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All Journal MATHunesa: Jurnal Ilmiah Matematika Kohesi: Jurnal Sains dan Teknologi
Muhammad Khoirul Alim
Universitas Negeri Surabaya
Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Education Energy Engineering Mathematics Other

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ANALISIS KORELASI ANTARA FAKTOR EKONOMI DAN DISTRIBUSI PENDUDUK DI JAWA TIMUR TAHUN 2020 MENGGUNAKAN METODE KORELASI PEARSON Muhammad Khoirul Alim; Dede Brahma Arianto
Kohesi: Jurnal Sains dan Teknologi Vol. 1 No. 5 (2023): Kohesi: Jurnal Sains dan Teknologi
Publisher : CV SWA Anugerah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.3785/kjst.v1i5.166

Abstract

Penelitian ini bertujuan untuk menganalisis adanya korelasi secara signifikan antara faktor ekonomi dan distribusi penduduk di Jawa Timur tahun 2020. Variabel yang digunakan adalah tingkat distribusi penduduk di lima kota besar Jawa Timur tahun 2020 yang mencangkup Kota Surabaya, Kota Sidoarjo, Kota Malang, Kota Gresik, Kota Malang sebagai variabel dependent (X). Variabel independent (Y) yaitu tingkat Produk Domestik Regional Bruto (PDRB), Tingkat Pengangguran Terbuka (TPT), Indeks Pembangunan Manusia (IPM), tingkat Inflasi. Metode yang digunakan adalah Metode Analisis Sekunder atau Studi Literatur. Penelitian ini menggunakan data sekunder dari Badan Pusat Statistik (BPS) dan diolah dengan menggunakan metode korelasi pearson. Studi ini menunjukkan bahwa hanya tingkat Indeks Pembangunan Manusia (IPM) yang berhubungan secara signifikan searah dengan tingkat distribusi penduduk yang menunjukkan nilai p-value = 5.208e-05, sedangkan PDRB, TPT, Inflasi tidak berhubungan secara signifikan dengan distribusi penduduk dan arah korelasi yang berbeda-beda yaitu menghasilkan nilai p-value lebih dari 0,05. Studi ini dapat memberikan landasan kuat sebagai pengambilan keputusan strategis terkait pertumbuhan ekonomi daerah terutama di Jawa Timur.
Prediksi Kekeringan Ekstrem di Jawa Timur Menggunakan Generalized Pareto Distribution (GPD) Muhammad Khoirul Alim; Dimas Avian Maulana
MATHunesa: Jurnal Ilmiah Matematika Vol. 13 No. 2 (2025)
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/mathunesa.v13n2.p597-606

Abstract

Extreme droughtin East Java is an event that has a significan timpact on the agricultural sector, water availability, and socio-economic conditions of the community. This study aims to analyze the characteristics of extreme drought using the Standardized Precipitation Index (SPI) and predict extreme rainfall events using the Generali zed Pareto Distribution (GPD) based on the return level. The data used is monthly rainfall data for the period 1990-2024 from BMKG observation stations in Malang Regency, East Java. SPI analysis was conducted to identify drought patterns based on rainfall in the dry season period (April-September). The results of the analysis show that extreme drought occurs more frequently at the end of the dry season (July-September) than at the beginning of the dry season (April-June), with some years experiencing SPI below-1.5, indicating extreme drought conditions. Extreme data were identified using the Peaks Over Threshold (POT) method with a threshold of 2.00 mm. The parameters of the GPD distribution were estima ted using Maximum Likelihood Estimation (MLE), with the results of shape ξ = 1.297 and scale σ = 2.983. The Kolmogorov-Smirnov test showed that the extreme data fit the GPD distribution (p-value = 0.301). The prediction results show that in the next 1-10 years, extreme rainfall tends to increase as the time period increases, so the risk of extreme drought decreases. Prediction accuracy may decrease in longer periods due to uncertainty in the estimation of the return level value. The results of this study provide insight into the pattern of extreme drought in East Java and the potential for future occurrence. The findings can serve as a reference in drought mitigation planning and water resources managementtoreduceits negative impacts. Keywords: Extreme drought, Standardized Precipitation Index (SPI), Generalized Pareto Distribution (GPD)
Co-Authors Dimas Avian Maulana