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IMPUTASI DATA MEDIS HATI KRONIS MENGGUNAKAN ALGORITMA K- NEAREST NEIGHBORS IM…
Medical data related to chronic liver disease often contain missing values that can reduce the quality of data analysis and the accuracy of predictive models. Handling missing values properly is essential to ensure optimal classification performance. This study aims to apply and evaluate the K-Nearest Neighbor (KNN) Imputation method to address missing values in a medical dataset of liver cirrh…
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- xiii, 101 hlm.; ilus.; tab.; 29 cm
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- T1901092025
ANALISIS SENTIMEN PENGGUNA MEDIA SOSIAL X MENGENAI PINJAMAN ONLINE DENGAN PER…
The rapid development of technology and social media has transformed the way people express their opinions on various issues, including online loan services. Application X has become a primary platform for users to openly share their views. This study aims to analyze user sentiment toward online loan services by comparing the performance of the XGBoost and Random Forest algorithms. From an init…
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- xiii, 87 hlm.; ilus.; tab.; 29 cm
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- T1901022025
KLASIFIKASI TULISAN TANGAN ARAB DENGAN HYBRID MOMENT INVARIANT-BACKPROPAGATIO…
This study presents a comparative analysis of Arabic handwritten character classification using the Hybrid Moment Invariant–Backpropagation (HMI-BP) and Convolutional Neural Network (CNN) approaches. The morphological complexity of Arabic script and the high variability in writing styles among writers demand models capable of distinguishing visually similar characters. The Arabic Handwritten …
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- xv, 139 hlm.; ilus.; tab.; 29 cm
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- T1899432025
KLASIFIKASI DIABETIK RETINOPATI DIABETES MELITUS MELALUI CITRA FUNDUS RETINA …
Diabetic retinopathy (DR) is a major complication of diabetes mellitus, characterized by damage to the retinal blood vessels and a high risk of blindness, particularly among individuals of productive age. Early detection of DR is essential, as the disease often presents no noticeable symptoms in its initial stages but can progress to permanent vision impairment if left untreated. This study aim…
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- xvii, 158 hlm.; ilus.; tab.; 29 cm
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- T1900622025
IMPLEMENTASI ADD-ON BLENDER UNTUK OTOMATISASI PEWARNAAN ACAK PADA OBJEK
3D object coloring is an important stage in digital design and animation, but this process often takes a long time and tends to be monotonous. This research aims to develop a Blender add-on called AutoColorize, designed using Python to automate the coloring process. The add-on is equipped with features to generate color palettes and apply colors to selected objects. The test results show that u…
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- xiv, 67 hlm.; ilus.; 29 cm
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- T1632352024
OPTIMASI FUZZY INFERENCE SYSTEMMODELMAMDANI DENGAN MENGGUNAKAN ALGORITMAPARTI…
Air is one of most importants thing in the world for all people, animals and plants. That’s why to check and maintain the air quality is one option to maintenance the world’s life. There are many way to check and maintain or even to predict the air polutions, and in this case i will use Fuzzy Inference System Mamdani. Not only with Fuzzy Inference System Mamdani, I will also optimize that w…
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- xvii, 67 hlm.; ilus.; 29 cm
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- T1631632024
FINE-TUNING MODEL ROBERTA UNTUK SISTEM TANYA JAWAB BERBASIS KONTEKS
The increasing amount of text-based information on the internet often requires users to read many long documents to find the answer information they need. Question Answering (QA) systems provide a solution to this problem by developing QA systems that can deliver direct answers from text without users having to read entire documents. This research focuses on developing an extractive question an…
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- xv, 101 hlm.; ilus.; tab.; 29 cm
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- T1898142025
KLASIFIKASI PENYAKIT ASMA DENGAN MENGGUNAKAN SELEKSI FITUR ANOVA F-TEST DAN A…
This study discusses the classification of asthma disease using Machine Learning algorithms to address three research questions: the application of Machine Learning in asthma classification, the effect of different dataset conditions, and the algorithm that produces the best performance. The asthma dataset obtained from Kaggle was processed under three scenarios: original, undersampling, and Sy…
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- xvii, 123 hlm.; ilus.; tab.; 29 cm.
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- T1899882025
PERBANDINGAN PERFORMA U-NET DAN SWIN UNETR PADA SEGMENTASI CITRA MRI TUMOR OTAK
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…
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- xvi, 138 hlm.; ilus.; tab.; 29 cm
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- T1900062025
PENGEMBANGAN DIALOG ADAPTIF MENGGUNAKAN KECERDASAN BUATAN GENERATIF PADA GIM …
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…
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- xvi, 90 hlm.; ilus.; tab.; 29 cm
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- T1900092025
ANALISIS SENTIMEN KOMENTAR PENGGUNA TERHADAP LAYANAN PAYLATER DI PLATFORM X M…
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-…
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- xiv, 97 hlm.; ilus.; tab.; 29 cm.
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- T1900552025
DETEKSI HUMOR TEKS PENDEK MENGGUNAKAN MODEL INDOBERT
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…
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- xv, 158 hlm.; ilus.; tab.; 29 cm.
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- T1900562025
REKOMENDASI PEMILIHAN SEKOLAH MENENGAH PERTAMA BERBASIS ISLAM KOTA PALEMBANG …
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…
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- xv, 124 hlm.; ilus.; tab.; 29 cm.
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- T1898152025
PENGEMBANGAN GAME MULTIPLAYER GUNTING BATU KERTAS BERBASIS DETEKSI GERAKAN TA…
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 …
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- xv, 98 hlm.; ilus.; tab.; 29 cm.
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- T1897352025
KLASIFIKASI EMOSI PADA LIRIK LAGU BERBAHASA INDONESIA DENGAN FINE-TUNING INDO…
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…
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- xiv, 126 hlm.; ilus.; tab.; 29 cm
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- T1899322025
OPTIMALISASI DETEKSI WAJAH KECIL BERBASIS YOLOV11 MENGGUNAKAN SAHI DAN REAL-E…
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…
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- xv, 136 hlm.; ilus.; tab.; 29 cm
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- T1899522025
PENERAPAN RETRIEVAL-BASED VOICE CONVERSION UNTUK MEMBANGUN ASET SUARA KARAKTE…
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…
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- xvi, 66 hlm.; ilus.; 29 cm
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- T1630482024
PERBANDINGAN TF-IDF DAN WORD2VEC UNTUK ANALISIS SENTIMEN MENGGUNAKAN SUPPORT …
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…
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- xvi, 66 hlm.; ilus.; 29 cm
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- T1627812024
PERBANDINGAN ARSITEKTUR U-NET++ DAN U-NET UNTUK SEGMENTASI PADA CITRA X-RAY DADA
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…
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- xv, 106 hlm.; ilus.; tab.; 29 cm
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- T1897222025
SISTEM REKOMENDASI DOSEN PEMBIMBING SKRIPSI MENGGUNAKAN PENDEKATAN HYBRID FIL…
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…
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- xiv, 110 hlm.; ilus.; tab.; 29 cm
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- T1897652025
SISTEM REKOMENDASI MAKANAN INDONESIA MENGGUNAKAN ALGORITMA LONG SHORT-TERM ME…
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…
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- xiv, 163 hlm.; ilus.; tab.; 29 cm
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- T1896432025
SISTEM REKOMENDASI BOARD GAME HYBRID MENGGUNAKAN JARINGAN SIAMESE DENGAN FUNG…
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…
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- xii, 145 hlm.; ilus.; tab.; 29 cm
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- T1899342025
KLASIFIKASI CITRA UNTUK MENDETEKSI KELUMPUHAN WAJAH MENGGUNAKAN ARSITEKTUR VG…
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…
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- xv, 125 hlm.; ilus.; tab.; 29 cm
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- T1897122025
KLASIFIKASI KOMENTAR JUDI ONLINE PADA TIKTOK MENGGUNAKAN METODE LONG SHORT-TE…
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…
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- xvi, 162 hlm.; ilus.; tab.; 29 cm
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- T1897252025
PENGEMBANGAN MODEL STEGANOGRAFI CITRA BERBASIS U-NET DENGAN CONVOLUTIONAL SPA…
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…
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- xviii, 231 hlm.; ilus.; tab.; 29 cm
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- T1897202025
PENERAPAN NAMED ENTITY RECOGNITION (NER) MENGGUNAKAN ARSITEKTUR LAYOUTLM UNTU…
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…
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- xvi, 156 hlm.; ilus.; tab.; 29 cm
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- T1897262025
SEGMENTASI POLIP KOLONOSKOPI REAL-TIME UNTUK DETEKSI DINI KANKER KOLOREKTAL D…
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…
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- xiv, 90 hlm.; ilus.; tab.; 29 cm
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- T1897302025
KLASIFIKASI TEKS LOWONGAN KERJA ASLI DAN PALSU MENGGUNAKAN BIDIRECTIONAL ENCO…
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 …
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- xv, 141 hlm.; ilus.; tab.; 29 cm
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- T1897572025
PENERAPAN MODEL BIDIRECTIONAL AND AUTOREGRESSIVE TRANSFORMER-BASE UNTUK ABSTR…
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…
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- xii, 120 hlm.; ilus.; tab.; 29 cm
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- T1897212025
PENERAPAN RANDOM FOREST UNTUK KLASIFIKASI POLA PENGETIKAN BERBASIS KEYSTROKE …
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 …
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- xiv, 109 hlm.; ilus.; tab.; 29 cm
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- T1897492025
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