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PENERAPAN FITUR SISTEM INFORMASI LAYANAN PENGAJUAN LEGALISIR IJAZAH TERINTEGR…
Manual diploma legalization services at the Faculty of Computer Science, Sriwijaya University face obstacles such as long queues, inefficient processes, and the risk of errors and document forgery. This study develops a web-based information system that is integrated with e-PPT and utilizes QR Codes to verify the authenticity of documents. This system makes it easier for alumni to apply for leg…
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- xv, 93 hlm.; ilus.; tab.; 29 cm.
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- T1761352025
PENERAPAN COGNITIVE WALKTROUGH UNTUK EVALUASI GAME EDUKASI “AYO BELAJAR MEN…
Educational games have become one of the effective learning media to enhance learning interest, especially among children. In this study, we developed an educational game titled (Let’s Learn About Fruits ) to provide an interactive and enjoyable learning experience. The game was designed using Construct 2, and the development process followed the Prototyping method, enabling design iterations…
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- v, 103 hlm., ilus., tab.; 29 cm
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- T1753112025
IMPLEMENTASI CONVOLUTIONAL NEURAL NETWORK (CNN) DENGAN EKSTRAKSI FITUR MFCC D…
Music is an important part of human life and continues to evolve with the advancement of information technology. The diversity of music genres that emerge due to differences in instruments, rhythm, technique, and lyrics presents a unique challenge in accurately classifying genres. This study aims to develop a music genre classification system using the Convolutional Neural Network (CNN) method …
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- xiv, 87 hlm.; ilus.; tab.; 29 cm.
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- T1761612025
EFFICIENTNET-B3 PADA METODE CONVOLUTIONAL NEURAL NETWORK UNTUK KLASIFIKASI CI…
Early and accurate classification of skin diseases is critical given the high global prevalence WHO estimates nearly 900 million cases worldwide, with dermatitis as the most common and the uneven distribution of dermatological expertise. EfficientNet-B3 within a Convolutional Neural Network (CNN) framework was therefore investigated for multiclass classification of skin disease images. A second…
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- xiii, 118 hlm.; ilus.; tab.; 29 cm.
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- T1761402025
KLASIFIKASI SINYAL ELEKTROENSEFALOGRAM (EEG) UNTUK MENGENALI JENIS EMOSI MENG…
Human emotion recognition can be done through facial expressions, voice, body posture, and physiological signals. However, these approaches tend to be subjective as individuals may consciously hide or manipulate their emotional expressions. As a more objective method, electroencephalogram signals can provide a more accurate understanding of a person's emotional state. In this regard, this resea…
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- xiv, 129 hlm.; ilus.; tab.; 29 cm.
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- T1759832025
KLASIFIKASI CITRA KUE TRADISIONAL MENGGUNAKAN METODE CONVOLUTIONAL NEURAL NET…
Traditional cake image classification aims to recognize various types of cakes based on visual features, thereby assisting in the effort to introduce traditional cakes. Indonesian traditional cakes hold significant cultural value that must be preserved while also presenting substantial potential in supporting tourism through culinary tourism. This study develops a classification model based on …
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- x, 96 hlm.; ill.; tab.; 29 cm.
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- T1699962025
KLASIFIKASI EMOSI PADA TEKS BERBAHASA INDONESIA DENGAN FINE-TUNING INDOBERT
The increasing use of social media has led to significant growth in Indonesian text data, creating complexity in emotion identification and classification tasks. To address this challenge, this study develops an emotion classification system using the fine-tuning method on the IndoBERT model. This research aims to classify emotions in Indonesian text using IndoBERT fine-tuning. The study utiliz…
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- xvi, 136 hlm.; ill.; tab.; 29 cm.
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- T1699922025
PENGELOMPOKKAN ARTIKEL ILMIAH MENGGUNAKAN MULTIBERT DAN K-MEANS
The publication rate of scientific articles has significantly increased over time. This presents a challenge for journal administrators and academics in organizing and sorting these articles to align with the journal's scope. This study aims to address this issue by developing a scientific article clustering system utilizing MultiBERT as the data representation model and K-Means for cluster ide…
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- xii, 65 hlm.; ill.; tab.; 29 cm.
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- T1699162025
KEMIRIPAN SEMANTIK DOKUMEN TUGAS AKHIR TERHADAP ONTOLOGI BIDANG ILMU INFORMAT…
The increasing number of multidisciplinary undergraduate theses in Informatics field presents challenges in categorizing these documents accurately. This study develops a system to measure the semantic similarity of final project documents to the ontology of Informatics using the Wu Palmer method as a solution to this problem. This method utilizes ontology tree structures and taxonomic depth to…
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- xiii, 80 hlm.; ill.; tab.; 29 cm.
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- T1699172025
KLASIFIKASI VARIETAS BERAS MENGGUNAKAN CONVOLUTIONAL NEURAL NETWORK DENGAN AR…
Rice consists of various varieties withdistinctmorphological characteristics, yet manual classification remains subjective and reliant on expert judgment. This study develops an automated rice variety classification system using the Convolutional Neural Network (CNN) method with the MobileNetV2 architecture. The dataset includes 75,000 images of five rice varieties, divided into 70% training, 5…
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- xvi, 100 hlm.; ilus.; tab.; 29 cm.
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- T1757572025
PERBANDINGAN PERFORMA METODE NAIVE BAYES DAN SUPPORT VECTOR MACHINE DALAM K…
Music genre classification has become a research topic that is gaining increasing attention, especially with the emergence of digital music platforms. One of the relevant features extracted from audio signals and capturing important characteristics of sound is MFCC, which is widely recognized as an effective technique. This study applies Naive Bayes and SVM algorithms for classification on a co…
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- xvi, 79 hlm.; ilus.; 29 cm
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- T1632702024
MPLEMENTASI OPENAI API UNTUK PEMBANGKITAN SOAL KUIS PADA QUIZ GAME SEJARAH
Quiz games serve not only as entertainment but also as educational media. However, manually creating varied questions, especially for production-level digital quiz games, requires significant resources. This research attempts to address this challenge by implementing GPT-3.5, through the OpenAI API, as a question generation system for quiz game question banks within the domain of history. The s…
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- xv, 40 hlm.; ilus.; 29 cm
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- T1632872024
KLASIFIKASI TUBERKULOSIS PADA CITRA CHEST X-RAY MENGGUNAKAN CONVOLUTIONAL NEU…
Tuberculosis is still one of the infectious diseases that causes high mortality rates worldwide. Early detection using Chest X-Ray images is very important in the effort to treat this disease. However, manual interpretation of X-ray results performed by doctors can cause differences in diagnosis. This study aims to classify tuberculosis in Chest X-Ray images by implementing three Convolutional …
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- xiv, 64 hlm., ilus., tab.; 29 cm
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- T1750112025
KLASIFIKASI KATARAK PADA CITRA MATA MENGGUNAKAN ARSITEKTUR VGGNET
Cataract is the leading cause of blindness, including in Indonesia, with 1.6 million reported cases. Early detection is crucial, yet access to eye healthcare remains limited, especially in remote areas, and is further hindered by economic constraints and a shortage of ophthalmologists. This study develops a cataract classification model based on fundus images using VGG-16 and VGG-19 architectur…
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- xiv, 176 hlm.; ilus.; tab.; 29 cm.
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- T1726282025
ANALISIS SENTIMEN ULASAN PENGGUNA APLIKASI IPUSNAS DI GOOGLE PLAYSTORE DENGAN…
Digital libraries, such as iPusnas, have become essential solutions for improving access to reading materials in the digital era. User reviews of the iPusnas application on the Google Play Store contain valuable information that can be utilized to enhance services and guide application development. This study aims to develop a sentiment analysis system for user reviews of the iPusnas applicatio…
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- xvi, 159 hlm.; ilus.; tab.; 29 cm.
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- T1725252025
TOPIC MODELLING DAN TOPIC GENERATION PADA REVIEW GAME STEAM DENGAN FINE-TUNIN…
This study aims to develop and evaluate a Topic Modelling and Topic Generation system using user review data from the Steam platform. The research utilizes the BERTopic model to cluster reviews into topics in an unsupervised manner, and the Qwen2.5 Large Language Model to generate more informative topic representations. Various algorithm combinations covering embedding, dimensionality reduction…
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- xvii, 184 hlm., ilus., tab.; 29 cm
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- T1750592025
FINE-TUNING MODEL BERT UNTUK NAMED ENTITY RECOGNITION
A sentence can contain various named entities with important meanings, such as names of people, locations, organizations, and time expressions. However, extracting this information manually requires significant time and resources. Named Entity Recognition (NER) offers an automated solution that improves the efficiency of this task. One method for developing an NER system is by using BERT, a tra…
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- xvii, 128 hlm., ilus., tab.; 29 cm
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- T1751502025
ANALISIS SENTIMEN TIKTOK SHOP PADA TWITTER MENGGUNAKAN METODE SUPPORT VECTOR …
TikTok Shop, as a social commerce feature in the TikTok application, has become a popular shopping platform in Indonesia. However, government regulations prohibiting direct transactions on social media forced TikTok to stop this service from October 4 until it reopened on December 12, 2023, after establishing a partnership with Tokopedia. This incident triggered various public opinions. This se…
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- xvi, 78 hlm., ilus., tab.; 29 cm
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- T1677192025
KLASIFIKASI JUDUL BERITA PALSU MENGGUNAKAN METODE BIDIRECTIONAL ENCODER REPRE…
This research aims to classify fake news headlines in Indonesian as an initial step in detecting and reducing the spread of misinformation. Headlines are often the first element read and have strong potential to shape public opinion, especially when they contain negative or sensational narratives. Unlike previous studies that analyze full news content or focus only on political news, this study…
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- xiii, 120 hlm.; ilus.; tab.; 29 cm.
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- T1723602025
ANALISIS SENTIMEN ULASAN APLIKASI SPOTIFY DI GOOGLE PLAY STORE MENGGUNAKAN MO…
Spotify, with 574 million active users and 226 million premium subscribers across 184 countries as of Q3 2023, represents a significant force in music streaming. While Google Play Store ratings provide initial app quality indicators, they fail to capture comprehensive user experiences. This research employs Bidirectional Encoder Representations from Transformers (BERT) to conduct sentiment anal…
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- xviii, 125 hlm.; ilus.; tab.; 29 cm.
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- T1723592025
PENERAPAN METODE LONG-SHORT TERM MEMORY (LSTM) DALAM ANALISIS SENTIMEN BERBAS…
This study discusses the application of the Long Short-Term Memory (LSTM) method in aspect-based sentiment analysis of reviews on the Gojek application in the Google Play Store. By utilizing Word2Vec for word representation and Latent Dirichlet Allocation (LDA) for topic modeling, this research aims to identify and classify user sentiment regarding various features of the Gojek app, such as use…
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- xxiii, 37 hlm.; ilus.; tab.; 29 cm.
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- T1694652025
KLASIFIKASI TUMOR OTAK PADA CITRA MAGNETIC RESONANCE IMAGING MENGGUNAKAN CONV…
Tumor otak merupakan penyakit serius yang memerlukan deteksi dini agar dapat ditangani dengan tepat dan efektif. Magnetic Resonance Imaging (MRI) sering digunakan dalam diagnosis tumor otak, namun analisis manual masih memiliki keterbatasan, seperti ketergantungan pada keahlian radiologi serta subjektivitas dalam interpretasi hasil.Penelitian ini bertujuan untuk mengembangkan model klasifikasi …
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- xv, 116 hlm.; ilus.; tab.; 29 cm.
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- T1702982025
SISTEM TANYA JAWAB DETEKSI KANKER DINI MENGGUNAKAN METODE BERT DAN TF-IDF
The increasing mortality rate due to cancer, particularly in developing countries like Indonesia, highlights the urgency of developing an effective question-answering detection system. According to data from Globocan 2020, Indonesia recorded 396,914 new cancer cases with 234,511 cancer-related deaths. Additionally, Riskesdas data shows that the prevalence of cancer in Indonesia increased from 1…
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- xvi, 189 hlm.; ilus.; tab.; 29 cm.
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- T1688322025
PREDIKSI TINGKAT KRIMINALITAS MENGGUNAKAN LONG SHORT TERM MEMORY (LSTM)
Prediction or also called forecasting is the process of estimating events that will occur in the future. In this research, software is developed that can predict crime rates using the Long Short-term Memory method using the Los Angles crime dataset which has a crime type domain of 139 with details of 9 types of crimes that have the most frequency, namely; vehicle - stolen, battery - simple assa…
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- x, 46 hlm., ilus., tab.; 29 cm
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- T1661912025
ANALISIS PERBANDINGAN KLASIFIKASI INTENT CHATBOT MENGGUNAKAN DEEP LEARNING BE…
A chatbot is a software application to designed handle user inputs and generate appropriate replies based on those inputs, which are then communicated back to the user. In able to provide accurate responses, the chatbot must be able to understand the intent of the user accurately. An issue in the development of chatbots is how to accurate classify user intent. Incorrectly understanding user int…
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- xii, 65 hlm., ilus., tab.; 29 cm
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- T1643912025
ANALISIS META KARAKTER DAN PERAN PADA GAME ONLINE FIRST PERSON SHOOTER VALORA…
Valorant is a form of online entertainment in the FPS (First-Person Shooter) genre, released by Riot Games in 2020, and it remains popular among gamers today. The online game Valorant offers a wide range of characters with unique skills and roles, requiring teamwork and strategy to win matches. This presents a challenge for new players entering the game, as they may struggle to adapt. Therefore…
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- xv, 78 hlm.; ilus.; tab.; 29 cm.
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- T1641572024
ANALISIS META SENJATA PADA PERMAINAN FIRST PERSON SHOOTER VALORANT MENGGUNAKA…
This research aims to analyze weapon meta in the First Person Shooter (FPS) game Valorant using the K-Median algorithm. This algorithm is applied to cluster weapons based on performance parameters such as Average Damage per Round (ADR) and Average Combat Score (ACS). The clustering results show that the K-Median algorithm produces groupings more resilient to outliers compared to other algorithm…
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- xi, 91 hlm.; ilus.; tab.; 29 cm.
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- T1641012024
OPTIMASI VEHICLE ROUTING PROBLEM WITH TIME WINDOWS (VRPTW) MENGGUNAKAN METODE…
The distribution of goods in the logistics sector faces challenges in optimizing distance, time, and delivery route efficiency. The Vehicle Routing Problem (VRP), including its variant VRPTW, which considers time constraints, is an effective approach to address these challenges. This study applies the Variable Neighborhood Search (VNS) algorithm as a heuristic method to solve the VRPTW. VNS lev…
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- xv, 97 hlm.; ilus.; tab.; 29 cm.
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- T1641102024
KLASIFIKASI PENYAKIT BERBASIS BAGGING MENGGUNAKAN NAÏVE BAYES, DECISION TREE…
In classification, finding the optimal model to handle a specific problem is crucial. Various algorithms, such as Naïve Bayes, Decision Tree, and Support Vector Machines (SVM), each have their own strengths and weaknesses. One commonly used technique to enhance model performance is Bagging, the ensemble technique. Bagging combines weak models into a stronger model by reducing bias and variance…
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- xvii, 88 hlm.; ilus.; tab.; 29 cm.
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- T1605072024
DELINEASI SINGLE-LEAD SINYAL ELEKTROKARDIOGRAM MENGGUNAKAN DEEP LEARNING DENG…
Electrocardiogram (ECG) is a medical procedure used to assess cardiac function, including its electrical activity. With the increasing prevalence of heart disease, which recorded an 18.71% rise in 2020 compared to 2010, the role of ECG interpretation has become critically important. Cardiac conditions can be analyzed through the morphology of ECG signals, consisting of the P wave, QRS complex, …
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- xvi, VI-1 hlm., ilus., tab.; 29 cm
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- T1643832024
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