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All Journal Journal of Tropical Life Science : International Journal of Theoretical, Experimental, and Applied Life Sciences Jurnal Pendidikan Teknologi dan Kejuruan Rekayasa Teknik Sipil Jurnal Teknik Sipil dan Perencanaan Lembaran Ilmu Kependidikan QIJIS (Qudus International Journal Of Islamic Studies) Kodifikasia: Jurnal Penelitian Islam Al-Jami'ah: Journal of Islamic Studies Gravity : Jurnal Ilmiah Penelitian dan Pembelajaran Fisika Management Analysis Journal AL-MAIYYAH JURNAL PENDIDIKAN TAMBUSAI Jurnal Mina Sains Ensiklopedia of Journal RELIGIA TELKA - Telekomunikasi, Elektronika, Komputasi dan Kontrol Jurnal Teknologi Kedirgantaraan (JTK) Al-MAIYYAH : Media Transformasi Gender dalam Paradigma Sosial Keagamaan Journal of Petroleum and Geothermal Technology Al-Manahij : Jurnal Kajian Hukum Islam Tsaqofah: Jurnal Penelitian Guru Indonesia YASIN: Jurnal Pendidikan dan Sosial Budaya MASALIQ: Jurnal Pendidikan dan Sains Indonesian Journal of Religion, Spirituality, and Humanity Darma Diksani: Jurnal Pengabdian Ilmu Pendidikan, Sosial, dan Humaniora Joong-Ki Scaffolding
Aris Widodo
Jurusan Teknik Sipil, Fakultas Teknik, Universitas Negeri Semarang (UNNES)
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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.
Sosialisasi dan Edukasi Peran Badan Penyelesaian Sengketa Konsumen dalam Melindungi Usaha dalam Konteks Perlindungan Konsumen Pelaku UMKM: Socialization and Education on the Role of Consumer Dispute Settlement Agency in Protecting Businesses within the Context of MSME Consumer Protection Subroto, Desty Endrawati; Agustin, Anisa Nur; Wardan, Rosyid; Firmansyah, Ahmad Tomi; Widodo, Aris
DARMADIKSANI Vol 5 No 2 (2025): Edisi Juli-September
Publisher : Jurusan Pendidikan Bahasa dan Seni, FKIP, Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/darmadiksani.v5i2.8001

Abstract

Penelitian berbasis pengabdian masyarakat ini bertujuan untuk memberikan sosialisasi dan edukasi mengenai peran Badan Penyelesaian Sengketa Konsumen (BPSK) dalam melindungi pelaku Usaha Mikro, Kecil, dan Menengah (UMKM). Fokus penelitian diarahkan pada efektivitas dan tingkat kepuasan pelaku usaha terhadap peran BPSK dengan menggunakan pendekatan kuantitatif deskriptif. Metode penelitian yang digunakan adalah survei melalui penyebaran kuesioner kepada 15 pelaku UMKM yang berada di kelurahan Bendung, kota Serang. Data yang diperoleh kemudian dianalisis secara deskriptif untuk menggambarkan distribusi jenis usaha, lokasi usaha, dan status legalitasnya. Hasil penelitian menunjukkan bahwa sebagian besar pelaku usaha telah memiliki legalitas usaha dan mayoritas bergerak di bidang makanan ringan. Analisis lebih lanjut mengungkapkan bahwa 86,7% pelaku usaha telah memiliki usaha yang sah secara hukum. Temuan ini menegaskan bahwa BPSK berperan penting dalam meningkatkan kesadaran hukum, memperkuat legalitas usaha, serta memberikan perlindungan melalui kegiatan edukasi dan pendampingan kepada pelaku UMKM.
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 Adhisuta, Prianindya Agustin, Anisa Nur Aini, Shofwatul Andi Mardian, Andi Annas, Muhamad Azwar Ardiansah, Ridwan Badiyah, Rohmatul Bambang Endroyo Bambang Haryadi Basith, Muhammad Abdil Basith, Muhammad Abdil Boni Swadesi Cahyani, Hana Dwi Chonora, Angelique Dermawan, Moch Husni Diana Zuhror, Diana DIMAS WICAKSONO Dzofir, Mohammad Eko Nugroho Julianto Elfrida Ratnawati Erwati Aziz Fairus Sabiq, Fairus Farmawati, Cintami Fia Sri Mumpuni Firmansyah, Ahmad Tomi Hakim , Luqmanul Hanggoro Tri Cahyo A, Hanggoro Tri Haris, Arkin Hayatuddin, Akh. Kholis Hidayat Suyuti Kayukatui, Melianus Kristanto, Dedy Listiyono Budi Listiyono, Listiyono M. USMAN Makrufah, Asmaul Lutfi Makrufah, Dini Mayasari, Retno Merlita Herbani Muhamad Azwar Annas Muktamar Cholifah Aisiyah Mulyana Mulyana Murwatiningsih Murwatiningsih, Murwatiningsih Musfiana, Masria Mustofa, Asysyafa Ningrum, Izza Eka Novianty, Nisvia Rahmah Ayu Pasalli, Damaris Ratnaningsih, Dyah Rini Ridha, Syahrir Rihaadatul'aisy, Dea Salsabila SAJOW, DETTY Sidik Sidik Siti Sarah, Siti Soraya, Angelia Nilam Subagio, Triono Subroto, Desty Endrawati Sucipto Suranto Suranto Tantri, Irma Dwi Tri Susilo Tugino Tugino, Tugino Untoro Nugroho Uswatun Chasanah Wardan, Rosyid