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All Journal Jurnal Teknik Informatika (JUTIF) Al-Ijtimā: Jurnal Pengabdian Kepada Masyarakat
Sidiq, Muhammad Rais
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Religion Humanities Computer Science & IT Economics, Econometrics & Finance Education Other

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STOCK PREDICTION PERFORMANCE OPTIMIZATION: ENHANCING COVARIANCE MATRIX WITH KNN Saputra , Iskandar Abdul Azis; Sidiq, Muhammad Rais; Guritno, Sangaji Suryo; Cahyono, Hasan Dwi
Jurnal Teknik Informatika (Jutif) Vol. 5 No. 6 (2024): JUTIF Volume 5, Number 6, Desember 2024
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2024.5.6.2399

Abstract

Stock price prediction is a fundamental yet complex challenge in quantitative finance. With the increasing availability of data and advancements in machine learning techniques, various models have been developed to capture intricate patterns in stock price movements. While complex neural network models such as Recurrent Neural Networks (RNNs), Graph Neural Networks (GNNs), and Transformers have shown potential in handling stock market data, they often face optimization difficulties and performance limitations, especially when data is scarce. This paper explores the use of simpler and more accessible prediction methods, specifically Linear Regression (LR) and K-Nearest Neighbors (KNN), alongside more advanced models like Temporal Spatial Transformer (TST) and a Multi-Layer Perceptron (MLP) model called Stockmixer. The NASDAQ dataset is utilized in this study, providing a comprehensive view of stock market dynamics with high variability. Results indicate that KNN, among the evaluated models, exhibits superior and more stable performance in predicting validation data compared to MLP. KNN achieved a low Mean Squared Error (MSE) at 100 epochs, and demonstrated positive Information Coefficient (IC) and Return Information Coefficient (RIC) values. Additionally, it showed high Precision at 10 (P@10) and Sharpe Ratio (SR), making it a robust choice for stock price prediction tasks. In contrast, MLP, despite its sophistication, revealed some weaknesses, particularly in the alignment between predictions and actual values. These findings offer valuable insights into the effectiveness of various models for stock price prediction and suggest that simpler models like KNN can provide competitive results compared to more complex models.
PENGENALAN DIGITAL MARKETING DALAM UPAYA OPTIMALISASI PEMASARAN PADA UMKM DI DUSUN GIRIMULYO A’yun, Efrida Qurotul; Piero, Alessandro Adrian; Nisa, Ayu Sofi Khairul; Nazhifah, Dafina; Orvala, Edelweis Zita; Erowati, Endang; Kinanthi, Gendis Surya; Ma’ruf, Muhammad Nur Fatah; Sidiq, Muhammad Rais; Billa, Shaqhirra Diva Salsa; Latifah, Emmy
Al-Ijtimā': Jurnal Pengabdian Kepada Masyarakat Vol 5 No 1 (2024): Oktober
Publisher : Lembaga Penelitian, Publikasi Ilmiah dan Pengabdian kepada Masyarakat (LP3M)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53515/aijpkm.v5i1.156

Abstract

With the rapid development of technology and the internet, the marketing world is experiencing a significant transformation. Optimizing and utilizing digital marketing helps in the product marketing activities of a business and the activities of tiny and medium enterprises. Realizing this potential, the UNS 336 KKN Team aims to help market UMKM in Girimulyo Hamlet, Trengguli Village, Jenawi District, Karanganyar, by adopting and optimizing digital marketing techniques to increase the visibility and sales of their products. The activities include socialization and training on marketing digitalization through various platforms such as e-commerce, Google Maps, e-wallet, and social media. The results of this program show a significant increase in the understanding and ability of UMKM players to utilize digital marketing tools. Several UMKM have succeeded in creating online business accounts, increasing visibility on Google Maps, and starting to use social media to promote their products. In conclusion, this marketing digitalization program has the potential to be an essential catalyst in local economic development in Girimulyo Hamlet, with recommendations for continued assistance and further training to ensure the continued adoption of digital technology by local UMKM.
Co-Authors A’yun, Efrida Qurotul Billa, Shaqhirra Diva Salsa Emmy Latifah Erowati, Endang Guritno, Sangaji Suryo Hasan Dwi Cahyono Kinanthi, Gendis Surya Ma’ruf, Muhammad Nur Fatah Nazhifah, Dafina Nisa, Ayu Sofi Khairul Orvala, Edelweis Zita Piero, Alessandro Adrian Saputra , Iskandar Abdul Azis