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All Journal Jurnal Nasional Komputasi dan Teknologi Informasi Journal of Innovation Information Technology and Application (JINITA)
Benny Ginting
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Implementasi Metode K-Means Clustering Dalam Pengelompokan Bibit Tanaman Kopi Arabika Benny Ginting; Fristi Riandari
Journal of Innovation Information Technology and Application (JINITA) Vol 2 No 2 (2020): JINITA, December 2020
Publisher : Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (682.187 KB) | DOI: 10.35970/jinita.v2i2.394

Abstract

The emergence of various information on good coffee seeds to be planted has prompted the Agriculture and Plantation Service to group the seeds to be recommended in coffee planting centers in the working area of Sarimunthe Village, Kec. Munte Karo District. Data mining is used to extract valuable information from a dataset and then present it in a format that is easily understood by humans with the aim of making a decision. In this study, data processing for Arabica Coffee seedlings consisted of 30 items, in the Karo Regency Agriculture sector, in preparing the seeds to be distributed to the public, the assessment was divided into 3 phases, namely coffee seeds that did not produce (Phase 0-1 Year), immature (Phase 1-2 years) and produce (Phase 2 years and above). The final result of the grouping of Arabica coffee seedlings is that there are 10 recommended items suitable for planting
Implementasi Metode K-Means Clustering Dalam Pengelompokan Bibit Tanaman Kopi Arabika Benny Ginting; Fristi Riandari
Jurnal Nasional Komputasi dan Teknologi Informasi (JNKTI) Vol 3, No 2 (2020): OKTOBER 2020
Publisher : Program Studi Teknik Informatika, Fakultas Teknik. Universitas Serambi Mekkah

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (469.603 KB) | DOI: 10.32672/jnkti.v3i2.2381

Abstract

The diversity of coffee seed material which in the end makes it difficult for the Department of Agriculture and Plantation in classifying recommended seeds to be distributed and planted in coffee planting centers in their working areas, especially in Sarimunthe Village, Kec. Munte Karo District. Data mining is used to extract valuable information from a dataset and then present it in a format that is easy for humans to understand in order to make a decision. In this study, data processing of Arabica coffee seeds consisting of 30 items, in the Karo District Agriculture sector, in preparing the seeds to be distributed to the public, the assessment is divided into 3 phases, namely coffee seeds that do not produce (Phase 0-1 Year), immature (Phase 0-1 Year). Phase 1-2 Years) and produce (Phase 2 Years and above). The results of the calculation of the K-Means algorithm which have been grouped into clusters, it can be concluded that the recommended coffee seeds (C1) consist of 10 items, the coffee seeds that are not recommended (C2) consist of 7 types of coffee seeds and unfit coffee seeds. (C3) consists of 13 types of coffee seeds. .
Implementasi Metode K-Means Clustering Dalam Pengelompokan Bibit Tanaman Kopi Arabika Benny Ginting; Fristi Riandari
Jurnal Nasional Komputasi dan Teknologi Informasi (JNKTI) Vol 3, No 2 (2020): OKTOBER 2020
Publisher : Program Studi Teknik Komputer, Fakultas Teknik. Universitas Serambi Mekkah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32672/jnkti.v3i2.2381

Abstract

The diversity of coffee seed material which in the end makes it difficult for the Department of Agriculture and Plantation in classifying recommended seeds to be distributed and planted in coffee planting centers in their working areas, especially in Sarimunthe Village, Kec. Munte Karo District. Data mining is used to extract valuable information from a dataset and then present it in a format that is easy for humans to understand in order to make a decision. In this study, data processing of Arabica coffee seeds consisting of 30 items, in the Karo District Agriculture sector, in preparing the seeds to be distributed to the public, the assessment is divided into 3 phases, namely coffee seeds that do not produce (Phase 0-1 Year), immature (Phase 0-1 Year). Phase 1-2 Years) and produce (Phase 2 Years and above). The results of the calculation of the K-Means algorithm which have been grouped into clusters, it can be concluded that the recommended coffee seeds (C1) consist of 10 items, the coffee seeds that are not recommended (C2) consist of 7 types of coffee seeds and unfit coffee seeds. (C3) consists of 13 types of coffee seeds. .
Co-Authors Fristi Riandari