Brain tumors require rapid and accurate diagnosis, while manual segmentation of Magnetic Resonance Imaging (MRI) scans is time-consuming and highly dependent on expert knowledge. This study compares the performance of two deep learning architectures for brain tumor segmentation, namely 3D U-Net and Swin UNETR, trained and validated using the BraTS dataset and evaluated on unseen cases. Model pe…
The use of generative artificial intelligence (AI) technology has brought breakthroughs in game development, particularly in the visual novel genre. This research aims to develop adaptive dialogue systems based on generative AI, which can enhance player experience by creating more dynamic and personalized interactions. The system is designed to produce more varied dialogues by leveraging genera…
The rapid growth of digital financial services in Indonesia has accelerated the adoption of PayLater features across various online transaction platforms. This trend has led to diverse public opinions and sentiments, particularly on social media platform X (Twitter). This study aims to analyze public sentiment toward PayLater services and compare the performance of the Bidirectional Long Short-…
The rapid growth of Indonesian text content on social media has increased the need for automatic systems capable of accurately detecting humor, as humor often contains implicit meanings, wordplay, and cultural context. This study develops an Indonesian short-text humor detection system using a fine-tuning approach on the IndoBERT model. The objective of this research is to classify text into tw…
Islamic education plays an important role in shaping students’ character and intelligence through the integration of knowledge and Islamic values. In Palembang City, the increasing public interest in Islamic-based junior high schools (SMP) has created challenges for parents in selecting the most appropriate school due to limited information and the complexity of decision criteria, such as sch…
In the era of computer vision and machine learning advancement, the integration of gesture recognition technology in interactive gaming continues to evolve. This study aims to develop a multiplayer rock-paper-scissors game based on hand gesture detection using MediaPipe and real-time communication with Socket.IO. The MediaPipe Hands model is utilized to detect and classify hand gestures, while …
Penelitian ini berfokus pada sistem aplikasi pengajuan cuti pegawai Tugas Akhir di kelurahan Baturaja Permai, tujuan dari penelitian ini adalah untuk mempermudah para pegawai dalam mengajukan permohonan cuti. Metode penelitian yang dipakai pada laporan ini adalah dengan cara melihat langsung permasalahan yang ada ditempat, menganalisis permasalahan serta memikirkan solusinya. Solusi yang didapa…
The rapid growth of digital music platforms and the increasing availability of Indonesian song lyrics have created a demand for automatic emotion identification to support content analysis and mood-based recommendation. However, emotion classification in song lyrics is challenging due to subjective interpretation, figurative language, and class imbalance across emotion categories. This study ai…
This study addresses the critical challenge of micro-scale face detection in lowresolution surveillance imagery by proposing a hybrid pipeline integrating YOLOv11-pose, Slicing Aided Hyper Inference (SAHI), and Real-ESRGAN using a two-phase methodology on the WIDER FACE dataset enriched with 5-point landmark annotations. The first phase focuses on architectural optimization, where YOLOv11s-pose…
Audio in video games plays a crucial role in creating an immersive and engaging gaming experience. However, indie game developers often face resource constraints, particularly in producing high-quality character voices. Voice cloning technology based on Retrieval-based Voice Conversion (RVC) offers an innovative solution by enabling accurate voice replication and transformation using minimal da…
Sentiment analysis is a branch of Natural Language Processing (NLP) used to determine public opinions on specific topics as positive, negative, or neutral. This study aims to compare the performance of two feature extraction methods across three scenarios: TF-IDF, Word2Vec-CBOW, and Word2Vec-skipgram. The dataset utilized consists of comments from the Instagram platform @magangmerdeka regarding…
Chest X-ray (CXR) is a vital diagnostic modality for detecting lung diseases, yet manual interpretation is often hindered by low contrast and overlapping anatomical structures. Automatic lung segmentation serves as a crucial pre-processing step in Computer-Aided Diagnosis (CAD) systems. The standard U-Net architecture, despite its popularity, suffers from a "semantic gap" between encoder and de…
Choosing the right academic supervisor is an important part of writing a thesis, but many students struggle to find the best fit. This study introduces a recommendation system that combines Content-Based Filtering (CBF) and Collaborative Filtering (CF). As part of Natural Language Processing (NLP), the CBF component applies TF-IDF and cosine similarity to process and measure how well a studentâ…
The vast diversity of Indonesian cuisine often leads to information overload and the "paradox of choice" for users. Existing conventional search systems are unable to understand specific personal preferences, necessitating an intelligent recommendation system. This research aims to (1) design and build a hybrid Indonesian food recommendation system model combining the Long Short-Term Memory (LS…
This research addresses the challenge users face in discovering board games that align with their preferences, particularly when those preferences are expressed descriptively in text. Traditional recommendation systems often struggle to capture the semantic nuances within natural language queries and effectively balance these with specific attribute criteria. To overcome this limitation, this s…
Facial paralysis is a condition characterized by the loss of motor function in the facial muscles and requires accurate clinical evaluation. Conventional visual assessments are often subjective, creating variability in diagnosis; therefore, a more consistent image-based assistance system is needed. This study develops an automated classification system for facial paralysis severity using the VG…
TikTok social media has evolved into one of the most popular digital platforms; however, its comment sections are frequently misused for the covert promotion of online gambling. The text disguise patterns employed by perpetrators render manual moderation mechanisms difficult and inefficient. This study performs text classification on online gambling comments. The method employed is Long Short-T…
This study proposes an image steganography architecture based on a modified U-Net integrated with Convolutional Spatial Attention (CSA) on the cover stream and a Laplacian-based Residual Map on the Y-channel, designed to produce an embedding probability map that more selectively targets textured regions. The model generates a residual embedding which is inserted using a ±1 modulation scheme wi…
This study implements the LayoutLM model for the Named Entity Recognition (NER) task to extract nutritional information from packaged food labels. The LayoutLM architecture was chosen for its ability to integrate textual and spatial layout information (bounding boxes), overcoming the limitations of text-only models in processing semi-structured documents. The model was fine-tuned using the open…
Colorectal cancer is a leading cause of cancer-related deaths globally, predominately developing from adenomatous polyps. While colonoscopy is the gold standard for polyp detection, it suffers from a miss rate of 26% due to operator fatigue and visual variability. This study aims to develop a real-time Computer-Aided Diagnosis (CADx) system for polyp segmentation using the efficient YOLOv11-Seg…
Job vacancy information is now more accessible to the public. However, this ease of access also has a negative impact, namely the increased ease with which fake job vacancies can be spread, causing harm to job seekers. Therefore, this study aims to develop a model based on Bidirectional Encoder Representation from Transformers (BERT) to classify genuine and fake job vacancies. The dataset used …
The massive growth of digital information, especially in the form of news articles, demands a system that is able to filter important information efficiently. Abstractive text summarization is a strategic solution in summarizing information by producing new sentences that still represent the main content of the source text. This study aims to apply the Bidirectional and Auto-Regressive Transfor…
Security in authentication systems is a crucial aspect of protecting user data and identity. One approach that can be applied is keystroke dynamics, which analyzes typing patterns as a form of behavioral biometric characteristics. This study aims to develop and evaluate a machine learning based classification model using the Random Forest algorithm to identify user typing patterns. The dataset …
This study develops a food image classification system for Indonesian traditional dishes based on Convolutional Neural Network to support the digitalization of internal processes in the culinary sector, particularly for automatic food identification and menu management. The model is built using the EfficientNet family and evaluated on a dataset consisting of 30 classes of Indonesian traditional…
Communication is very important for humans in their daily lives. However, for people with hearing impairments, this can be a problem. Many people do not understand the sign language used by people with hearing impairments. In order to communicate with people with hearing impairments, people must learn sign language. Therefore, a system that predicts sign language movements based on sound can he…
Pneumonia is a lung infection caused by various pathogens and poses a global health threat with a high mortality rate. The World Health Organization (WHO) reports that pneumonia caused approximately 740,180 deaths among children under five years of age in 2019, making early detection essential. Pneumonia is generally diagnosed using chest X-ray images because they are inexpensive, easily access…
The increasing problem of drug abuse has made it difficult for families to determine whether noticeable changes in a person’s behavior are normal or early signs of addiction. To address this challenge, this study develops an addiction-screening system using the Fuzzy Tsukamoto method combined with Particle Swarm Optimization (PSO). The system assesses four main indicators—physical, psycholo…
Artificial intelligence in video games plays an important role in managing the behavior of non-player characters (NPC) to make them appear dynamic and unpredictable. One method often used is the Finite State Machine (FSM), but this method has limitations because the transitions between states are deterministic and not varied. This study aims to design and implement a Probabilistic Finite State …
Intrusion Detection System (IDS) plays a critical role in maintaining network security by identifying abnormal or potentially malicious activities. However, the increasing complexity and volume of network traffic in distributed environments pose challenges for conventional detection systems in terms of accuracy and real-time capability. This study proposes an unsupervised learning-based IDS usi…
Indonesia has a high prevalence of active smokers, reaching 70.6% among adult males in 2019. Smoking is known to cause various physical changes in facial skin, such as accelerated aging and wrinkles. This research aims to develop and test an automated system for classifying smokers based on facial physical characteristics using a deep learning approach. The method used is Transfer Learning, uti…