PERANCANGAN SISTEM MONITORING PEMILAHAN LIMBAH MEDIS BASAH, KERING, DAN LOGAM…

Medical waste is a type of waste that requires special handling because it can affect health and the environment if not properly managed. One important stage in managing medical waste is sorting it by type. However, sorting, which is still done manually, can be prone to errors in categorising waste. Therefore, a monitoring system for sorting wet, dry, and metal medical waste based on the Intern…

RANCANG BANGUN SISTEM PEMILAHAN LIMBAH MEDIS BASAH DAN KERING BERBASIS ESP32 …

Medical waste generated from operating rooms has the potential to pose risks to health and the environment if not properly managed. One of the important stages in medical waste management is the waste sorting process based on its characteristics. However, the sorting process is still largely carried out manually, which risks causing sorting errors and increasing direct contact with infectious w…

IMPLEMENTATION AND ANALYSIS OF THE STATE-ACTION-REWARD-STATE-ACTION (SARSA) A…

Flooding is one Malware is one of the major threats to cybersecurity and continues to evolve, making it increasingly difficult to detect using conventional methods. This study aims to implement and analyze the State-Action-Reward-State-Action (SARSA) and Deep Q-Network (DQN) algorithms for binary malware classification based on static features extracted from the dataset. Data preprocessing, fea…

RANCANG BANGUNSISTEM STREAMING SENSOR DATA MENGGUNAKAN LARAVEL 12 BERBASIS WE…

The development of Internet of Things (IoT) technology has encouraged the creation of monitoring systems capable of transmitting and displaying sensor data quickly and in real-time. Web-based sensor data streaming systems have become one of the solutions to simplify the process of monitoring environmental conditions through internet networks. This research focuses on the design and development …

Komputer Cerdas untuk Mahasiswa Teknik Informatika

Edition

-

ISBN/ISSN

978-602-401-976-1

Collation

viii, 243 hlm. 23 cm

Series Title

-

Call Number

621.381 542 Naf k

PEMROGRAMAN DATABASE

Edition

-

ISBN/ISSN

978-602-401-822-1

Collation

viii, 37 hlm.; 20 cm

Series Title

-

Call Number

005.1 Tur p

SISTEM PEMANTAUAN SUHU TUBUH DAN LINGKUNGAN BERBASIS IOT DENGAN IMPLEMENTASI …

Hypothermia is a condition in which body temperature drops below the normal limit because the body loses heat faster than it can produce it. This condition can be influenced by low environmental temperature and humidity, which may endanger human health. This study aims to design an Internet of Things (IoT)-based body and environmental temperature monitoring system with the implementation of Mam…

SEGMENTASI JANTUNG ANAK MENGGUNAKAN VISION TRANSFORMER DAN SEGMENT ANYTHING M…

Congenital heart disease in children requires accurate early detection through ultrasonography (USG) imaging. This study aims to develop a deep learning–based system for view classification and hole segmentation in pediatric cardiac images. A Vision Transformer (ViT) model was employed to classify five cardiac views (4CH, 5CH, LA, SA, and SUB), while segmentation was performed using YOLO11-se…

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…

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…

PENERAPAN METODE RANDOM FOREST DALAM SISTEM PERINGATAN BANJIR BERBASIS INTERN…

Flooding is one of the most common natural disasters and can cause significant losses. This study aims to design and develop an Internet of Things (IoT)-based flood warning system using the Random Forest algorithm. The system utilizes BMP280 sensors to measure water level and an optocoupler sensor to measure water flow velocity. Sensor data are processed by an ESP32 microcontroller and sent to …

PERANCANGAN HEALTH MONITORING SYSTEM PENDETEKSI DETAK JANTUNG, SATURASI OKSIG…

Monitoring vital signs such as heart rate, oxygen saturation, and body temperature is a primary indicator for the early detection of a person's health condition. However, conventional monitoring is often still manual and limited by distance, making it inefficient for continuous supervision. This research aims to design an Internet of Things (IoT)-based health monitoring system capable of presen…

PERBANDINGAN IOB1 DAN IOE TAGGING SCHEME PADA NAMED ENTITY RECOGNITION UNTUK …

Advanced Persistent Threat (APT) reports in Cyber Threat Intelligence (CTI) are generally presented as unstructured text, making them difficult to analyze manually and requiring automated methods to extract important entities quickly and accurately. This study aims to analyze the performance of Named Entity Recognition (NER) using a Bidirectional Long Short-Term Memory (BiLSTM) model with two s…

EKSTRAKSI INDICATOR OF COMPROMISE PADA CYBER THREAT INTELLIGENCE MENGGUNAKAN …

Penelitian ini bertujuan untuk mengembangkan sistem ekstraksi Indicator of Compromise (IoC) dari teks Cyber Threat Intelligence (CTI) menggunakan pendekatan Named Entity Recognition (NER). Permasalahan utama dalam CTI adalah data yang bersifat semi-terstruktur sehingga menyulitkan identifikasi informasi penting secara manual. Metode yang digunakan adalah model BiLSTM-CRF dengan skema BIO untuk …

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 …

IMAGE CAPTIONING BERBASIS DEEP LEARNING PADA CITRA REUMATOLOGI

The advancement of medical imaging technology has produced increasingly complex data that require fast and accurate analysis. However, the interpretation of medical images still requires considerable time, relies heavily on medical professionals, and is prone to interpretation errors. Therefore, this study aims to develop an Image Captioning system capable of automatically generating descriptio…

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…

SISTEM LOAD BALANCING SERVER SMART FARMING BERBASIS DOCKER SWARM MENGGUNAKAN …

Smart farming requires a reliable server infrastructure to handle real-time data requests. The use of a single server may cause overload and reduce service performance. This study aims to implement a Docker Swarm-based load balancing system for smart farming servers using Single Board Computers in the form of Raspberry Pi. The system architecture consists of one manager node and two worker node…

PENGEMBANGAN INFOGRAFIS INTERAKTIF BERBASIS AI MATERI LEMBAGA SOSIAL TONARIGU…

This research is entitled "Development of AI-Based Interactive Infographics on the Tonarigumi Social Institution During the Japanese Occupation at SMA Negeri Plus 2 Banyuasin III." The problem in this research focuses on how to develop interactive infographic media based on Artificial Intelligence that meets the criteria for validity and practicality as a history learning medium. The purpose of…

ANALISIS DAN PERENCANAAN SISTEM JARINGAN DISTRIBUSI AIR DI KAMPUS UNIVERSITAS…

This study aims to analyze the effectiveness of plenary meetings held by the Trial and Legislation Section at the Bangka Regency DPRD Secretariat. The research problem stems from the postponement and cancellation of meetings, which impact the regularity of the agenda and the effectiveness of decision-making. The analysis used Stephen P.Robbins' (1990) Systems Approach, which assesses effectiven…

SOFT VOTING ENSEMBLE LEARNING YOLO DENGAN FINETUNING CNN RESNET, EFFICIENTNET…

The rapid advancement of computer vision and deep learning has greatly improved image classification performance. However, maintaining consistent accuracy across diverse datasets and visual conditions remains challenging. This study proposes a soft voting ensemble learning approach for image classification using three fine-tuned Convolutional Neural Networks (CNNs): ResNet, EfficientNet, and De…

RANCANG BANGUN APLIKASI PENGELOLAAN KEUANGAN BERBASIS WEB PADA HOMESCHOOLING …

Pengelolaan keuangan pada Homeschooling Sriwijaya Kids sebelumnya masih sangat bergantung pada ketelitian pegawai, sehingga berisiko menimbulkan kesalahan pencatatan, data ganda, keterlambatan rekapitulasi, serta kesulitan dalam penyusunan laporan keuangan. Penelitian ini bertujuan untuk merancang dan membangun aplikasi pengelolaan keuangan berbasis web yang dapat membantu proses pencatatan, pe…

PENGEMBANGAN MEDIA PEMBELAJARAN INTERAKTIF BERBANTUAN GOOGLE SITES PADA MATER…

The development of an interactive learning media assisted by Google Sites on the topic of plane figures for fourth-grade elementary school students SDN 10 Talang Kelapa aims to determine the development stages, assess the validity level, and evaluate the media practicality. This study employed the Research and Development (R&D) method using the ADDIE model, which consists of the Analyze, Design…

ANALISIS SENTIMEN PENGGUNA INSTAGRAM TERHADAP POSTINGAN PROGRAM MAKAN SIANG G…

Social media is widely used today for communication and information exchange. One of the most popular social media platforms is Instagram. The comments section on an Instagram post creates discussions among users regarding issues that are currently being widely discussed. One of the issues that is currently being widely discussed is the free lunch program, which is a new program created by the …

PERANCANGAN PROTOTIPE CLINICAL DECISION SUPPORT SYSTEM UNTUK PREDIKSI RISIKO …

Type 2 diabetes is a chronic disease that requires early detection to reduce the risk of complications. This study aims to design a web-based prototype Clinical Decision Support System (CDSS) to predict diabetes risk using the XGBoost algorithm and improve interpretability through the SHAP method. The dataset used was obtained from Kaggle and consisted of approximately 100,000 records with eigh…

SISTEM PREDIKSI BANJIR MENGGUNAKAN SENSOR TEKANAN DAN WATERFLOW SENSOR DENGAN…

Most current flood prediction studies rely on secondary data with limited temporal resolution and Deep Learning models with high computational demands. This research addresses this gap by designing an early warning system that is computationally efficient, utilizing direct physical sensor data within a controlled simulation. The objectives are to measure water flow velocity (m/s) using an optoc…

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 …