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All Journal JURNAL KEPEMIMPINAN DAN PENGURUSAN SEKOLAH Journal of Socioeconomics and Development Jurnal Ners Riayah: Jurnal Sosial dan Keagamaan Journal of Industrial Engineering and Operation Management (JIEOM) Community Services and Social Work Bulletin Jurnal Ekonomi dan Bisnis Digital Jurnal Keperawatan JAR'S (Journal of Advanced Research in Informatics) SEULANGA: Jurnal Pengabdian Kepada Masyarakat J-CEKI
Fitriani, Novi
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Agriculture, Biological Sciences & Forestry Arts Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Medicine & Pharmacology Nursing Social Sciences Other

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PERBANDINGAN PERFORMA MODEL MACHINE LEARNING SUPPORT VECTOR MACHINE, NEURAL NETWORK, DAN K-NEAREST NEIGHBORS DALAM PREDIKSI HARGA SAHAM Sudriyanto, Sudriyanto; Syahro, Fatimatus; Fitriani, Novi
Journal of Advanced Research in Informatics Vol 2 No 1 (2023): JARS : Journal of Advanced Research in Informatics
Publisher : Fakultas Teknik, Universitas Wiraraja

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24929/jars.v2i1.2983

Abstract

This study aims to analyze the performance of three prediction models, namely K-Nearest Neighbors (K-NN), Neural Network (NN), and Support Vector Machine (SVM), in predicting the stock price of PT Astra International Tbk (ASII.JK). The research encompasses the initial stages through evaluation using optimal parameters for these three algorithms. The research findings reveal that the K-NN prediction model has the lowest Root Mean Square Error (RMSE) value, with a value of 0.037, indicating the most accurate prediction compared to the other models. Despite the NN model having an RMSE of 0.048, which is higher than K-NN, it still provides reasonably accurate predictions. Meanwhile, the SVM model has an RMSE of 0.075, indicating a higher level of error in its predictions. Based on these results, the recommendation is to utilize the K-NN model as the preferred choice for predicting the ASII.JK stock price.
Co-Authors Ahmadi, Muhammad Alcaritzy AKHMAD FAOZI Al Mustaqim, Dede Anggraini, Sanitianing Anita Rahmiwati Apriliani, Ferenadia Astari, Dea Widya Ayu Pitaloka, Ariani Ayu Wulandari, Putri Cynthia Cynthia Doddy Setiawan Fany Apriliani Farhan, Edrian Arizal Fathimah, Muthia Zahira Fathira, Nur Hikmah Fauzan, Muhammad Yunus Haerawati Idris, Haerawati Hayati, Thursina Vera Hidayatullah, Muhammad Dwi Husyairi, Khoirul Aziz Juliyanda, Nugraha Khaeriyah, Muthia Khasanah, Zuhrotul Khusnia Amanina, Nurul Lestari, Peggy Ayu Lindayani, Emi Munadilhaq, Ahmad Nur Alam Fajar Nur Khasanah Nurul Ilmi Azizah, Annafi Pradisa, Dea Putri Heryanto, Suci Nurlathifah Rostika Flora Safithri, Vani Sari, Merry Afriliana Sari, Novrika Shalihah, Nadhira Nur Susanti Marisya Syahro, Fatimatus Yuanita Windusari Yuliantari, Devy Zulfikar, Farrel Ziyad Zuraida Khairani