Integrasi Industrial Internet of Things (IIoT) dalam sistem gardu listrik telah meningkatkan efisiensi operasional tetapi juga meningkatkan kerentanan terhadap ancaman siber, khususnya serangan Man-in-the-Middle (MITM) di mana informasi diubah dan stabilitas jaringan terpengaruh. Tulisan ini menyajikan struktur Deep Neural Network (DNN) yang didedikasikan untuk mengidentifikasi serangan Man-in-…
Indicator of Compromise (IoC) merupakan artefak digital penting dalam Cyber Threat Intelligence (CTI), seperti IP address, domain, URL, hash file, dan nama malware, yang digunakan untuk membantu identifikasi aktivitas berbahaya. Ekstraksi IoC dari teks CTI masih menjadi tantangan karena data umumnya bersifat semi-terstruktur serta mengandung variasi istilah teknis yang kompleks. Penelitian ini …
The rapid growth of social media has enabled the misuse of comment sections as a medium for promoting online gambling. The high volume of comments makes manual moderation ineffective, thus requiring an automated classification system. This study aims to develop a classification system for online gambling comments using the IndoBERT model and to evaluate its performance based on accuracy, precis…
Medical metal waste such as syringes and scalpels are Hazardous and Toxic Waste (B3) which has the potential to cause injury, infection, and environmental pollution if not managed properly. This study aims to design and build a medical metal waste classification system based on ESP32-CAM with integrated inductive metal sensors to assist the automatic waste sorting process. The research method u…
Air quality is an important environmental element that needs to be continuously monitored, especially in urban areas. Air quality data collected from sensors is often not displayed in a website format that is easily accessible and understandable by users. This research aims to design and develop a website-based air quality dashboard using the Laravel framework. Data is obtained from various air…
3D video streaming services require a network infrastructure capable of supporting large-scale data transmission in a stable and efficient manner. A Content Delivery Network (CDN) plays an important role in improving content distribution performance by bringing servers closer to end users. This study aims to analyze the performance of the Cloudflare CDN in terms of Quality of Service (QoS) and …
The internship application process at the Management Informatics Study Program of Sriwijaya University still uses Google Form with document management that is not yet integrated, causing the administration and monitoring process to become less effective. This study aims to develop a web-based Internship Application Information System (SIKP) that can support the internship submission, verificati…
Medical waste is a type of waste that requires special handling because it can affect health and the environment if not properly managed. One important stage in managing medical waste is sorting it by type. However, sorting, which is still done manually, can be prone to errors in categorising waste. Therefore, a monitoring system for sorting wet, dry, and metal medical waste based on the Intern…
Medical waste generated from operating rooms has the potential to pose risks to health and the environment if not properly managed. One of the important stages in medical waste management is the waste sorting process based on its characteristics. However, the sorting process is still largely carried out manually, which risks causing sorting errors and increasing direct contact with infectious w…
Flooding is one Malware is one of the major threats to cybersecurity and continues to evolve, making it increasingly difficult to detect using conventional methods. This study aims to implement and analyze the State-Action-Reward-State-Action (SARSA) and Deep Q-Network (DQN) algorithms for binary malware classification based on static features extracted from the dataset. Data preprocessing, fea…
The development of Internet of Things (IoT) technology has encouraged the creation of monitoring systems capable of transmitting and displaying sensor data quickly and in real-time. Web-based sensor data streaming systems have become one of the solutions to simplify the process of monitoring environmental conditions through internet networks. This research focuses on the design and development …
Hypothermia is a condition in which body temperature drops below the normal limit because the body loses heat faster than it can produce it. This condition can be influenced by low environmental temperature and humidity, which may endanger human health. This study aims to design an Internet of Things (IoT)-based body and environmental temperature monitoring system with the implementation of Mam…
Congenital heart disease in children requires accurate early detection through ultrasonography (USG) imaging. This study aims to develop a deep learning–based system for view classification and hole segmentation in pediatric cardiac images. A Vision Transformer (ViT) model was employed to classify five cardiac views (4CH, 5CH, LA, SA, and SUB), while segmentation was performed using YOLO11-se…
In this study, the feature selection method employed is the Genetic Algorithm (GA), while the classification method used is the Support Vector Machine (SVM), with the aim of improving the performance of myocardial infarction disease classification. The study utilizes the Myocardial Infarction Complications dataset, which consists of 123 features. The research process includes several preprocess…
Myocardial infarction complications require early, accurate prediction for clinical intervention. This study optimizes the K-nearest neighbor (KNN) algorithm to classify these complications using Z-Score normalization and three feature selection methods: Information Gain, Gain Ratio, and Symmetrical Uncertainty.Using a dataset from the UCI Machine Learning Repository, preprocessing included mea…
Flooding is one of the most common natural disasters and can cause significant losses. This study aims to design and develop an Internet of Things (IoT)-based flood warning system using the Random Forest algorithm. The system utilizes BMP280 sensors to measure water level and an optocoupler sensor to measure water flow velocity. Sensor data are processed by an ESP32 microcontroller and sent to …
Monitoring vital signs such as heart rate, oxygen saturation, and body temperature is a primary indicator for the early detection of a person's health condition. However, conventional monitoring is often still manual and limited by distance, making it inefficient for continuous supervision. This research aims to design an Internet of Things (IoT)-based health monitoring system capable of presen…
Advanced Persistent Threat (APT) reports in Cyber Threat Intelligence (CTI) are generally presented as unstructured text, making them difficult to analyze manually and requiring automated methods to extract important entities quickly and accurately. This study aims to analyze the performance of Named Entity Recognition (NER) using a Bidirectional Long Short-Term Memory (BiLSTM) model with two s…
Penelitian ini bertujuan untuk mengembangkan sistem ekstraksi Indicator of Compromise (IoC) dari teks Cyber Threat Intelligence (CTI) menggunakan pendekatan Named Entity Recognition (NER). Permasalahan utama dalam CTI adalah data yang bersifat semi-terstruktur sehingga menyulitkan identifikasi informasi penting secara manual. Metode yang digunakan adalah model BiLSTM-CRF dengan skema BIO untuk …
Digital game development requires efficient pathfinding algorithms. This study compares A* and Jump Point Search (JPS) in a hill-climbing adventure game based on Roblox. The three-dimensional terrain was converted into a 181x209 uniform-cost two-dimensional grid with a cell size of 4 Roblox units. Both algorithms were implemented in Roblox Studio using Lua and the octile distance heuristic for …
The advancement of medical imaging technology has produced increasingly complex data that require fast and accurate analysis. However, the interpretation of medical images still requires considerable time, relies heavily on medical professionals, and is prone to interpretation errors. Therefore, this study aims to develop an Image Captioning system capable of automatically generating descriptio…
Diagnosis of congenital heart disease in children, namely Atrial Septal Defect (ASD), Atrioventricular Septal Defect (AVSD), and Ventricular Septal Defect (VSD), is hindered by the limited availability of cardiologists in interpreting echocardiography images, necessitating an automated system based on artificial intelligence. This study implements and evaluates a deep learning-based image capti…
Ultrasound (USG) image analysis for detecting Congenital Heart Disease (CHD), such as Atrial Septal Defect (ASD), Ventricular Septal Defect (VSD), and Atrioventricular Septal Defect (AVSD), is still limited by the scarcity of clinical datasets. This study evaluates three Generative Adversarial Network (GAN) architectures, namely Deep Convolutional GAN (DCGAN), Wasserstein GAN with Gradient Pena…
Smart farming requires a reliable server infrastructure to handle real-time data requests. The use of a single server may cause overload and reduce service performance. This study aims to implement a Docker Swarm-based load balancing system for smart farming servers using Single Board Computers in the form of Raspberry Pi. The system architecture consists of one manager node and two worker node…
This research is entitled "Development of AI-Based Interactive Infographics on the Tonarigumi Social Institution During the Japanese Occupation at SMA Negeri Plus 2 Banyuasin III." The problem in this research focuses on how to develop interactive infographic media based on Artificial Intelligence that meets the criteria for validity and practicality as a history learning medium. The purpose of…
This study aims to analyze the effectiveness of plenary meetings held by the Trial and Legislation Section at the Bangka Regency DPRD Secretariat. The research problem stems from the postponement and cancellation of meetings, which impact the regularity of the agenda and the effectiveness of decision-making. The analysis used Stephen P.Robbins' (1990) Systems Approach, which assesses effectiven…
The rapid advancement of computer vision and deep learning has greatly improved image classification performance. However, maintaining consistent accuracy across diverse datasets and visual conditions remains challenging. This study proposes a soft voting ensemble learning approach for image classification using three fine-tuned Convolutional Neural Networks (CNNs): ResNet, EfficientNet, and De…
Pengelolaan keuangan pada Homeschooling Sriwijaya Kids sebelumnya masih sangat bergantung pada ketelitian pegawai, sehingga berisiko menimbulkan kesalahan pencatatan, data ganda, keterlambatan rekapitulasi, serta kesulitan dalam penyusunan laporan keuangan. Penelitian ini bertujuan untuk merancang dan membangun aplikasi pengelolaan keuangan berbasis web yang dapat membantu proses pencatatan, pe…