https://journal.univpancasila.ac.id/index.php/jiac/issue/feed Journal of Informatics and Advanced Computing (JIAC) 2024-09-04T13:26:44+00:00 Ionia Veritawati ionia.veritawati@univpancasila.ac.id Open Journal Systems https://journal.univpancasila.ac.id/index.php/jiac/article/view/7291 Sistem Informasi Manajemen Inventori Berbasis Website Untuk Proses Operasional PT Bumi Bara Sakti 2024-09-04T13:26:31+00:00 Faeqal Hafidh Muhammad Asfian eqalasfiant@gmail.com Desti Fitriati desti.fitriati@univpancasila.ac.id <p><em>Inventory plays a crucial role in the operational management of companies, ensuring smooth supply chains and business continuity. Bumi Bara Sakti (BBS), a coal trading company, relies on accurate inventory management. But, BBS faces difficulties in managing inventory data due to a high volume of transactions, leading to heavy workloads and information delays. Additionally, limited Excel proficiency among BBS executives and employees deepens these issues. This study aims to create a web-based Inventory Management Information System using the waterfall method, MySQL for database management, and CodeIgniter4 as the framework. The research mainly focuses on recording coal sales and purchases, total stock, and truck movements to stockpiles based on data obtained from BBS. The system is expected to facilitate real-time recording of purchases, sales, and stock updates while maintaining information accuracy. Furthermore, it provides data visualization and easily understandable reports. Evaluation results indicate that the Inventory Management Information System simplifies inventory data management and data interpretation for BBS executives and employees.</em></p> 2024-05-01T00:00:00+00:00 Copyright (c) 2024 Journal of Informatics and Advanced Computing (JIAC) https://journal.univpancasila.ac.id/index.php/jiac/article/view/7271 Implementation of MikroTik Failover Router to Enhance Network Availability at Faculty of Engineering Pancasila University 2024-09-04T13:26:35+00:00 Husein Zidan zidan.idros14@gmail.com Zahra Jane Arnecia zahrajanearnc@gmail.com Leni Oktaviani oktavianileni28@gmail.com Gina Anisa ginaannisa55@gmail.com Bambang Riono Arsad bambang.riono@univpancasila.ac.id <p>Technology can help manage connectivity that can support data exchange in the network. Using a well-designed topology can improve network performance optimally. The use of computer networks in agencies can enable data exchange via hardware and software that are connected to each other in a network. Topology implementation can be adjusted to user needs. In this research, the author used the Informatics Engineering Study Program building at Pancasila University as an object. Please be aware that the network can experience problems, such as stopping system performance which can hinder the data exchange process that is taking place. The solution provided can be in the form of implementing failover using a MikroTik router. MikroTik routers can be used as backup routers in server infrastructure and failover is an automatic or manual process for switching from a system or component that is failing to a backup system or component that is functioning properly. This can be a strategy and factor in increasing network availability in the Pancasila University engineering faculty building. The final result of the analysis carried out is a MikroTik failover design that will be used in the Pancasila University Faculty of Engineering building.</p> 2024-05-01T00:00:00+00:00 Copyright (c) 2024 Journal of Informatics and Advanced Computing (JIAC) https://journal.univpancasila.ac.id/index.php/jiac/article/view/7198 Perbandingan Metode Decision Tree dan Naive Bayes untuk Memprediksi Thyroid Cancer Recurrence 2024-09-04T13:26:41+00:00 Fidya Hafizd fidyahafizd234@gmail.com Dian Rizky Julyani rizkyjulyanidian@gmail.com Hasna Yuliza yulizahasna@gmail.com Emely Nemy Agustine nemyagustine31@gmail.com Kessya Immanuella Surbakti kessya.surbakti18@gmail.com Iman Paryudi iman.paryudi@univpancasila.ac.id <p><em>Abstract – This study aims to predict thyroid cancer recurrence by comparing two data mining methods, namely </em><br><em>Decision Tree and Naive Bayes. The data used is classification data that has gone through preprocessing and </em><br><em>modeling processes, then tested using test and score tests on analysis software called Orange. By using Orange </em><br><em>as an analysis tool, experiments were conducted to determine which method gave the best accuracy. The results </em><br><em>show that the two methods have different accuracy comparisons in predicting thyroid cancer recurrence. This </em><br><em>research is expected to help in identifying symptoms that are at high risk of causing thyroid cancer recurrence </em><br><em>and provide valuable insights in data analysis.</em></p> 2024-05-01T00:00:00+00:00 Copyright (c) 2024 Journal of Informatics and Advanced Computing (JIAC)