Penerapan Data Mining dengan Metode Regresi Linear untuk Memprediksi Data Nilai Hasil Ujian Menggunakan RapidMiner
Prediction is one of the methods in data mining. One of the models that can be used in prediction is using linear regression. Linear regression is used to make predictions on the data that has been provided. In this study, a linear regression model was made with a datasheet containing data that aff...
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| Format: | Article |
| Language: | English |
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Universitas Islam Negeri Sunan Kalijaga Yogyakarta
2023-01-01
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| Series: | JISKA (Jurnal Informatika Sunan Kalijaga) |
| Subjects: | |
| Online Access: | https://ejournal.uin-suka.ac.id/saintek/JISKA/article/view/3439 |
| _version_ | 1797699694770520064 |
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| author | Muhammad Sholeh Erna Kumalasari Nurnawati Uning Lestari |
| author_facet | Muhammad Sholeh Erna Kumalasari Nurnawati Uning Lestari |
| author_sort | Muhammad Sholeh |
| collection | DOAJ |
| description |
Prediction is one of the methods in data mining. One of the models that can be used in prediction is using linear regression. Linear regression is used to make predictions on the data that has been provided. In this study, a linear regression model was made with a datasheet containing data that affected student achievement in achieving final exam scores. The linear regression model developed can be used to predict student test scores. The linear regression model developed can be used to predict student test scores. The datasheet used in the test uses a public datasheet, namely student_performance.csv. The datasheet consists of 395 records and 33 attributes. The attributes used are selected that influence the label. The selection of attributes is based on the results of the weighting in the process of checking the correlation matrix. Based on the weighting, the attributes used are seven attributes and one attribute becomes a label. The research method uses CRISP DM which consists of business understanding, data understanding, data preparation, model making, evaluation, and deploying. The data mining process uses the Rapid Miner application. The results of the study resulted in a linear regression model y=0.729-(0.024×Medu)-(0.020×Fedu)+(0.053×failures)-(0.077×goout)-(0.012×absences)+(0.126×G1)+(0.862×G2). The result of evaluating the performance of the RMSE value was 0.675. Based on these results, it can be concluded that the resulting model can be recommended for use in predicting student test scores.
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| first_indexed | 2024-03-12T04:11:31Z |
| format | Article |
| id | doaj.art-04a4a7f75e794995a8dda292d4eceb45 |
| institution | Directory Open Access Journal |
| issn | 2527-5836 2528-0074 |
| language | English |
| last_indexed | 2024-03-12T04:11:31Z |
| publishDate | 2023-01-01 |
| publisher | Universitas Islam Negeri Sunan Kalijaga Yogyakarta |
| record_format | Article |
| series | JISKA (Jurnal Informatika Sunan Kalijaga) |
| spelling | doaj.art-04a4a7f75e794995a8dda292d4eceb452023-09-03T10:57:08ZengUniversitas Islam Negeri Sunan Kalijaga YogyakartaJISKA (Jurnal Informatika Sunan Kalijaga)2527-58362528-00742023-01-0181Penerapan Data Mining dengan Metode Regresi Linear untuk Memprediksi Data Nilai Hasil Ujian Menggunakan RapidMinerMuhammad Sholeh0Erna Kumalasari Nurnawati1Uning Lestari2Institut Sains & Teknologi AKPRINDInstitut Sains & Teknologi AKPRINDInstitut Sains & Teknologi AKPRIND Prediction is one of the methods in data mining. One of the models that can be used in prediction is using linear regression. Linear regression is used to make predictions on the data that has been provided. In this study, a linear regression model was made with a datasheet containing data that affected student achievement in achieving final exam scores. The linear regression model developed can be used to predict student test scores. The linear regression model developed can be used to predict student test scores. The datasheet used in the test uses a public datasheet, namely student_performance.csv. The datasheet consists of 395 records and 33 attributes. The attributes used are selected that influence the label. The selection of attributes is based on the results of the weighting in the process of checking the correlation matrix. Based on the weighting, the attributes used are seven attributes and one attribute becomes a label. The research method uses CRISP DM which consists of business understanding, data understanding, data preparation, model making, evaluation, and deploying. The data mining process uses the Rapid Miner application. The results of the study resulted in a linear regression model y=0.729-(0.024×Medu)-(0.020×Fedu)+(0.053×failures)-(0.077×goout)-(0.012×absences)+(0.126×G1)+(0.862×G2). The result of evaluating the performance of the RMSE value was 0.675. Based on these results, it can be concluded that the resulting model can be recommended for use in predicting student test scores. https://ejournal.uin-suka.ac.id/saintek/JISKA/article/view/3439ModelData MiningLinear RegressionRapidMinerDatasheet |
| spellingShingle | Muhammad Sholeh Erna Kumalasari Nurnawati Uning Lestari Penerapan Data Mining dengan Metode Regresi Linear untuk Memprediksi Data Nilai Hasil Ujian Menggunakan RapidMiner JISKA (Jurnal Informatika Sunan Kalijaga) Model Data Mining Linear Regression RapidMiner Datasheet |
| title | Penerapan Data Mining dengan Metode Regresi Linear untuk Memprediksi Data Nilai Hasil Ujian Menggunakan RapidMiner |
| title_full | Penerapan Data Mining dengan Metode Regresi Linear untuk Memprediksi Data Nilai Hasil Ujian Menggunakan RapidMiner |
| title_fullStr | Penerapan Data Mining dengan Metode Regresi Linear untuk Memprediksi Data Nilai Hasil Ujian Menggunakan RapidMiner |
| title_full_unstemmed | Penerapan Data Mining dengan Metode Regresi Linear untuk Memprediksi Data Nilai Hasil Ujian Menggunakan RapidMiner |
| title_short | Penerapan Data Mining dengan Metode Regresi Linear untuk Memprediksi Data Nilai Hasil Ujian Menggunakan RapidMiner |
| title_sort | penerapan data mining dengan metode regresi linear untuk memprediksi data nilai hasil ujian menggunakan rapidminer |
| topic | Model Data Mining Linear Regression RapidMiner Datasheet |
| url | https://ejournal.uin-suka.ac.id/saintek/JISKA/article/view/3439 |
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