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All Journal Journal of Electrical Technology Jurnal Armada Informatika
Tomy Satria Alasi
Asosiasi Informatika Sumatera Utara
Automotive Engineering Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology

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Clustering of Stunting, Wasting, and Underweight Case Volumes Using K-Means: An Exploratory Study of Monthly Data in Southeast Aceh Regency Ahmad Taufik Al Afkari; Tomy Satria Alasi; Yuvi Darmayunata
Jurnal Armada Informatika Vol 10 No 1 (2026): Juni
Publisher : STMIK Methodist Binjai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36520/jai.v10i1.310

Abstract

The availability of open data enables computational-based monitoring of toddler nutritional problems, but local administrative datasets are often small, aggregated, and lack target labels for supervised modeling. This study aims to (1) determine the most appropriate number of case volume clusters, (2) characterize the clusters of stunting, wasting, and underweight, and (3) build a simple and reproducible analysis baseline using Google Colab. Secondary data was obtained from the Aceh Government's open sources and consists of 15 aggregate observations from Southeast Aceh Regency between November 2022 and March 2023. The modeling variable is the number of cases in individuals. The research stages include data understanding, quality checking, descriptive analysis, K-Means modeling for k=2 to k=5, and internal evaluation using the Silhouette Coefficient, Davies-Bouldin Index (DBI), and Calinski-Harabasz Index (CHI). The results show no missing values or duplications. The highest silhouette value was obtained at k=2 with 0.8189, alongside a DBI of 0.2286 and a CHI of 150.6841. The high-volume cluster is centered at 1,182.6 individuals and contains five stunting observations, while the lower-volume cluster is centered at 545.7 individuals and contains five wasting observations and five underweight observations. The total of the three indicators changed from 2,469 individuals in November 2022 to 2,122 individuals in March 2023 (-14.05%), but the change was not monotonic as an increase occurred in February 2023. The novelty of this research lies in a minimal baseline that empirically selects k, uses three evaluation indices, incorporates temporal examination, and limits cluster interpretation to relative volumes. The results can serve as an analytic audit prototype for regional nutrition data, but cannot yet be used to infer prevalence, causality, or individual risk. The research testing can be downloaded from github.com. Keywords: Data Mining; K-Means; Clustering; Stunting; Wasting; Underweight; Google Colab
Smart Home ESP32 Dual-Kontrol Mengatasi Kerentanan Ketergantungan Jaringan Mewujudkan Otomatisasi Rumah Stabil dan Aman Tomy Satria Alasi; Allwine Allwine; Mutiara S Simanjuntak
JET (Journal of Electrical Technology) Vol 11, No 3 (2026): Edisi Oktober
Publisher : Universitas Islam Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30743/jet.v11i3.14187

Abstract

Ketergantungan penuh pada layanan cloud menurunkan ketersediaan smart home ketika koneksi Internet terganggu, sementara kontrol suara tanpa autentikasi membuka peluang eksekusi perintah oleh pengguna yang tidak berwenang. Penelitian ini merancang dan mengevaluasi prototipe smart home berbiaya rendah yang membagi kendali ke dua jalur: jalur online melalui aplikasi Flutter dan Firebase Realtime Database serta jalur lokal melalui aturan sensor, voice assistant Vosk, dan autentikasi wajah. ESP32 memproses sensor HC-SR04, LDR, sensor hujan, dan DHT11; mengendalikan servo pagar, servo jemuran, lampu melalui relay, serta menampilkan status pada LCD. ESP32-CAM dan pustaka face_recognition memverifikasi identitas sebelum sistem menerima perintah suara. Penelitian menggunakan metode prototipe selama tiga bulan dengan inti pengembangan sepuluh minggu. Pengujian mencakup 38 skenario fungsional: 18 skenario keputusan sensor, lima pembacaan suhu, tujuh perintah suara, dua skenario autentikasi wajah, dan enam fungsi aplikasi-cloud. Seluruh skenario menghasilkan keluaran sesuai aturan yang ditetapkan (38/38 atau 100% keberhasilan fungsional). Pagar terbuka pada jarak 3–6 cm dan tertutup pada 8–15 cm dengan ambang 7 cm. Lampu aktif mulai nilai LDR 2400 dengan ambang 2350, sedangkan jemuran masuk sampai nilai sensor hujan 3400 dan keluar mulai 3600 dengan ambang 3500. Pembacaan DHT11 menghasilkan rata-rata 29,8 °C, simpangan baku sampel 0,84 °C, dan rentang 2 °C. Jalur online menunjukkan waktu respons observasional 1–2 detik. Kebaruan penelitian terletak pada integrasi kontrol cloud, kontrol lokal berbasis sensor dan suara, serta autentikasi wajah berurutan dalam satu prototipe ESP32. Hasil membuktikan kelayakan fungsi, tetapi belum membuktikan akurasi sensor terkalibrasi, word error rate, false acceptance rate, ketahanan jaringan, atau keamanan produksi.
Co-Authors Ahmad Taufik Al Afkari Allwine darmayunata, yuvi Mutiara S. Simanjuntak