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All Journal Syntax Literate: Jurnal Ilmiah Indonesia Jurnal Review Pendidikan dan Pengajaran (JRPP)
Kurnianto, Benedict Ariel
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Humanities Economics, Econometrics & Finance Education Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Social Sciences Other

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Predictive Maintenance Using Linear Regression Prayogo, Rudy Hartono; Kurnianto, Benedict Ariel; Nababan, Nidia Pialina; Suharjito, Suharjito
Syntax Literate Jurnal Ilmiah Indonesia
Publisher : Syntax Corporation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36418/syntax-literate.v9i3.15366

Abstract

Problems regarding machine damage often occur in many industries, especially the manufacturing industry, which causes large losses for companies. This is of course influenced by various factors such as engine temperatures that are too high, engine rotation that is too fast, poor engine torque values, and so on. This research aims to provide predictive analysis results regarding engine conditions that have the potential to experience damage. To achieve this goal, this research will carry out predictive maintenance analysis using a linear regression analysis approach in which two linear regression models will be carried out where the first model involves PCA preprocessing and the second model is carried out without PCA. This research will use the predictive maintenance dataset from the conference (Matzka, 2020). It is known that the MSE, RMSE, MAE, and R2 values of the two methods have the same values, namely 0.909, 0.953, 0.806, and 0.772 respectively. Based on this research, it is concluded that whether PCA is performed or not, it does not significantly affect the results of the regression analysis. This outcome can be attributed to the artificial nature of the dataset, rendering it ideal. Moreover, the retained PCA value of 98% is close to the number of attributes in the original dataset.
ANALISA DERET WAKTU DENGAN MENGGUNAKAN METODE ARIMA DAN VAR PADA APLIKASI ORANGE Fadilah, Mieldha Hamzah; Novendra, Hendri; Kurnianto, Benedict Ariel; Kasih, Tota Pirdo
Jurnal Review Pendidikan dan Pengajaran Vol. 7 No. 1 (2024): Volume 7 No 1 Tahun 2024
Publisher : LPPM Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jrpp.v7i1.23785

Abstract

Kita tahu bahwa teknologi sedang berkembang pesat saat ini. Banyak manfaat yang dapat diperoleh khususnya mengenai data science dimana sangat membantu perusahaan dalam mengatasi masalah mereka. Salah satu permasalahan yang sering ditemui yaitu sulit memprediksi masa depan dimana data science dengan menggunakan analisa deret waktu akan membantu perusahaan dalam memprediksi masa depan. Penelitian ini akan melakukan analisa deret waktu dengan menggunakan metode ARIMA dan VAR yang dimana akan dibandingkan untuk mendapatkan metode yang paling tepat dalam menganalisa data saham yang akan dianalisa. Diketahui bahwa metode VAR merupakan metode terbaik yang dimana memiliki nilai RMSE, MAE, MAPE, POCID, R2, AIC, dan BIC yaitu sebesar 76.3, 32.7, 0.006, 42.9, 0.608, 15.2, 15.2 secara berurutan. Selain itu, VAR memprediksi bahwa nilai saham di 5 periode kedepan akan bernilai 8935.56, 8938.88, 8938.65, 8936.68, dan 8933.86.
Co-Authors Fadilah, Mieldha Hamzah Kasih, Tota Pirdo Nababan, Nidia Pialina Novendra, Hendri Prayogo, Rudy Hartono Suharjito Suharjito, Suharjito