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All Journal Jurnal Sistem Cerdas Jurnal Informatika: Jurnal Pengembangan IT
Kurniawan, Heru Purnomo
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Automotive Engineering Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering

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Hybrid Model of Artificial Neural Networks and Flower Pollination Algorithm for Stock Price Prediction Farhatuaini, Lia; Kurniawan, Heru Purnomo; Muslihah, Isnawati
Jurnal Sistem Cerdas Vol. 7 No. 3 (2024)
Publisher : APIC

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37396/jsc.v7i3.433

Abstract

Predicting the future behavior of the stock market is a difficult task due to its complex and ever-changing nature. This study focuses on predicting BBRI stock prices using an Artificial Neural Network (ANN) improved with the Flower Pollination Algorithm (FPA). We found that the model works well with a 9-100-1 setup, achieving accurate predictions with a Root Mean Square Error (RMSE) of 0.127579154. While FPA effectively reduces errors in the initial 10 iterations, it faces challenges in further improvement, especially in responding to sudden changes in stock prices. Despite performing well overall, the model tends to have a wider margin during unexpected market shifts, indicating a need for additional fine-tuning. This research provides valuable insights into stock price prediction, highlighting the importance of refining models to handle unexpected market changes.
Identifikasi Pola Kepuasan Mahasiswa Terhadap Proses Pembelajaran Menggunakan Algoritma K-Means Clustering. Kurniawan, Heru Purnomo; Farhatuaini, Lia
Jurnal Informatika: Jurnal Pengembangan IT Vol 9, No 2 (2024)
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v9i2.6740

Abstract

Student satisfaction levels with the learning experience at higher education institutions often exhibit variability. This study aims to comprehend the varying degrees of student satisfaction at Institut Agama Islam Negeri (IAIN) Syekh Nurjati Cirebon. Employing the K-Means clustering method, this research categorizes students based on their satisfaction levels. The survey data analyzed includes 20 dimensions of Service Quality criteria evaluated by students, with these 20 dimensions grouped into five key aspects of Service Quality assessment: tangible, reliability, responsiveness, assurance, and empathy. The analysis reveals three distinct groups of students with differing satisfaction levels: neutral/fair (class 1), agree/good (class 2), and strongly agree/excellent (class 3). Comparisons among these groups highlight the diversity of student perceptions. Furthermore, an examination of the distribution of evaluations within each class uncovers differing priorities in assessment criteria. These research findings offer insights into the spectrum of student satisfaction levels and pinpoint areas warranting further attention in each class. Such insights can inform the development of policies and strategies aimed at enhancing the quality of learning experiences at IAIN Syekh Nurjati Cirebon.
Co-Authors Farhatuaini, Lia Muslihah, Isnawati