IMPLEMENTATION OF DATA MINING TO PREDICT THE VALUE OF INDONESIAN OIL AND NON-OIL AND GAS IMPORT EXPORTS USING THE LINEAR REGRESSION METHOD
Main Article Content
Abstract
Indonesia's export-import activities in recent years, the value of Indonesia's exports and imports has decreased due to global conditions. The problems that occur are the uncertainty and complexity in estimating the value of international trade in the oil and gas and non-oil and gas sectors, dependence on just one or a few markets, and the problem of unfair competition, unfair competition between business actors can reduce export-import prices. The value of oil and gas and non-oil and gas exports and imports is influenced by several external factors that are difficult to predict, such as fluctuations in oil and gas prices, changes in trade policies, and global economic factors. The prediction results are obtained every month from the export value data using the rapid miner application. From the export data, the value of non-oil and gas exports obtains a very high value compared to the export data of oil and gas values. Then the results from rapid miner using the linear regression algorithm are obtained. The predicted import value of oil and gas and non-oil and gas value data in June is 209,162,268, and the predicted export value of oil and gas and non-oil and gas value data in June is 349,285,781 and non-oil and gas which more are predicted to have the highest value compared to the value of oil and gas in each month.
Article Details
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Authors who publish their manuscripts through the Journal of Information Systems and Computer Science agree to the following:
- Copyright to the manuscripts of scientific papers in this Journal is held by the author.
- The author surrenders the rights when first publishing the manuscript of his scientific work and simultaneously the author grants permission / license by referring to the Creative Commons Attribution-ShareAlike 4.0 International License to other parties to distribute his scientific work while still giving credit to the author and the Journal of Information Systems and Computer Science as the first publication medium for the work.
- Matters relating to the non-exclusivity of the distribution of the Journal that publishes the author's scientific work can be agreed separately (for example: requests to place the work in the library of an institution or publish it as a book) with the author as one of the parties to the agreement and with credit to sJournal of Information Systems and Computer Science as the first publication medium for the work in question.
- Authors can and are expected to publish their work online (e.g. in a Repository or on their Organization's/Institution's website) before and during the manuscript submission process, as such efforts can increase citation exchange earlier and with a wider scope.
References
Astuti, I.P. and Ayuningtyas, F.J., 2018. Pengaruh Ekspor Dan Impor Terhadap Pertumbuhan Ekonomi Di Indonesia. Jurnal Ekonomi & Studi Pembangunan, 19(1), pp.1-10.
Fauziah, Elsa Siti, and Abd Kholik Khoerulloh. "Pengaruh ekspor dan impor terhadap pertumbuhan ekonomi dengan kurs sebagai variabel intervening." Khazanah Sosial 2.1 (2020): 15-24.
Kafil, M. (2019). Penerapan Metode K-Nearest Neighbors Untuk Prediksi Penjualan Berbasis Web Pada Boutiq Dealove Bondowoso. JATI (Jurnal Mahasiswa Teknik Informatika), 3(2), 59-66.
Dewi, Sri Puspita, Nurwati Nurwati, and Elly Rahayu. "Penerapan Data Mining Untuk Prediksi Penjualan Produk Terlaris Menggunakan Metode K-Nearest Neighbor." Building of Informatics, Technology and Science (BITS) 3.4 (2022): 639- 648.
Mahena, Y., Rusli, M., & Winarso, E. (2015). Prediksi Harga Emas Dunia Sebagai Pendukung Keputusan Investasi Saham Emas Menggunakan Teknik Data Mining. Kalbiscentia J. Sains dan Teknol, 2(1), 36-51.
Ordila, Rian, et al. "Penerapan Data Mining Untuk Pengelompokan Data Rekam Medis Pasien Berdasarkan Jenis Penyakit Dengan Algoritma Clustering (Studi Kasus: Poli Klinik Pt. Inecda)." Jurnal Ilmu Komputer 9.2 (2020): 148-153.
Arafah, S., & Tanjung, Y. (2019). Analisis Faktor Determinan yang Mempengaruhi pemakaian metode JIT. STUDI KASUS UD. PUSAKA BAKTI). Bisei: JurnalBisnisdanEkonomiIslam, 4(01).
Suryanto, Andik Adi, and Asfan Muqtadir. "Penerapan metode mean absolute error (MEA) dalam algoritma regresi linear untuk prediksi produksi padi." Saintekbu 11.1 (2019): 78-83.
Sarah, Anggi Mei, Bambang Kurniadi, and Endang Warsini. "Implementasi Metode Regresi Linear Dalam Memprediksi Penyakit Anemia Secara Dini" JURNAL TEKNISI 3.1 (2023): 14-23.
Akhmad, E. P. A. (2020). Data Mining Menggunakan Regresi Linear untuk Prediksi Harga Saham Perusahaan Pelayaran. Jurnal Aplikasi Pelayaran dan Kepelabuhanan, 10(2), 120-131.
Arhami, M., Kom, M., & Muhammad Nasir, S. T. (2020). Data Mining-Algoritma dan Implementasi. Penerbit Andi