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All Journal Sistemasi: Jurnal Sistem Informasi Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Jurnal Informatika Universitas Pamulang J-SAKTI (Jurnal Sains Komputer dan Informatika) JURTEKSI JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Jurnal ICT : Information Communication & Technology JSAI (Journal Scientific and Applied Informatics) Jurnal Informatika dan Rekayasa Elektronik JATI (Jurnal Mahasiswa Teknik Informatika) Respati JIKA (Jurnal Informatika) Jurnal Teknik Informatika (JUTIF) JNANALOKA Journal of Electrical Engineering and Computer (JEECOM) Information System Journal (INFOS) Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) International Journal of Artificial Intelligence and Robotics (IJAIR) Jurnal Pendidikan dan Teknologi Indonesia J-SAKTI (Jurnal Sains Komputer dan Informatika) Jurnal Informatika Teknologi dan Sains (Jinteks) Duta.com : Jurnal Ilmiah Teknologi Informasi dan Komunikasi Journal of Comprehensive Science Jurnal Ilmiah Sistem Informasi dan Ilmu Komputer Jurnal Bangkit Indonesia Jurnal Pendidikan Indonesia (Japendi) Prosiding SEMNAS INOTEK (Seminar Nasional Inovasi Teknologi) Jurnal Indonesia : Manajemen Informatika dan Komunikasi Intechno Journal : Information Technology Journal The Indonesian Journal of Computer Science International Journal of Information Engineering and Science
DHANI ARIATMANTO
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Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Mechanical Engineering Social Sciences Transportation Other

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Journal : Jurnal Teknik Informatika (JUTIF)

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CATTLE BODY WEIGHT PREDICTION USING REGRESSION MACHINE LEARNING Anjar Setiawan; Utami, Ema; Ariatmanto, Dhani
Jurnal Teknik Informatika (Jutif) Vol. 5 No. 2 (2024): JUTIF Volume 5, Number 2, April 2024
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2024.5.2.1521

Abstract

Increasing efficiency and productivity in the cattle farming industry can have a significant economic impact. Cow health and productivity problems directly impact the quality of the meat and milk produced. In the cattle farming industry, it can help predict cow weight oriented to beef and milk quality. The importance of predicting cow weight for farmers is to monitor animal development. Meanwhile, for traders, knowing the animal's weight makes it easier to calculate the price of the animal meat they buy. This research aims to predict cow weight by increasing the results of smaller MAE values. The methods used are linear Regressor (LR), Random Forest Regressor (RFR), Support Vector Regressor (SVR), K-Neighbors Regressor (KNR), Multi-layer Perceptron Regressor (MLPR), Gradient Boosting Regressor (GBR), Light Gradient boosting (LGB), and extreme gradient boosting regressor (XGBR). Producing cattle weight predictions using the SVR method produces the best values, namely mean absolute error (MAE) of 0.09 kg, mean absolute perception error (MAPE) of 0.02%, root mean square error (RMSE) of 0.08 kg, and R-square of 0.97 compared to with other algorithm methods and the results of statistical correlation analysis showed several significant relationships between morphometric variables and live weight.
STACKING ENSEMBLE LEARNING AND INSTANCE HARDNESS THRESHOLD FOR BANK TERM DEPOSIT ACCEPTANCE CLASSIFICATION ON IMBALANCED DATASET Bangun Watono; Ema Utami; Dhani Ariatmanto
Jurnal Teknik Informatika (Jutif) Vol. 5 No. 4 (2024): JUTIF Volume 5, Number 4, August 2024 - SENIKO
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2024.5.4.2022

Abstract

Bank term deposits are a popular banking product with relatively high interest rates. Predicting potential customers is crucial for banks to maximize revenue from this product. Therefore, bank term deposits acceptance classification is an important challenge in the banking industry to optimize marketing strategies. Previous studies have been conducted using machine learning classification techniques with the imbalanced Bank Marketing Dataset from the UCI Repository. However, the accuracy results obtained still need to be improved. Using the same dataset, this study proposes an Instance Hardness Threshold (IHT) undersampling technique to handle imbalanced datasets and Stacking Ensemble Learning (SEL) for classification. In this SEL, Decision Tree, Random Forest, and XGBoost are selected as base classifiers and Logistic Regression as meta classifier. The model trained on SEL with the dataset undersampled using IHT shows a high accuracy rate of 98.80% and an AUC-ROC of 0.9821. This performance is significantly better than the model trained with the dataset without undersampling, which achieved an accuracy of 90.30% and an AUC-ROC of 0.6898. The findings of this research demonstrate that implementing of the suggested IHT undersampling technique combined with SEL has been evaluated to effectively enhance the performance of term deposit classification on the dataset.
Co-Authors Adrianto M. Wijaya Ahsan, Muhammad Salimy Alfansani, Abdul Rauf Alva Hendi Muhammad Amali, Amali Anggriandi, Dendi Anjar Setiawan Anton, Tri Arfian Hendro Priyono Arfian Yogi Ferianto Arief Setyanto Aris Setiyadi Bangun Watono BHANU SRI NUGRAHA Chaedar Fatach, Muhamad Reza Darmawan, Eko Rahmad Didi Kurniawan Edy Widodo Ema Utami Eva Putriany Fadilla, Rizqi Mirza Fahma Inti Ilmawati Firdaus, M. Haikal Ghifari, Dloifur Rohman Al Hadiguna Setiawan Hayaty, Mardhiya Jordy, Roy Karim, Hildamayanti Khairani, Fatihatul KUSRINI Kusrini Kusrini Kusrini, Kusrini Linggama, Muhamad Nurfaizi Lukman Lukman M. Ilham Arief M. Ulil Albab Majid, Muhammad Arif Kholis Metha, Halifa Sekar Mohammad Suyanto Muhammad Rifa'i, Anggi Muhammad Salimy Ahsan Mulia Sulistiyono Napitupulu, Harapan Norhikmah . Nugroho, Agung Nurrizky, Akbar Nur’aini Pramudyantoro, Arvi Prasetiyanto, Ari Eka Prayoga, Dimas Putriany, Eva Quratul Ain Ramdhani, Mohamad Dhicy Rifai, Anggi Muhammad Rosmantyo, Windhy Rokhmat Royali, Rainer Maghma Rusdi Rahman, Muhammad Selvi Marcellia Silvi Agustanti Bambang Slameto, Andika Agus Subandono, Anelta Tirta Putri Sukoco Sukoco Supriadi, Oki Akbar Suryono, Wachid Daga Suyanto, M Tikasni, Elisa Triesa Wea, Engel Bertus Turmudi Zy, Ahmad Wijaya, Adrianto Mahendra Wiwik Handayani Zakaria Zakaria zakinah, annisa gatri Zuhri, Muhammad Rafli Zulpan Hadi