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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Ulul Albab: Jurnal Studi Islam MATICS : Jurnal Ilmu Komputer dan Teknologi Informasi (Journal of Computer Science and Information Technology) Prosiding Seminas Competitive Advantage Prosiding SNATIKA Vol 01 (2011) Applied Information System and Management Letters in Information Technology Education (LITE) Journal of Applied Data Sciences Science in Information Technology Letters International Journal of Engineering, Science and Information Technology Bulletin of Social Informatics Theory and Application
Fachrul Kurniawan
Universitas Islam Negeri Malang
Religion Arts Humanities Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Social Sciences Transportation

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Journal : Bulletin of Social Informatics Theory and Application

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Comparing neural network with linear Regression for stock market prediction Kurniawan, Fachrul; Arif, Yunifa Miftachul; Nugroho, Fresy; Ikhlayel, Mohammed
Bulletin of Social Informatics Theory and Application Vol. 7 No. 1 (2023)
Publisher : Association for Scientific Computing Electrical and Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/businta.v7i1.621

Abstract

There are both gains and losses possible in stock market investing. Brokerage firms' stock investments carry a higher risk of loss since their stock prices are not being tracked or analyzed, which might be problematic for businesses seeking investors or individuals. Thanks to progress in information and communication technologies, investors may now easily collect and analyze stock market data to determine whether to buy or sell. Implementing machine learning algorithms in data mining to obtain information close to the truth from the desired objective will make it easier for an individual or group of investors to make stock trades. In this study, we test hypotheses on the performance of a financial services firm's stock using various machine learning and regression techniques. The relative error for the neural network method is only 0.72 percentage points, while it is 0.78 percentage points for the Linear Regression. More training cycles must be applied to the Algortima neural network to achieve more accurate results.
Optimization of k-means clustering using particle swarm optimization algorithm for human development index Laili, Ufil Hidayatul; Faisal, Muhammad; Kurniawan, Fachrul
Bulletin of Social Informatics Theory and Application Vol. 8 No. 1 (2024)
Publisher : Association for Scientific Computing Electrical and Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/businta.v8i1.678

Abstract

K-Means algorithm can be used to cluster the Human Development Index in East Java in particular for the people, the hope is that with this development all the problems that exist in the community including poverty, unemployment, school dropouts, health and social inequality can be resolved. However, this algorithm has a weakness that is sensitive to the determination of the initial centroid. Initial centroids that are determined randomly will reduce the level of accuracy, often get stuck at the local optimum, and get random solutions. Optimization algorithms such as PSO can overcome this by determining the optimal initial centroid. The quality of clusters produced by K-Means algorithm with and without PSO algorithm is measured using the average Silhouette Coefficient (SC). In this study, better accuracy was obtained between pure kmeans and PSO based kmeans where the comparison value of pure kmeans was 0.27% while PSO based kmeans obtained a value of 0.34%. The Human Development Index data set was obtained from the official website of the Central Bureau of Statistics and used as secondary data in this study, especially the East Java region. In addition to program planning in the following year, the clustering carried out from 2019 to 2022 is also an evaluation of the East Java Provincial Government's program targets that have been implemented in that year, especially related to the human quality of life development program.
Co-Authors ., Rahmadwati Ady Wicaksono Aji Prasetya Wibawa Ajib Hanani Albas, Juan Alfachruddin, M. Nabil Fahd Andri Pranolo Anusua Ghosh, Anusua Artanti, Vera Ashar, Muhammad Camargo, Jair Cengiz, Korhan Fachry Khusaini Fresy Nugroho Gianto Widodo Hani Nurhayati Hoz, César De La Ikhlayel, Mohammed Kadir, Nurchaerani Karisma, Alfiana Intan Kurubacak, Gulsun Laili, Ufil Hidayatul Leonel Hernandez, Leonel Lokapitasari Belluano, Poetri Lestari M. Faisal Mubdik, M. Ahsanul Muhammad Faisal Nia, Nur Jazilah Purnomo Budi Santoso Qurrohman, Taufiq Ridho, Faiz Mohammad Siti Helmyati Sunu Jatmika, Sunu Supriyono Supriyono Suyono Suyono Syaad Patmanthara Triyo Supriyatno Voliansky, Roman W, Delliana Eka Wahyu Setiawan Yunifa Miftachul Arif