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Transformasi Pemantauan Gizi Anak: Implementasi Aplikasi Website di PKD Desa Karangkemojing Hellyana, Corie Mei; Fadlilah, Nuzu Imam; Saifudin, Saifudin; Widayanto, Aprih
JURNAL PENGABDIAN KEPADA MASYARAKAT Vol 15 No 1 (2025): Juli 2025
Publisher : LPPM UNINUS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30999/jpkm.v15i1.3361

Abstract

Children's nutritional health is a crucial factor for their growth and development. Regular monitoring of nutrition is essential for detecting and preventing nutritional issues. This study aims to develop a web-based application for monitoring children's nutrition at the Village Health Center (PKD) in Karangkemojing Village. The methodology employed is the System Development Life Cycle (SDLC) approach, involving analysis, design, implementation, and evaluation. This web-based application allows health workers and parents to monitor children's nutritional status regularly through data on weight, height, and other nutrition indicators. It is expected that the use of this application will enhance the efficiency of posyandu cadres in monitoring children's nutrition. Additionally, the application facilitates access to nutritional information for health workers and parents while supporting decision-making regarding nutritional interventions. The utilization of this application is anticipated to serve as a model for other regions in improving the quality of children's health services at the village level.
Transformasi Pemantauan Gizi Anak: Implementasi Aplikasi Website di PKD Desa Karangkemojing Hellyana, Corie Mei; Fadlilah, Nuzul Imam; Saifudin, Saifudin; Widayanto, Aprih
JURNAL PENGABDIAN KEPADA MASYARAKAT Vol 15 No 1 (2025): Juli 2025
Publisher : LPPM UNINUS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30999/jpkm.v15i2.3362

Abstract

Children's nutritional health is a crucial factor for their growth and development. Regular monitoring of nutrition is essential for detecting and preventing nutritional issues. This study aims to develop a web-based application for monitoring children's nutrition at the Village Health Center (PKD) in Karangkemojing Village. The methodology employed is the System Development Life Cycle (SDLC) approach, involving analysis, design, implementation, and evaluation. This web-based application allows health workers and parents to monitor children's nutritional status regularly through data on weight, height, and other nutrition indicators. It is expected that the use of this application will enhance the efficiency of posyandu cadres in monitoring children's nutrition. Additionally, the application facilitates access to nutritional information for health workers and parents while supporting decision-making regarding nutritional interventions. The utilization of this application is anticipated to serve as a model for other regions in improving the quality of children's health services at the village level.
Komparasi K-Nearest Neighbors (KNN) dan Naive Bayes pada Klasifikasi Sentimen Ulasan Aplikasi Tokopedia di Google Play Store Ragil Wijianto; Pratmanto, Dany; Widayanto, Aprih; Ubaidilah
Informatics and Computer Engineering Journal Vol 5 No 2 (2025): Periode Agustus 2025
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat (LPPM) Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/r1sgr558

Abstract

Ulasan pengguna aplikasi e-commerce di platform seperti Google Play Store merupakan sumber umpan balik vital bagi pengembang, namun volumenya yang masif menyulitkan analisis manual. Penelitian ini bertujuan untuk mengatasi tantangan tersebut dengan melakukan analisis sentimen otomatis pada ulasan aplikasi Tokopedia. Fokus utama adalah mengklasifikasikan sentimen ulasan ke dalam kategori positif dan negatif serta membandingkan secara empiris kinerja dua algoritma klasifikasi populer, yaitu Naive Bayes (NB) dan K-Nearest Neighbors (KNN). Metodologi penelitian mencakup tahapan pengumpulan data ulasan dari Google Play Store, pra-pemrosesan teks ekstensif (termasuk case folding, cleaning, tokenizing, stopword removal, stemming), ekstraksi fitur numerik dari teks, implementasi model NB dan KNN, serta evaluasi komparatif menggunakan metrik Akurasi, F1-Score, dan Area Under the Curve (AUC). Hasil evaluasi pada data uji menunjukkan bahwa algoritma KNN menunjukkan kinerja yang secara signifikan lebih unggul dibandingkan Naive Bayes. KNN berhasil mencapai akurasi sebesar 80.00% dengan nilai AUC 0.865, sementara Naive Bayes hanya mencapai akurasi 71.50% dengan nilai AUC 0.576 yang mengindikasikan kemampuan diskriminatif rendah. Penelitian ini menyimpulkan bahwa KNN merupakan metode yang lebih efektif dan reliabel dibandingkan NB untuk tugas klasifikasi sentimen pada dataset ulasan aplikasi Tokopedia ini, dan menawarkan potensi aplikasi praktis untuk memonitor opini pengguna secara otomatis.