employing a data-driven approach Annas, Muhamad Azwar; Marufah, Asmaul Lutfi; Chasanah, Uswatun
Gravity : Jurnal Ilmiah Penelitian dan Pembelajaran Fisika Vol 11, No 1 (2025)
Publisher : Universitas Sultan Ageng Tirtayasa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30870/gravity.v11i1.28900

Abstract

Breast cancer is a leading cause of death among women. Early detection helps prevent the spread of cancer to other organs, thereby reducing serious risks. This characterization aims to determine the potential of the TF Mini Lidar sensor if used as an early detection tool for breast cancer. Basically, this characterization uses a data-based approach. The method used in this study is to position the TFmini and HC-SR04 sensors in a fixed and stable position, after which the reflective object is positioned at a predetermined distance according to the distance to be used when detecting breast cancer, which is at a distance of 51-100 cm. PLX daq version 2.11 was used to facilitate data collection. The characterization of this sensor is based on the standard deviation, relative standard deviation, error and accuracy. This study concludes that the TFmini lidar sensor has a high potential to be used in breast cancer detection devices as a contour detector. This is in accordance with the measurement accuracy value of the tfmini sensor of 99.87%. However, additional sensors, such as cameras, are needed to obtain better contours and visual images.
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.
PELATIHAN EVALUASI AKUSTIK RUANG DI MASJID KI BAGUS HADIKUSUMO UNIVERSITAS MUHAMMADIYAH LAMONGAN Satria Praja, Tatag; Azwar Annas, Muhamad; Widodo, Aris
Martabe : Jurnal Pengabdian Kepada Masyarakat Vol 6, No 6 (2023): martabe : jurnal pengabdian kepada masyarakat
Publisher : Universitas Muhammadiyah Tapanuli Selatan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31604/jpm.v6i6.2107-2116

Abstract

Rancang bangun masjid di Indonesia menyesuaikan budaya masing-masing daerahnya. Namun, dibalik keindahan interior maupun eksterior masjid tersebut kurang menghiraukan aspek akustik ruangannya. Hal ini mengakibatkan munculnya permasalahan akustik seperti waktu dengung yang tinggi dan kurang meratanya distribusi SPL. Pemuda masjid yang biasa membantu pengurusan masjid berupa menyiapkan fasilitas ibadah, menjadi muazin, menggantikan imam saat tidak hadir, mengadakan kegiatan keagamaan di masjid dan lain sebagainya. Peran pemuda masjid yang vital ini bisa menjadi kader akustik masjid di daerah masing-masing. Hal ini menjadikan inisiasi Takmir Masjid KBH untuk memperbaiki kondisi masjid dan sekaligus membimbing pada pemuda masjid agar lebih peka terhadap permasalahan sarana dan prasarana ibadah di masjid, utamanya terkait tata suara atau akustik masjid. Metode yang digunakan pada pelatihan ini adalah, ceramah, diskusi, demo alat dan praktek langsung. Analisis pengamatan dan evaluasi tingkat pemahaman peserta menggunakan kuesioner pretest dan posttest. Hasil dari kedua tes tersebut didapatkan peningkatakan nilai rata-rata dari yang awalnya 48% menjadi 75%. Sehingga kenaikan pemahaman rata-rata peserta adalah 27%. Simpulan dari kegiatan pelatihan ini adalah Adanya peningkatkan pemahaman peserta tentang akustik ruang masjid dibuktikan dari hasil kedua tes.
Rancang Bangun Sistem Deteksi Dini Kanker Payudara Berdasarkan Indikator Warna Pada Kulit Berbasis ESP32-Cam Terintegrasi Edge Impulse Hana Dwi Cahyani; Muhamad Azwar Annas; Uswatun Chasanah; Muktamar Cholifah Aisiyah
BULETIN FISIKA Vol. 26 No. 2 (2025): BULETIN FISIKA
Publisher : Departement of Physics Faculty of Mathematics and Natural Sciences, and Institute of Research and Community Services Udayana University, Kampus Bukit Jimbaran Badung Bali

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/BF.2025.v26.i02.p10

Abstract

Deteksi dini kanker payudara merupakan langkah penting untuk meningkatkan peluang kesembuhan dan menekan angka kematian. Penelitian ini merancang sistem deteksi dini berbasis citra digital dengan memanfaatkan indikator visual berupa warna kemerahan pada kulit. Sistem dikembangkan menggunakan ESP32-Cam yang terintegrasi dengan Edge Impulse untuk pelatihan dan inferensi model klasifikasi berbasis Artificial Intelligence (AI). Deteksi dilakukan melalui pengolahan citra warna dan metode machine learning (ML) yang bekerja berdasarkan prinsip fisika optik dan sensorika, khususnya interaksi cahaya dengan permukaan kulit, serta merupakan bentuk penerapan prinsip-prinsip fisika dalam pengembangan teknologi deteksi visual modern. Dataset dikumpulkan dari phantom payudara dengan variasi tingkat kemerahan, dua jenis warna kulit (kuning langsat dan sawo matang), serta pencahayaan berbeda (600 lux, 800 lux, dan 1000 lux). Gambar diambil dari jarak 20 cm dengan sudut 90° dan 45° menggunakan kamera handphone. Model dilatih menggunakan metode CNN dan diintegrasikan ke ESP32-Cam, namun proses inferensi masih memerlukan koneksi internet untuk dapat dijalankan. Hasil menunjukkan bahwa pencahayaan 800 lux memberikan visual optimal, dan berhasil menjalankan klasifikasi dengan akurasi rata-rata sebesar 90,9%. Evaluasi menggunakan confusion matrix menunjukkan bahwa sistem ini baik dan akurat. Kata kunci: Deteksi dini; edge impulse; ESP32-cam; fisika optik; kanker payudara.
Co-Authors Abelia Arianingsih Agistina Agus Salim, Alfi Tranggono Aris Widodo Aris Widodo Asmaul Lutfi Marufah Badiyah, Rohmatul Bagus Dwi Jauhari Cahyani, Hana Dwi Dian Nur Faizah Dini Makrufah Dwi Indah Setyo Pratiwi Febrianti, Denisa Eka Hana Dwi Cahyani Hariono Hariono Henny Dwi Bhakti Maida Nanda Widiatiningsih Makrufah, Asmaul Lutfi Makrufah, Dini Muktamar Cholifah Aisiyah Musfiana, Masria Musfiana, Masria Ningrum, Izza Eka Sandi, Aris Satria Praja, Tatag Suyatno Suyatno Tatag Satria Praja Tegar Sabilliah Uswatun Chasanah Wida Yuliar Rezika, Wida Yuliar