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Robust Biplot Analysis of Natural Disasters in Indonesia from 2019 To 2021 Hilda Venelia; Khoirin Nisa; Rizki Agung Wibowo; Mona Arif Muda
Jurnal Aplikasi Statistika & Komputasi Statistik Vol 13 No 2 (2021): Journal of Statistical Application and Computational Statistics
Publisher : Pusat Penelitian dan Pengabdian Masyarakat Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/jurnalasks.v13i2.349

Abstract

Indonesia is one of the most natural disaster-prone countries in the world, frequently exposed to a range of hazards. Currently, Indonesia has 34 provinces and natural disasters that occur in each province are different, therefore it is necessary to analyze the mapping of natural disasters that often occur in each province to provide scientific analysis for risk management of the natural disasters. One of the quick steps in describing data that can be used is biplot analysis, as biplot analysis can describe a lot of data then summarized it into the form of a two-dimensional graph. The aim of this research is to map 34 provinces in Indonesia based on the incidence of natural disasters from 2019 to 2021 using robust biplot analysis. Based on the result, robust biplot analysis can explain 87,9% of the information on natural disasters in every province in Indonesia. Lampung, Bengkulu, Bangka Belitung, Special Region of Yogyakarta, North Sulawesi, West Sulawesi, Southeast Sulawesi, Gorontalo, East Nusa Tenggara, Bali, Maluku, West Maluku, Papua, and West Papua are provinces that have similar natural disaster characteristics. Flood, tornado and forest and land fires are natural disasters that often occur in Indonesia. The provinces that have the highest risk of flood, landslide, and tornado were West Java, Central Java, and East Java. Then, the provinces with the highest risk of forest and land fires were Aceh and South Kalimantan.
SIMULASI PEMILIHAN METODE ANALISIS CLUSTER HIRARKI AGGLOMERATIVE TERBAIK ANTARA AVERAGE LINKAGE DAN WARD PADA DATA YANG MENGANDUNG MASALAH MULTIKOLINEARITAS Rizki Agung Wibowo; Khorin Nisa; Ahmad Faisol; Eri Setiawan
Jurnal Siger Matematika Vol 1, No 2 (2020)
Publisher : FMIPA Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (435.947 KB) | DOI: 10.23960/jsm.v1i2.2497

Abstract

Multikolinearitas adalah hubungan linear yang ada di antara variabel independen,  pada analisis klaster efek yang ditimbulkan oleh multikolinearitas berbeda, dikarenakan pada dasarnya multikolinearitas adalah bentuk pembobotan implisit.  Analisis komponen utama dapat digunakan untuk mereduksi jumlah himpunan peubah yang banyak dan saling berkorelasi menjadi peubah-peubah baru yang  tidak berkorelasi dengan mempertahankan sebanyak mungkin keragaman data tersebut, dengan menggunakan hasil analisis komponen utama dilakukan analisis klaster menggunakan metode average linkage dan Ward, yang kemudian akan dipilih metode terbaiknya berdasarkan nilai indeks Dunn dan indeks RS, didapat kesimpulan bahwa metode Ward adalah metode terbaik dibandingkan average linkage yang ditinjau berdasarkan indeks RS, sedangkan dengan menggunakan indeks Dunn didapatkan kesimpulan bahwa metode average linkage adalah metode terbaik dibandingkan Ward.