Denial of Service (DoS) attacks pose a serious threat to IPv6-based smart home networks, causing disruptions in device connectivity and significantly reducing system performance. This study aims to detect DoS attacks in IPv6 smart home networks using the Logistic Regression machine learning algorithm. The dataset was generated from network traffic captured using the THC-IPv6 tool, followed by f…
Supply Chain Management involves several parties who play a role in the process of delivering goods or services so it requires transparency regarding transaction records for all parties involved with the aim of avoiding falsification of transaction data. To overcome this problem, this research aims to build a security system using the Proof-of-Stake (poS) method. A collection of blocks containi…
The development of smart home technology provides convenience for users in managing household devices automatically and through internet connectivity; however, it also raises potential security threats, such as SSL Pinning Bypass, which allows attackers to intercept communications, and Distributed Denial of Service (DDoS) attacks, which can disrupt service availability. To address these issues,…
Monitoring outdoor air quality requires clear data visualization to enable rapid understanding of environmental conditions. This study develops an air quality visualization system using Streamlit based on CO₂, temperature, and humidity data obtained from the Air Quality Detection device. The data undergo preprocessing, quality classification, and analysis of trends and parameter correlations.…
Insider threat is one of the most challenging security threats to detect because the attacker possesses legitimate access rights to the system. This research aims to analyze an insider attack scenario that exploits legal access through the Secure Shell (SSH) service in the process of data acquisition and privilege escalation on a Linux system. The research method involves simulating insider act…
Maximal Extractable Value (MEV) bot activity on blockchain networks poses a significant challenge, as MEV bots exploit transaction-processing mechanisms to gain profit in ways that may hinder fairness, increase gas fees, and disrupt network stability. This study employs the Extreme Gradient Boosting (XGBoost) model to classify MEV bot activity in Ethereum blockchain transactions using numerical…
This study aims to detect and classify Distributed Denial of Service (DDoS) and Man-in-the-Middle (MiTM) attacks in smart home networks using the Light Gradient Boosting Machine (LightGBM) algorithm. With the rapid growth of Internet of Things (IoT) devices, cybersecurity challenges have become crucial due to vulnerabilities in smart home devices. This research utilizes the COMNETS SMARTHOME da…
This study examines the effect of Quizwhizzer, a web-based interactive learning platform, on students’ learning motivation in the Economics subject at SMA Negeri 12 Palembang. The research employed a quantitative approach with a pre-experimental one-group pre-test post-test design and involved 33 eleventh-grade students (class XI.4) as participants. The increase in learning motivation was evi…
The advancement of Internet of Things (IoT) technology has brought significant changes to everyday life, especially through the adoption of smart home devices. The use of smart homes is growing rapidly because it can help make housework easier. However, the increasing use of these devices also increases cyber threats. Some dangerous threats are SSL Pinning Bypass and MITM. In this study, we wil…
This studyaims to describe the Higher Order Thinking Skill of high school students in trigonometry through the Problem BasedLearning (PBL) learning model assisted by Digital Worksheet, namely Liveworksheet.This type of research uses a descriptive research method. The subjectsof the study consisted of 37 tenth grade students. Data collection techniqueswere carried out through tests and interview…
Fire is a serious threat that can cause significant material and human losses. Early detection of fire and identification of surrounding objects is crucial to minimize risk. In this final project, a real-time fire and object detection system was developed using HSV-based image processing to identify the typical colors of fire, and the YOLOv3 algorithm to detect various objects such as humans an…
This research aims to compare the performance of the Random Forest and Support Vector Machine methods in analyzing Facebook data sentiment related to traffic congestion in Palembang City. Data was obtained through a web scraping process and labeled using a lexicon-based approach into three sentiment classes, namely positive, negative, and neutral. Feature representation was performed using the …
This study aims to analyze public sentiment toward traffic congestion in Palembang City based on Facebook social media comments using the Naïve Bayes algorithm. Data were collected through web scraping of Facebook comments related to traffic conditions in Palembang and labeled using a lexicon-based approach into three sentiment classes: positive, negative, and neutral. The dataset consists of …
General vision-language models often face domain shift issues when applied to medical imaging. This study compares the performance of a general model (BLIP) against a medically pre-trained model (MedBLIP) for Chest X-ray reporting using the IU X-Ray dataset. Through quantitative metrics and expert pulmonologist validation, MedBLIP consistently outperformed BLIP, achieving a BLEU-4 of 0.0789, RO…
Modern agriculture increasingly relies on technology to improve efficiency and productivity, one of which is through the application of the Internet of Things (IoT). This study aims to develop an IoT-based automatic irrigation system for tomato plants with real-time temperature and humidity monitoring. The system is designed using the DS18B20 sensor to measure environmental temperature and humi…
The increasing number of APKs in mobile technology each year often coincides with the emergence of APKs containing malware. Through the Metasploit framework, threat actors are able to embed payloads into benign APKs. To address this issue, forensic investigation on mobile devices becomes crucial. This research aims to conduct forensic analysis on Android devices infected with Trojan APKs, apply…
In the era of computer vision and machine learning advancement, the integration of gesture recognition technology in interactive gaming continues to evolve. This study aims to develop a multiplayer rock-paper-scissors game based on hand gesture detection using MediaPipe and real-time communication with Socket.IO. The MediaPipe Hands model is utilized to detect and classify hand gestures, while …
Tanaman anggur merupakan komoditas hortikultura bernilai ekonomi tinggi yang rentan terhadap serangan hama belalang, sehingga diperlukan sistem identifikasi yang cepat dan akurat. Penelitian ini bertujuan untuk mengimplementasikan sistem klasifikasi hama belalang pada tanaman anggur berbasis Internet of Things (IoT) menggunakan metode machine learning. Sistem dikembangkan dengan mengombinasikan…
Kematangan buah anggur merupakan faktor utama dalam menentukan kualitas dan nilai jual buah karena berpengaruh langsung terhadap rasa, tekstur, dan tingkat kesegaran. Penilaian kematangan buah anggur secara manual masih memiliki keterbatasan karena bersifat subjektif dan bergantung pada pengalaman manusia. Penelitian ini bertujuan untuk merancang dan menganalisis sistem klasifikasi kematangan b…
Pertanian anggur di Indonesia menghadapi tantangan serius akibat serangan hama yang menurunkan kualitas dan kuantitas hasil panen, sehingga diperlukan sistem deteksi yang cepat dan akurat. Penelitian ini bertujuan mengimplementasikan metode Convolutional Neural Network (CNN) berbasis MobileNetV2 yang terintegrasi dengan Internet of Things (IoT) untuk mendeteksi dan mengklasifikasikan hama pada …
Audio in video games plays a crucial role in creating an immersive and engaging gaming experience. However, indie game developers often face resource constraints, particularly in producing high-quality character voices. Voice cloning technology based on Retrieval-based Voice Conversion (RVC) offers an innovative solution by enabling accurate voice replication and transformation using minimal da…
Sentiment analysis is a branch of Natural Language Processing (NLP) used to determine public opinions on specific topics as positive, negative, or neutral. This study aims to compare the performance of two feature extraction methods across three scenarios: TF-IDF, Word2Vec-CBOW, and Word2Vec-skipgram. The dataset utilized consists of comments from the Instagram platform @magangmerdeka regarding…
Ojin is the first online transportation application in Indralaya. The potential for user dissatisfaction cannot be dismissed solely based on the application's user count. Therefore, it is essential to assess the Ojin application through methods such as the user experience questionnaire and cognitive walkthrough. This study aims to evaluate user experience and measure the usability level of the …
MSMEs need to understand consumer behavior and improve business efficiency through transaction data analysis. This research focuses on purchasing patterns for chips and crackers products using the Apriori algorithm on transaction data for Rizan 858 Snack MSMEs. The transaction data includes 200 transactions recorded between October 2023 and May 2024. The analysis process was conducted in severa…
Lettuce (Lactuca sativa L.), is a commodity crop that is frequently consumed around the world. During cultivation, lettuce often faces challenges such as diseases that can cause losses. Classification of diseases on lettuce leaves is an important challenge in maintaining the quality and quantity of crop yields.. This study compares the performance of Convolutional Neural Network (CNN) and Visio…
Climate change and air pollution drive the search for environmentally friendly solutions, such as electric cars. Although they offer benefits like reduced emissions and energy efficiency, public acceptance varies depending on factors like price, infrastructure, and environmental awareness. This study employs the Support Vector Machine (SVM) algorithm as a machine learning model and the ADASYN m…
This research presents the implementation and evaluation of a LightWeight Vision Transformer (ViT) architecture for classifying seven different types of skin cancer using medical dermoscopic images from the HAM10000 dataset. The methodology includes data preprocessing, class balancing using Random Oversampling, and splitting the dataset into training and testing sets. Several hyperparameter con…
JOOX is an online music streaming platform that gives users the opportunity to listen to music from various genres live. JOOX provides a free streaming service that is accompanied by some advertisements, and also presents a premium subscription service that provides additional access such as ad-free playback, better audio quality, and other exclusive content. According to data obtained from moj…
Perkembangan teknologi telah mempengaruhi manusia dalam menonton film terutama bioskop. Penggunaan teknologi aplikasi mobile telah meningkatkan proses pembelian tiket bioskop secara online. Salah satu aplikasi yang menerapkan pemesanan tiket online adalah M-Tix. Aplikasi M-Tix telah mengalami beberapa kali pembaruan yang berguna untuk meningkatkan kinerja dan pengalaman pengguna. Dalam peneliti…
The rapid development of digital technology has a significant impact on the entertainment industry, especially on mobile games. Evaluation is needed to ensure usability, experience, and player satisfaction. The rapid increase in the mobile game industry makes evaluating these aspects important to ensure that games are not only attractive from the virtual, but also provide an optimal playing exp…