MEO, Tarsisius Bei (2023) Analisis Data Pertanian Tanaman Pangan Untuk Memprediksi Hasil Panen (Studi Kasus Desa Tarawaja Kabupaten Ngada). Undergraduate thesis, Universitas Katolik Widya Mandira Kupang.
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Abstract
Tarawaja Village is one of the villages in Soa District, Ngada Regency which has a community with a livelihood as farmers. The community has made the lowland rice commodity a locality-specific superior commodity which is supported by natural resources which are very suitable for developing lowland rice farming. In addition to paddy rice commodities, there are food crop commodities and other plantation crops. So, it is necessary to predict the agricultural yield of these food crops. Prediction is an attempt to predict a business situation that will occur in the future. Predictions also have two possibilities, namely between happening and not happening. In this study, predictions were made on the yields of food crop agriculture using the linear regression method, so that a number could be output that could determine how many crops were harvested, and would be used as evaluation material for local governments for each amount of food crop yields. This study uses the Orange Data Mining Tool as a tool to carry out the data mining process. From the test results the coefficient of determination is 0.879, 0.270, 0.727. This means that the level of compatibility of the multiple linear regression model has a reliability level of 87.9%, 27.2 and 72.7%. As much as 87.9%, 27.2 and 72.7% of the variation in the value of harvest results depend on the independent variables measured, which include planting area and harvest area. While the rest is influenced by other variables not measured in this study.
Item Type: | Thesis (Undergraduate) |
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Uncontrolled Keywords: | Prediction, Agriculture, Tarawaja Village,Linear Regression |
Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software |
Divisions: | Fakultas Teknik > Program Studi Ilmu Komputer |
Depositing User: | S. Kom Tarsisius Bei Meo |
Date Deposited: | 03 Mar 2023 00:20 |
Last Modified: | 03 Mar 2023 00:20 |
URI: | http://repository.unwira.ac.id/id/eprint/12234 |
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