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ROUTERS: Jurnal Sistem dan Teknologi Informasi
Published by Politeknik Negeri Lampung
ISSN : -     EISSN : 29621224     DOI : https://doi.org/10.25181
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Library & Information Science
ROUTERS: Jurnal Sistem dan Teknologi Informasi includes research in the field of Computer Science, Computer Networks and Engineering, Software Engineering and Information Systems, and Information Security. Editors invite research lecturers, reviewers, practitioners, industry, and observers to contribute to this journal. ROUTERS is a national scientific journal that is open to seeking innovation, creativity, and novelty. Either letters, research notes, articles, supplemental articles, or review articles. ROUTERS aims to achieve state-of-the-art theory and application in this field. ROUTERS provides a platform for scientists and academics across Indonesia to promote, share, and discuss new issues and the development of systems and information technology.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 34 Documents
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Pengaruh Aksi Boikot Terhadap Harga Saham Unilever: Pendekatan Prediktif Dengan Neural Network Dan Linear Regression Yani, Ririn Yuli; Nidaa, Syafiqotun; Suseno, Akrim Teguh; Wulandari, Umi Meganinditya
ROUTERS: Jurnal Sistem dan Teknologi Informasi Vol. 3 No. 1, Februari 2025
Publisher : Program Studi Teknologi Rekayasa Internet, Politeknik Negeri Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25181/rt.v3i1.4009

Abstract

PT Unilever Indonesia Tbk is a  multinational company that produces and markets various consumer goods in various countries to fulfill needs ranging from health, nutrition, daily care and so on. PT Unilever Indonesia Tbk is facing a crisis of calls for a boycott of products due to pro-Israel which has an impact on the Company’s reputation and performance. In the face of this situation, stock price prediction analysis is important to help investors in making decisions. To overcome this problem, this research applies Data Mining Techniques in predicting the share price of PT Unilever Tbk. The two algorithms used are Neural Network and Linear Regression, which are then tested using the Root Mean Squared Error (RMSE) evaluation method. Data processing is done using RapidMiner with historical data period from December 2023 to May 2024. Based on the analysis results, the Linear Regression algorithm produces an RMSE value of 22,745, showing a more accurate prediction compared to the Neural Network algorithm which has an RMSE value of 44,830. The test results show that predicting stock prices using Linear Regression has a lower error rate than the Neural Network. Thus, in this study, the Linear Regression algorithm is superior in predicting the stock price of PT Unilever Indonesia Tbk compared to the Neural Networj. The results of this study are also compared with previous research which shows thaht the accuracy of the stock price prediction model depends on the characteristics of the dataset and the method used. Some previous studies concluded that Neural Network is superior in capturing complex patterns in certain stocks, while Linear Regression is more suitable for data with linear relationships. Therefore, although Linear Regression is better in this study, model selection still needs to be tailored to the characteristics and objectives of the analysis.
Customer Segmentation Based on Spending Patterns Using K-Means Clustering and PCA Dzakwan Akbar Perdana Wijaya; sasmita, Chesie fenta; Naufaldi Favian Archi
ROUTERS: Jurnal Sistem dan Teknologi Informasi Vol. 3 No. 2, Juli 2025 (In Progress)
Publisher : Program Studi Teknologi Rekayasa Internet, Politeknik Negeri Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25181/rt.v3i2.3923

Abstract

Companies face challenges in understanding customer spending patterns, which can lead to ineffective marketing strategies. Traditional customer segmentation approaches often fail to accurately identify groups with different consumption behaviors. Therefore, this study proposes the implementation of the K-Means algorithm combined with Principal Component Analysis (PCA) to segment customers based on their spending patterns. This study uses a dataset containing customer spending information across various product categories, including wine, meat, fish, sweets, fruits, and gold. The Elbow method is applied to determine the optimal number of clusters, followed by K-Means clustering. The results are visualized using PCA to facilitate the interpretation of customer spending patterns. The findings indicate that the optimal number of clusters is six, with the Within-Cluster Sum of Squares (WCSS) decreasing from 50,000 for one cluster to 29,000 for six clusters. Cluster 3 exhibits the highest spending, particularly on meat at 566.91 and fish at 183.58, whereas Cluster 0 has the lowest spending, with its highest value being only 91.60 for wine. Silhouette Score evaluation shows that K-Means achieves a score of 0.4745, outperforming the Gaussian Mixture Model (GMM) with 0.0674
Evaluasi Usability Aplikasi Sibersih UP3 Jambi Menggunakan System Usability Scale (SUS) Refriansyah, Evan
ROUTERS: Jurnal Sistem dan Teknologi Informasi Vol. 3 No. 2, Juli 2025 (In Progress)
Publisher : Program Studi Teknologi Rekayasa Internet, Politeknik Negeri Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25181/rt.v3i2.4167

Abstract

Digital transformation in public services encourages the development of internal information systems, such as the SIBERSIH application by PT. PLN (Persero) UP3 Jambi, which functions to record, report, and monitor the cleanliness of workspaces. The success of an application is not only determined by its features and technology, but also by its usability—how easy, efficient, and satisfying it is to use. Therefore, an initial usability evaluation of the SIBERSIH application was conducted using the System Usability Scale (SUS) method, which offers a simple and effective solution. This study contributes by providing an initial measurement of the usability quality of the SIBERSIH application based on direct experiences from early users. The method used in this study is the System Usability Scale (SUS), which consists of 10 questionnaire items with responses using a 5-point Likert scale. A total of 12 cleaning staff members were involved as early users. The data collected were analyzed using the standard SUS calculation formula. The evaluation results showed an average SUS score of 86.87. This score places the SIBERSIH application in the "acceptable" category within the acceptability range, receives a grade scale of B, and has an adjective rating of “excellent.” This means the application is considered very good and easy to use by non-technical users. This assessment indicates that the application meets the aspects of ease, convenience, and user satisfaction. In conclusion, the SIBERSIH application has a high usability rating and is well-received by early users. This evaluation provides a strong foundation for further development of the application to better support office cleanliness services.
Desain dan Rancang Bangun Sistem E-Learning Menggunakan Framework Laravel Berbasis WEB Jinan, Abwabul; Siregar, Manutur Pandapotan; Suryani, Dede Fika; Rolanda, Vicky; Muis, Abdul
ROUTERS: Jurnal Sistem dan Teknologi Informasi Vol. 3 No. 2, Juli 2025 (In Progress)
Publisher : Program Studi Teknologi Rekayasa Internet, Politeknik Negeri Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25181/rt.v3i2.4182

Abstract

The design and development of a web-based E-Learning system using the Laravel framework aims to provide an effective and structured digital learning solution. This system is developed to address the limitations of face-to-face learning time in traditional classrooms and to leverage technological advancements in order to enhance educational quality. Utilizing Laravel as the primary development framework, the system is built with PHP, HTML, CSS, and JavaScript technologies, and MySQL as the database engine. The E-Learning platform features core functionalities such as instructional material management, class administration, structured user accounts (admin, teacher, and student roles), as well as support for material download and task submission. Testing results indicate that the system performs effectively and supports flexible and efficient teaching and learning processes. It is expected that this system will serve as a reliable and sustainable learning medium to support technology-based academic activities.

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