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All Journal Jurnal Sains Matematika dan Statistika BAREKENG: Jurnal Ilmu Matematika dan Terapan
Pratiwi, Rosidun Nindyo
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Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Energy Engineering Mathematics Mechanical Engineering Physics Transportation

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Analisis Multidimensional Scaling Faktor-Faktor Yang Mempengaruhi Indeks Pembangunan Manusia (IPM) Di Jawa Timur Tahun 2022 Pratiwi, Rosidun Nindyo; Wijayawati, Evi; Uljanah, Lulu; Faizah, Atikah; Amelia, Dita
Jurnal Sains Matematika dan Statistika Vol 11, No 1 (2025): JSMS Januari 2025
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/jsms.v11i1.28041

Abstract

Peningkatan mutu sumber daya manusia merupakan salah satu indikator pengukur tingkat keberhasilan pertumbuhan ekonomi, dan rencana pembangunan saat ini selalu menitikberatkan pada perkembangan manusia. Kini, pencapaian kualitas manusia seringkali menjadi tolok ukur keberhasilan pembangunan. Indeks Pembangunan Manusia menjadi metrik yang digunakan untuk mengevaluasi tingkat perkembangan manusia dalam suatu negara. Tiga dimensi utama pembangunan manusia yang tercakup dalam IPM melibatkan angka harapan hidu, durasi rata-rata pendidikan, serta pengeluaran per kapita. Tujuan dari penelitian ini adalah untuk menganalisis faktor-faktor yang berdampak pada IPM (Indeks Pembangunan Manusia) di wilayah Jawa Timur. Dari hasil analisis menggunakan metode Multidimensional Scaling, tampak bagaimana kabupaten/kota di Jawa Timur terkelompok berdasarkan indikator IPM. Dari analisis tersebut, teridentifikasi empat kelompok dengan karakteristik yang serupa di dalamnya, tetapi berbeda dengan kelompok lainnya. Hasil pengelompokannya sangat cocok ditunjukan dari nilai stress sebesar 1,804% dan mencapai ???? 2 99,962%.
MODELING THE INFLUENCE OF CRUDE OIL PRODUCTION AGAINST INDONESIAN SOLAR WHOLESALE PRICE INDEX WITH LEAST SQUARE SPLINE ESTIMATOR APPROACH Pratiwi, Rosidun Nindyo; Fauziah, Nathania; Syahputra, Bimo Okta; Firmanda, Ahmad Wahyu; Amelia, Dita
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 19 No 2 (2025): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol19iss2pp805-818

Abstract

Solar plays a crucial role in supporting energy sector activities in Indonesia. The fluctuating price of solar is influenced by crude oil production, as crude oil is the main raw material in solar production. The Russia-Ukraine war, which reached its peak in March 2020, also impacted global oil production, given that Russia is one of the largest oil producers and exporters in the world. This study aims to model the effect of crude oil production on the Solar Wholesale Price Index (SWPI) in Indonesia after the Russia-Ukraine war using the Least Squares Spline estimator approach. This approach was chosen because the relationship between the variables is complex and nonlinear, making linear models unsuitable. The results show that the best model is a nonparametric model with three knot points at a polynomial degree of one, which explains 90.26% of the variability in crude oil production relative to the SWPI. The optimal knot points were selected using the Generalized Cross Validation (GCV) method, resulting in a minimum GCV value of 320.9889. Crude oil production was found to have a significant effect on the SWPI and meets the classical assumption tests. However, this study has limitations, as it only considers the effect of crude oil production without including other external factors, such as energy policies or geopolitical influences. Additionally, the model still has limitations in capturing more complex relationship patterns. This study offers an original contribution through the application of the Least Squares Spline estimator approach, which has not been widely used before in analyzing the relationship between crude oil production and SWPI in Indonesia. For future research, it is recommended that the model be expanded by considering more knot points and higher polynomial degrees to capture more complex relationship patterns between these variables.
Co-Authors Dita Amelia, Dita Faizah, Atikah Fauziah, Nathania Firmanda, Ahmad Wahyu Syahputra, Bimo Okta Uljanah, Lulu Wijayawati, Evi