Aplikasi Rekomendasi Produk Makanan dan Minuman Kemasan Berdasarkan Analisis Kandungan Nutrisi dengan Menggunakan Machine Learning
Abstract
Konsumsi makanan dan minuman kemasan telah menjadi bagian integral dari gaya hidup modern, namun kurangnya pemahaman tentang kandungan nutrisi dalam produk-produk tersebut menimbulkan kekhawatiran serius terhadap kesehatan jangka panjang. Berdasarkan survei yang telah dilakukan, sebanyak 88% responden merasa khawatir dengan dampak konsumsi produk kemasan terhadap kesehatan, sementara 72,8% masih mengalami kesulitan dalam memilih produk yang sesuai dengan kebutuhan nutrisi mereka. Untuk mengatasi permasalahan tersebut, penelitian ini mengembangkan aplikasi BeWise, sebuah platform rekomendasi produk makanan dan minuman kemasan berdasarkan analisis kandungan nutrisi dengan pendekatan machine learning. Aplikasi ini mengimplementasikan fuzzy logic untuk mengklasifikasikan produk ke dalam kategori Nutri-Score (A-E) berdasarkan parameter nutrisi seperti energi, lemak jenuh, gula, natrium, protein, dan serat. Dengan fitur pemindaian barcode yang terintegrasi dengan ML Kit, pengguna dapat dengan mudah mendapatkan informasi nutrisi produk secara instan dan menerima rekomendasi alternatif yang lebih sehat berdasarkan preferensi mereka. Hasil pengujian menunjukkan bahwa model machine learning yang dikembangkan mencapai akurasi 90% dalam mengklasifikasikan Nutri-Score produk, dengan performa API yang stabil pada waktu respons rata-rata 422,85 ms bahkan dalam kondisi beban tinggi. Pengujian usability menggunakan System Usability Scale (SUS) menghasilkan skor 86,1 dalam kategori sangat baik, mengindikasikan bahwa aplikasi dirancang dengan mempertimbangkan kemudahan penggunaan bagi berbagai kalangan masyarakat.
Kata kunci— Aplikasi, Fuzzy Logic, Machine Learning, Nutrisi, Nutri-Score
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