RANCANG BANGUN MEDIA CERITA CERDAS BERBASIS DEEP LEARNING UNTUK MENANAMKAN NI…

This study aims to develop deep learning-based Smart Storytelling media to improve Indonesian language literacy and instill Sustainable Development Goals (SDGs) values among fifth-grade elementary school students. Employing a Research and Development (R&D) approach, the study used the ADDIE model, consisting of five stages: Analysis, Design, Development, Implementation, and Evaluation. The resu…

KEMAMPUAN NUMERASI MELALUI PROBLEM BASED LEARNING BERBANTUAN LIVEWORKSHEETS P…

This study aimed to describe students’ numeracy skills after the implementation of the Problem Based Learning (PBL) model assisted by Liveworksheets on exponential material. This study employed a descriptive research design conducted at SMAN 1 Indralaya Utara involving students of class X-4 in the 2025/2026 academic year selected through purposive sampling technique. Data were collected throu…

PENGEMBANGAN LKPD IPA TERPADU BERBASIS PROBLEM BASED LEARNING TOPIK BAHAYA AS…

This development research was conducted to produce valid student worksheets (LKPD) based on Problem-Based Learning. The research method used is the ADDIE development model, with the evaluation phase employing Tessmer’s formative evaluation. Data were collected through walkthroughs and questionnaires. The results of the study indicate that the integrated science LKPD based on problem-based lea…

KLASIFIKASI PENYAKIT JANTUNG BERBASIS SELEKSI FITUR CHI-SQUARE DAN MACHINE LE…

Heart disease is one of the leading causes of death worldwide, making accurate early detection methods essential. Machine learning can be used to classify patients conditions, but data imbalance and feature selection can affect model performance. This study applied Chi-Square feature selection and the Synthetic Minority Over-sampling Technique (SMOTE) to 918 patient records with 11 clinical att…

KLASIFIKASI KOMPOSISI PADA PRODUK KEMASAN MAKANAN UNTUK IDENTIFIKASI ALERGEN …

Eczema is a skin condition that can be triggered by food allergens, requiring sufferers to carefully examine the composition of packaged food products. The complexity of ingredient labels often makes manual identification difficult. This study aims to develop a food composition classification system to detect allergens that trigger eczema using the Convolutional Recurrent Neural Network (CRNN) …

THE CORRELATION BETWEEN INFORMAL DIGITAL LEARNING OF ENGLISH AND RECEPTIVE VO…

This study investigated the correlation and contribution of Meaning-Focused Informal Digital Learning of English (IDLE) to the receptive vocabulary knowledge of English Education students at Sriwijaya University. A correlational research design was employed with 98 undergraduate students from the fourth and sixth semesters of the academic year 2025/2026. Data were collected through a 12-item Me…

ANALISIS PENGARUH VARIASI MATERIAL DYE ALAMI TERHADAP PERFORMA KELISTRIKAN DY…

The electrical performance of Dye Sensitized Solar Cells (DSSC) is significantly influenced by the characteristics of the dye material used as a sensitizer. Variations in natural dye materials produce differences in light absorption capability and electrical characteristics, which directly affect power conversion efficiency. This study aims to analyze the effect of natural dye material variatio…

MODEL TRANSFORMER BERBASIS DEEP LEARNING UNTUK SEGMENTASI CITRA JANTUNG JANIN

Masalah: Identifikasi batas jantung dan rongga dada pada citra USG jantung janin masih dilakukan secara manual sehingga berpotensi menimbulkan variabilitas hasil. Selain itu, karakteristik citra USG seperti speckle noise, kontras yang rendah, serta dominasi intensitas abu-abu membuat proses segmentasi struktur anatomi menjadi lebih menantang. Tujuan: Penelitian ini bertujuan mengimplementasikan…

SEGMENTASI CITRA PARU-PARU MENGGUNAKAN ARSITEKTUR CUSTOM U-NET

Manual analysis of COVID-19 chest CT scans is often time-consuming and prone to subjectivity, thereby hindering diagnostic efficiency. Therefore, this study aims to develop an automatic segmentation system using a Custom U-Net architecture with a pre-trained DenseNet-169 encoder to accurately map infection areas, including Ground Glass Opacity (GGO), Consolidation, and Pleural Effusion classes.…

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…

Learning to Teach, SEVENTH EDITION

Edition

7

ISBN/ISSN

978-0-07-312813-9

Collation

xxiii, 584 p. : ill. ; 28 cm.

Series Title

-

Call Number

370.152 3 Are l

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…

KEMAMPUAN COMPUTATIONAL THINKING PADA MATERI BARISAN DAN DERET MENGGUNAKAN PR…

Perkembangan teknologi di era digital saat ini mengalami akselerasi yang luar biasa, memberikan dampak signifikan terhadap berbagai sektor terutama dunia pendidikan. Situasi ini mengharuskan siswa untuk memiliki sejumlah kompetensi fundamental, dengan Computational Thinking (CT) menjadi salah satu yang paling krusial. Riset ini difokuskan untuk menggambarkan bagaimana indikator-indikator CT ter…

IDENTIFIKASI DAN DETEKSI OTOMATIS TERHADAP KARIES GIGI MENGGUNAKAN CONVOLUTIO…

Deteksi karies gigi masih menjadi tantangan karena bergantung pada interpretasi visual subjektif, yang dapat menyebabkan inkonsistensi. Metode deep learning, khususnya Convoulutional Neural Network (CNN), telah menunjukkan potensi besar dalam meningkatkan akurasi diagnostik berbasis radiografi. Tujuan: Untuk meninjau literatur terkini mengenai aplikasi deep learning dalam deteksi karies gigi ot…

IMAGE CAPTIONING BERBASIS DEEP LEARNING PADA CITRA JANTUNG ANAK

Diagnosis of congenital heart disease in children, namely Atrial Septal Defect (ASD), Atrioventricular Septal Defect (AVSD), and Ventricular Septal Defect (VSD), is hindered by the limited availability of cardiologists in interpreting echocardiography images, necessitating an automated system based on artificial intelligence. This study implements and evaluates a deep learning-based image capti…

GENERATIVE AI BERBASIS DEEP LEARNING PADA ANALISIS CITRA ULTRASONOGRAFI

Ultrasound (USG) image analysis for detecting Congenital Heart Disease (CHD), such as Atrial Septal Defect (ASD), Ventricular Septal Defect (VSD), and Atrioventricular Septal Defect (AVSD), is still limited by the scarcity of clinical datasets. This study evaluates three Generative Adversarial Network (GAN) architectures, namely Deep Convolutional GAN (DCGAN), Wasserstein GAN with Gradient Pena…

DEVELOPING A LOCAL CULTURE-BASED AUDIOVISUAL MEDIA IN EFL TEACHING TO PROMOTE…

In the era of globalization, integrating local culture into English language teaching is important to promote students’ cultural awareness while improving their language skills. This study aimed to develop a local culture-based audiovisual media in EFL teaching for seventh-grade students. The product was designed as supplementary learning media integrating Palembang local culture into English…

PENGEMBANGAN ARSITEKTUR 3D U-NET DENGAN RESIDUAL NETWORK DAN INCEPTIONV3 UNTU…

A lung cancer diagnosis can be performed using 3D CT scan images. Cancerous areas are identified through a segmentation process. This study develops a 3D U-Net with Residual Network (ResNet) and InceptionV3 to segment lung cancer in 3D CT scans. The 3D U-Net architecture was applied because it can exploit volumetric spatial information in 3D CT scan images. ResNet is applied to the encoder sect…

PENERAPAN PEMBELAJARAN DENGAN PENDEKATAN DEEP LEARNING PADA MATERI SISTEM PER…

This study aims to describe the mathematics learning process and analyze the learning outcomes of Two Variable Linear Equation Systems (SPLDV) material using a Deep Learning approach. The research subjects were 23 ninth-grade students at SMP Negeri 58 Palembang. This study used a descriptive method with data collection through observation and written tests consisting of three contextual questio…

ANALISIS KOMPARATIF MACHINE LEARNING DAN EXPLAINABLE ARTIFICIAL INTELLIGENCE …

Traffic accidents are a road safety issue that can result in fatalities. This study aims to compare the performance of machine learning models namely, Random Forest, XGBoost and LightGBM and to explain the prediction results of the best model using the Explainable Artificial Intelligence (XAI) approach, with SHapley Additive exPlanations (SHAP) employed as the interpretation method. The data us…

EVALUASI METODE UNSUPERVISED LEARNING DALAM PENGELOMPOKAN DATA KECELAKAAN LAL…

Traffic accidents are one of the transportation issues that require distribution analysis to identify areas with different accident characteristics. This study aims to compare the K-Means, DBSCAN, and Hierarchical Clustering methods in clustering traffic accident data based on geographical location and accident severity. The dataset used is derived from traffic accident data in the United Kingd…

PENINGKATAN KINERJA KLASIFIKASI GANGGUAN JANTUNG PADA SINYAL ELEKTROKARDIOGRA…

Electrocardiogram (ECG) signals represent the electrical activity of the heart and are used to record disorders such as arrhythmia and heart failure. Due to their non-stationary nature, ECG signals require a time-frequency domain approach to capture their dynamic characteristics more accurately. This study aims to develop and evaluate machine learning-based heart disorder classification models …

MULTI OBJECT TRACKING PADA CITRA JANTUNG ANAK MENGGUNAKAN DEEP LEARNING

Congenital heart disease (CHD) in children, such as atrial septal defects (ASD), ventricular septal defects (VSD), and atrioventricular septal defects (AVSD), requires accurate diagnosis through dynamic analysis. However, existing methods for analyzing echocardiographic video are often limited to frame-by-frame analysis and are not yet capable of consistently tracking temporal changes. This stu…

IMAGE CAPTIONING PADA CITRA SERVIKS UNTUK LAPORAN MEDIS BERBASIS MODEL DEEP L…

Image captioning is a task in the fields of computer vision (CV) and natural language processing (NLP) that aims to generate textual descriptions from an image. In this study, various combinations of encoder–decoder architectures were designed and evaluated to improve captioning performance on cervical medical images from the International Agency for Research on Cancer (IARC). The encoders us…

PENGARUH PENERAPAN MODEL EXPERIENTIAL LEARNING TERHADAP MOTIVASI BELAJAR PESE…

This study aims to determine the effect of the application of the Experiential Learning model on students' learning motivation in the Pancasila Education subject at SMAN 2 Indralaya Utara. This study uses a quantitative approach with an experimental method. Data collection was carried out through documentation, observation, and questionnaire techniques. The study population included all 93 stud…

SMART INDUSTRY: PENDEKATAN ARSITEKTUR EDGE COMPUTING BERBASIS MACHINE LEARNIN…

Kebakaran hutan merupakan bencana lingkungan dengan dampak ekologis, ekonomi, dan sosial yang signifikan secara global. Sistem deteksi konvensional berbasis visual (kamera) dan sensor asap memiliki keterbatasan dalam hal cakupan area, latensi deteksi, akurasi dalam kondisi lingkungan kompleks, dan ketergantungan pada infrastruktur komunikasi yang memadai. Penelitian ini mengusulkan pendekatan i…

SISTEM PATH PLANNING PADA AUTONOMOUS ELECTRIC VEHICLE BERBASIS HYBRID IMPROVE…

Teknologi kendaraan otonom memerlukan sistem navigasi yang andal untuk menghadapi lingkungan dinamis dan kondisi jalan yang kompleks. Tantangan utama meliputi perencanaan rute optimal, deteksi objek secara real-time, serta adaptasi terhadap rintangan. Penelitian ini mengusulkan integrasi Improved Ant Colony Optimization (IACO) dan YOLOv8 sebagai solusi terpadu untuk perencanaan rute dan deteksi…

PENGEMBANGAN E-LKPD BERBASIS DISCOVERY LEARNING MATERI FILTRASI BERBANTUAN ME…

Penelitian ini bertujuan untuk menghasilkan produk berupa e-LKPD berbasis discovery learning pada materi filtrasi berbantuan membran nanofiber guna melatih keterampilan berpikir kreatif peserta didik SMP secara valid, praktis, dan efektif. Penelitian ini menggunakan metode penelitian pengembangan dengan model ADDIE dan melibatkan 217 peserta didik kelas VII dari sepuluh kelas (VIIA–VIIJ) di S…

KEMAMPUAN MEMPREDIKSI POLA KONFIGURASI OBJEK SISWA KELAS VIII MTS AISYIYAH 1 …

This research is motivated by the importance of predicting skills as a fundamental aspect of mathematical inference, enabling students to project beyond observed data. The study aims to describe the numerical predicting ability of eighthgrade students at MTs Aisyiyah 1 Palembang on object configuration patterns using the Discovery Learning model assisted by GeoGebra Web. A descriptive qualitati…

PENGARUH OPERASI STERIL TERHADAP POLA MAKAN KUCING DAN SUMBANGANNYA PADA PEMB…

Sterilization surgery is one alternative for controlling the cat population and improving the quality of life for cats. However, understanding and managing changes in eating patterns after sterilization is an important part of the commitment to maintaining healthy cats in the long term. This study aims to analyze the effect of sterilization surgery on cats' eating patterns and to develop a Stud…