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Mustofa, Dinar
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Journal : Sistemasi: Jurnal Sistem Informasi

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K-Means and Fuzzy C-Means Cluster Food Nutrients for Innovative Diabetes Risk Assessment darmayanti, irma; Mustofa, Dinar; Hidayati, Nurul; Saputri, Inka
Sistemasi: Jurnal Sistem Informasi Vol 13, No 5 (2024): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v13i5.4552

Abstract

Packaged food and beverages often pose a risk of increasing diabetes when consumed regularly. This study aims to classify these products based on their nutritional content listed on the labels, with a focus on identifying diabetes risk. The methods employed include K-Means and Fuzzy C-Means, K-Means is used to determine initial center of cluster, while Fuzzy C-Means enhances the clustering by assigning probabilistic memberships to each data point. These methods are applied to products sold in stores in Banyumas Regency, Central Java, Indonesia. This research is the first to combine these two methods in the context of product clustering based on nutritional labels. The results indicate that packaged food and beverage products can be classified into high-risk and low-risk clusters for diabetes. Consequently, this study provides important guidance for consumers in choosing healthier.
Co-Authors Adam Prayogo Kuncoro Adhimah, Laily Farkhah Afrig Aminuddin Agus Pramono Al Azhar, Nadilla Albana, Ilham Amin, M. Syaiful Apitiadi, Satyo Dwi Dhanar Intan Surya Saputra Dwi Krisbiantoro, Dwi Hellik Hermawan Innolda, Dola Irma Darmayanti Khaerullah, Syifana Muflih Kristiaji, Fandi Kusuma, Velizha S Kusuma, Velizha Sandy Mahendra, Duta Aditya Muntahar, Adnan Aditya Nandang Hermanto Nurhafiyah, Isti Nurul Hidayati Pandega, Dimas Marsus Prayoga, Agung Ramadhan, Muhammad Bintang Sadewo, Rizki Saputri, Inka Tarwoto, Tarwoto Wirasto, Anggit Yusmedi Nurfaizal