MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer最新文献_第4页

Optimizing the Amount of Production Using Hybrid Fuzzy Logic and Census II 基于混合模糊逻辑和普查的产量优化[j]

MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Pub Date : 2023-07-10 DOI: 10.30812/matrik.v22i3.2938

Susana Limanto, Vincentius Riandaru Prasetyo, Mirella Mercifia

引用次数: 0

Hate Speech Detection for Banjarese Languages on Instagram Using Machine Learning Methods 使用机器学习方法检测Instagram上的孟加拉语仇恨言论

MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Pub Date : 2023-07-07 DOI: 10.30812/matrik.v22i3.2939

Muhammad Alkaff, Muhammad Afrizal Miqdad, Muhammad Fachrurrazi, Muhammad Nur Abdi, Ahmad Zainul Abidin, Raisa Amalia

{"title":"Hate Speech Detection for Banjarese Languages on Instagram Using Machine Learning Methods","authors":"Muhammad Alkaff, Muhammad Afrizal Miqdad, Muhammad Fachrurrazi, Muhammad Nur Abdi, Ahmad Zainul Abidin, Raisa Amalia","doi":"10.30812/matrik.v22i3.2939","DOIUrl":"https://doi.org/10.30812/matrik.v22i3.2939","url":null,"abstract":"Hate speech refers to verbal expression or communication that aims to provoke or discriminate against individuals. The Ministry of Communication and Information of Indonesia has encountered and dealt with 3,640 cases of hate speech transmitted through digital channels between 2018 and 2021. Particularly in South Kalimantan, hate speech in the local language, Banjarese has become increasingly prevalent in recent years. Surprisingly, there is a lack of research on using machine learning to detect hate speech in the Banjarese language, specifically on Instagram. Therefore, this study aimed to address this gap by constructing a dataset of Banjarese language hate speech and comparing various feature extraction and machine learning models to detect Banjarese language hate speech effectively. Thisresearch used several feature extraction techniques and machine learning methods to detect Banjareselanguage hate speech. The feature extraction methods used were Word N-Gram, Term Frequency- Inverse Document Frequency (TF-IDF), a combination of Word N-Gram and TF-IDF, Word2Vec, and Glove, while the machine learning methods used were Support Vector Machine (SVM), Na¨ıve Bayes, and Decision Tree. The results of this study revealed that the combination of TF-IDF for feature extraction and SVM as the model achieves exceptional performance. The average Recall, Precision, Accuracy, and F1-Score score exceeded 90%, demonstrating the model’s ability to identify Banjarese hate speech accurately.","PeriodicalId":364657,"journal":{"name":"MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124195539","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

OWASP Framework-based Network Forensics to Analyze the SQLi Attacks on Web Servers 基于OWASP框架的网络取证分析Web服务器的SQLi攻击

MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Pub Date : 2023-07-06 DOI: 10.30812/matrik.v22i3.3018

I. Riadi, A. Fadlil, Muh. Amirul Mu'min

{"title":"OWASP Framework-based Network Forensics to Analyze the SQLi Attacks on Web Servers","authors":"I. Riadi, A. Fadlil, Muh. Amirul Mu'min","doi":"10.30812/matrik.v22i3.3018","DOIUrl":"https://doi.org/10.30812/matrik.v22i3.3018","url":null,"abstract":"One of dangerous vulnerabilities that attack the web is SQLi. With this vulnerability, someone can obtain user data information, then change and delete that data. The solution to this attack problem is that the design website must improve security by paying attention to input validation and installing a firewall. This study's objective is to use network forensic tools to examine the designlink website's security against SQLi attacks, namely Whois, SSL Scan, Nmap, OWASP Zap, and SQL Map. OWASP is the framework that is employed; it is utilized for web security testing. According to the research findings, there are 14 vulnerabilities in the design website, with five medium level, seven low level, and two informational level. When using SQL commands with the SQL Map tool to get username and password information on its web server design. The OWASP framework may be used to verify the security of websites against SQLi attacks using network forensic tools, according to the study's findings. So that information about the vulnerabilities found on the website can be provided. The results of this study contribute to forensic network knowledge against SQLi attacks using the OWASP framework as well as for parties involved in website security.","PeriodicalId":364657,"journal":{"name":"MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122523615","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

Automated Detection of Breast Cancer Histopathology Image Using Convolutional Neural Network and Transfer Learning 基于卷积神经网络和迁移学习的乳腺癌组织病理学图像自动检测

MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Pub Date : 2023-07-03 DOI: 10.30812/matrik.v22i3.2803

Didih Rizki Chandranegara, Faras Haidar Pratama, Sidiq Fajrianur, Moch Rizky Eka Putra, Zamah Sari

{"title":"Automated Detection of Breast Cancer Histopathology Image Using Convolutional Neural Network and Transfer Learning","authors":"Didih Rizki Chandranegara, Faras Haidar Pratama, Sidiq Fajrianur, Moch Rizky Eka Putra, Zamah Sari","doi":"10.30812/matrik.v22i3.2803","DOIUrl":"https://doi.org/10.30812/matrik.v22i3.2803","url":null,"abstract":"cancer caused 2.3 million cases and 685,000 deaths in 2020. Histopathology analysis is one of the tests used to determine a patient’s prognosis. However, histopathology analysis is a time-consuming and stressful process. With advances in deep learning methods, computer vision science can be used to detect cancer in medical images, which is expected to improve the accuracy of prognosis. This study aimed to apply Convolutional Neural Network (CNN) and Transfer Learning methods to classify breast cancer histopathology images to diagnose breast tumors. This method used CNN, Transfer Learning ((Visual Geometry Group (VGG16), and Residual Network (ResNet50)). These models undergo data augmentation and balancing techniques applied to undersampling techniques. The dataset used for this study was ”The BreakHis Database of microscopic biopsy images of breast tumors (benign and malignant),” with 1693 data classified into two categories: Benign and Malignant. The results of this study were based on recall, precision, and accuracy values. CNN accuracy was 94%, VGG16 accuracy was 88%, and ResNet50 accuracy was 72%. The conclusion was that the CNN method is recommended in detecting breast cancer to diagnose breast cancer.","PeriodicalId":364657,"journal":{"name":"MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121109879","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

Detecting Vehicle Numbers Using Google Lens-Based ESP32CAM to Read Number Characters 检测车辆号码使用谷歌镜头为基础的ESP32CAM读取数字字符

MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Pub Date : 2023-07-03 DOI: 10.30812/matrik.v22i3.2818

Tukino Paryono, Ahmad Fauzi, Rizki Aulia Nanda, Saepul Aripiyanto, Muhammad Khaerudin

引用次数: 0

Automation Reporting Bed Efficiency Using Verification and Validation Method 使用验证和确认方法的自动化报告床效率

MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Pub Date : 2023-06-19 DOI: 10.30812/matrik.v22i3.2823

Iis Gugum Gumilar, Yuda Syahidin, Erix Gunawan, Jeri Sukmawijaya

{"title":"Automation Reporting Bed Efficiency Using Verification and Validation Method","authors":"Iis Gugum Gumilar, Yuda Syahidin, Erix Gunawan, Jeri Sukmawijaya","doi":"10.30812/matrik.v22i3.2823","DOIUrl":"https://doi.org/10.30812/matrik.v22i3.2823","url":null,"abstract":"Beds are important in several hospital operations decisions, such as admitting patients to a hospital room. Lack of information regarding bed effectiveness can lead to long wait times and even rejection of patients, which impedes hospital healthcare services, especially internal medicine departments Reside. The existence of an efficient system using an electronic bed is seen as a solution also makes the inpatient service process more efficient. It aims to create an electronic bed availability system that meets the needs of a hospital in Bandung city. This research using Qualiatif methods with verification and validationmodel as development method, called the verification and validation mode, was chosen because it is approriate for rapid system development. Resulted that easier to adjust as the hospital can contribute to the developing system. System information hospitalization indicator produce report about Bed Occupancy Rate, Length Of Stay, Turn Over Interval , and Bed Turn Over Interval bed availability, daily census, daily report, monthly report and all reporting. Based on the blackbox testing as s testing method, Reporting bed efficiency system developed has overcome information gap of bed availability at Hospital. Making processing and reporting more efficient and easier to use and understand","PeriodicalId":364657,"journal":{"name":"MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122803037","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

Drowsiness Detection Based on Yawning Using Modified Pre-trained Model MobileNetV2 and ResNet50 基于改进的预训练模型MobileNetV2和ResNet50的哈欠睡意检测

MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Pub Date : 2023-06-06 DOI: 10.30812/matrik.v22i3.2785

Hepatika Zidny Ilmadina, Muhammad Naufal, Dega Surono Wibowo

引用次数: 1

Predicting Handling Covid-19 Opinion using Naive Bayes and TF-IDF for Polarity Detection 使用朴素贝叶斯和TF-IDF极性检测预测处理Covid-19意见

MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Pub Date : 2023-03-31 DOI: 10.30812/matrik.v22i2.2227

S. Supangat, Mohd Zainuri Saringat, Mochamad Yovi Fatchur Rochman

{"title":"Predicting Handling Covid-19 Opinion using Naive Bayes and TF-IDF for Polarity Detection","authors":"S. Supangat, Mohd Zainuri Saringat, Mochamad Yovi Fatchur Rochman","doi":"10.30812/matrik.v22i2.2227","DOIUrl":"https://doi.org/10.30812/matrik.v22i2.2227","url":null,"abstract":"There are many public responses about implementing government policies related to Covid-19. Some have positive and negative opinions, especially on the official social media portal of the government. Twitter is one social media where people are free to express their opinions. This study aims to find out the opinion of sentiment analysis on Twitter in implementing government policies related to Covid-19 to classify public opinion. Several stages in analyzing public sentiment are taken from the tweet data. The first step is data mining to get the tweets that will be analyzed later. Furthermore, cleaning tweet data and equalizing tweet data into lowercase. After that, perform the tweet's basic word search process and calculate its appearance frequency. Then calculate using the Naïve Bayes method and determine the sentiment classification of the tweet. The results showed that Indonesia's public sentiment about covid-19 prevention is neutral. The performance of the application shows an Accuracy value of 76.7%. In conclusion this means that the Indonesian government needs to evaluate the policies taken to deal with COVID-19 to create positive opinions to create solid cooperation between the government and the government. Residents in tackling the COVID-19 outbreak.","PeriodicalId":364657,"journal":{"name":"MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer","volume":"79 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132300435","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

Application of KNN Machine Learning and Fuzzy C-Means to Diagnose Diabetes KNN机器学习和模糊C-Means在糖尿病诊断中的应用

MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Pub Date : 2023-03-31 DOI: 10.30812/matrik.v22i2.2777

Anthony Anggrawan, Mayadi Mayadi

{"title":"Application of KNN Machine Learning and Fuzzy C-Means to Diagnose Diabetes","authors":"Anthony Anggrawan, Mayadi Mayadi","doi":"10.30812/matrik.v22i2.2777","DOIUrl":"https://doi.org/10.30812/matrik.v22i2.2777","url":null,"abstract":"The disease is a common thing in humans. Diseases that attack humans do not know anyone and do not know age. The disease experienced by a person starts from an ordinary level until it can be declared severe to the point of being at risk of death. In this study, the early diagnosis was carried out related to diabetes, where diabetes is a condition in which the sufferer’s body has low sugar levels above normal. Symptoms experienced by sufferers include frequent thirst, frequent urination, frequent hunger, and weight loss. Based on these problems, a system is needed that can quickly find out the diagnosis experienced by a patient. This research aimed to diagnose diabetes early on based on early symptoms. The methods used are KNN and web-based fuzzy C-means. Creating a web-based system can represent medical personnel experts in a fast-diagnosing approach to diabetes. This system was a computer program embedded with the knowledge of the characteristics of diabetes. The results of testing the KNN and Fuzzy C-means applications and methods get an accuracy of 96% for the KNearest Neighbor method, while for the Fuzzy C-Means method with Confusion Matrix calculations, an accuracy of 96% is obtained, so it can be concluded that the Fuzzy C-means method Means better than the K-Nearest Neighbor method.","PeriodicalId":364657,"journal":{"name":"MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123079978","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: 1

The Application of Usability Testing to Analyze the Quality of Android-Based Acupressure Smart Chair Applications 应用可用性测试分析基于android的指压智能椅应用质量

MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Pub Date : 2023-03-31 DOI: 10.30812/matrik.v22i2.2312

M. K. Anam, Esi Tri Emerlada, Susi Erlinda, Tashid Tashid, Torkis Nasution

{"title":"The Application of Usability Testing to Analyze the Quality of Android-Based Acupressure Smart Chair Applications","authors":"M. K. Anam, Esi Tri Emerlada, Susi Erlinda, Tashid Tashid, Torkis Nasution","doi":"10.30812/matrik.v22i2.2312","DOIUrl":"https://doi.org/10.30812/matrik.v22i2.2312","url":null,"abstract":"A smart chair is a reflection smart chair that utilizes waste tires as an alternative to acupuncture. Smart chairs are designed for people who are phobic about acupuncture needles by replacing these needles with waste tires. Acupuncture smart chairs also make it easier for users without having to go to the acupuncture practice place. This smart chair is equipped with an application that is directly connected to android. The smart chair application is an android-based remote control where users can control the application remotely. However, this application has not been tested so it is not yet known how effective and efficient the use of the application is. Therefore, researchers would conduct testing by using the usability testing method. The usability testing method is a method carried out to measure the ease of the application that has been made. The analysis in this method used five evaluation components, namely learnability, efficiency, memorability, errors, and satisfaction. This research would make instruments based on usability testing and then distribute instruments to samples by using sampling techniques. The results of this study showed a variable learnability value was 65% while the efficiency variable got a value of 74%. In terms of memorability, its value was 59%, then the Errors variable value was 74%, and the last variable, namely satisfaction, reached a value of 74%.","PeriodicalId":364657,"journal":{"name":"MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132438762","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