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All Journal Jusikom : Jurnal Sistem Komputer Musirawas JRIIN :Jurnal Riset Informatika dan Inovasi
Andika Veriando Saragih
Universitas Negeri Medan
Computer Science & IT Decision Sciences, Operations Research & Management

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Desain dan Implementasi Algoritma Decision Tree untuk Klasifikasi Kategori Obesitas Yusrida Jelianti Sihite; Andika Veriando Saragih; Jatmiko Althaf Aziz
Jurnal Riset Informatika dan Inovasi Vol 3 No 12 (2026): JRIIN : Jurnal Riset Informatika dan Inovasi (INPRESS)
Publisher : shofanah Media Berkah

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Abstract

Perkembangan teknologi machine learning memungkinkan pengklasifikasian data kesehatan secara cepat dan akurat. Penelitian ini bertujuan menerapkan algoritma Decision Tree untuk klasifikasi kategori obesitas berdasarkan variabel tinggi badan, berat badan, dan Indeks Massa Tubuh (BMI). Dataset terdiri dari 200 sampel individu yang telah dibersihkan dan diberi label kategori obesitas: Underweight, Normal weight, Overweight, dan Obese. Model Decision Tree dioptimasi dengan pembatasan kedalaman (max_depth=5) untuk mengurangi overfitting dan meningkatkan kemampuan generalisasi. Evaluasi menggunakan data testing menghasilkan akurasi 99,5%, sementara rata-rata cross-validation 5-fold mencapai 0,995. Analisis feature importance menunjukkan bahwa BMI merupakan variabel dominan dalam klasifikasi, sedangkan tinggi badan dan berat badan tidak memberikan kontribusi tambahan. Visualisasi pohon keputusan memperlihatkan jalur klasifikasi yang jelas dan mudah diinterpretasikan, mendukung implementasi model sebagai Decision Support System (DSS) untuk identifikasi awal risiko obesitas. Penelitian ini menegaskan efektivitas Decision Tree dalam klasifikasi kategori obesitas dan konsistensinya dengan literatur sebelumnya, sekaligus memberikan dasar untuk pengembangan model yang lebih kompleks dengan menambahkan fitur pola makan, aktivitas fisik, atau algoritma ensemble.
Platform Web Promosi Bisnis Mahasiswa Terintegrasi Firebase dan WhatsApp YUSRIDA JELIANTI SIHITE SIHITE; Jatmiko Althaf Aziz; Andika Veriando Saragih; Debi Yandra Niska
Jusikom : Jurnal Sistem Komputer Musirawas Vol. 11 No. 1 (2026): Jurnal Sistem Komputer Musirawas JUNI
Publisher : LPPM UNIVERSITAS BINA INSAN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32767/jusikom.v11i1.3146

Abstract

This study was motivated by the challenges of student business promotion, which is still primarily conducted through social media and WhatsApp groups, making business information difficult to access and poorly organized. This study aims to develop a web-based student business promotion platform integrated with WhatsApp and a popularity-based recommendation system to help users discover the most preferred businesses. The research methods included observation, interviews, and literature review to analyze system requirements, while the system development adopted the Waterfall method consisting of analysis, design, implementation, and testing phases. The system was developed using Node.js, Firebase Realtime Database, and Bootstrap. The main features include user registration, business data management, business search, WhatsApp integration, and a popularity-based recommendation system utilizing user interaction data. The integration of Firebase and WhatsApp enables responsive and real-time data management and communication. System testing was conducted using Black Box Testing and usability testing involving 50 students from Universitas Negeri Medan. The results showed a 100% success rate for all main features, while usability testing achieved an average score of 4.17, categorized as high. The findings indicate that the system effectively supports structured student business promotion, simplifies business information access, and improves communication effectiveness between users and business owners.
Co-Authors Jatmiko Althaf Aziz Niska, Debi Yandra Yusrida Jelianti Sihite YUSRIDA JELIANTI SIHITE SIHITE