CD Skripsi

Penerapan K-Means Clustering Untuk Pengelompokan Hasil Sortasi Tandan Buah Segar (Tbs) Dengan Kondisi Cuaca Pada Pks Tandun Ptpn Iv Regional III

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PT. Perkebunan Nusantara (PTPN) IV Regional III is an agribusiness company focused on palm oil processing in Riau Province. Each Palm Oil Mill (POM) implements a Fresh Fruit Bunch (FFB) sorting process to maintain the quality of incoming FFB, including PKS Tandun (TAN). Weather factors (temperature, rainfall, and humidity) influence FFB ripeness, necessitating data clustering analysis to understand the relationship between weather conditions and FFB quality. This research applies the K-Means clustering algorithm using php-ml on Laravel with a dataset of 1.011 data stored in MySQL. This dataset underwent pre-processing (cleaning, integration, and selection) and successfully formed three clusters after modeling with K-Means. Cluster 0 consists of 322 data with low FFB sorting percentage and high rainfall. Cluster 1 consists of 451 data with the lowest rainfall and stable FFB sorting percentage. Cluster 2 consists of 56 data with high rainfall and FFB sorting percentage. The model evaluation with K=3 showed good performance with a silhouette score of 0,54 and a Calinski-Harabasz index of 1.019,34.

Keywords: Data Mining, K-Means Clustering, PTPN IV Regional III, TBS Sorting, Weather.

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Ketersediaan

Informasi Detail

Judul Seri

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No. Panggil

2103112017

Penerbit

Pekanbaru : Universitas Riau FMIPA Sistem Informasi., 2025

Deskripsi Fisik

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Bahasa

Indonesia

ISBN/ISSN

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Klasifikasi

2103112017

Tipe Isi

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Tipe Media

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Tipe Pembawa

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Edisi

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Subjek

SISTEM INFORMASI

Info Detail Spesifik

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Pernyataan Tanggungjawab

Mutia

Versi lain/terkait

Lampiran Berkas

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