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All Journal Jurnal Teknik Informatika (JUTIF) Jurnal Sistem Informasi dan Teknik Informasi
Cahyani, Yonaka Titin Nur
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Computer Science & IT Medicine & Pharmacology Other

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OPTIMIZATION OF STOCK PRICE PREDICTION WITH RIDGE REGRESSION AND HYPERPARAMETER SELECTIONS Marwa, Adeline Fellita; Setiyawan, Sitti Ayuningrum; Cahyani, Yonaka Titin Nur; Cahyono, Hasan Dwi
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 1 (2025): JUTIF Volume 6, Number 1, February 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.1.2384

Abstract

Stock price prediction is a topic that has garnered significant attention in the investment world and has been the subject of various studies. Despite the massive attention, predicting stock price movements using algorithms remains challenging as the algorithms must be agile and highly adaptive to movement trends. Recent studies using deep learning methods for stock price prediction show that deep learning methods have high reliability. However, their computational complexity limits widespread implementation. This study aims to predict Netflix stock prices using a linear regression model with ridge and hyperparameter optimisation. The research consists of three stages: data preprocessing, building a linear regression model with ridge, and predicting and visualizing results. The dataset used is historical Netflix stock price data from 2017 to 2022. In the preprocessing stage, the data was normalized using MinMaxScaler and split into training and test sets. A ridge regression model was built with hyperparameter alpha optimization using GridSearch. Predictions were compared to stock prices and evaluated using Root Mean Squared Error (RMSE). The ridge regression model with hyperparameter optimization performed best with an RMSE of 13.8082. Although the linear regression model demonstrated the fastest execution time of 0.7717 seconds, the ridge regression model with hyperparameter optimization provided an optimal balance between prediction accuracy and time efficiency.
Sistem Publikasi Event 'Semar Event Hub' Berbasis Website Adiar, Shalsabila Aura; Rahmawan, Rizki Dwi Rahmawan; Cahyani, Yonaka Titin Nur
Jurnal SANTI - Sistem Informasi dan Teknik Informasi Vol. 3 No. 1 (2023)
Publisher : Yayasan Rahmatan Fiddunya Wal Akhirah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58794/santi.v3i1.452

Abstract

Perkembangan teknologi yang pesat di era globalisasi mendorong penyebaran informasi event di lingkungan universitas untuk menggunakan teknologi agar penyebaran menjadi cepat, akurat, dan tepat. Salah satu bentuk penyebaran informasi event yaitu dengan melakukan publikasi event yang bertujuan agar target jumlah peserta dapat tercapai. Belum adanya media berupa website yang menampung informasi berbagai event yang diselenggarakan oleh civitas akademika Universitas Sebelas Maret mendukung penelitian ini untuk menciptakan sistem publikasi event berbasis website. Penelitian ini dibangun dengan metode waterfall dimana setiap tahapan membangun sistem dilakukan secara berurutan. Sistem publikasi event yang diciptakan memuat 9 kebutuhan fungsional dengan 3 aktor yang berperan pada sistem. Setiap halaman pada website dibangun dengan menerapkan bahasa pemrograman PHP, HTML, dan dibantu oleh framework Bootstrap. Kemudian, digunakan PHPMyAdmin sebagai penyedia basis data yang digunakan pada sistem. Pengujian terhadap fungsional sistem dilakukan dengan metode black-box. Sistem berbasis website ini diharapkan mampu menjadi media bagi mahasiswa Universitas Sebelas Maret untuk melakukan publikasi event dan mencari informasi.
Co-Authors Adiar, Shalsabila Aura Hasan Dwi Cahyono Marwa, Adeline Fellita Rahmawan, Rizki Dwi Rahmawan Setiyawan, Sitti Ayuningrum