MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer最新文献_第3页

Performance Prediction of Airport Traffic Using LSTM and CNN-LSTM Models 基于LSTM和CNN-LSTM模型的机场交通性能预测

MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Pub Date : 2023-07-28 DOI: 10.30812/matrik.v22i3.3032

Willy Riyadi, Jasmir Jasmir

{"title":"Performance Prediction of Airport Traffic Using LSTM and CNN-LSTM Models","authors":"Willy Riyadi, Jasmir Jasmir","doi":"10.30812/matrik.v22i3.3032","DOIUrl":"https://doi.org/10.30812/matrik.v22i3.3032","url":null,"abstract":"During the COVID-19 pandemic, airports faced a significant drop in passenger numbers, impacting the vital hub of the aircraft transportation industry. This study aimed to evaluate whether Long Short-Term Memory Network (LSTM) and Convolutional Neural Network - Long Short-Term Memory Network (CNN-LSTM) offer more accurate predictions for airport traffic during the COVID-19 pandemic from March to December 2020. The studies involved data filtering, applying min-max scaling, and dividing the dataset into 80% training and 20% testing sets. Parameter adjustment was performed with different optimizers such as RMSProp, Stochastic Gradient Descent (SGD), Adam, Nadam, and Adamax. Performance evaluation uses metrics that include Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), Root Mean Square Error (RMSE), and R-squared (R2). The best LSTM model achieved an impressive MAPE score of 0.0932, while the CNN-LSTM model had a slightly higher score of 0.0960. In particular, the inclusion of a balanced data set representing a percentage of the base period for each airport had a significant impact on improving prediction accuracy. This research contributes to providing stakeholders with valuable insights into the effectiveness of predicting airport traffic patterns during these unprecedented times.","PeriodicalId":364657,"journal":{"name":"MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128665265","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Digital Forensic Analysis of WhatsApp Business Applications on Android-Based Smartphones Using NIST 基于NIST的android智能手机上WhatsApp商业应用程序的数字取证分析

MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Pub Date : 2023-07-26 DOI: 10.30812/matrik.v22i3.3033

William Barkem, Jeckson Sidabutar

{"title":"Digital Forensic Analysis of WhatsApp Business Applications on Android-Based Smartphones Using NIST","authors":"William Barkem, Jeckson Sidabutar","doi":"10.30812/matrik.v22i3.3033","DOIUrl":"https://doi.org/10.30812/matrik.v22i3.3033","url":null,"abstract":"WhatsApp Business is an Android application that can be downloaded on Playstore to serve small business owners. This provides an opportunity for criminals to take advantage of the app’s features. These crimes can take the form of fraud, misdirection, and misuse of applications, so digital forensics is necessary because there has never been any research that has done this. This study aims to obtain digital evidence and is carried out on Android smartphones with the WhatsApp Business application installed with four scenarios tested. This study uses the NIST SP 800-101 Rev 1 guidelines with four stages: preservation, acquisition, inspection & analysis, and reporting. The forensic method used is static forensics using the MOBILedit forensic express forensic tools and SysTools SQLite Viewer. The results of this study in scenario 1, by not deleting, get a 100% percentage. Then, scenario 2, namely direct write-off, gets a percentage of 71%. Furthermore, scenario 3, namely uninstalling the application, does not get digital evidence, and scenario 4, namely deleting data through the application manager, also does not get any evidence. The contribution of this research is expected to be a reference in uncovering cases in the WhatsApp Business application with digital forensics.","PeriodicalId":364657,"journal":{"name":"MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132828955","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Social Media Engagement and Student’s Intention in Indonesian Higher Education Using Unified Theory of Acceptance and Use of Technology 基于技术接受与使用统一理论的印尼高等教育社交媒体参与与学生意向研究

MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Pub Date : 2023-07-25 DOI: 10.30812/matrik.v22i3.3019

M. Hermita, B. Hermana., Suryadi Harmanto, Adang Suhendra, Munawir Pasaribu

{"title":"Social Media Engagement and Student’s Intention in Indonesian Higher Education Using Unified Theory of Acceptance and Use of Technology","authors":"M. Hermita, B. Hermana., Suryadi Harmanto, Adang Suhendra, Munawir Pasaribu","doi":"10.30812/matrik.v22i3.3019","DOIUrl":"https://doi.org/10.30812/matrik.v22i3.3019","url":null,"abstract":"Understanding the motivations behind the use of social media in higher education is crucial for assessing its potential benefits and challenges. However, examining the contribution of social media on collaborative learning within the context of Indonesian universities holds significance due to the country’s growing digital landscape and increasing adoption of social media platforms. This research aimed to analyze proposed collaborative learning models involving social media use among Indonesian University students. The proposed models are constructed based on the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT). The quantitative method used was analyzing primary data from 143 private university students in Indonesia. Data were collected using a 5-point Likert scale self-reported questionnaire of Internet Anxiety, Habit, and Performance Expectancy and Behavior Intention as well as Social Media Engagement to mediate collaborative learning. The result of this study was that Social Media Engagement and Behavior Intention significantly influence Performance Expectancy and Habit. There was also a significant influence of Internet Anxiety on behavioral intention. Thus, Collaborative Learning is significantly influenced by Social Media Engagement. These results provided insight into developing effective strategies for integrating social media into higher education.","PeriodicalId":364657,"journal":{"name":"MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer","volume":"94 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133629263","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

K Value Effect on Accuracy Using the K-NN for Heart Failure Dataset K值对心力衰竭数据集准确性的影响

MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Pub Date : 2023-07-25 DOI: 10.30812/matrik.v22i3.2984

Alya Masitha, M. K. Biddinika, Herman Herman

{"title":"K Value Effect on Accuracy Using the K-NN for Heart Failure Dataset","authors":"Alya Masitha, M. K. Biddinika, Herman Herman","doi":"10.30812/matrik.v22i3.2984","DOIUrl":"https://doi.org/10.30812/matrik.v22i3.2984","url":null,"abstract":"Heart failure is included in the category of cardiovascular disease. Heart disease is not easy to detect, and its detection needs to be done by experienced and skilled medical professionals. Most patients with heart failure require hospitalization. Common symptoms of heart disease, such as chest pain and high or low blood pressure, vary from person to person. This study aims to find the most optimal k value based on the accuracy obtained based on calculations by testing different k values, namely 1, 3, 5, 7, and 9. After getting the results of the accuracy of the five k values, compare which accuracy has the highest value, best for K-Nearest Neighbor (K-NN) models. The classification process uses the K-NN algorithm. This algorithm is quite easy to use because some parameters work using distance metrics and k values. Therefore, the value of k in the K-NN algorithm greatly affects the accuracy that will be produced. In the results of this study, the accuracy obtained was k = 7 and k = 9, which are the most optimal results because they have the highest accuracy compared to other k values, with an accuracy of 88%. The expected benefit of this research is that it can make a scientific contribution to research in the field of machine learning classification, especially in predicting heart failure","PeriodicalId":364657,"journal":{"name":"MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134403438","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Data Mining Earthquake Prediction with Multivariate Adaptive Regression Splines and Peak Ground Acceleration 基于多变量自适应回归样条曲线和峰值地加速度的数据挖掘地震预测

MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Pub Date : 2023-07-24 DOI: 10.30812/matrik.v22i3.3061

Dadang Priyanto, B. K. Triwijoyo, Deny Jollyta, H. Hairani, Ni Gusti Ayu Dasriani

{"title":"Data Mining Earthquake Prediction with Multivariate Adaptive Regression Splines and Peak Ground Acceleration","authors":"Dadang Priyanto, B. K. Triwijoyo, Deny Jollyta, H. Hairani, Ni Gusti Ayu Dasriani","doi":"10.30812/matrik.v22i3.3061","DOIUrl":"https://doi.org/10.30812/matrik.v22i3.3061","url":null,"abstract":"Earthquake research has not yielded promising results because earthquakes have uncertain data parameters, and one of the methods to overcome the problem of uncertain parameters is the nonparametric method, namely Multivariate Adaptive Regression Splines (MARS). Sumbawa Island is part of the territory of Indonesia and is in the position of three active earth plates, so Sumbawa is prone to earthquake hazards. Therefore, this research is important to do. This study aimed to analyze earthquake hazard prediction on the island of Sumbawa by using the nonparametric MARS and Peak Ground Acceleration (PGA) methods to determine the risk of earthquake hazards. The method used in this study was MARS, which has two completed stages: Forward Stepwise and Backward Stepwise. The results of this study were based on testing and parameter analysis obtained a Mathematical model with 11 basis functions (BF) that contribute to the response variable, namely (BF) 1,2,3,4,5,7,9,11, and the basis functions do not contribute 6, 8, and 10. The predictor variables with the greatest influence were 100% Epicenter Distance and 73.8% Magnitude. The conclusion of this study is based on the highest PGA values in the areas most prone to earthquake hazards in Sumbawa, namely Mapin Kebak, Mapin Rea, Pulau Panjang, and Pulau Saringi.","PeriodicalId":364657,"journal":{"name":"MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122753381","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

E-Mortality using Agile Scrum Method to Improve Information Services Effectiveness 使用敏捷Scrum方法提高信息服务的有效性

MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Pub Date : 2023-07-24 DOI: 10.30812/matrik.v22i3.2830

Ardafa Ihromi, Yuda Syahidin, Erix Gunawan, Neneng Yuniarty

{"title":"E-Mortality using Agile Scrum Method to Improve Information Services Effectiveness","authors":"Ardafa Ihromi, Yuda Syahidin, Erix Gunawan, Neneng Yuniarty","doi":"10.30812/matrik.v22i3.2830","DOIUrl":"https://doi.org/10.30812/matrik.v22i3.2830","url":null,"abstract":"The advancement of information system technology is presently used extensively in many disciplines, including the field of health care or hospitals. This research aims to create an information system to handle hospital data to facilitate the processing patient data that has been declared dead with quality. In this study, it was found that there was no information system in the form of a program or application to handle death data. The management process still relies on Microsoft Excel, considered less efficient. In addition, the development of this information system is assisted by choosing the suitable software development methodology and considering existing needs. This research uses the Agile Development Method with the Scrum framework for software development. This research is qualitative descriptive and uses the observation method in data collection. C# programming language and MySQL database are also used in this system. This research produces an information system to handle death data by the product backlog. It is intended to meet user needs to assist in processing death data more effectively and efficiently and reduce the error rate associated with recording death data manually.","PeriodicalId":364657,"journal":{"name":"MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer","volume":"119 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133605516","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Image Processing Using Morphology on Support Vector Machine Classification Model for Waste Image 基于形态学支持向量机分类模型的垃圾图像处理

MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Pub Date : 2023-07-17 DOI: 10.30812/matrik.v22i3.2819

Miftahuddin Fahmi, A. Yudhana, S. Sunardi

{"title":"Image Processing Using Morphology on Support Vector Machine Classification Model for Waste Image","authors":"Miftahuddin Fahmi, A. Yudhana, S. Sunardi","doi":"10.30812/matrik.v22i3.2819","DOIUrl":"https://doi.org/10.30812/matrik.v22i3.2819","url":null,"abstract":"Sorting waste has always been an important part of managing waste. The primary issue with the waste sorting process has been the discomfort caused by prolonged contact with waste odor. A machinelearning method for identifying waste types was created to address this issue. The study’s goal was to create machine learning to solve waste management challenges by applying the most accurate categorization model available. The research approach was the quantitative analysis of the classification model accuracy. The Kaggle dataset was used to collect and curate data, which was subsequently preprocessed using the morphology approach. Based on picture sources, the data was trained and used to classify waste. The Support Vector Machine model was used in this investigation and feature extraction via the Convolutional Neural Network. The results showed that the system categorized waste successfully, with an accuracy of 99.30% and a loss of 2.47% across all categories. According to the findings of this study, SVM combined with morphological image processing functioned as a strong classification model, with a remarkable accuracy rate of 99.30%. This study’s outcomes contributed to waste management by giving an efficient and dependable waste classification solution compared to many previous studies.","PeriodicalId":364657,"journal":{"name":"MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer","volume":"185 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124697981","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Comparison of Support Vector Machine Performance with Oversampling and Outlier Handling in Diabetic Disease Detection Classification 过采样与离群值处理支持向量机在糖尿病疾病检测分类中的性能比较

MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Pub Date : 2023-07-17 DOI: 10.30812/matrik.v22i3.2979

Firda Yunita Sari, Maharani Sukma Kuntari, Hani Khaulasari, Winda Ari Yati

{"title":"Comparison of Support Vector Machine Performance with Oversampling and Outlier Handling in Diabetic Disease Detection Classification","authors":"Firda Yunita Sari, Maharani Sukma Kuntari, Hani Khaulasari, Winda Ari Yati","doi":"10.30812/matrik.v22i3.2979","DOIUrl":"https://doi.org/10.30812/matrik.v22i3.2979","url":null,"abstract":"Diabetes mellitus is a disease that attacks chronic metabolism, characterized by the body’s inability to process carbohydrates, fats so that glucose levels are high. Diabetes mellitus is the sixth cause of death in the world. Classifying data about diabetes mellitus makes it easier to predict the disease. As technology develops, diabetes mellitus can be detected using machine learning methods. The method that can be done is the support vector machine. The advantage of SVM is that it is very effective in completing classification, so it can quickly separate each positive and negative point. This study aimed to obtain the best SVM classification model based on accuracy, sensitivity, and precision values in detecting diabetes by adding Synthetic Minority Over-Sampling Technique (SMOTE) and handling outliers. The SMOTE method was applied to handle class imbalance. The Support Vector Machine (SVM) method aimed to produce a function as a dividing line or what can be called a hyperplane that matches all input data with the smallest possible error. The data studied were indications of diabetes, consisting of 8-factor variables and 1 class variable. The test results show that the SVM-SMOTE scenario produces the best accuracy. The SVM SMOTE scenario produced an accuracy value of the RBF kernel of 88% with an error of 12%, and this is obtained from the division of test data and training data of 90:10. This SVM-SMOTE scenario produced a precision value of 0.880 and a sensitivity value of 0.880. The research results showed that factor classification was more accurate if it is carried out using the support vector machine (SVM) method with imbalance data handling (SMOTE), and it can be concluded that the distribution of test data and training data influences a test scenario.","PeriodicalId":364657,"journal":{"name":"MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer","volume":"161 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129274985","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Incorporating User Experience Evaluation into Application Design for Optimal Usability 将用户体验评估纳入应用程序设计以实现最佳可用性

MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Pub Date : 2023-07-17 DOI: 10.30812/matrik.v22i3.2793

Helen Sastypratiwi, Yulianti Yulianti, Hafiz Muhardi, Desepta Isna Ulumi

{"title":"Incorporating User Experience Evaluation into Application Design for Optimal Usability","authors":"Helen Sastypratiwi, Yulianti Yulianti, Hafiz Muhardi, Desepta Isna Ulumi","doi":"10.30812/matrik.v22i3.2793","DOIUrl":"https://doi.org/10.30812/matrik.v22i3.2793","url":null,"abstract":"Forest and land fires have become a national issue every year, especially in West Kalimantan. From 2015 to 2020, around 331,268.35 hectares of forest and land were burned in West Kalimantan. As a result of forest and land fires, the haze disrupts public health, the economy, and river, land, sea, and air transportation. As anticipation and prevention, the community and government monitor forest and land fires using the Forest Fire Monitoring System Application. The purpose of this study was to the User Experience (UX) evaluation for design improvement in the Forest Fire Monitoring System Application (SIPONGI) inWest Kalimantan. The method used was User Centered Design (UCD) and Website Usability Evaluation Tool (WEBUSE) to provide new design solutions in the form of a website prototype. The research methodology included a literature study of the SIPONGI application. The study used a sample of 25 respondents with different work backgrounds to represent the population using the SIPONGI application. The results of this study showed that usability points per attribute and category are superior after making UI/UX improvements using the UCD process in prototype form. In conclusion, using the UCD method is better if it is accompanied by the WEBUSE method in improving the design of an application.","PeriodicalId":364657,"journal":{"name":"MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer","volume":"109 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122509741","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Evading Antivirus Software Detection Using Python and PowerShell Obfuscation Framework 使用Python和PowerShell混淆框架逃避杀毒软件检测

MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Pub Date : 2023-07-14 DOI: 10.30812/matrik.v22i3.3088

Umar Aditiawarman, Alfian Dody, T. Mantoro, H. A. Maarif, Anggy Pradiftha

{"title":"Evading Antivirus Software Detection Using Python and PowerShell Obfuscation Framework","authors":"Umar Aditiawarman, Alfian Dody, T. Mantoro, H. A. Maarif, Anggy Pradiftha","doi":"10.30812/matrik.v22i3.3088","DOIUrl":"https://doi.org/10.30812/matrik.v22i3.3088","url":null,"abstract":"Avoiding antivirus detection in penetration testing activities is tricky. The simplest, most effective, and most efficient way is to disguise malicious code. However, the obfuscation process will also be very complex and time-consuming if done manually. To solve this problem, many tools or frameworks on the internet can automate the obfuscation process, but how effective are obfuscation tools to avoid antivirus detection are. This study aimed to provide an overview of the effectiveness of the obfus- cation framework in avoiding antivirus detection. This study used experimental design to test and determine the effectiveness of the payload obfuscation process. The first step was generating Python and PowerShell payloads, followed by the obfuscation process. The results showed that by using the \u0000right method of obfuscation, malware could become completely undetectable. The automatic obfus- cation process also did not deteriorate the malware’s function. It was proven that the malware could run and open a connection on the server. These findings required more Python obfuscator techniques to determine the effectiveness of the obfuscated payload on the target machines using both static and dynamic analysis","PeriodicalId":364657,"journal":{"name":"MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121161472","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0