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All Journal Jurnal Teknologi Informasi : Jurnal Keilmuan dan Aplikasi Bidang Teknik Informatika Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi)
Muhamad Zulfani
Universitas Atma Jaya Yogyakarta
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering Library & Information Science

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Perancangan Model Enterprise Architecture Planning pada PT. Bestari Kalimantan Zulfani, Muhamad; Emanuel, Andi Wahju Rahardjo
Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 8 No 2 (2024): APRIL-JUNE 2024
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jtik.v8i2.1795

Abstract

PT Bestari Kalimantan is a contracting company specializing in network installation. Currently, the system used is still manual and not computerized for data management, including employee payroll, equipment and inventory processing, and other data. In this technological era, adopting a computerized system is crucial for companies to support the smooth flow of their business processes. Therefore, at PT. Bestari Kalimantan, an Enterprise Architecture Planning has been designed, encompassing a Strategic Plan for the computerized system, aiming to assist in optimizing business processes. From the results of the Enterprise design, proposals for applications have been generated that can be used by PT. Bestari Kalimantan to replace the current manual system. With the Blueprint from the Enterprise Architecture design, it is hoped that PT. Bestari Kalimantan can enhance its service to customers
PREDIKSI HARGA SAHAM MENGGUNAKAN ALGORITMA NEURAL NETWORK Muhamad Zulfani; Dapadeda, Ardiyanto
Jurnal Teknologi Informasi: Jurnal Keilmuan dan Aplikasi Bidang Teknik Informatika Vol. 18 No. 1 (2024): Jurnal Teknologi Informasi : Jurnal Keilmuan dan Aplikasi Bidang Teknik Inform
Publisher : Universitas Palangka Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47111/jti.v18i1.11303

Abstract

In recent years, the development of technology and artificial intelligence has brought forth new opportunities in analyzing and predicting stock prices. One of the approaches used is the Neural Network algorithm, which is a part of the branch of artificial intelligence known as Deep Learning. This algorithm can learn complex patterns and relationships among data by modeling inspired by the human neural network. This research utilizes the Neural Network for stock price prediction and aims to understand the application of Neural Network in predicting stock prices, which can benefit investors and market participants. Additionally, historical stock price data can be used as input for the Neural Network algorithm. The Neural Network is a frequently used algorithm for accurate predictions and is widely employed in prediction-based or forecasting research. The result of this research is the Root Mean Squared Error (RMSE) value of 19.734 +/- 0.000. The use of the Neural Network as an algorithm for stock price prediction provides investors with valuable information for making investment decisions for companies..
Co-Authors Andi Wahju Rahardjo Emanuel Dapadeda, Ardiyanto