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All Journal JURNAL REKAYASA TEKNOLOGI INFORMASI Jurnal Teknologi Elekterika Seminar Nasional Pengabdian Kepada Masyarakat IPTEK: Jurnal Hasil Pengabdian kepada Masyarakat Seminar Nasional Hasil Penelitian LP2M UNM Information Technology Education Journal Journal of Security, Computer, Information, Embedded, Network and Intelligence System Jurnal MediaTIK Repeater: Publikasi Teknik Informatika dan Jaringan Journal of Computers, Informatics, and Vocational Education Journal of Digital Technology and Computer Science
Abd. Rahman Patta
Universitas Negeri Makassar
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Journal : journal of digital technology and computer science

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K-Means Clustering of Salty Snacks Based on Nutritional Information for Calorie-Deficit Diet Support Athiyyah Anandira; Mustari S Lamada; Muhammad Ayat Hidayat; Dewi Fatmarani Surianto; Abdul Rahman Patta
Journal of Digital Technology and Computer Science Vol. 3 No. 3 (2026): August 2026
Publisher : Academic Bright Collaboration

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66053/dtcs.v3i3.1389

Abstract

Purpose – This study aimed to cluster salty snack products based on their nutritional information using the K-Means algorithm and to identify the most suitable cluster for supporting a calorie-deficit diet, addressing high obesity rates in Indonesia and consumer difficulties with nutrition labels. Methods – This study used a quantitative data mining approach, 620 products were collected from FatSecret Indonesia via purposive sampling across variables of calories, fat, protein, fiber, sugar, and sodium. The data were processed through cleaning, missing-value checking, transformation, and Z-Score normalization, followed by K-Means clustering, Elbow method optimization, and evaluation via Silhouette Coefficient and Davies-Bouldin Index (DBI). Findings – The analysis identified three optimal clusters (k=3). The overall Silhouette Coefficient was 0.431 and DBI was 1.1534. C1 (461 products) featured lower calories, fat, sugar, and sodium, making it the most suitable cluster among the identified clusters. However, only 185 of the 461 products in C1 met the defined product-level safety criteria. C2 (96 products) was high in calories and fat, and C3 (63 products) had high protein but extreme sodium levels. Research implications – The study's validity is constrained by its reliance on secondary online data without direct laboratory verification. Furthermore, the use of mean imputation for the missing fiber data may have attenuated inter-cluster variance and reduced the discriminatory role of fiber. Originality – This research provides a novel contribution in grouping salty snack products by combining six main nutritional variables along with comprehensive model performance evaluation. C1 was identified as the most suitable cluster for supporting a calorie-deficit diet.
Co-Authors Abdul Wahid Andi Baso Kaswar Andi Baso Kaswar Andi R Andi R, Athiyyah Anandira B, Hendriyati Eko Baharuddin, Andi Rakhmat Dewi Fatmarani Surianto Elma Nurjannah Fathahillah Hasrul Hasrul Hendriyati Eko B Irmawati Iskandar Irwansyah Suwahyu Iwan Suhardi Jumadi Mabe Parenreng Kurnia Prima Putra Mappeasse, Muhammad Yusuf Muh. Rahmat Wahyudi JY Muhammad Alwi Muhammad Ayat Hidayat Muhammad Fadlu Rahman Muhammad Fatwa Ma'arij Fatwa Muhammad Ilham Muhammad Yahya Muliadi Muliadi Muliaty Yantahin Rafika Hutami Putri Satria Gunawan Zain Suharto Suharto Suhartono, Suhartono Syamsinar Veronika Asri Tandirerung