Prediction of Rice Production to Support Food Security in Bogor Regency using Linear Regression and Support Vector Machine (SVM)
A prediction is an estimation of something that has not yet occurred. Its purpose is to minimize uncertainty and reduce errors in planning. Bogor Regency, with the largest population in West Java, requires a substantial amount of food. Rice production must meet the consumption needs of the populatio...
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| Format: | Article |
| Language: | Indonesian |
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Fakultas Teknik Universitas Islam Lamongan
2024-04-01
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| Series: | Jurnal Teknika |
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| Online Access: | https://jurnalteknik.unisla.ac.id/index.php/teknika/article/view/1192 |
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| author | Ani Apriani Nono Carsono Mas Dadang Enjat Munajat |
| author_facet | Ani Apriani Nono Carsono Mas Dadang Enjat Munajat |
| author_sort | Ani Apriani |
| collection | DOAJ |
| description | A prediction is an estimation of something that has not yet occurred. Its purpose is to minimize uncertainty and reduce errors in planning. Bogor Regency, with the largest population in West Java, requires a substantial amount of food. Rice production must meet the consumption needs of the population. To anticipate potential rice shortages, effective planning, and reduced dependence on rice imports, research is needed to predict rice production. This study aims to predict rice production using Linear Regression and Support Vector Machine (SVM) algorithms. Secondary data from the Department of Food Crops and Horticulture, and the Central Statistics Agency (BPS) of Bogor Regency were utilized. Results show that the Linear Regression method outperformed SVM, with MSE 236202.323, RMSE 486.007, MAE 388.712, and R2 1.000. In contrast, SVM yielded MSE 1461472466.751, RMSE 38229.2.10, MAE 303333.535, and R2 -0.065. In conclusion, the prediction using Linear Regression demonstrated better accuracy than SVM.
Keywords: Prediction, Algorithm, SVM. Linear Regression. |
| format | Article |
| id | doaj-art-029ffdae241e4ef88c875573e92bcc63 |
| institution | Kabale University |
| issn | 2085-0859 2620-4770 |
| language | Indonesian |
| publishDate | 2024-04-01 |
| publisher | Fakultas Teknik Universitas Islam Lamongan |
| record_format | Article |
| series | Jurnal Teknika |
| spelling | doaj-art-029ffdae241e4ef88c875573e92bcc632025-01-24T07:36:27ZindFakultas Teknik Universitas Islam LamonganJurnal Teknika2085-08592620-47702024-04-01161131810.30736/jt.v16i1.11921147Prediction of Rice Production to Support Food Security in Bogor Regency using Linear Regression and Support Vector Machine (SVM)Ani Apriani0Nono Carsono1Mas Dadang Enjat Munajat2Program Studi Magister Inovasi Regional, Sekolah Pasca Sarjana, Universitas PadjadjaranProgram Studi Agroteknologi, Fakultas Pertanian, Universitas Padjadjaran Program Studi Magister Inovasi Regional, Sekolah Pasca Sarjana, Universitas PadjadjaranA prediction is an estimation of something that has not yet occurred. Its purpose is to minimize uncertainty and reduce errors in planning. Bogor Regency, with the largest population in West Java, requires a substantial amount of food. Rice production must meet the consumption needs of the population. To anticipate potential rice shortages, effective planning, and reduced dependence on rice imports, research is needed to predict rice production. This study aims to predict rice production using Linear Regression and Support Vector Machine (SVM) algorithms. Secondary data from the Department of Food Crops and Horticulture, and the Central Statistics Agency (BPS) of Bogor Regency were utilized. Results show that the Linear Regression method outperformed SVM, with MSE 236202.323, RMSE 486.007, MAE 388.712, and R2 1.000. In contrast, SVM yielded MSE 1461472466.751, RMSE 38229.2.10, MAE 303333.535, and R2 -0.065. In conclusion, the prediction using Linear Regression demonstrated better accuracy than SVM. Keywords: Prediction, Algorithm, SVM. Linear Regression.https://jurnalteknik.unisla.ac.id/index.php/teknika/article/view/1192support vector machinemsermsemaer-squarer2 |
| spellingShingle | Ani Apriani Nono Carsono Mas Dadang Enjat Munajat Prediction of Rice Production to Support Food Security in Bogor Regency using Linear Regression and Support Vector Machine (SVM) Jurnal Teknika support vector machine mse rmse mae r-square r2 |
| title | Prediction of Rice Production to Support Food Security in Bogor Regency using Linear Regression and Support Vector Machine (SVM) |
| title_full | Prediction of Rice Production to Support Food Security in Bogor Regency using Linear Regression and Support Vector Machine (SVM) |
| title_fullStr | Prediction of Rice Production to Support Food Security in Bogor Regency using Linear Regression and Support Vector Machine (SVM) |
| title_full_unstemmed | Prediction of Rice Production to Support Food Security in Bogor Regency using Linear Regression and Support Vector Machine (SVM) |
| title_short | Prediction of Rice Production to Support Food Security in Bogor Regency using Linear Regression and Support Vector Machine (SVM) |
| title_sort | prediction of rice production to support food security in bogor regency using linear regression and support vector machine svm |
| topic | support vector machine mse rmse mae r-square r2 |
| url | https://jurnalteknik.unisla.ac.id/index.php/teknika/article/view/1192 |
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