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Penerapan Data Mining untuk Menganalisis Kandungan Gizi Sayuran dan Buah Menggunakan Metode K-Means

Hasna, Hasna (2023) Penerapan Data Mining untuk Menganalisis Kandungan Gizi Sayuran dan Buah Menggunakan Metode K-Means. Undergraduate thesis, Fakultas Teknologi Informasi Universitas Merdeka Malang.

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Abstract

Indonesia is a country where the majority of the population are commodity-oriented farmers. Indonesia is also known as a country that produces many garden plants, especially vegetables and fruits. Vegetables and fruits are important components in the body, because they contain vitamins, essential trace elements, fiber, vegetable protein and biofunctional components (FAO, 2010). According to I Dewa Nyoman (2002: 17-18) nutrition is the process by which organisms use food that is consumed normally through the processes of digestion, absorption, and transportation. Storage, metabolism and excretion of substances that are not used to maintain life, growth and normal function of organs and produce energy. In general, vegetables and fruits are usually a source of vitamins and minerals. The collected data is entered into Excel and then processed using the K-Means algorithm. When using the K-Means algorithm, a midpoint or centroid value will be formed from the data if the desired grouping is 3, the grouping is divided into three parts, with each nutrient level namely. High, medium and low level. Then the value of the center point or center of gravity also has 3 points. The cluster score is determined by taking the highest (maximum) score for the high cluster (C1), the average score for the medium cluster (C2), and the lowest (minimum) score for the low cluster.
The results obtained from the data analysis formed 3 clusters of nutritional content from vegetables and fruit. One of the clusters that have similarities is that Moringa and cucumber leaves have almost the same water and phosphorus content. So people who want to consume vegetables and fruit daily but can't find vegetables and fruits There are still other vegetables and fruits that have the same nutritional content and can replace them.

Item Type: Thesis (Undergraduate)
Additional Information: Hasna NIM : 180830000185
Uncontrolled Keywords: Clustering, K-Means, Data Mining, Vegetable and Fruit Nutrition
Subjects: Q Science > QA Mathematics > QA76 Computer software
Divisions: Fakultas Teknologi Informasi > S1 Sistem Informasi
Depositing User: Gendhis Dwi Aprilia
Date Deposited: 10 Mar 2025 03:38
Last Modified: 10 Mar 2025 03:38
URI: https://eprints.unmer.ac.id/id/eprint/4534

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