Skripsi

PENERAPAN ANALISIS KLASTER K-MEDOIDS DALAM PENGELOMPOKKAN SAYURAN BERDASARKAN ‎VARIABEL KANDUNGAN GIZI

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The high percentage of insufficient vegetable consumption in Indonesia remains a ‎concern, as it is still below the recommended intake. Identifying alternative vegetables ‎with similar nutritional content can facilitate the clustering process and assist in ‎selecting substitute vegetables with comparable nutrients. Therefore, clustering ‎analysis is required to identify groups of vegetables with similar nutritional ‎characteristics. This study aims to cluster 34 fresh vegetables based on seven variables: ‎energy, fat, carbohydrates, protein, dietary fiber, calcium, and potassium. The K-‎Medoids method was applied with the number of clusters ranging from k = 2 to k = 5. ‎Evaluation of the optimal number of clusters using the Silhouette Coefficient and ‎Elbow methods indicated that the best number of clusters was k = 3. Cluster 1 ‎consisted of 12 vegetables (Asparagus, Eggplant, Angled Luffa, Bitter Melon, ‎Spinach, Radish, Lettuce, Cucumber, Chinese Cabbage, Celery, Winter Melon, and ‎Tomato), representing vegetables with low average nutritional content across all ‎variables. Cluster 2 consisted of 17 vegetables, (Cauliflower, Cabbage, Bamboo ‎Shoots, Papaya Flowers, Bean Sprouts, Carrots, Chayote, Ferns, Potatoes, Water ‎Spinach, Green Beans, Long Beans, Winged Beans, Red Spinach, Watercress, and ‎Beetroot), characterized by high dietary fiber content. Cluster 3 consisted of five ‎vegetables (Melinjo, Katuk Leaves, Cassava Leaves, Moringa Leaves, and Parsley), ‎which were dominated by higher levels of energy, fat, carbohydrates, protein, calcium, ‎and potassium. The clustering results indicate that vegetable nutritional content varies ‎and can be utilized to determine alternative vegetable substitutes based on nutritional ‎similarity, thereby supporting efforts to increase vegetable consumption and achieve ‎balanced nutrition.‎ Keywords: Nutritional Content, K-Medoids, Elbow Method, Silhouette Coeffiecient ‎Method, Vegetables.‎

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Detail Information

Series Title

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Call Number

T1914042025

Publisher

Indralaya : Prodi Ilmu Matematika, Fakultas Matematika Dan Ilmu Pengetahuan Alam Universitas Sriwijaya., 2025

Collation

xiv, 58 hlm.; ilus.; 29 cm

Language

Indonesia

ISBN/ISSN

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Classification

006.312 07

Content Type

Text

Media Type

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Carrier Type

-

Edition

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Subject(s)

Data mining
Prodi Ilmu Matematika

Specific Detail Info

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Statement of Responsibility

TUTI

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