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Akademika
Published by Universitas Nurdin Hamzah
ISSN : 19073984     EISSN : 25411760     DOI : https://doi.org/10.53564
Core Subject : Science,
Computer Science & IT
Jurnal Akademika merupakan media publikasi hasil penelitian dari para akademisi serta praktisi yang berkenaan dengan teknologi informasi dengan beberapa topik bahasan meliputi sistem informasi, jaringan komputer, keamanan sistem, multimedia, kecerdasan buatan, dan sistem pakar. Jurnal Akademika dikelola dibawah Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Nurdin Hamzah yang rutin terbit 2 kali setahun pada bulan april dan november.
Arjuna Subject : Ilmu Komputer (semua kategori) - Sistem Informasi
Articles 16 Documents
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Search results for , issue "Vol 17 No 2 (2025): Jurnal Akademika" : 16 Documents clear
ANALISIS PERBANDINGAN MODEL GRU DAN LSTM UNTUK PREDIKSI HARGA SAHAM BANK RAKYAT INDONESIA: Deep Learning, GRU (Gated Recurrent Unit), LSTM (Long Short-Term Memory), Stock Price Prediction Perdana, Yogi; Raisa Hanum, Nindy; Rabiula, Andre; Anzari, Yandi
JURNAL AKADEMIKA Vol 17 No 2 (2025): Jurnal Akademika
Publisher : LP2M Universitas Nurdin Hamzah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53564/akademika.v17i2.1692

Abstract

This research implements and compares two deep learning architectures, Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU), for predicting the stock price of Bank Rakyat Indonesia (BRI) using historical data from February 2023 to October 2024. Through systematic hyperparameter tuning and comprehensive evaluation, the study finds that GRU consistently outperforms LSTM across all regression metrics, with a 10.7% improvement in R² and an 18.5% reduction in MAPE. The optimal GRU configuration (100 units, 100 epochs, batch size 32, learning rate 0.001) achieves an MSE of 6517.5 and MAPE of 1.3764%. Visual analysis confirms GRU's superior ability to capture stock price fluctuations and adapt more quickly to trend changes. The simpler architecture of GRU with fewer parameters proves more effective for handling the high-noise characteristics and varying volatility of stock price data. While both models face challenges in predicting extreme market events, GRU demonstrates better resilience and faster recovery after such occurrences. This research contributes to the understanding of recurrent neural network applications in financial time series forecasting and provides practical insights for developing more accurate stock price prediction systems.
PEMODELAN PREDIKTIF TRAFIK WEBSITE BERDASARKAN VOLUME KONTEN: PENDEKATAN REGRESI: Web performance, content strategy, linear regression model, page view analysis, digital content optimization Hasanatul Iftitah; Nindy Raisa Hanum
JURNAL AKADEMIKA Vol 17 No 2 (2025): Jurnal Akademika
Publisher : LP2M Universitas Nurdin Hamzah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53564/akademika.v17i2.1694

Abstract

In today's digital landscape, a website's performance serves as a key metric of an institution’s online presence and communication strategy. This research focuses on forecasting website performance by analyzing the relationship between the number of published articles and the volume of page views using a simple linear regression approach. Monthly data was obtained from the official website of the Faculty of Science and Technology at Universitas Jambi, comprising content publication frequency and corresponding traffic. The analysis reveals a strong positive correlation, where each additional published article contributes to a notable increase in page views. The regression model yields a coefficient of 103.75 with an R² value of 0.7278, indicating that over 72% of traffic variation is attributable to content volume. These results emphasize the importance of consistent content production in enhancing web visibility and provide valuable insights for content strategy development.
SISTEM PAKAR DIAGNOSA KERUSAKAN SEPEDA MOTOR HONDA MATIC INJEKSI DENGAN MENGGUNAKAN METODE FORWARD CHAINING BERBASIS WEB: Injection Automatic Motorcycle, Expert System, Forward Chaining sopian, abu; Wahyuning Astuti, Reny; Louis, Ahmad; Antika, Rahma
JURNAL AKADEMIKA Vol 17 No 2 (2025): Jurnal Akademika
Publisher : LP2M Universitas Nurdin Hamzah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53564/akademika.v17i2.1697

Abstract

The development of the injection automatic motorcycle industry in Indonesia has experienced significant development, injection automatic motorcycles that are more fuel efficient and environmentally friendly, with the high number of injection automatic motorcycle users currently, the problem arises that not all injection automatic motorcycle users have the ability to repair damage to their motorcycles. With the advancement of smartphone technology today, an idea or concept of an expert system application has emerged into smartphone service quality activities. The system to be created is "Expert system for diagnosing injection automatic motorcycle damage using the web-based forward chaining method".
ANALISIS PENERIMAAN APLIKASI MCDONALD’S DENGAN MENGGUNAKAN METODE TECHNOLOGI ACCEPTANCE MODEL (TAM): Actual Use, Attitude, Behavioral Intention, McDonald’s Application, Perceived Ease of Use, Perceived Usefulness, Technology Acceptance Model Mh. Khathamy Fhadlullah Haq Syahlevy; Pradita Eko Prasetyo Utomo; Abidin, Zainil
JURNAL AKADEMIKA Vol 17 No 2 (2025): Jurnal Akademika
Publisher : LP2M Universitas Nurdin Hamzah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53564/akademika.v17i2.1726

Abstract

This research aims to analyze user acceptance of the McDonald’s application using the Technology Acceptance Model (TAM) framework. TAM is a theoretical model used to understand the factors influencing technology adoption. In this study, five main variables were examined to determine the relationships between user acceptance elements: Perceived Usefulness (PU), Perceived Ease of Use (PEOU), Attitude Toward Using (ATU), Behavioral Intention to Use (BI), and Actual Use (AU). The sample size in this study consisted of 80 respondents, determined using Hair's formula. The questionnaires were distributed in two ways: by handing out paper leaflets at McDonald’s outlets and by distributing them online via Google Forms. The data analysis in this study involved testing several models and conducting hypothesis testing. The results indicate that Perceived Usefulness has a significant positive effect on Attitude Toward Using, while Perceived Ease of Use has a significant negative effect on Attitude, yet a positive influence on Perceived Usefulness. Furthermore, Attitude significantly and positively affects Behavioral Intention, and Behavioral Intention significantly influences Actual Use. These findings suggest that users’ attitudes and intentions play a crucial role in encouraging the actual use of the McDonald’s application.
PENGOLAHAN DATA PENGARSIPAN KARTU AK-1 PADA DINAS TENAGA KERJA, KOPERASI DAN UKM (DISNAKERKOP) KOTA JAMBI BERBASIS WEB : Archiving, Data Flow Diagram (DFD), Data Processing, Waterfall, Web. rahmawati, Noni; Sopian, Abu; -, Radhiallah; Huda Aminuddin, Fattachul; -, Riswan
JURNAL AKADEMIKA Vol 17 No 2 (2025): Jurnal Akademika
Publisher : LP2M Universitas Nurdin Hamzah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53564/akademika.v17i2.1730

Abstract

Processing AK-1 Card archiving data is an important aspect of administration at the Jambi City Manpower, Cooperatives and SMEs Service (Disnakerkop). This study aims to design and implement a filing system that is efficient, accurate and easy to access. The method used in this research is the Waterfall method and data flow diagram (DFD). The application created from this research shows that a computer-based filing system can increase speed and accuracy in searching for AK-1 Card data, as well as reducing the risk of data loss. Implementation of this system can make a positive contribution to the performance of the Jambi City Department of Manpower, Cooperatives and SMEs (Disnakerkop) in managing workforce data. Keywords : Archiving, Data Flow Diagram (DFD), Data Processing, Waterfall, Web
IMPLEMENTASI PENGOLAHAN CITRA UNTUK PEMBUATAN FILTER GAMBAR BERBASIS WEB MENGGUNAKAN OPENCV DAN FLASK: Pengolahan citra digital, filter gambar, OpenCV, Flask, Python, web Setiadi, Arif; Fadhliazis, Fadhliazis; Ahadi, Ahmad Husna; Gustina, Gustina
JURNAL AKADEMIKA Vol 17 No 2 (2025): Jurnal Akademika
Publisher : LP2M Universitas Nurdin Hamzah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53564/akademika.v17i2.1737

Abstract

Pengolahan citra digital merupakan salah satu bidang dalam dunia teknologi informasi, terutama pada pengembangan aplikasi berbasis visual. Penelitian ini bertujuan untuk mengembangkan sebuah web yang dapat menerapkan beberapa filter pada gambar digital menggunakan library OpenCV dengan dukungan framework Flask berbasis Python. Aplikasi ini memungkinkan pengguna untuk mengunggah gambar dan memilih jenis filter yang tersedia yaitu grayscale, blur, dan edge detection. Proses pengolahan citra dilakukan di sisi server, kemudian hasilnya akan ditampilkan kembali kepada pengguna. Hasil menunjukkan bahwa web dapat memproses gambar secara server-side dan menampilkan hasilnya secara real time. Web ini dapat memberikan gambaran penggunaan filter dalam pemrosesan gambar untuk kebutuhan pembelajaran, riset, maupun pengembangan sistem lebih lanjut.

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