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INDONESIA
JOURNAL OF APPLIED INFORMATICS AND COMPUTING
Published by Politeknik Negeri Batam
ISSN : -     EISSN : 25486861     DOI : 10.3087
Core Subject : Science,
Computer Science & IT
Journal of Applied Informatics and Computing (JAIC) Volume 2, Nomor 1, Juli 2018. Berisi tulisan yang diangkat dari hasil penelitian di bidang Teknologi Informatika dan Komputer Terapan dengan e-ISSN: 2548-9828. Terdapat 3 artikel yang telah ditelaah secara substansial oleh tim editorial dan reviewer.
Arjuna Subject : -
Articles 695 Documents
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Performance Analysis of the Item-Based Collaborative Filtering Model in Yogyakarta Tourism Recommendations Dewi, Melany Mustika; Andriani, Ria; M. Nuraminudin
Journal of Applied Informatics and Computing Vol. 9 No. 2 (2025): April 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i2.8866

Abstract

Yogyakarta is one of the most popular tourist destinations in Indonesia, offering a variety of attractions ranging from beaches and mountains to historical sites. This diversity poses a challenge for tourists in selecting destinations that match their preferences. This study employs the Item-Based Collaborative Filtering method to recommend tourist destinations based on the similarity between attractions, calculated using cosine similarity. The data analyzed includes 1,069 tourist destinations in Yogyakarta, obtained from Google Maps API, Scrapetable, and Outscraper. The results indicate that the developed recommendation model achieves high accuracy with a Mean Absolute Error (MAE) of 2.537. Compared to previous approaches, this method improves the relevance and quality of recommendations, helping tourists find destinations that suit their preferences. This study contributes to the development of more personalized and effective recommendation systems for the tourism sector.
Optimization of Inventory Management with QR Code Integration and Sequential Search Algorithm: A Case Study in a Regional Revenue Office Fajar, Moh; Azhar, Ryfial; Anshori, Yusuf; Laila, Rahma; ., Rinianty; Lapatta, Nouval Trezandy
Journal of Applied Informatics and Computing Vol. 9 No. 2 (2025): April 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i2.8919

Abstract

Inventory management at a government office was previously conducted manually, leading to issues such as data inaccuracies, delays in item searches, and low work efficiency. This study develops a web-based inventory management system integrated with QR Code technology and a sequential search algorithm to address these challenges. The system was developed using the prototyping method, with iterative design based on user feedback until the final version met the office's operational needs. Key features of the system include digital inventory recording, item tracking using QR Codes, and real-time information access through a web-based interface. The system was tested in two stages: simulation and direct implementation in a real-world environment, involving 10 respondents to evaluate effectiveness and usability. The test results showed a 95% improvement in data recording accuracy, a 60% reduction in item search time, and an average user satisfaction score of 77.25 based on the System Usability Scale (SUS). This research successfully improved inventory management efficiency and demonstrated the system’s potential for adoption by other similar organizations, with modular adjustments tailored to their needs.
Implementation of LSTM Method on Tidal Prediction in Semarang Region Ambadar, Panreshma Rizkha; Novitasari, Dian C Rini; Farida, Yuniar; Hafiyusholeh, Moh; Setiawan, Fajar
Journal of Applied Informatics and Computing Vol. 9 No. 2 (2025): April 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i2.8932

Abstract

Semarang is the capital of the Central Java province, located in the north and directly adjacent to the Java Sea. Having an almost flat land condition with a slope of about 0-2%, Semarang City has the opportunity to experience tidal flooding. The occurrence of tides does not have a fixed period. So, it is necessary to predict the height of the tide and the ebb of the seawater. Thus, this research aims to predict tides in the Semarang area using the LSTM method. The data used is tidal data in Semarang waters from 2020 to 2024. The advantage of the LSTM method is its ability to effectively remember time series data or data with long-term dependence. LSTM can store past information using special cells contained in its structure. This research on tidal prediction using the LSTM method with 70% training data trial batch size 32 and epoch 200 obtained the smallest error value, namely the MAE value of 0.0388 and MAPE of 0.0313 which is the best LSTM result.
Optimization of Application Deployment Architecture in Container Orchestration Fachrudin, Mochamad Rizal; Muslikh, Ahmad Rofiqul
Journal of Applied Informatics and Computing Vol. 9 No. 2 (2025): April 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i2.8972

Abstract

Container orchestration has become a widely adopted standard for application deployment among medium to large-scale organizations. Docker Swarm is one of the popular container orchestration tools due to its relatively simple configuration. However, if the Docker Swarm cluster architecture is not properly designed, the goal of container orchestration, which is availability, cannot be achieved optimally. Challenges such as centralized traffic on a single node and service dependency on a single node are critical issues that need to be addressed. This study proposes solutions through an experimental approach involving the design, implementation, testing, and evaluation of a Docker Swarm cluster architecture to address these challenges. The results of this study demonstrate that the proposed architecture successfully resolves these issues. Traffic can be distributed more evenly across all nodes. When only one node is available, 5 out of 10 requests can be handled with a response latency of 197.4 ms. With two nodes available, the number of requests handled increases to 7 out of 10, with a response latency of 534.86 ms. The greater the number of available nodes, the more requests can be successfully processed. Services also become more flexible, and capable of running on any node, while offering additional benefits such as dual load balancing through DNS-based load balancing and the default load balancing provided by Docker Swarm's routing mesh. However, limitations such as the need for more complex adjustments and configurations should be considered, especially when implementing this architecture in on-premise environments, to ensure the best adoption and results.
Evaluation of Wireless LAN Quality of Service (QoS) in Primary Education Using TIPHON Standards Oktaseli, Hizkiana Ruli; Slameto, Andika Agus
Journal of Applied Informatics and Computing Vol. 9 No. 2 (2025): April 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i2.8979

Abstract

In the current digital era, internet connectivity in schools is crucial to support teaching and learning activities. SD Negeri 2 Sumber has implemented a wireless LAN network to provide internet access for students and teachers. This study aims to evaluate the network performance by measuring Quality of Service or QoS parameters, namely throughput, packet loss, delay, and jitter. The evaluation was conducted using Wireshark to monitor network traffic. The results show that the average throughput for video streaming is 4.251 Kbps, browsing is 1.425 Kbps, and downloading is 3.106 Kbps. The average packet loss is 1.66 % for video streaming, 4.6 % for browsing, and 2.66 % for downloading. The average delay for video streaming is 1.64 ms, browsing is 5.92 ms, and downloading is 2.32 ms. The average jitter is 1.62 ms for video streaming, 5.92 ms for browsing, and 2.16 ms for downloading. Based on the QoS parameters, the network quality is categorized as good according to TIPHON standards with a final score of 3.75. Although the overall network quality is good, there are several areas that need optimization, such as browsing activities, which show slightly higher throughput and jitter compared to other activities. This study provides a clear overview of wireless network performance and offers recommendations for further optimization to enhance user experience, particularly in activities involving browsing and school administration.
The Role of Marketplaces in Assisting MSME Growth Using the Systematic Literature Review Method Sari, Rizqi Kurnia; Syaputra, Muhammad Adie
Journal of Applied Informatics and Computing Vol. 9 No. 2 (2025): April 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i2.8981

Abstract

Digital technology provides significant opportunities for Micro, Small, and Medium Enterprises (MSMEs) to grow and innovate, contributing to national economic growth. This study aims to analyze the role, impact, and supporting factors of marketplaces in fostering MSME development in Indonesia. Using the Systematic Literature Review (SLR) method, 103 journals were identified through Publish or Perish via Crossref for the 2019–2024 period. These journals were then filtered down to 40 journals selected for descriptive analysis. The 2019–2024 timeframe was chosen as it reflects a significant surge in marketplace adoption during the COVID-19 pandemic.The findings reveal that marketplaces significantly enhance MSMEs by increasing market reach by up to 40%, improving operational efficiency through a 30% reduction in order processing time, and building customer trust through reviews and ratings. The study also highlights the importance of supporting factors such as adequate digital infrastructure, digital literacy, and support from the government and platform providers. However, challenges such as limited internet access, low digital literacy, high commission fees, and intense competition with larger brands hinder the optimal use of marketplaces by MSMEs.This study recommends several practical solutions, including strengthening digital infrastructure, subsidizing internet costs, providing digital literacy training, and offering special promotion programs for small MSMEs. Although this study relies on secondary data, the findings provide relevant insights for policymakers, platform providers, and MSME actors. Further studies using primary data are needed to enhance the generalizability of these findings.
Twitter Sentiment Analysis on Digital Payment in Indonesia Using Artificial Neural Network Febriani, Siska; wati, Vera; Wijayanti, Yuli; Siswanto, Irwan
Journal of Applied Informatics and Computing Vol. 9 No. 2 (2025): April 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i2.8988

Abstract

In the rapid development of technology, the need for big data processing is increasingly important, especially in the context of digital transactions such as e- wallets in Indonesia. On the other hand, sentiment analysis of digital payment platforms via Twitter requires fast and accurate data processing, but often faces challenges in managing big data and optimal classification quality. This study uses the Term TF-IDF method for text preprocessing and Artificial Neural Network (ANN) for sentiment classification. The preprocessing process includes case folding, removing numbers and punctuation, tokenization, filtering, and stemming. For classification, ANN is used which is optimized with the Backpropagation and K-fold Cross Validation algorithms to improve the accuracy of the model in grouping positive and negative sentiments from tweets about digital payment platforms. Through this approach, the study produces a sentiment classification model in analyzing big data. The results in this study are Gopay gets a positive value and gets the first value in sentiment assessment with an accuracy rate of 72% using ANN. Of the 5 digital payments that received a negative value and ranked last, namely Link Aja with an achievement rate of 43%. Based on these results, it shows that this approach contributes to identifying consumer sentiment towards e-wallet platforms, which is useful for developing digital marketing strategies. The contribution given is in improving sentiment analysis of digital payment platforms by utilizing Big Data processing technology and machine learning, so that it can be used to improve services and marketing strategies based on user data.
Prediction of Corrosion Inhibitor Efficiency Based on Quinoxaline Compounds Using Polynomial Regression Rana, Bastion Jader; Setiyanto, Noor Ageng; Akrom, Muhamad
Journal of Applied Informatics and Computing Vol. 9 No. 2 (2025): April 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i2.9031

Abstract

Corrosion is a natural process that leads to material degradation due to environmental factors. It significantly impacts financial and safety aspects, including structural weakening and economic losses in various industries such as oil, gas, and nuclear. Corrosion inhibitors, especially organic compounds like quinoxaline, are widely used to reduce corrosion by forming protective layers on metal surfaces. Quinoxaline compounds, characterized by their heterocyclic structure with nitrogen atoms, demonstrate promising inhibition efficiency in corrosive environments. In this study, machine learning (ML) approaches are utilized to predict the corrosion inhibition efficiency of quinoxaline compounds. Algorithms such as Gradient Boosting Regressor (GBR), Extreme Gradient Boosting Regressor (XGBR), and Automatic Relevance Determination (ARD) regression are compared. The implementation of polynomial functions significantly improves the prediction accuracy of these models. Among them, GBR achieved the best value with MSE, RMSE, MAE, MAPE, and R2 values of 0.0000001, 0.0003229, 0.0000029, 0.0002294, and 0.999999998, respectively. These findings highlight the potential of polynomial-enhanced ML models in accurately predicting corrosion inhibition efficiency. Moreover, the study demonstrates the viability of GBR as a reliable tool for analyzing and optimizing corrosion inhibitors for industrial applications.
Long Short-Term Memory as a Rainfall Forecasting Model for Bogor City in 2025-2026 Fadhilah, Nur Anggraini; Dzulhij Rizki, Muhammad Abshor; Azahran, Muhammad Ryan; Arbaynah, Siti; Antique Yusuf, Rakesha Putra; Angraini, Yenni; Nurhambali, Muhammad Rizky
Journal of Applied Informatics and Computing Vol. 9 No. 2 (2025): April 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i2.9068

Abstract

Indonesia is a country with a tropical climate that has unique and changing weather patterns. Accurate rainfall prediction can help local governments, farmers, and the broader community plan activities that depend on rainfall patterns. This research aims to develop a rainfall prediction model for Bogor City using past rainfall data in Bogor City, which is known as an area with high rainfall levels and dynamic rainfall patterns. The analysis utilizes rainfall data recorded by the JAXA satellite from January 1, 2014, to December 31, 2024. The prediction method implemented in this research is the long short-term memory (LSTM). The LSTM modelling process evaluates various models by comparing RMSE, MAE, and correlation values through expanding window cross-validation, selecting the model with the lowest average RMSE and MAE with the highest correlation as the optimal choice. The best-performing model was achieved with 25 epochs and a batch size of 1, resulting in an average RMSE of 56.3340, MAE of 35.5223, and correlation of 0.3209. This best-performing model is then employed to predict rainfall for the next two years. The results show significant daily variations in the predicted rainfall but can capture existing seasonal patterns.
Enhancing Website Security Using Vulnerability Assessment and Penetration Testing (VAPT) Based on OWASP Top Ten Rohmaniah, Diana; Ashari, Wahid Miftahul; Lukman, Lukman; Putra, Andriyan Dwi
Journal of Applied Informatics and Computing Vol. 9 No. 2 (2025): April 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i2.9069

Abstract

Website security is one of the main concerns in the digital era, given the increasing potential for cyber threats. This research aims to improve website security by using the Vulnerability Assessment and Penetration Testing (VAPT) method that refers to the OWASP Top Ten standard. The applied method includes four main stages: information gathering, vulnerability scanning, exploitation, and reporting. The results showed that there were several successfully exploited vulnerabilities, such as Clickjacking, Improper HTTP to HTTPS Redirection, Directory Listing, and Sensitive Information Disclosure, which were classified based on the OWASP Top Ten. The severity of the vulnerabilities was analyzed using Common Vulnerabilities and Exposures (CVE), Common Weakness Enumeration (CWE), and Common Vulnerability Scoring System (CVSS). The analysis results show that some vulnerabilities have high severity after considering the factual conditions of the system. This research provides specific remediation recommendations to address these vulnerabilities, such as the implementation of security headers, deletion of sensitive configuration files, and dependency updates. With this approach, the research is expected to contribute to improving website security and provide effective mitigation guidelines.

Page 31 of 70 | Total Record : 695

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