K-Means Cluster with Calinski Harabasz Index Evaluation to Map Forest Degradation and Deforestation Areas
DOI:
https://doi.org/10.25077/jmua.15.2.237-248.2026Keywords:
Clustering, Ecology, Sustainability, CHI, deforestationAbstract
Although Indonesia is home to a rich biodiversity, the country is threatened
by forest degradation and deforestation, particularly in West Kalimantan. As a
significant contributor to the agricultural sector’s gross domestic product (PDRB), the Sanggau Regency is vital for preserving the environment and promoting sustainable development. This research uses the K-Means Cluster to categorize regions in Sanggau that can potentially experience forest degradation. Then, the Calinski Harabasz Index will be used to determine which clusters are the most effective. Two thousand twentythree, the research findings revealed five ideal clusters, each with a Calinski Harabasz Index value of 3.87. The first cluster consists of one sub-district, the second cluster consists of three sub-districts, the third cluster consists of two sub-districts, the fourth cluster consists of five sub-districts, and the fifth cluster consists of four sub-districts, which are all included in the distribution of clusters. A map illustrating the degree of urgency associated with forest degradation is produced as a result of this study. The map serves as a strategic reference for the government of Sanggau in its efforts to reduce the
forest’s degradation and develop areas per the peculiarities of each sub-districts.
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References
Ministry of Enviroment and Forestry, 2023, Deforestasi Indonesia Tahun 2021-2022, Directorate of Forest Resource Inventory and Monitoring, Directorate General of Forestry Planning and Environmental Management, Jakarta.
Ministry of Enviroment and Forestry, 2023, Neraca Sumber Daya Hutan Tahun 2023, Directorate of Forest Resource Inventory and Monitoring, Directorate General of Forestry Planning and Environmental Management, Jakarta.
Badan Pusat Statistik Provinsi Kalimantan Barat, 2024, Provinsi Kalimantan Barat dalam Angka 2024 [Kalimantan Barat Province in Figures 2024], Vol. 41, Badan Pusat Statistik Kalimantan Barat.
T. I. Fauzi and F. M. Hazz, 2020, â€Optimalisasi Data Satelit Penginderaan Jauh untuk Perhitungan Neraca Sumber Daya Hutan Kota Bukit Tinggi, †JURNAL SWARNABHUMI: Jurnal Geografi dan Pembelajaran Geografi, vol. 5, no. 2, pp. 67–75.
N. Jainuddin, 2023, â€Dampak Deforestasi Terhadap Keanekaragaman Hayati dan Ekosistem,†HUMANITIS: Jurnal Homaniora, Sosial dan Bisnis, vol. 1, no. 2, pp. 131–140.
F. Musharyadi and M. Kom, 2017, â€Tingkat Pemahaman Mahasiswa Terhadap Norma-Norma Agama Islam Menggunakan Algoritme K-Means Clustering,†Menara Ilmu: Jurnal Penelitian dan Kajian Ilmiah, vol. 11, no. 78, pp. 48–54.
S. P. Lima and M. D. Cruz, 2020, â€A Genetic Algorithm Using Calinski Harabasz Index for Automatic Clustering Problem,†Revista Brasileira de Computa¸cËœao Aplicada, vol. 12, no. 3, pp. 97–106.
N. Syahfitri, E. Budianta, A. Nazir, and I. Afrianty, 2023, â€Pengelompokan Produk Berdasarkan Data Persediaan Barang Mengunakan Metode Elbow dan K-Medoid,†KLIK: Kajian Ilmiah Informatika dan Komputer, vol. 4, no. 3, pp. 1668–1675.
D. R. Ningrat, I. M. Di Asih, and T.Wuryandari, 2016, â€Analisis Cluster dengan Algoritma K-Means dan Fuzzy C-Means Clustering untuk Pengelompokan Data Obligasi Korporasi,†Jurnal Gaussian, vol. 5, no. 4, pp. 641–650.
I. G. B. R. Utama, 2016, Analisis Factor Explomatory, ResearchGate. [Online]. Address: https://doi.org/10.20527/Klik.V5i2.157 [access: 10 September
.
J. Nugraha, 2019, â€Penerapan Metode Regresi Ridge dalam Mengatasi Masalah Multikolinearitas Pada Kasus Index Pembangunan Manusia di Indonesia Tahun 2017,†Jurnal Prosiding Sendika, vol. 5, no. 2, pp. 239–248.
N. A. A. Lestari, M. N. Hayati, and F. D. T. Amijaya, 2021, â€Analisis Cluster Pada Data Kategorik dan Numerik dengan Pendekatan Cluster Ensemble,†EKSPONENSIAL, vol. 11, no. 2, pp. 117–126.
S. Saniah and E. V. Haryanto, 2023, â€Rancang Bangunan Aplikasi Pencarian Lokasi Vaksin Pada Pukesmas di Kota Medan Menggunakan Metode Euclidean Distance Berbasis Android,†Jurnal Ilmiah Sistem Informasi dan Ilmu Komputer, vol. 3, no. 1, pp. 01–11.
R. A. Shafira, Y. Yahfizam, and A. M. Harahap, 2023, â€Menentukan Jarak Terpendek Dalam Pengiriman Barang dengan Perbandingan Euclidean Distance dan Manhattan Distance,†Journal of Science and Research, vol. 6, no. 3, pp. 678–685.
R. N. Puspita, 2021, â€Analisis K-Means Clusters Pada Kabupaten/Kota di Provinsi Banten Berdasarkan Indikator Indeks Pembangunan Manusia,†Jurnal Lebesgue: Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika, vol. 2, no. 3, pp. 267–281.
H. Hidayatullah, S. Martha, and S. Aprizkiyandari, 2022, â€Analisis K-Means Menggunakan Metode Dunn Index dalam Menentukan Jumlah Cluster Optimal (Studi Kasus: Indikator Pendidikan SMA di Indonesia Tahun 2022),†Bimaster: Buletin Ilmiah Matematika, Statistika dan Terapannya, vol. 13, no. 3, pp. 303–310.
S. K. Mann and S. Chawla, 2023, â€A proposed hybrid clustering algorithm using K-Means and BIRCH for cluster based cab recommender system (CBCRS),†International Journal of Information Technology, vol. 15, no. 1, pp. 219–227.
M. N. Zhafar, K. Usman, and F. Akhyar, 2023, †Penerapan Metode Clustering dengan Algoritma K-Means untuk Analisis Persebaran Varian Covid-19 (Studi Kasus Kelurahan Antapani Kidul),†eProceedings of Enegineering, vol. 10, no. 5, pp. 4257–4264.
X. Wang and Y. Xu, 2019, â€An improved index for clustering validation based on Silhouette index and Calinski Harabasz index,†in IOP Conference Series: Materials Science and Engineering, vol.569, no. 5, p. 052024, IOP Publishing.
d. R. S. Saputro, â€Algoritme Partitioning Around Medoid (Pam) dengan Calinski Harabasz Index untuk Clustering Data Outlier,†UNEJ e-Proceeding, pp. 22–29.
R. F. Silamon, M. H. Idris, and S. Anggara, 2015, â€Analisis Degradasi Lahan dan Evaluasi Kesesuaian Lahan Hutan Tanaman Industri di Desa Marga Karya Resort Semamung, Kphp Batulanteh,†Jurnal Sains Teknologi & Lingkungan, vol. 1, no. 2, pp. 9–15.
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