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All Journal BAREKENG: Jurnal Ilmu Matematika dan Terapan Journal of Mathematics Education and Science
Ain, Dzuria Hilma Qurotu
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Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Energy Engineering Mathematics Mechanical Engineering Physics Transportation

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PREDICTION OF UNIT VALUE INDEX OF EXPORTS OF SITC 897 JEWELRY AND PRECIOUS GOODS GROUP IN INDONESIA Koesnadi, Grace Lucyana; Pratama, Bagas Shata; Ain, Dzuria Hilma Qurotu; Pusporani, Elly; Mardianto, M. Fariz Fadillah
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 4 (2024): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol18iss4pp2247-2262

Abstract

Export is an international trade activity that plays an important role in the economic progress in Indonesia. One of Indonesia's leading commodities that dominate the export market is jewelry. In export activities, the export unit value index is an important component that serves to describe the development of export commodity prices. This unit value index always changes every time and fluctuates. This research conducts a comparative analysis of the performance of parametric method, non-parametric method, and machine learning, specifically, ARIMA, Fourier series estimator, and Support Vector Regression (SVR). This study aims to evaluate the effectiveness of various methods in improving prediction accuracy for the unit value index of the SITC code 897 in Indonesia. The research data used is secondary data including monthly export unit value index data with SITC code 897 in Indonesia obtained from the Central Bureau of Statistics. The data divided into 90% training data and 10% testing data. The methods used in this analysis are ARIMA, Fourier series estimator, and SVR. The best model obtained from each method is ARIMA (1,1,1) with MAPE of 10.92%, Fourier series estimator with MAPE of 8.47%, and an SVR RBF kernel function with MAPE of 3.73%. The results of this study obtained the best method for predicting the unit value index of SITC code 897 is SVR with an RMSE value of 8.288 and very good prediction accuracy.
Identifikasi Faktor yang Mempengaruhi Kemiskinan di Papua dengan Principal Component Analysis Ain, Dzuria Hilma Qurotu; Kusuma, Shalwa Oktavia; Zahrani, Vista Vanadya; Suryono, Alda Fuadiyah; Mardianto, M. Fariz Fadillah; Amelia, Dita; Ana, Elly
Journal of Mathematics Education and Science Vol. 7 No. 1 (2024): Journal of Mathematics Education and Science
Publisher : Universitas Nahdlatul Ulama Sunan Giri Bojonegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32665/james.v7i1.1336

Abstract

Penelitian ini bertujuan untuk menganalisis faktor-faktor kemiskinan terhadap pengentasan kemiskinan di Provinsi Papua. Metode yang digunakan yaitu Analisis Komponen Utama (AKU). Cakupan data yang digunakan dalam penelitian ini adalah data statistik kesejahteraan rakyat Provinsi Papua pada bulan Maret tahun 2021 yang diperoleh dari Badan Pusat Statistik (BPS). Hasil penelitian ini menunjukkan bahwa faktor-faktor yang mempengaruhi kemiskinan di Kabupaten dan Kota Provinsi Papua dapat dikategorikan menjadi tiga komponen yaitu Komponen 1 : “Pendidikan dan Kependudukan“, Komponen 2 : ”Fasilitas Imunisasi dan Penerangan”, serta Komponen 3 :  “Fasilitas Teknologi dan Kesehatan”. Dengan demikian,  penelitian  ini  bermanfaat  bagi  para  pembuat  kebijakan  baik pemerintah  pusat maupun  daerah  untuk  memperhatikan  faktor-faktor  yang  mempengaruhi terjadinya peningkatan kemiskinan di Provinsi Papua. Kemiskinan merupakan prioritas pada SDGs yang dinyatakan pada poin pertama yaitu no poverty (tanpa kemiskinan).
Co-Authors Dita Amelia, Dita Elly Ana Elly Pusporani Koesnadi, Grace Lucyana Kusuma, Shalwa Oktavia M. Fariz Fadillah Mardianto Pratama, Bagas Shata Suryono, Alda Fuadiyah Zahrani, Vista Vanadya