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INDONESIA
Jurnal Teknik Komputer AMIK BSI
Published by Universitas Bina Sarana Informatika
ISSN : 24412436     EISSN : 25500120     DOI : http://dx.doi.org/10.31294/jtk
Core Subject : Science,
Computer Science & IT
Jurnal Teknik Komputer merupakan jurnal ilmiah yang diterbitkan oleh LPPM Universitas Bina Sarana Informatika. Jurnal ini berisi tentang karya ilmiah hasil penelitian yang bertemakan: Networking, Robotika, Aplikasi Sains, Animasi Interaktif, Pengolahan Citra, Sistem Pakar, Sistem Komputer, Soft Computing, Web Programming, Data Mining, dan Sistem Penunjang Keputusan. Jurnal Teknik Komputer berisi pokok-pokok permasalahan baik dalam pengembangan kerangka teoritis, implementasi maupun kemungkinan pengembangan sistem secara keseluruhan. Diharapkan setiap naskah yang diterbitkan di dalam jurnal ini memberikan kontribusi yang nyata bagi peningkatan sumberdaya penelitian di dalam bidang informatika dan komputer. Tim redaksi membuka komunikasi lebih lanjut baik kritik, saran dan pembahasan.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 336 Documents
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Development of an Android Application to Identify Fish Species Using Kotlin-based Android Studio Sampurna, Adam Mulya; ., Alfani; Setiawan, Ade; Al Kautsar, Hanggoro Aji
JURNAL TEKNIK KOMPUTER AMIK BSI Vol 11, No 1 (2025): Periode Januari 2025
Publisher : Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/jtk.v11i1.24456

Abstract

Indonesia has a rich variety of fish species, but the understanding and knowledge of the public about these fish species is still limited. This is the background of the problem raised in this research, with the aim of providing education to the Indonesian people about the types of fish in Indonesia. The solution offered is the development of an Android application that can identify fish species in Indonesia. This application is expected to be an effective educational tool for the community. The methods used in the development of this application include collecting data documentation from the internet, literature studies from various research journals, literature, and other scientific articles. The collected data is then used as a basis for application development. Tools used in the development of this application include Android Studio as the main software, Firebase as a database, Kotlin as a programming language, and XML as a markup language for data storage and transmission. Figma is used to design the application interface. Application testing is carried out using the black box testing method to ensure application functionality runs well. The algorithm used in this application is a recursive algorithm for processing fish identification data. With this application, it is hoped that Indonesian people can more easily recognize and understand the types of fish that exist in Indonesia, so that they can reduce the number of fish species in Indonesia.
Comparison of News Text Summarization Using NLTK and TextRank Based on Python Programming Surniandari, Artika; Rachmi, Hilda; Fauzi, Ahmad; Utami, Lila Dini
JURNAL TEKNIK KOMPUTER AMIK BSI Vol 11, No 1 (2025): Periode Januari 2025
Publisher : Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/jtk.v11i1.24497

Abstract

Text summarization technology is increasingly used to simplify the vast amount of news information available in the digital era. This study compares two popular text summarization methods, the Natural Language Toolkit (NLTK) and TextRank, in the context of news summarization using the Python programming language. The goal of this research is to evaluate the performance of both algorithms based on summary quality and processing time. The dataset comprises a collection of news articles in Indonesian, processed using both methods. The results indicate that each algorithm has distinct advantages: TextRank excels in generating more coherent summaries, while NLTK demonstrates faster processing times. This study aims to contribute insights into the selection of an appropriate text summarization method for automating news summarization across various applications.
Application of Random Forest Algorithm To Classify Credit Status of KPR Customers at Bank BTN Based on Machine Learning Fitri, Maysade; Sobri, Ahmad; Rizki, Fido
JURNAL TEKNIK KOMPUTER AMIK BSI Vol 11, No 1 (2025): Periode Januari 2025
Publisher : Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/jtk.v11i1.25261

Abstract

In the banking sector, this study is very suitable for determining and improving accuracy and determining credit status classification. This study aims to apply the Exploratory Data Analysis (EDA) method in supporting credit status classification at PT. Bank Tabungan Negara KCP Lubuklinggau Persero Tbk. Exploratory Data Analysis (EDA) as data exploration and Machine Learning Algorithms such as Random Forest as modeling in determining classification. The results show that the Exploratory Data Analysis (EDA) method successfully determines data patterns, while Random Forest in modeling achieves accuracy, recall, Precision, F1-Score of 100% in predicting the credit status of KPR customers. This method is expected to be useful in making decisions on more accurate credit status by the bank.
Implementation Of MVC Model In Web-Based Online Ticket Ordering For Magic Art 3d Museum Putra, Rendi Aditya; Bahri, Syamsul; wahyudin, wahyudin
JURNAL TEKNIK KOMPUTER AMIK BSI Vol 11, No 2 (2025): Periode Juli 2025
Publisher : Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/jtk.v11i2.27161

Abstract

The 3D Magic Art Museum is located in the old town. This museum is currently the best museum destination in the old city. This museum displays many interesting paintings and three-dimensional works of art and provides new experiences for visitors. Because previously ticket reservations were made conventionally so tourists had to come directly to the location or use the telephone, so agents were overwhelmed in processing ticket orders. Most visitors who want to pay for tickets still use cash and do not use mobile banking services, which often results in quite long and very inefficient queues, as well as the large number of visitors to the 3D Magic Art Museum, allegedly due to a mismatch between ticket orders and the number of guests in the group. . This research aims to help tourists book tickets more easily and efficiently. At the application design stage, the Model-View-Controller (MVC) method was used. Meanwhile, the programming technology uses the CodeIgniter framework. Therefore, this system can provide a website for museums so that it can be used as a means of ordering and paying online (Payment Gateway), as well as increasing visitor satisfaction through the functionality of this website.
Dynamic Routing Performance Analysis with Border Gateway Protocol (BGP) Single Multi-Homed Diskominfosantik Saputra, Angga; Komalasari, Yuli; Haryadi, Eko
JURNAL TEKNIK KOMPUTER AMIK BSI Vol 11, No 2 (2025): Periode Juli 2025
Publisher : Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/jtk.v11i2.25529

Abstract

The study approach uses network simulation software to scan various traffic patterns and network topologies. This study reveals the performance of dynamic routing with Border Gateway Protocol (BGP) in a single multi-homed setting. BGP is the basic routing protocol that governs the exchange of information between autonomous systems (AS) on the internet. In a single multi-homed situation, autonomous systems are connected to multiple egress paths through two internet service providers (ISPs). This study evaluates the performance of BGP by exploiting time convergence, route stability, bandwidth utilization efficiency, and latency. The study approach uses network simulation software to simulate various traffic patterns and network topologies. The research method involves network simulation using a network simulator to simulate various scenarios and topologies.
Comparative Analysis of Machine Learning Model Performance for Classification of Edible or Non-edible Mushrooms Pahlevi, Omar; Sriyadi, Sriyadi
JURNAL TEKNIK KOMPUTER AMIK BSI Vol 11, No 2 (2025): Periode Juli 2025
Publisher : Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/jtk.v11i2.26007

Abstract

Mushrooms provide significant nutritional benefits and play a crucial role in the global food industry. However, not all mushroom species are safe for consumption, as some contain toxic compounds that can cause severe poisoning and even death. Accurate identification is essential to differentiate between edible and poisonous mushrooms. Traditional classification methods relying on manual morphological identification are often inaccurate, especially when toxic and edible mushrooms have similar physical characteristics. Machine Learning (ML) technology offers an innovative solution to enhance classification accuracy and improve safety in mushroom consumption. This study compares the performance of three major classification algorithms—Random Forest, Logistic Regression, and Naïve Bayes—using an open dataset from Kaggle. The analysis was conducted using the KNIME platform, evaluating the algorithms based on accuracy, sensitivity, and computational efficiency. The results indicate that Random Forest achieved the highest accuracy at 98.90%, followed by Logistic Regression at 69.67% and Naïve Bayes at 55.46%. These findings highlight the superiority of ensemble methods in classification tasks. This research contributes to the development of a reliable ML-based mushroom classification system. However, limitations remain, such as the exclusion of other high-performance algorithms like Support Vector Machine and Artificial Neural Networks. Future studies may incorporate optimization techniques to improve model performance. Additionally, implementing this classification system into mobile or web-based applications could provide broader benefits by enabling quick identification of mushrooms, minimizing health risks, and improving consumer confidence in mushroom safety.

Page 34 of 34 | Total Record : 336

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