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Muhammad Fauzan
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Perum Kanaya Land 2 no. 17 Rt. 01/RW. 03, kel. Kebonbatur, Kec. Mranggen, Kab. Demak, Jawa Tengah, Indonesia, 59567
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Router : Jurnal Teknik Informatika dan Terapan
Published by Asosiasi Riset Teknik Elektro Dan Informatika Indonesia
ISSN : 30263611     EISSN : 30323312     DOI : -
Core Subject : Science,
Computer Science & IT
Router : Jurnal Teknik Informatika dan Terapan merupakan jurnal penerbitan online yang mempunyai e-ISSN : 3032-3312 p-ISSN : 3026-3611 Jurnal ini fokus mempublikasikan berbagai hasil penelitian dari berbagai disiplin ilmu di bidang Teknik Informatika dan ilmu terapan. Router : Jurnal Teknik Informatika dan Terapan dengan menggunakan sistem Open Journal Sistem (OJS). Naskah yang diserahkan merupakan naskah asli atau hasil penelitian dan belum pernah dipublikasikan dimanapun. Jurnal ini terbit 1 tahun sebanyak 4 kali (Maret, Juni, September dan Desember).
Arjuna Subject : Ilmu Komputer (semua kategori) - Sistem Informasi
Articles 102 Documents
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Pengembangan Bisnis Startup Menggunakan Metode SWOT pada Platform Aplikasi Goto Gojek Tokopedia Nauroh Nazhiifah; Tata Sutabri
Router : Jurnal Teknik Informatika dan Terapan Vol. 2 No. 4 (2024): Desember: Router: Jurnal Teknik Informatika dan Terapan
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/router.v2i4.301

Abstract

Startups in Indonesia are growing very quickly which has an impact on the economy in Indonesia. High public enthusiasm is proven by Indonesia being one of the 5 countries with the highest number of startups in the world. There are several startups with good financial valuations that can be said to be unicoms or even decacorns. In this process, capital cannot be separated from the strategies taken by the Company. One alternative funding is to carry out an Initial Public Offering (IPO) on the Indonesia Stock Exchange (BEI). Until 2022, the startup that has carried out an IPO is PT. Goto Gojek Tokopedia conducted a Strength, Weakness, Opportunity, Threats (SWOT) analysis on the two companies to analyze the company's business strategy model. Method used in this research is a descriptive qualitative method and a data collection process by conducting literature studies from accredited scientific publication and digital news sources.
Implementasi Data Mining untuk Mengetahui Minat Baca Peserta Didik Menggunakan Naives Bayes pada Perpustakaan SMP Negeri 2 Palembang Tiara Siti Nadira; Tata Sutabri
Router : Jurnal Teknik Informatika dan Terapan Vol. 2 No. 4 (2024): Desember: Router: Jurnal Teknik Informatika dan Terapan
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/router.v2i4.302

Abstract

Students reading interest is a crucial factor in enhancing the quality of education. However, the lack of structured data makes it challenging to identify specific patterns of reading interest. This study aims to implement a data mining method using the Naive Bayes algorithm to analyze students' reading interest at SMP Negeri 2 Palembang's library. The data used includes book borrowing history, types of books, and library visit frequency over one semester. The analysis results indicate that the Naive Bayes method achieves an accuracy rate of 80% in classifying reading interest based on predetermined categories. These findings are expected to assist the school in designing more effective literacy programs.
Analisis Distribusi Frekuensi dan Uji Chi-Square pada Laju Pertumbuhan Penduduk dan Kepadatan Penduduk di Provinsi Kalimantan Tengah, 2023 Gedeon Gedeon; Yudha Rinsaghi; Tantri Tantri; Jadiaman Parhusip
Router : Jurnal Teknik Informatika dan Terapan Vol. 2 No. 4 (2024): Desember: Router: Jurnal Teknik Informatika dan Terapan
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/router.v2i4.328

Abstract

This study analyzes demographic data from regencies/cities in Central Kalimantan Province, including population, population growth rate, population percentage, population density per km², and sex ratio. The results of the analysis show significant differences between regencies/cities, with population growth rates ranging from 0.98% to 1.97% per year. The highest population density was recorded in East Barito, while Lamandau had the lowest density. The sex ratio tends to show a male dominance, with Lamandau having the highest ratio. These findings provide an overview of the challenges and opportunities in development planning, as well as the need to design policies that are in accordance with the demographic characteristics of each region. A deeper understanding of this data is expected to support more effective policies in population management and development in Central Kalimantan.
Identification of Flower Type Images Using KNN Algorithm With HSV Color Extraction and GLCM Texture Edhy Poerwandono; M. Endang Taufik
Router : Jurnal Teknik Informatika dan Terapan Vol. 3 No. 1 (2025): Maret: Router : Jurnal Teknik Informatika dan Terapan
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/router.v3i1.385

Abstract

Due to the variety of types of flowers that exist and having and tracking each variety, making plant lovers and cultivators difficult to distinguish in determining the type of flower, it takes a very long time to find out the type of flower if you only rely on the five senses. With the application of the K-Nearest Neighbor algorithm and feature extraction of color and texture, it is very helpful in image processing to identify flowers more easily and shorten the time, with the greatest accuracy of 71% using the K-7 value, the flower was successfully carried out.
Penerapan Algoritma Machine Learning dalam Prediksi Prestasi Akademik Mahasiswa Riska Rismaya; Dwi Yuniarto; David Setiadi
Router : Jurnal Teknik Informatika dan Terapan Vol. 3 No. 1 (2025): Maret: Router : Jurnal Teknik Informatika dan Terapan
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/router.v3i1.389

Abstract

This study explores the application of machine learning algorithms, specifically Linear Regression and Decision Tree Regressor, for predicting student academic performance using academic grade data from Kaggle. The analyzed factors include attendance, assignment grades, midterm exam grades, and final exam grades. The research methodology encompasses data collection, preprocessing, model development, training, and validation. This study contributes to the field of educational data analytics by demonstrating how machine learning can provide actionable insights into students' learning patterns and academic outcomes. The findings emphasize the effectiveness of Linear Regression for linearly distributed data and Decision Tree Regressor for capturing complex, non-linear relationships. The implications of this research suggest that machine learning models can assist educators in identifying key factors influencing student performance, enabling targeted interventions to enhance learning outcomes. Future research should explore larger, more diverse datasets and incorporate ensemble methods, such as Random Forest or Gradient Boosting, to improve model generalization and prediction accuracy. Additionally, integrating socio-economic and psychological factors could provide a more holistic perspective on academic achievement.
Analisis Sentimen Review Film Avatar 2 pada Platform IMDb Menggunakan LSTM dan GRU Rani Saputri; Anna Baita
Router : Jurnal Teknik Informatika dan Terapan Vol. 3 No. 1 (2025): Maret: Router : Jurnal Teknik Informatika dan Terapan
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/router.v3i1.395

Abstract

This research uses a deep learning-based sentiment analysis approach with several main stages, namely data collection, preprocessing, model preparation, and model building. In addition, this research also evaluates the impact of data splitting techniques on the model's performance during the training process.The evaluation results show that the LSTM-GRU model achieved the best performance on the character aspect, with an F1-score of 0.72 in the 90:10 splitting scenario. Meanwhile, the lowest F1-score was found in the editing aspect, with a value of 0.51 in the 80:20 splitting scenario. These findings indicate that the model is more effective in recognizing sentiment in narrative aspects compared to technical aspects. Furthermore, the data splitting technique significantly influences model performance, both in determining accuracy levels and in optimizing the model's effectiveness in identifying sentiment patterns more accurately.
Sistem Pengelolaan Sarpras Berbasis RFID di SMK Widya Praja Ungaran B. Suhartono; Yunus Ridwan
Router : Jurnal Teknik Informatika dan Terapan Vol. 2 No. 4 (2024): Desember: Router: Jurnal Teknik Informatika dan Terapan
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/router.v2i4.397

Abstract

In the current era of globalization and technology, computers, RFID are examples of information technology tools that are indispensable for meeting human needs in almost every aspect of life, including the management of infrastructure and equipment lending.According to direct research at Widya Praja Ungaran Vocational School, there are only two workers who handle facilities and infrastructure. In carrying out their work assignments, they still experience difficulties. Excess workload and the process of borrowing tools that still lacks a sense of responsibility, so that the results of the work are not maximized.The existence of increasingly sophisticated technology, the management of infrastructure and equipment lending can be done with the help of technological tools that will be implemented in this school. This research aims to make it easier to administer, because this school has not yet added a new workforce.This research can be designed with the help of software (Bootstrap, MySql), programming (PHP, Arduino IDE) and equipment (NodeMCU ESP8266, RFID, LCD, I2C, buzzer, power supply, breadboard, jumper cables, resistors, LEDs) to provide data information. more accurate, effective, efficient and provide a good working atmosphere in this school. It is hoped that this research can reduce work overload and create a sense of responsibility in borrowing equipment, using local networks (wifi / handphone) and computers or laptops, with the research method used is research and development (R&D).
Predicting Hotel Booking Cancellations Using Machine Learning for Revenue Optimization Andy Hermawan; Aji Saputra; Nabila Lailinajma; Reska Julianti; Timothy Hartanto; Troy Kornelius Daniel
Router : Jurnal Teknik Informatika dan Terapan Vol. 3 No. 1 (2025): Maret: Router : Jurnal Teknik Informatika dan Terapan
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/router.v3i1.400

Abstract

Hotel booking cancellations pose significant challenges to the hospitality industry, affecting revenue management, demand forecasting, and operational efficiency. This study explores the application of machine learning techniques to predict hotel booking cancellations, leveraging structured data derived from hotel management systems. Various classification algorithms, including Random Forest, XGBoost, and LightGBM were evaluated to identify the most effective predictive model. The findings reveal that XGBoost model outperforms other models, achieving F2-score of 0.7897. Key influencing factors include deposit type, total number of special requests, and marketing segment. The results underscore the potential of predictive modeling in optimizing hotel revenue strategies by enabling proactive measures such as dynamic pricing, targeted customer engagement, and improved overbooking policies. This study contributes to the ongoing advancements in data-driven decision-making within the hospitality industry, offering insights into how machine learning can mitigate financial risks associated with booking cancellations.
Pengembangan Pembelajaran Virtual Reality Berbasis Metaverse Menggunakan Metode ADDIE Arek Satria; Tata Sutabri
Router : Jurnal Teknik Informatika dan Terapan Vol. 3 No. 2 (2025): Juni: Router : Jurnal Teknik Informatika dan Terapan 
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/router.v3i2.409

Abstract

The application of Virtual Reality (VR) based on the Metaverse in education is an innovation that can enhance the quality of learning by providing a more interactive and immersive learning experience. This article discusses the development of VR-based learning integrated with the Metaverse using the ADDIE model (Analysis, Design, Development, Implementation, Evaluation). Through the stages of analysis, design, development, implementation, and evaluation, VR and Metaverse-based learning can be tailored to students' needs, creating a more flexible and collaborative learning experience. The use of this technology allows students to learn independently or in groups, while improving practical skills and creativity. This study shows that by applying the ADDIE model, VR and Metaverse-based learning can be more effective in increasing student motivation and learning outcomes, addressing the challenges of education in the future.
Penerapan Metodologi Agile dalam Pengembangan Perangkat Lunak Chandra Ramadhan; Mamok Andri Senubekti; Dien Amalia
Router : Jurnal Teknik Informatika dan Terapan Vol. 3 No. 2 (2025): Juni: Router : Jurnal Teknik Informatika dan Terapan 
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/router.v3i2.411

Abstract

This literature review discusses the application of Agile methodology in modern software development. Agile offers a flexible, iterative approach that contrasts with traditional waterfall models. The objective of this study is to provide insights into how Agile frameworks such as Scrum, Kanban, and Extreme Programming have influenced development speed, software quality, and team collaboration. Methodologically, the study synthesizes findings from recent academic and industrial literature from the last five years. The results show that Agile enhances adaptability and customer satisfaction, although challenges remain in large-scale implementations.

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