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All Journal Jurnal Teknoin Jurnal Teknik Kimia USU Jurnal Simetris Telematika : Jurnal Informatika dan Teknologi Informasi OPSI Dharmakarya : Jurnal Aplikasi Ipteks Untuk Masyarakat Jurnal Informatika dan Teknik Elektro Terapan Journal of Electrical Technology UMY Jurnal Gizi Klinik Indonesia Communications in Science and Technology Journal of Appropriate Technology for Community Services Prosiding Seminar Nasional Multidisiplin Ilmu Jurnal Pengabdian Dharma Bakti Respati Indonesian Applied Physics Letters Charity : Jurnal Pengabdian Masyarakat Journal mechanical and manufacture technology (JMMT) Jurnal Rekayasa Elektro Sriwijaya Jurnal Teknik Kimia USU ETAM: Jurnal Pengabdian kepada Masyarakat Jurnal Litek : Jurnal Listrik Telekomunikasi Elektronika
Listyalina, Latifah
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IMPLEMENTATION OF FAST FOURIER TRANSFORM (FFT) FOR INFANT CRYING DETECTION Listyalina, Latifah; Utari, Evrita Lusiana; Wizando, Mario Warran
Indonesian Applied Physics Letters Vol. 4 No. 1 (2023): Indonesian Applied Physics Letters - June 2023
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/iapl.v4i1.46916

Abstract

Babies cry based on the discomfort felt by the baby which is a reflex such as when a hungry baby will suck his hand and then he will start crying, hunger can be interpreted from the baby's crying. At each of the baby's cries, when each crying pattern was responded to with the solution applied to the previous baby, each baby would stop crying. For this reason, to carry out this solution, a research was carried out to identify the pattern recognition of the sound of a baby's cry using the fast fourier transform (FFT) method with several different frequency ranges. The voice recording process is stored in digital form in the form of frequency-based sound spectrum waves, where signals that were previously in the time domain will be changed in the frequency domain. The sounds that will be distinguished in this study include the sounds of crying babies, adults, and colliding objects. This can be obtained through several stages, namely sound sample recording, sampling, signal cutting, frame blocking, final normalization, hamming window, and finally the FFT calculation process. From these series of stages, the results of the frequency range of baby crying are 101-1863 Hz, for adults the frequency range is 101-1376 Hz and for the sound of colliding objects 101-2233 Hz.
Beach Litter Detection as an Environmental Conservation Effort Against Plastic Waste Using Artificial Intelligence Listyalina, Latifah; Mario Sarisky Dwi Ellianto; Midarto Dwi Wibowo
Jurnal Rekayasa Elektro Sriwijaya Vol. 7 No. 2 (2026): Jurnal Rekayasa Elektro Sriwijaya
Publisher : Jurusan Teknik Elektro Fakultas Teknik Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36706/ap8wjq69

Abstract

The increasing presence of plastic debris in these areas not only disrupts biodiversity but also threatens the balance and sustainability of marine habitats. Addressing this problem requires innovative approaches that combine environmental science with modern technology. This study was conducted to develop a beach litter detection system as part of a broader effort to support environmental preservation and reduce the detrimental effects of plastic waste on coastal areas in Indonesia. The research employed a secondary dataset obtained from Kaggle.com, which consisted of labeled images of beach waste. A deep learning method was applied through the use of Convolutional Neural Networks (CNN), with MobileNetV2 selected as the primary architecture due to its lightweight design, computational efficiency, and proven effectiveness in image classification tasks. Experimental results demonstrated that the model performed exceptionally well, achieving a training accuracy of 100%, which indicates its strong ability to capture patterns in the dataset. More importantly, the validation accuracy reached 97.83%, reflecting the model’s robustness and capacity to generalize effectively to unseen data. These findings emphasize the potential of artificial intelligence in supporting environmental monitoring and management. In particular, automated detection and classification of plastic waste on beaches can enhance current conservation strategies and provide timely information for waste management interventions. Furthermore, this research serves as a foundation for future studies aimed at advancing intelligent waste management systems. The integration of AI in this domain remains relatively underexplored, and continued exploration could contribute significantly to mitigating the global challenge of plastic pollution in coastal environments.
Pengembangan Alat Monitoring Infus Berbasis Arduino: Fondasi Awal untuk Integrasi Industri Material Plastik Biomedis Masa Depan Engelbertus, Yustinus; Buyung, Irawadi; Listyalina, Latifah
Teknoin Vol. 31 No. 1 (2026)
Publisher : Faculty of Industrial Technology Universitas Islam Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/teknoin.vol31.iss1.art1

Abstract

Penelitian ini bertujuan merancang dan mengembangkan perangkat monitoring volume infus berbasis mikrokontroler Arduino dengan kemampuan deteksi aliran cairan secara real-time. Perangkat ini ditujukan untuk meningkatkan efisiensi pemantauan infus oleh tenaga medis serta meminimalkan risiko keterlambatan pergantian cairan yang berpotensi memengaruhi kondisi pasien. Sistem yang dirancang menggunakan sensor flow rate untuk mendeteksi aliran cairan infus dan menampilkan data volume cairan pada layar LCD, serta dilengkapi dengan mekanisme peringatan ketika aliran terhenti atau volume cairan berada pada ambang minimum. Dalam tahap implementasi awal, konstruksi fisik dan casing masih memanfaatkan material konvensional. Namun, sebagai bentuk inovasi berkelanjutan, penelitian ini merekomendasikan pengembangan lanjutan melalui integrasi material plastik biomedis, seperti plastik transparan biokompatibel, plastik tahan suhu tinggi, maupun plastik biodegradable. Pemanfaatan material tersebut berpotensi meningkatkan aspek keamanan, kenyamanan pasien, serta mendukung prinsip keberlanjutan dalam industri alat kesehatan. Hasil pengujian menunjukkan bahwa sistem memiliki tingkat akurasi dan respons yang baik, yaitu tingkat kesalahan relatif kecil, yaitu sebesar 3,07%, yang masih berada dalam batas toleransi untuk aplikasi monitoring non-kritis sehingga prototipe ini berpotensi menjadi dasar pengembangan perangkat monitoring infus cerdas yang tidak hanya efisien, tetapi juga adaptif terhadap penerapan teknologi material plastik medis modern
Co-Authors Adetya, Nais Pinta Agus Qomaruddin Munir Andri Saputra Ariyanto, Ipan Azmi, Desvika Arnila Bagus Seno Wulung, Raden Chandra, Hekin Irfan Desty Ervira Puspaningtyas Dharmawan, Dhimas Arief Dwi Wibowo, Midarto Eko Susilo Ellianto, Mario Sariski Dwi Engelbertus, Yustinus Evrita Lusiana Utari Evrita Lusiana Utari Evrita Lusiana Utari, Evrita Lusiana Hanung Adi Nugroho Ikhwan Mustiadi Irawadi Buyung, Irawadi Mario Sarisky Dwi Ellianto Mario Sarisky Dwi Ellianto Midarto Dwi Wibowo Muh. Wahyu Syabani Muhammad Ikhwan Novi Irawati Nurwijayanti Oktoeberza, Widhia KZ Pambudi, Wisnu Pani Satwikanitya Putrama, Fala Putri, Naimah Ratnaningsih, Wahyu Ratri Retno Utami RR. Ella Evrita Hestiandari Sabdullah, Mursid Sarisky Dwi Ellianto, Mario Sarisky, Mario Satwikanitya, Pani Sugeng Winardi Suharyanto Sunu Wibirama Suwarno, Yuli Syahbani, Muhammad Wahyu Uma Fadzilia Arifin Uma Fadzilia Arifin, Uma Fadzilia Utarianingrum, Ratna Wahyu Ratnaningsih Wijaya, Nurhadi Wisnu Pambudi Wizando, Mario Warran Yudianingsih Yudianingsih Yudianingsih, Yudianingsih