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Articles
Articles
Studi Independent Prediksi Harga Komoditi Petani Bawang Merah Menggunakan Amazon Forecast di PT. Techno International Mandira
Desy Arisandy, Tri Apriani
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- Desy Arisandy: Universitas Bina Darma, Indonesia
- Tri Apriani: Universitas Bina Darma, Indonesia
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Abstract
The Certified Independent Study, under the Kampus Merdeka initiative and supported by the Ministry of Education, Culture, Research, and Technology (Kemendikbud Ristekdikti), fosters collaborative partnerships with key industry players. A prime example is PT. Techno International Mandira's contribution, which involves employing Amazon Forecast within Amazon Web Services for the predictive analysis of shallot farmers' commodity prices. This study centers on developing web-based predictive models to accurately forecast shallot market values. Utilizing Amazon Forecast's fully managed services, which integrate advanced machine learning algorithms, this project aims to provide vital insights into commodity pricing trends, thereby supporting shallot farmers in strategic decision-making. The methodology encompasses the application of Amazon Forecast for efficient and data-driven price prediction, demonstrating the practical utility of machine learning in agricultural economics.
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Author Biographies
Desy Arisandy
Universitas Bina Darma
Program Studi Psikologi, Fakultas Sosial Humaniora, Universitas Bina Darma, Kota Palembang, Provinsi Sumatera Selatan, Indonesia
Tri Apriani
Universitas Bina Darma
Program Studi Psikologi, Fakultas Sosial Humaniora, Universitas Bina Darma, Kota Palembang, Provinsi Sumatera Selatan, Indonesia
Article Identifiers
- Article Title: Studi Independent Prediksi Harga Komoditi Petani Bawang Merah Menggunakan Amazon Forecast di PT. Techno International Mandira
- DOI: 10.59431/ajad.v3i3.238
- Publication Date: 2023-12-30
- Journal: AJAD : Jurnal Pengabdian kepada Masyarakat
- Volume: 3
- Issue: 3
- Pages: 431–436
References
-
Herlina, L., REFLINUR, R., SOBIR, S., MAHARIJAYA, A., & WIYONO, S. (2019). The genetic diversity and population structure of shallots (Allium cepa var. aggregatum) in Indonesia based on R gene-derived markers. Biodiversitas Journal of Biological Diversity, 20(3), 696-703. DOI: https://doi.org/10.13057/biodiv/d200312.
-
Suryana, A. (2014). Dinamika kebijakan harga gabah dan beras dalam mendukung ketahanan pangan nasional. Pengembangan Inovasi Pertanian, 7(4), 30887. DOI: https://dx.doi.org/10.21082/pip.v7n4.2014.155-168.
-
Fitriana, R., Siregar, H., & Anggraeni, L. (2022). The impact of El Nino and La Nina towards the prices of cabbage and shallot in Indonesia. Jurnal Manajemen & Agribisnis, 19(2), 195-195. DOI: https://doi.org/10.17358/jma.19.2.195.
-
Novaliana, I., & Mahendra, P. T. (2023). Analysis of Price Factors and Business Competition in The Covid-19 Pandemic NN Efforts to Increase Sales Volume. International Journal of Multidisciplinary: Applied Business and Education Research, 4(4), 1376-1382. DOI: https://doi.org/10.11594/ijmaber.04.04.31.
-
Mulatu, E., Ibrahim, O. E., & Bekele, E. (2005). Policy changes to improve vegetable production and seed supply in Hararghe, Eastern Ethiopia. Journal of Vegetable Science, 11(2), 81-106. DOI: https://doi.org/10.1300/J484v11n02_08.
-
Bose, S., Dey, S. K., & Bhattacharjee, S. (2023). Big data, data analytics and artificial intelligence in accounting: An overview. Handbook of Big Data Research Methods.
-
Ma, W., Nowocin, K., Marathe, N., & Chen, G. H. (2019, January). An interpretable produce price forecasting system for small and marginal farmers in india using collaborative filtering and adaptive nearest neighbors. In Proceedings of the Tenth International Conference on Information and Communication Technologies and Development (pp. 1-11). DOI: https://doi.org/10.1145/3287098.3287100.
-
Martin, R. L. (2009). The design of business: Why design thinking is the next competitive advantage. Harvard Business Press.
-
Weinman, J. (2015). Digital disciplines: Attaining market leadership via the cloud, big data, social, mobile, and the Internet of things. John Wiley & Sons.
-
Alabdali, M. A., & Salam, M. A. (2022). The impact of digital transformation on supply chain procurement for creating competitive advantage: An empirical study. Sustainability, 14(19), 12269. DOI: https://doi.org/10.3390/su141912269.
-
Awalia, S., Elpisah, M. D., SE, M., PD, D. S. S., PD, M., Hamid, N. A., & SE, M. (2020). Pengantar Bisnis. Penerbit CV. Pena Persada.
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Article Details
| Volume: | 3 |
| Issue: | 3 |
| Year: | 2023 |
| Published: | 2023-12-30 |
| Pages: | 431–436 |
| Section: | Articles |
Additional Information
How to Cite
Arisandy, D., & Apriani, T. (2023). Studi Independent Prediksi Harga Komoditi Petani Bawang Merah Menggunakan Amazon Forecast di PT. Techno International Mandira. AJAD : Jurnal Pengabdian Kepada Masyarakat, 3(3), 431–436. https://doi.org/10.59431/ajad.v3i3.238
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This work is licensed under a Creative Commons License.
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