KLASIFIKASI KOMENTAR JUDI ONLINE MENGGUNAKAN INDOBERT

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…

ANALISIS SENTIMEN TERHADAP ULASAN APLIKASI DANA MENGGUNAKAN WORD2VEC DAN LONG…

DANA has become one of the most popular e-wallet applications in Indonesia. This development has elicited various reactions and responses from users in the form of reviews. These reviews can provide important insights for improving the quality of the application's services. This study aims to conduct sentiment analysis on user reviews by utilizing Long Short-Term Memory (LSTM) as the model arch…

PERBANDINGAN MACHINE LEARNING XGBOOST DAN DEEP LEARNING CNN 1D UNTUK MENDETEK…

Phishing is a form of cyberattack that exploits fraudulent websites to obtain users’ sensitive information. This study aims to compare the performance of the XGBoost machine learning algorithm and CNN 1D deep learning in detecting phishing URLs using tabular URL data. XGBoost was chosen because it is effective in handling tabular data and capable of modeling nonlinear relationships among feat…

PERBAIKAN KUALITAS CITRA DENGAN NONLINEAR ACTIVATION FREE NETWORK UNTUK KLASI…

Alzheimer’s disease is a progressive neurodegenerative disorder that is the leading cause of dementia. The use of Magnetic Resonance Imaging (MRI) in ResNet18-based classification can be hindered by the presence of noise, particularly Rician noise, which obscures important structural details and reduces model performance. This study employs the Nonlinear Activation Free Network (NAFNet) to im…

PERBANDINGAN FUZZY TIME SERIES CHENG DAN LEE PADA PREDIKSI PENGUNJUNG WISATA …

Fluctutations in daily visitor numbers at Kampung Radja Jambi present challanges for optimal operation planning. This study aims to compare the performance of the Fuzzy Time Series (FTS) Cheng and FTS Lee methods in forecasting daily visitor number using secondary data from Januari 1, 2024 to December 31, 2025. After preprocessing, 648 observations were analyzed using FTS approach, and forecast…

PENGEMBANGAN MODEL PENERJEMAHAN BAHASA INGGRIS KE BAHASA JAWA MENGGUNAKAN LST…

One of the main challenges in English to Javanese machine translation is the model's difficulty in capturing contextual relationships between words, especially in complex sentences. Without an Attention Mechanism, the model tends to be unable to focus on the relevant parts of the source sentence during the translation process. This study aims to develop a Neural Machine Translation (NMT) model …

ANALISIS DAN PERBANDINGAN ARSITEKTUR PIPELINE DATA DAN SISTEM PEMANTAUAN PENE…

Penelitian ini bertujuan menganalisis hubungan kausalitas antara indeks kebahagiaan, pengeluaran pemerintah, dan pertumbuhan ekonomi di 12 negara emerging market selama periode 2013–2024. Data yang digunakan merupakan data sekunder yang diperoleh dari World Happiness Report dan World Bank. Metode analisis yang digunakan adalah Panel Vector Autoregression (PVAR) dengan uji kausalitas Granger u…

PREDIKSI HASIL SPMB JALUR TKA DENGAN PENDEKATAN ENSEMBLE LEARNING STACKING

The Seleksi Penerimaan Murid Baru (SPMB) through the Tes Kemampuan Akademik (TKA) pathway for senior high schools in Palembang is a competitive process that creates uncertainty in determining students’ admission chances. This study aims to develop a prediction model for student admission using a machine learning approach based on ensemble learning stacking. The dataset consists of 4,952 appli…

REKOMENDASI PEMILIHAN SEKOLAH MENENGAH ATAS BERBASIS DOMISILI DENGAN MENGGUNA…

School selection at the senior high school level is an important decision amid intense competition in the student admission process and multiple influencing factors such as academic performance, domicile, and school capacity. This study aims to develop a recommendation system based on stacking ensemble learning that combines Random Forest and XGBoost as base learners, with Logistic Regression a…

ANALISIS SENTIMEN TERHADAP CRYPTOCURRENCY MENGGUNAKAN MODEL BERT

The rapid development of digital technology has driven various innovations in the financial sector, one of which is cryptocurrency, which is increasingly discussed on social media and various digital platforms. On the other hand, price volatility, security issues, and evolving regulations have led to diverse public opinions regarding cryptocurrency. Therefore, this study aims to analyze public …

SEGMENTASI MULTI-CLASS BERBASIS TRANSFORMER PADA CITRA MEDIS MRI OTAK

Brain tumor segmentation from Magnetic Resonance Imaging (MRI) is crucial for accurate diagnosis and therapy planning. CNN architectures like U-Net are considered the gold standard, but they have intrinsic limitations in processing long-range spatial context globally. This study proposes the use of a Vision Transformer architecture, specifically UNETR, and compares its performance against a bas…

ANALISIS SENTIMEN ULASAN PENGGUNA GOPAY MENGGUNAKAN INDOBERT

The rapid growth of digital wallets in Indonesia, particularly GoPay, has generated tens of thousands of user reviews containing valuable information about service satisfaction. This study aims to classify GoPay application user satisfaction into positive, neutral, and negative categories using the Fine-Tuning IndoBERT (Indonesian BERT) method. As a Transformer-based model trained specifically …

ANALISIS SENTIMEN PUBLIK TERHADAP CHATGPT DI PLATFORM X MENGGUNAKAN ROBERTA

ChatGPT is an artificial intelligence technology that triggers diverse public opinions on social media, particularly on the X platform. The high volume of data and unstructured text characteristics make manual mapping of public perception difficult. Therefore, this study aims to develop an automated sentiment analysis system to classify public opinion toward ChatGPT into Negative, Neutral, and …

PENGANTAR TEKNOLOGI INFORMATIKA dan KOMUNIKASI DATA

Edition

-

ISBN/ISSN

978-623-209-852-7

Collation

vi, 121 hlm.; 23 cm

Series Title

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Call Number

004.071 Bag p

ANALISIS SENTIMEN TERHADAP CONTENT CREATOR PAPI ABE MENGGUNAKAN METODE LONG S…

The phenomenon of Papi Abe as a family content creator who has gone viral on TikTok has generated a wide range of public responses, both positive and negative, particularly regarding father-child interactions in parenting content and the potential for child exploitation. Therefore, it is important to understand public opinions toward Papi Abe as a basis for evaluating and improving content qual…

ANALISIS SENTIMEN MASYARAKAT TERHADAP AWAL KEPEMIMPINAN PRESIDEN PRABOWO SUBI…

This research aims to analyze public sentiment toward the early leadership of President Prabowo Subianto using the IndoBERT language model. Public opinions were collected from various social media platforms, including X, YouTube and TikTok, resulting in a dataset of 78,851 texts labeled into positive and negative sentiments. The data underwent preprocessing stages such as cleaning, case folding…

DETEKSI PENYAKIT PADA TANAMAN MANGGA BERDASARKAN CITRA DAUN DENGAN ALGORITMA …

Healthy and diseased mango plants are difficult to distinguish at early stages due to insignificant differences in leaf color, texture, and spot patterns, which often leads to delayed identification and results in decreased mango production and fruit quality. This study develops an Android-based application to detect diseases in mango plants based on leaf images using the YOLO11 algorithm. The …

PREDIKSI HASIL TANGKAPAN IKAN YANG DISETORKAN KE PPS NIZAM ZACHMAN JAKARTA DE…

Prediction is the process of estimating future conditions using historical data as the basis for decision-making. This research develops a web-based fish catch prediction system using XGBoost algorithm based on time series with nonlinear regression method to predict fish production results submitted to the port. The data used is aggregate fish catch data from 12 fishing points during 2020– 20…

IMPLEMENTASI ALGORITMA LIGHT GRADIENT BOOSTING MACHINE UNTUK PREDIKSI WAKTU P…

Formula 1 qualifying sessions play a crucial role in determining race outcomes, as grid position strongly influences competitive advantage, particularly on circuits with limited overtaking opportunities. This study aims to implement the Light Gradient Boosting Machine (LightGBM) algorithm to predict drivers’ qualifying lap times in Formula 1 using historical time-series data from the 2018–2…

PENGGUNAAN CONDITIONAL GENERATIVE ADVERSARIAL NETWORK (CGAN) UNTUK PENINGKATA…

This study implements a Conditional Generative Adversarial Network (CGAN) to enhance the contrast of fetal abdominal ultrasound images. The novelty lies in increasing the Reconstruction Loss weight (λL1) to 1000 to ensure structural stability in medical data. Using U-Net and PatchGAN architectures, the model was trained against CLAHE targets. The results demonstrate significant enhancement wit…

DETEKSI DAN PENGENALAN TEKS PADA TABEL NILAI GIZI MENGGUNAKAN PADDLEOCR DAN T…

Nutrition facts tables on food packaging are a crucial source of information for consumers, but manual data extraction is often inefficient and prone to errors due to varied table structures and small text sizes. This research proposes an automated system for text detection and recognition in nutrition tables by integrating two advanced deep learning models: PaddleOCR and TrOCR. PaddleOCR is em…

OPTIMASI PERILAKU KARAKTER BOSS PADA PERMAINAN MULTIPLAYER MENGGUNAKAN FUZZY …

Adaptive Artificial Intelligence (AI) plays a significant role in shaping player experience in digital games, particularly in action-based combat scenarios where behavioral dynamics influence perceived challenge, fairness, and engagement. This study investigates the implementation of a Fuzzy State Machine (FuSM) compared to a conventional Finite State Machine (FSM) for boss behavior in a 2D mul…

ANALISIS SENTIMEN ULASAN PENGGUNA APLIKASI GOJEK MENGGUNAKAN LONG SHORT TERM …

his study aims to analyze user sentiment toward the Gojek application using the Long Short-Term Memory (LSTM) method. Review data was obtained through scraping the Gojek application service, resulting in a dataset that was then classified into positive and negative sentiment categories. The data underwent class balancing using the undersampling technique, followed by a pre-processing stage that…

ANALISIS SENTIMEN ULASAN FILM INTERNET MOVIE DATABASE (IMDB) MENGGUNAKAN BIDI…

The large and unstructured volume of IMDb movie review data makes it difficult to map the opinions of the audience manually. Therefore, this study aims to develop a sentiment analysis system using BERT to classify IMDb movie reviews into positive and negative categories. The data used is secondary data amounting to 50,000 English-language data. This research stage includes pre-processing of tex…

KLASIFIKASI PENYAKIT HEPATITIS MENGGUNAKAN TEACHING-LEARNING BASED OPTIMIZATI…

Hepatitis is one of the global health problems with a persistently high incidence rate and the potential to cause serious complications if not detected early. Meanwhile, the use of laboratory data for machine learning-based diagnosis still faces challenges such as missing values, imbalanced class distribution, and the limited application of optimal combinations of feature selection methods and …

PREDIKSI VOLUME TOTAL TRANSAKSI HARIAN ETHERIUM MENGGUNAKAN METODE XGBOOST

The development of blockchain technology has increased cryptocurrency transaction activities, especially Ethereum, whose daily transaction volume is highly fluctuating. This condition makes transaction volume prediction important for understanding network activity patterns. This study aims to develop a prediction model for daily Ethereum transaction volume using the XGBoost Regressor algorithm.…

KLASIFIKASI JENIS BAKTERI CITRA MIKROSKOPIS MENGGUNAKAN CONVOLUTIONAL NEURAL …

Identifying bacteria traditionally takes 24–72 hours and is prone to human error. With bacterial infections and antimicrobial resistance causing over 1 million deaths annually, faster and more accurate methods are urgently needed. This study compares two deep learning models, ResNet-50 (a classic CNN) and ConvNeXt-Tiny (a modern CNN) for classifying microscopic bacteria images using the DIBaS…

SISTEM REKOMENDASI PEMILIHAN LAPTOP MENGGUNAKAN KOMBINASI METODE ROC DAN MOORA

The increasing demand for laptops in the digital era is often not aligned with the ease of choosing the right specifications due to the vast variety of brands and features available in the market. This research aims to develop an objective Decision Support System (DSS) for laptop selection by integrating the Rank Order Centroid (ROC) method for criteria weighting and Multi-Objective Optimizatio…

SISTEM PENDUKUNG KEPUTUSAN PEMILIHAN SMARTWATCH MENGGUNAKAN VIKOR DENGAN OPTI…

The development of wearable technology has increased the use of smartwatches as devices that support daily activities and health monitoring. However, the large number of product choices with conflicting specifications and technical criteria makes the smartwatch selection process complex. This study aims to develop a web-based Decision Support System (DSS) for smartwatch selection by integrating…

ANALISIS PERBANDINGAN ALGORITMA A* DAN JUMP POINT SEARCH DALAM PENCARIAN JALU…

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 …