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All Journal Jurnal Masharif al-Syariah: Jurnal Ekonomi dan Perbankan Syariah Jurnal Aplikasi Teknologi Pangan Jurnal Pengabdian Magister Pendidikan IPA Bulletin of Information Technology (BIT) International Journal of Education and Teaching Zone Jurnal Ilmiah Sistem Informasi dan Ilmu Komputer Jurnal Semiotika-Q: Kajian Ilmu al-Quran dan Tafsir International Journal of Health, Engineering and Technology Jurnal Bima: Pusat Publikasi Ilmu Pendidikan Bahasa dan Sastra Sevaka: Hasil Kegiatan Layanan Masyarakat
Putri Ramadani
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Penyuluhan Klasifikasi Gejala Keterlambatan Bicara (Speech Delay) Pada Anak Menggunakan Algoritma Naive Bayes, C4.5, Dan K-Nerest Neighbor (K-NN) Putri Ramadani; Ika Ima Nissa; Nur Indah Nasution; Baginda Restu Al Ghazali
Sevaka : Hasil Kegiatan Layanan Masyarakat Vol. 2 No. 2 (2024): Mei : Sevaka : Hasil Kegiatan Layanan Masyarakat
Publisher : STIKES Columbia Asia Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62027/sevaka.v2i2.534

Abstract

Speech delay in children is a developmental issue commonly encountered in society, which can affect various aspects of a child's life, including communication, social interaction, and academic development. Early detection of speech delay is crucial for providing appropriate interventions to minimize its long-term impact on the child. This study aims to introduce the use of machine learning algorithms in detecting speech delay symptoms in children. Three machine learning algorithms applied in this study are Naïve Bayes, C4.5, and K-Nearest Neighbor (K-NN). These algorithms are used to classify speech delay symptoms based on health data, medical history, and environmental factors such as speaking habits and eating patterns. The outreach was conducted at Puskesmas Kota Rantauprapat with the involvement of parents and healthcare providers as participants. The experimental results showed that all three algorithms performed well in terms of accuracy, though with varying error rates. Naïve Bayes achieved relatively high accuracy but had a higher false positive rate compared to C4.5 and K-NN. C4.5 provided more stable results and was easier to interpret due to its decision tree structure. Meanwhile, K-NN performed better with data that had irregular distribution. This outreach is expected to assist both the community and healthcare providers in early detection of speech delay in children, providing a more efficient and affordable means for early intervention, which ultimately leads to better outcomes for children with speech delay.
Co-Authors Ade Irma Yanti Hasibuan Akmal Akmal Al Ramzy Awaludin Baginda Restu Al Ghazali Dikie Rezekia Dinda Fatimatuz Zahra Fatwa Aulia Fitriyani Nasution Habibah, Fitriatul Hargono Hargono Helmawati Hery Sunandar Igha Devira Pristine Ika Ima Nissa Khistinah Haryani Lale Hidayatin Shani Lalu Maulana Kusumaningrat Magistra Sayyidina Al Kautsar Mhd.Furqan Mira Anggraini Muhammad Albadar Adren Muhammad Muayyadin Nazwa Khaerinnita Noer Abyor Handayani Nur Aisyah Pandia Nur Indah Nasution Nurhilallaily Parulian Sibuea Rabiatul Adawiyah Ridwan Sholeh Riszki Fadillah Riyan Agus Faisal Rohani Salwa Latipah Santosa Pohan Saprina Putri Utama Ritonga Sentosa Pohan Septa Viani Sri Muliani Sukiyat, Sukiyat Tiwi Widiastuti Tria Putri Andini Yori Marwinda Yusril Iza Mahendra Hasibuan Zulfahri Salim