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PENERAPAN PARTICLE SWARM OPTIMIZATION UNTUK PROCEDURAL CONTENT GENERATION PAD…
The rice farming sector plays a strategic role in supporting national food security; however, its sustainability is under serious pressure due to the conversion of paddy fields into oil palm plantations. In Banyuasin Regency, the sustainability of rice farming has been increasingly threatened by this land-use conversion. The binary logistic regression analysis shows that farm income is the only…
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- xvii, 122 hlm.; ilus.; tab.; 29 cm.
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- T1985432026
ANALISIS SENTIMEN ULASAN APLIKASI MOBILE JKN MENGGUNAKAN NAÏVE BAYES, KNN, D…
Sentiment analysis of user reviews on the Mobile JKN application plays an important role in identifying user satisfaction levels and obstacles encountered when accessing BPJS Kesehatan’s digital services. This study aims to evaluate the performance of three classification algorithms Naïve Bayes, KNN, and SVM optimized using the SMOTE approach to address data imbalance. A total of 19,186 user…
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- xvii, 128 hlm.; ilus.; tab, 29 cm
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- T1981482026
PENERAPAN METODE NAÏVE BAYES UNTUK KLASIFIKASI PENGGUNAAN LAYANAN ANJUNGAN T…
This study aims to classify the level of Automated Teller Machine (ATM) usage among students of Sriwijaya University using the Naïve Bayes method in a data mining approach. The level of ATM usage is divided into three categories, namely passive (0–2 times), moderate (3–5 times), and active (>5 times) per month. The data used is primary data collected from 120 respondents with variables inc…
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- xvi, 63 hlm.; ilus.; tab.; 29 cm.
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- T1978752026
ANALISIS SENTIMEN PERSPEKTIF PUBLIK DI MEDIA SOSIAL (X, INSTAGRAM, TIKTOK) TE…
The rapid development of information technology has transformed social media into an important space for shaping public opinion. One emerging phenomenon is the #KaburAjaDulu hashtag on X, Instagram, and TikTok, reflecting public perspectives on social and economic conditions in Indonesia. This study aims to analyze public sentiment toward the hashtag using the Naive Bayes method, including prep…
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- xxiii, 112 hlm.; ilus.; 29 cm
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- T1962932026
ANALISIS SENTIMEN KOMENTAR PADA INSTAGRAM BADAN EKSEKUTIF MAHASISWA UNIVERSIT…
This study aims to analyze the sentiment of Instagram user comments on the account of the Student Executive Board of Sriwijaya University (BEM Unsri) for the 2024–2025 period. The background of this research is based on the increasing use of social media as a public communication platform that reflects students’ perceptions of student organization performance. This study employs a quantitat…
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- xv, 89 hlm.; ilus.; 29 cm
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- T1967312026
INSTANCE SEGMENTATION PADA CITRA MIKROSKOPIS TELUR CACING PARASIT MENGGUNAKAN…
Helminthiasis is classified by the World Health Organization (WHO) as one of the Neglected Tropical Diseases (NTDs) due to its wide distribution, yet it often remains a low priority in global health agendas. Control efforts for helminthiasis are generally carried out through manual microscopic examination. However, this method requires specialized expertise, has technical limitations such as lo…
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- xiv, 110 hlm.; ilus.; tab.; 29 cm.
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- T2015982026
ANALISIS KOMPARATIF ROBUSTNESS ALGORITMA ENSEMBLE LEARNING TERHADAP PERGESERA…
Data distribution changes over time have become one of the main challenges in the application of machine learning to intelligent transportation systems. This phenomenon, known as concept drift, can lead to performance degradation when the testing data exhibit characteristics that differ from those of the training data. This study aims to analyze the robustness of machine learning algorithms aga…
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- xvii, 110 hlm.; ilus.; tab.; 29 cm.
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- T2013082026
SELEKSI FITUR KLASIFIKASI PENYAKIT INFARK MIOKARD MENGGUNAKAN GENETIC ALGORIT…
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…
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- xiv, 81 hlm.; ilus.; tab.; 29 cm.
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- T2012862026
OPTIMASI ALGORITMA K-NEAREST NEIGHBOR (KNN) DENGAN NORMALISASI DAN SELEKSI FI…
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…
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- xiii, 92 hlm.; ilus.; tab.; 29 cm.
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- T2012632026
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.…
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- xv, 99 hlm.; ilus.; tab.; 29 cm.
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- T2012582026
PERBANDINGAN LOGISTIC REGRESSION DAN XGBOOST DALAM KLASIFIKASI KONDISI MENTAL…
Accurate mental state identification is important across various fields, and EEG is a biomedical signal widely used for this purpose as it can directly and non-invasively record brain electrical activity. However, the complex, nonlinear, and high-dimensional characteristics of EEG signals require effective classification methods. This study aims to implement and compare the performance of Logis…
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- xiv, 108 hlm.; ilus.; tab.; 29 cm.
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- T2010352026
KLASIFIKASI TALENT SCOUTING RENANG MENGGUNAKAN HYBRID DECISION TREE DAN ALGOR…
Talent Scouting in sports is a systematic process of finding, identifying, and evaluating individuals who show potential for achievement from an early age, so that their talents can be developed through a tiered training program to achieve optimal performance. The use of classification methods is one effective solution to support this process. Classification is the main method in machine learni…
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- xxiii, 61 hlm.; ilus.; 29 cm
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- T1949882026
PENGELOMPOKAN PROVINSI DI INDONESIA MENGGUNAKAN ALGORITMA K-MEANS BERDASARKAN…
The high school dropout rate in public high schools remains a significant problem in Indonesia due to various factors, such as socioeconomic conditions, educational facilities, and the ratio of teachers to students. This study aims to group provinces in Indonesia based on the indicator of high school dropout rates in 2024/2025 using the K-Means Clustering algorithm. The data used were obtained …
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- xiv, 61 hlm.; ilus.; 29 cm
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- T1950012026
CLUSTERING DATA GAJI KARYAWAN DI INDONESIA MENGGUNAKAN ALGORITMA KNN
Salary is an important aspect in the employment sector as it reflects job value and employee welfare. Along with the rapid growth of salary data availability, effective analytical methods are required to transform raw data into meaningful information. However, salary data are often complex and unlabeled, making direct analysis difficult. This study aims to group salary data using the K-Means al…
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- xvi, 83 hlm.; ilus.; 29 cm
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- T1932292026
ANALISIS PERBANDINGAN ALGORITMA ANN, ANN-PSO, DAN ANN-GA UNTUK KLASIFIKASI KE…
Flight departure delays affect operational efficiency and the quality of air transportation services. This study compares the performance of the Artificial Neural Network (ANN), ANN optimized using Particle Swarm Optimization (ANN-PSO), and ANN optimized using Genetic Algorithm (ANN-GA) for flight delay classification using a two-class dataset, namely on-time and delayed flights, based on opera…
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- xiv, 79 hlm.; ilus.; tab.; 29 cm.
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- T1931722026
ANALISIS PERBANDINGAN ALGORITMA MACHINE LEARNING UNTUK PREDIKSI KETERLAMBATAN…
This research was conducted because departure delays on the Light Rail Transit can reduce passenger comfort and satisfaction. Therefore, a predictive model that can estimate delays accurately is needed. The purpose of this study is to implement, compare, and determine the best machine learning algorithm for predicting LRT departure delays in Canberra. The dataset used consists of static and rea…
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- xiv, 81hlm.; ilus.; tab.; 29 cm.
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- T1931772026
IMPLEMENTASI METODE ADAPTIVE BOOSTING (ADABOOST) DALAM KLASIFIKASI KEJADIAN H…
Classifying rainfall events can be challenging when the available data is incomplete or contains missing values. Several imputation methods can be used to address missing data, such as the mean imputation method and the K-Nearest Neighbors Imputation method. For classification purposes, many techniques can be utilized, one of which is the Adaptive Boosting (AdaBoost) method. AdaBoost is designe…
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- xv, 237 hlm.; ilus.; tab.; 29 cm.
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- T1911612025
ANALISIS K-MEANS CLUSTERING UNTUK MENGELOMPOKKAN WAKTU MINGGUAN BERDASARKAN E…
Infused water or spa water is water that is added with pieces of fruit and left to stand for a few hours until the juice comes out, then ready to be consumed, thus providing flavor and health benefits. The lime peel of an orange contains more than 60% flavonoids and 170 different types of phytonutrients. Processing lime as an infused water drink can be an alternative to overcome acidity in citr…
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- xvii, 61 hlm.; ilus.; 29 cm
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- T1906992025
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
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
PENERAPAN ALGORITMA RANDOM FOREST UNTUK SENTIMEN ANALISIS PADA POSTINGAN FACE…
Traffic congestion is a recurring issue in Palembang City and significantly affects the daily activities of its residents. Social media, particularly Facebook, serves as a platform for the public to express their opinions and complaints regarding traffic conditions. This study aims to analyze public sentiment toward traffic congestion in Palembang City using the Random Forest algorithm. The res…
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- xv, 106 hlm.; ilus.; tab.; 29 cm
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- T1893912025
KNOWLEDGE DISCOVERY DALAM KOMPARASI ALGORITMA ENSEMBLE BOOSTING PADA KLASIFIK…
Good water quality is one of the leading indicators in supporting the life of living things. However, pollution from industrial, domestic, and agricultural waste has resulted in a decline in water quality, which has the potential to cause environmental and health problems. Rapid technological advancements have made machine learning algorithms a viable alternative for classifying water quality. …
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- xvi, 74 hlm.; ilus.; tab.; 29 cm.
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- T1895992025
KNOWLEDGE DISCOVERY DALAM MEMPREDIKSI SKOR SUSTAINABLE DEVELOPMENT GOALS (SDG…
SDGs score prediction is important in assisting the planning and evaluation of policies to achieve these global targets. This study aims to compare the performance of several regression algorithms in predicting the SDGs score: Polynomial Regression, Support Vector Regression, Random Forest Regression, and Gradient Boosting Regressor. The dataset used consists of data on country names, years, SD…
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- xiv, 83 hlm.; ilus.; tab.; 29 cm.
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- T1895962025
EVALUASI PENDEKATAN ENSEMBLE LEARNING UNTUK ANALISIS SENTIMEN PADA ULASAN APL…
The development of online transportation applications such as Maxim has increased the need for sentiment analysis to understand user opinions from reviews on the Google Play Store. The main challenges in this analysis are language diversity, variations in writing style, and data imbalance, which affect model accuracy. This study aims to evaluate the performance of the Support Vector Machine (SV…
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- xiii, 95 hlm.; ilus.; tab.; 29 cm.
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- T1895342025
PERBANDINGAN ALGORITMA RANDOM FOREST, LOGISTIC REGRESSION, DAN XGBOOST DALAM …
Understanding user sentiment from e-commerce reviews is essential for platform improvement and business strategy. This study compares three machine learning algorithms—Logistic Regression, Random Forest, and XGBoost—for sentiment classification of Indonesian-language Tokopedia reviews. A dataset of 6,822 user reviews was preprocessed through tokenization, stopword removal, and TF-IDF vector…
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- xv, 98 hlm.; ilus.; tab.; 29 cm.
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- T1895732025
PENERAPAN METODE MACHINE LEARNING DAN TEKNIK SMOTE UNTUK PREDIKSI DIABETES
Diabetes merupakan salah satu penyakit tidak menular yang prevalensinya terus meningkat secara global maupun nasional. Kondisi ini menimbulkan risiko komplikasi serius seperti penyakit jantung, stroke, hingga gagal ginjal apabila tidak terdeteksi sejak dini. Oleh karena itu, dibutuhkan metode prediksi berbasis data yang mampu membantu proses deteksi awal secara cepat, akurat, dan efisien. Penel…
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- xix, 93 hlm.; ilus.; tab.; 29 cm.
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- T1895142025
ANALISIS SENTIMEN ULASAN PENGGUNA APLIKASI TOKOPEDIA MENGGUNAKAN ALGORITMA RA…
Dalam beberapa tahun terakhir, pertumbuhan e-commerce di Indonesia menunjukkan peningkatan yang signifikan, menjadikan ulasan konsumen sebagai acuan utama dalam menilai kualitas layanan dan pengalaman pengguna. Tokopedia, sebagai salah satu platform e-commerce terbesar, menerima jutaan ulasan yang merefleksikan opini serta pengalaman pelanggan terhadap berbagai produk dan layanan. Karena berben…
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- xvi, 88 hlm.; ilus.; tab.; 29 cm.
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- T1895122025
ANALISIS PERBANDINGAN ALGORITMA MACHINE LEARNING UNTUK PREDIKSI KATEGORI PENJ…
The rapid growth of the cosmetics industry on e-commerce platforms has intensified competition, creating a critical need for effective, data-driven marketing strategies. This study aims to conduct a comparative analysis of machine learning algorithms to predict the sales categories (High, Medium, Low) of cosmetic products on the Tokopedia marketplace. Four classification models; Random Forest, …
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- xvi, 69 hlm.; ilus.; tab.; 29 cm.
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- T1894152025
PERBANDINGAN KINERJA LSTM, RANDOM FOREST, DAN SVR BERBASIS KNOWLEDGE DISCOVER…
Rice is a primary staple food in Indonesia, particularly in South Sumatra Province. In February 2024, BBC News Indonesia reported that the price of premium rice surged to Rp18,000 per kilogram, marking the highest price in the country’s history. To anticipate and predict similar spikes in the future, this study applies a Knowledge Discovery approach and compares three machine learning models:…
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- xvi, 96 hlm.; ilus.; tab.; 29 cm.
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- T1895362025
ANALISIS SENTIMEN PENGGUNA MEDIA SOSIAL X TERHADAP FILM SORE: ISTRI DARI MASA…
Indonesia’s film industry is rapidly expanding with diverse genres and new titles, creating a need for fast, data-driven mapping of audience sentiment. This study maps social media X users’ sentiment toward the film “Sore: Istri dari Masa Depan,” which carries an unconventional theme, while addressing limited manual labels on short and noise tweets. Support Vector Machine (SVM) is selec…
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- xvi, 131 hlm.; ilus.; tab, 29 cm
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- T1893632025
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