Clustering Titik Panas Menggunakan Algoritma Agglomerative Hierarchical Clustering (AHC)

نویسندگان

چکیده

Kebakaran hutan di Indonesia setiap tahunnya masih sering terjadi. Dalam menanggulangi kebakaran sendiri, para peneliti belakangan ini semakin fokus untuk melakukan pengembangan sistem yang mampu prediksi hutan. Selain mengenai hutan, antisipasi dapat dilakukan membantu menangani pencegahan salah satunya adalah pengelompokkan terhadap wilayah memiliki potensi kebakaran. Pada penelitian Clusterisasi titik panas (hotspot) membagi berpotensi terbakar. Pengelompokkan berdasarkan cluster rendah, sedang, dan tinggi. menggunakan algoritma Agglomerative Hierarchical Clustering (AHC). Data digunakan pada perhitungan Kalimantan Barat dengan variable longitude, latitude, frp, confidence, curah hujan menentukan clustering Tujuan dalam mengcluster terjadi sehingga peluang segera ditindaklanjuti. Dari hasil pengujian diperoleh pembentukan 2 dimana menunjukkan terbentuk kelas sedang tinggi nilai evaluasi silhouette coefficient 0,771.
 Kata kunci— Clustering, panas,

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Modern hierarchical, agglomerative clustering algorithms

This paper presents algorithms for hierarchical, agglomerative clustering which perform most efficiently in the general-purpose setup that is given in modern standard software. Requirements are: (1) the input data is given by pairwise dissimilarities between data points, but extensions to vector data are also discussed (2) the output is a “stepwise dendrogram”, a data structure which is shared ...

متن کامل

Divisive Hierarchical Clustering with K-means and Agglomerative Hierarchical Clustering

To implement divisive hierarchical clustering algorithm with K-means and to apply Agglomerative Hierarchical Clustering on the resultant data in data mining where efficient and accurate result. In Hierarchical Clustering by finding the initial k centroids in a fixed manner instead of randomly choosing them. In which k centroids are chosen by dividing the one dimensional data of a particular clu...

متن کامل

Clustering Acoustic Segments Using Multi-Stage Agglomerative Hierarchical Clustering

Agglomerative hierarchical clustering becomes infeasible when applied to large datasets due to its O(N2) storage requirements. We present a multi-stage agglomerative hierarchical clustering (MAHC) approach aimed at large datasets of speech segments. The algorithm is based on an iterative divide-and-conquer strategy. The data is first split into independent subsets, each of which is clustered se...

متن کامل

Implementing Agglomerative hierarchical clustering using multiple attribute

Agglomerative hierarchical clustering algorithm used with top down approach. It implement with multiple attributes. In multiple attributes frequency calculation is allocated. Memory requirements are less in this process. Hierarchical clustering produce accurate result than any other algorithm. This is very less time consuming process.

متن کامل

2 Review of Agglomerative Hierarchical Clustering Algorithms

Hierarchical methods are well known clustering technique that can be potentially very useful for various data mining tasks. A hierarchical clustering scheme produces a sequence of clusterings in which each clustering is nested into the next clustering in the sequence. Since hierarchical clustering is a greedy search algorithm based on a local search, the merging decision made early in the agglo...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: Cogito smart journal

سال: 2022

ISSN: ['2541-2221', '2477-8079']

DOI: https://doi.org/10.31154/cogito.v8i2.438.501-513