Journal of Computer Networks, Architecture and High Performance Computing
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Diagnosis and Prediction of Chronic Kidney Disease Using a Stacked Generalization Approach
Get PDFChronic Kidney Disease (CKD) is. In the past, several learners have been applied for prediction of CKD but there is still enough space to develop classi?ers with higher accuracy. The study utilizes chronic kidney disease dataset from UCI Machine Learning Repository. In this paper, individual approaches, viz., linear-SVM, kernel methods including polynomial, radial basis function, and sigmoid have been used while among ensembles majority voting and stacking strategies have been applied. Stacked Ensemble is based on various types of meta-learners such as C4.5, NB, k-NN, SMO, and logit-boost. The stacking approach with meta-learner Logit-Boost (ST-LB) achieves accuracy 98,50%, sensitivity 98,50%, false positive rate 20,00%, precision 98,50%, and F-measure 98,50% demonstrating that it is the best classi?er as compared to any of the individual and ensemble approache
K-Nearest Neighbor Algorithm and Case Base Reasoning on Xenia Car Damage Detection Expert System
Get PDFPT Astra Daihatsu Motor or commonly abbreviated as ADM is the Sole Agent Brand Holder (ATPM) of Daihatsu cars in Indonesia. Xenia car is one of the most popular cars in Indonesia. Although there are many Xenia car users, it is not uncommon for Xenia cars to experience damage caused by the ignorance of car users, where the car user only knows how to use it but does not know how to maintain the car properly and correctly. Before damage occurs to the car, the car usually experiences several symptoms of damage that the user does not realize. With that, there are often difficulties experienced by users to find out the type of damage to the car. The purpose of applying and designing applications in this study is to apply the Case Based Reasoning method with the K-Nearest Neighbor Algorithm to detect damage to Xenia cars and to design and build applications with the Case Based Reasoning method with the K-Nearest Neighbor Algorithm to detect damage to web-based Xenia cars. This research uses the Research and Development method. Based on the results of research from previous cases, the new case has similarities with 5 cases and the highest similitude value is with the highest type, namely the type of Injector Malfunction damage with a value of 0.625 or around 62.5%. This expert system application can detect and determine the results of Xenia car engine damage detection by applying a method that looks for the closest similarity value of new cases to old cases, namely the Case Based Reasoning method and the K-Nearest Neighbor Algorithm looking for the closest neighbors of the same weight value. This web-based expert system can be used by users to find the results of Xenia Car engine damage detection experienced by determining the symptoms that are available in web-based applications. This web-based application can also provide solutions from the detection results of the type of Xenia car engine damage
Implementation of 3D Animation Video-Based Learning Media in the Introduction of Silat Martial Arts in the Brotherhood of Setia Hati Terate (PSHT)
Get PDFPersaudaraan Setia Hati Terate (PSHT) is one of the organizations that has an important role in the development and preservation of martial arts in Indonesia. Saifullah An-Nahdliyah Islamic Boarding School is one of the educational institutions that organizes the teaching of martial arts of the Persaudaraan Setia Hati Terate (PSHT). However, in the learning process applied to the introduction of martial arts Silat Persaudaraan Setia Hati Terate at Saifullah An-Nahdliyah Islamic Boarding School, there are still problems that can affect the effectiveness of Silat martial arts learning for students, namely the unavailability of learning media that supports other than direct training at Saifullah An-Nahdliyah Islamic Boarding School. This study aims to implement 3D animation video-based learning media in the introduction of martial arts of the Setia Hati Terate Brotherhood at Saifullah An-Nahdliyah Islamic Boarding School. The data collection techniques used to obtain the research data needed in this study are observation techniques, interviews, documentation, and literature studies. 3D animation video for learning media introduction to martial arts Pencak Silat Persaudaraan Setia Hati Terate at Saifullah An-Nahdliyah Islamic Boarding School is made using Blender application. The concept of 3D animation video made in this research is to present the introduction of martial arts by making moving characters, which can be accessed offline
Analysis of User Journey Mapping Factors to Enhance User Experience in the Tokopedia Mobile E-Commerce Application
Get PDFRecent technological advancements have significantly transformed human life, particularly with the advent of the Fourth Industrial Revolution, which has profoundly influenced the use of the internet for business and economic activities. E-commerce has emerged as a crucial medium for online buying and selling, propelled by these digital advancements. This growth is especially evident in Indonesia, which ranks among the countries with the highest number of internet users globally. This study aims to identify the dominant factors influencing user journey mapping and their impact on the user experience of Tokopedia mobile application users. The research sample comprises 125 users of the Tokopedia application, with data collected through questionnaires distributed via Google Forms. The analysis involves factor analysis and simple linear regression. The findings reveal that the dominant factors influencing user journey mapping are user persona and opportunity. Furthermore, the study demonstrates that user journey mapping positively impacts the user experience for Tokopedia application users. This research underscores the importance of understanding user journey mapping in enhancing the overall user experience, which is crucial for e-commerce platforms like Tokopedia. The insights gained from this study can assist developers and marketers in better tailoring their strategies to improve user engagement and satisfaction. This study provides valuable perspectives on how user journey mapping can be utilized as a strategic tool to optimize user interactions and ensure that each step in the user journey delivers maximum value. Thus, user journey mapping not only enhances individual experiences but also contributes to the overall success of e-commerce platforms in an increasingly competitive market
The Use of K-Means Algorithm Clustering in Grouping Life Expectancy (Case Study: Provinces in Indonesia)
Get PDFLife expectancy is defined as information that illustrates the age of the death of a population. Life expectancy is a general picture of the state of a region. If the infant mortality rate is high, then the life expectancy in the area is low. And vice versa, if the infant mortality rate is low, the life expectancy in the region is high. Life expectancy is also a benchmark for government actions in improving the welfare of society and the human development index. For this reason, it is necessary to group life expectancy data to make it easier to determine the provinces with high, middle, and low life expectancy. The results of cluster testing using the silhouette score method showed that two subjects had a low silhouette score level, which caused the cluster value to be less than optimal, namely East Java & Gorontalo. The clustering results found that the cluster was divided into 3, namely cluster 1, with a high level of life expectancy consisting of 10 provinces, namely East Java, Riau, North Sulawesi, Bali, North Kalimantan, DKI Jakarta, West Java, Central Java, East Kalimantan and Special Region of Yogyakarta. Cluster 2 has a level of middle-life expectancy consisting of 18 provinces, namely Gorontalo, North Maluku, Central Sulawesi, South Kalimantan, North Sumatra, Bengkulu, West Sumatra, Central Kalimantan, Aceh, South Sumatra, Banten, Kep. Riau, South Sulawesi, Kep. Bangka Belitung, Lampung, West Kalimantan, Southeast Sulawesi and Jambi. Cluster 3, with a low level of life expectancy, consists of 6 provinces, namely West Sulawesi, Papua, Maluku, West Papua, West Nusa Tenggara, and East Nusa Tenggara
Disguising Text Using Caesar Cipher, Reverse Cipher and Least Significant Bit (LSB) Algorithms in Video
Get PDFIn communication, there is a process of transferring information from the sender to the recipient. The information sent must be the same as the information received. If there are differences, it means that there has been a data change process carried out by irresponsible parties. One technique for changing the content of information is man in the middle. The data changer will receive information from the sender, then change it and forward it to the recipient, so that the changed information appears to have come from the sender.To protect information, this can be done by utilizing the science of cryptography and steganography which aims to protect information by changing it to another form or by inserting the information into other media. In this research, to protect information the Caesar Cipher Algorithm is used, this algorithm will change the letters in plaintext to another letter (ciphertext) by using an alphabetical shift according to the number in the form of the key used, namely > 1 and < 26, then the Reverse Cipher algorithm is carried out, namely changing the position of the letters of the plaintext from the first order to the last order and so on. The encrypted information will then be inserted into a video using the Steganography Algorithm, namely Least Significant Bit (LSB). Before being inserted, the video will first be converted into several image frames, then in one frame the information will be inserted. This can be done because the frame is a collection of RGB arrays which have values 0-255 or 0 and 1. So the insertion is done in bit form. Frames containing information will then be converted back into a video.On the receiving side, the video will be converted into a frame, next is the process of retrieving the information that was previously inserted. The information that has been taken is then reversed in order and then shifted using the Caesar chipper algorithm according to the key used by the sender, then the first letter of each word is changed to capital, so that the information sent is the same as that received. The implication of this research is that it is a way to combine cryptography with steganography as an information security technique
Association Relationship Analysis in Finding Sales of Goods With Apriori Algorithm
Get PDFTechnology can be designed to help human life from all aspects ranging from agriculture, health science, industry and daily life. Toko Intan, a business engaged in the sale of basic and daily necessities. Every day, Toko Intan records every sales transaction in an archive stored in Microsoft Excel, containing data on goods sold every day. The purpose of this research is to find out what items are bought simultaneously by consumers to manage inventory, with the data mining method used in this research is the Association Rules method. Association Rules is one of the data mining techniques from the a priori algorithm which functions to find a combination pattern of an item. Tests carried out to process data in this study using the RapidMiner application, from tests carried out with the specified parameters, namely minimum support 30% and minimum confidence 65%, resulted in a lift ratio validation rule of 1.206. Personal Care Biscuits with 30.8% support and 90.9% confidence with a validation lift ratio of 1.206. Sales transaction data analysis can be applied well, and is able to generate a new association rule from the sales transaction dataset. With this research, it is hoped that it can provide information to the owner of the Intan store in providing the stock of goods needed by consumers and to find out the combination of item sets from the sales transaction dataset
Sentiment Analysis of Reviews of Tourist Attractions in the Lake Toba Area Using the Naïve Bayes Method
No full textLake Toba is one of the tourism destinations in Indonesia which is the main destination for domestic and foreign tourists. However, the natural beauty of Lake Toba is not enough to develop quality tourist destinations, so analysis needs to be carried out in order to develop tourist destinations that suit tourist needs with the aim of improving the economy from tourism, especially at Lake Toba. One aspect that must be analyzed is comments from tourists who have visited Lake Toba via various platforms. This is very influential for potential future tourists to have a reference for Lake Toba tourism. The analysis process can be carried out by analyzing comments using the Naive Bayes method so that managers of the Lake Toba tourist destination can improve tourist attractions and provide tourist satisfaction and develop various tourism innovations to meet various tourist needs in a sustainable manner. The results of the sentiment analysis of Lake Toba tourist reviews using Naive Bayes detected 31 positive labels, 378 neutral labels and 7 negative labels with an accuracy result of 77.49% from 1260 data, where training data was 1008 and test data was 252 data
Analysis of Vina Film Sentiment on Social Media X Using The Naïve Bayes Method
Get PDFThe increasingly rapid development of technology and information, one of which is the internet. Where users can share opinions and discuss various topics or problems around them, namely social media One of the news items that frequently appears as a trending topic on X is the Vina film controversy. However, with the large amount of review data available, it will be difficult to process manually. Therefore, sentiment analysis is needed to see whether people's tendencies toward the Vina film case are positive or negative. The stages carried out were data collection taken via web scrapping with an initial amount of data of 833 and processed through the preprocessing stage, including cleaning, case folding, normalization, stopword removal, tokenization, and stemming, the data became 830. The application of the Naïve Bayes algorithm in this research uses the probability method to classify and predict 664 training data and 166 test data, with the help of the Python library. The accuracy calculation results show quite good performance with TF-IDF weighting producing an accuracy of 78%, precision of 80%, and recall of 90%, f1-score of 84%. Analysis from this research shows that the dominance of negative sentiment is 517 while positive sentiment is 313. The amount and quality of training data play an important role in system quality, where high data quality provides better accuracy in predicting sentiment classes
Comparison of Deep Learning Methods for Detecting Tuberculosis Through Chest X-Rays
Get PDFChronic diseases are the leading cause of death worldwide, accounting for 73% of deaths in 2020. Tuberculosis (TB), caused by the bacterium Mycobacterium tuberculosis, is one of these diseases and has a significant impact on countries with a high TB burden due to a lack of radiologists and medical equipment. Early diagnosis of TB is crucial but challenging because of its similarity to lung cancer and the shortage of radiologists. A semi-automatic TB detection system is needed to support medical diagnosis and improve public health services. Deep learning technology, such as Convolutional Neural Networks (CNN), offers an effective solution for disease diagnosis with high accuracy. This study compares deep learning methods using an 8-layer CNN and VGG-19, both enhanced with Histogram Equalization (HE) for improved image quality. The study utilizes chest X-ray images of normal lungs and TB-affected lungs from Kaggle. Model performance is evaluated using accuracy, precision, recall, and F1-score metrics. Results indicate that the VGG-19 model outperforms the 8-layer CNN across all evaluation metrics, achieving an accuracy of 72.00% compared to 65.00% for the 8-layer CNN. VGG-19 also demonstrates better precision, recall, and F1-score, making it a more suitable choice for TB detection with enhanced image quality