MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer最新文献_第5页

Multi-Level Pooling Model for Fingerprint-Based Gender Classification 基于指纹的性别分类多级池化模型

MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Pub Date : 2023-03-31 DOI: 10.30812/matrik.v22i2.2551

S. Suwarno, Erick Kurniawan

{"title":"Multi-Level Pooling Model for Fingerprint-Based Gender Classification","authors":"S. Suwarno, Erick Kurniawan","doi":"10.30812/matrik.v22i2.2551","DOIUrl":"https://doi.org/10.30812/matrik.v22i2.2551","url":null,"abstract":"It has been widely reported that CNN (Convolutional Neural Network) has shown satisfactory results in classifying images. The strength of CNN lies in the type and the number of layers that construct it. However, the most apparent drawbacks of CNN are the requirement for a large labeled dataset and its lengthy training time. Although datasets are available, labeling that data is a significant problem. This work mimics the CNN model but only utilizes its pooling layers. The novelty of this model is removing convolution layers and directly processing fingerprint images using pooling layers. Three pooling layer models, namely maximum pooling, average pooling, and minimum pooling, are used to generate fingerprint features to classify their owner gender. These pooling layers are arranged consecutively up to eight levels. Removing convolution layers makes the process straightforward, and the computation is much faster. This study utilized 200 fingerprint datasets from the NIST (National Institute of Standards and Technology), with male and female fingerprints of 100 samples each. The extracted features were then classified using K-NN (K-Nearest Neighbors) algorithm. The proposed method resulted in an accuracy of 61% to 71.5% or an average of 66.25%.","PeriodicalId":364657,"journal":{"name":"MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer","volume":"22 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":"132418623","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

Customer Segmentation with RFM Model using Fuzzy C-Means and Genetic Programming 基于模糊c均值和遗传规划的RFM客户细分模型

MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Pub Date : 2023-03-31 DOI: 10.30812/matrik.v22i2.2408

A. Syaifudin, Purwanto Purwanto, Heribertus Himawan, M. Soeleman

{"title":"Customer Segmentation with RFM Model using Fuzzy C-Means and Genetic Programming","authors":"A. Syaifudin, Purwanto Purwanto, Heribertus Himawan, M. Soeleman","doi":"10.30812/matrik.v22i2.2408","DOIUrl":"https://doi.org/10.30812/matrik.v22i2.2408","url":null,"abstract":"One of the strategies a company uses to retain its customers is Customer Relationship Management (CRM). CRM manages interactions and supports business strategies to build mutually beneficial relationships between companies and customers. The utilization of information technology, such as data mining used to manage the data, is critical in order to be able to find out patterns made by customers when processing transactions. Clustering techniques are possible in data mining to find out the patterns generated from customer transaction data. Fuzzy C-Means (FCM) is one of the best-known and most widely used fuzzy grouping methods. The iteration process is carried out to determine which data is in the right cluster based on the objective function. The local minimum is the condition where the resulting value is not the lowest value from the solution set. This research aims to solve the minimum local problem in the FCM algorithm using Genetic Programming (GP), which is one of the evolution-based algorithms to produce better data clusters. The result of the research is to compare the application of fuzzy c-means (FCM) and genetic programming fuzzy c-means (GP-FCM) for customer segmentation applied to the Cahaya Estetika clinic dataset. The test results of the GP-FCM yielded an objective function of 20.3091, while for the FCM algorithm, it was 32.44741. Furthermore, evaluating cluster validity using Partition Coefficient (PC), Classification Entropy (CE), and Silhouette Index proves that the results of cluster quality from gp-fcm are more optimal than fcm. The results of this study indicate that the application of genetic programming in the fuzzy c-means algorithm produces more optimal cluster quality than the fuzzy c-means algorithm.","PeriodicalId":364657,"journal":{"name":"MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer","volume":"1 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":"129060033","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

Information Security Analysis of Online Education Management System using Information Technology Infrastructure Library Version 3 基于Information Technology Infrastructure Library Version 3的在线教育管理系统信息安全分析

MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Pub Date : 2023-03-31 DOI: 10.30812/matrik.v22i2.2474

Michelle Cantika Pontoan, Jay Idoan SIhotang, E. Lompoliu

{"title":"Information Security Analysis of Online Education Management System using Information Technology Infrastructure Library Version 3","authors":"Michelle Cantika Pontoan, Jay Idoan SIhotang, E. Lompoliu","doi":"10.30812/matrik.v22i2.2474","DOIUrl":"https://doi.org/10.30812/matrik.v22i2.2474","url":null,"abstract":"The rapid development of information affects many aspects of human life. So that the field of information security becomes one aspect that must be considered. This study aims to measure the information security awareness and to improve daily operational activities of managing IT services effectively and efficiently. Salemba Adventist Academy has used the Wium Online Education Management System (WIOEM) online system, but in its implementation the security aspects of the system are not yet known. The Information Technology Infrastructure Library (ITIL) v3 framework which is globally recognized for managing information technology is broken down into five parts: Service Strategy, Service Design, Service Transition, Service Operation, Continual Service Improvement. This study focuses on Service Operations with 4 attributes, namely: Security, Privacy, Risk, and Trust. The data collection method used by the researcher was through observation in the form of a questionnaire in taking the number of samples to several students by taking population samples using the Lemeshow method. After the data were collected, the results of the ITIL indicator questionnaire are calculated based on the data security level. The results show that the Security indicator is Level 1, the Privacy indicator is level 3, the Risk indicator is level 3, and the Trust indicator is level 4 on the Data Security Level scale. This shows that the WIOEM system can be used properly according to user expectations and meets several levels of data security according to ITIL v3 framework. \u0000 \u0000 ","PeriodicalId":364657,"journal":{"name":"MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer","volume":"20 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":"125777557","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: 2

Comparative Analysis of SVM and Perceptron Algorithms in Classification of Work Programs SVM与感知机算法在工作方案分类中的比较分析

MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Pub Date : 2023-03-31 DOI: 10.30812/matrik.v22i2.2479

Jaka Tirta Samudra, Rika Rosnelly, Z. Situmorang

{"title":"Comparative Analysis of SVM and Perceptron Algorithms in Classification of Work Programs","authors":"Jaka Tirta Samudra, Rika Rosnelly, Z. Situmorang","doi":"10.30812/matrik.v22i2.2479","DOIUrl":"https://doi.org/10.30812/matrik.v22i2.2479","url":null,"abstract":"Government agencies are required to mobilize every aspect of publication which is carried out every year which must be accounted for and also carried out for each device that receives it such as assisted villages by utilizing available apbd funds in maximizing work programs designed so that they can be implemented optimally and effectively. by getting the best from all aspects of the work program implementation, of course there are important points in designing an annual work program without exception. data mining itself can help the department of population, family planning, women's empowerment and child protection in analyzing each work program design from before it is implemented onwards to look at various aspects of past data whose grouping is in the form of classification. The purpose of this study is to build a classification model with the addition of a sigmoid activation function that uses svm and perceptron to obtain a comparison value for the accuracy of the algorithm used to obtain the best working program design. The classification results are used to get the best value for classifying the best P2KBP3A work program dataset where it can be seen that the average accuracy value is 87.5%, the f1 value is 82.2%, the precision value is 80.2%, and the recall value is 87.5% so that the final result of the research results obtained a good accuracy value.","PeriodicalId":364657,"journal":{"name":"MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer","volume":"1 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":"129358743","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

Google Trends and Technical Indicator based Machine Learning for Stock Market Prediction 基于谷歌趋势和技术指标的机器学习股票市场预测

MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Pub Date : 2023-03-31 DOI: 10.30812/matrik.v22i2.2287

Mamluatul Hani’ah, Moch. Zawaruddin Abdullah, W. I. Sabilla, Syafaat Akbar, Dikky Rahmad Shafara

引用次数: 0

Utilization of Data Mining on MSMEs using FP-Growth Algorithm for Menu Recommendations 基于FP-Growth算法的菜单推荐数据挖掘在中小微企业中的应用

MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Pub Date : 2023-03-31 DOI: 10.30812/matrik.v22i2.2166

Firman Noor Hasan, Achmad Sufyan Aziz, Yos Nofendri

{"title":"Utilization of Data Mining on MSMEs using FP-Growth Algorithm for Menu Recommendations","authors":"Firman Noor Hasan, Achmad Sufyan Aziz, Yos Nofendri","doi":"10.30812/matrik.v22i2.2166","DOIUrl":"https://doi.org/10.30812/matrik.v22i2.2166","url":null,"abstract":"Existing transaction data is only recorded and stored as a sales transaction memorandum, so it has not been utilized optimally. The data is only stored and used as transaction history. The availability of a lot of data and having a pattern of sales transactions that are similar to MSME Cafe Over Limit will be utilized by using data mining science. This research uses the association rules method. Implementation of fp-growth to get item combinations. The purpose of this research is to make it easier for MSMEs to determine menu recommendations for customers. The fp-growth algorithm is used to process as many as 2038 transaction data with a minimum support value of 10%, while for a minimum confidence value of 50%. So that there are 3 rules, namely \"if you order Mariam chocolate cheese milk then the customer will order Kopsus Overlimit\", from this rule it will form a support value of 10.79%, using a confidence value of 54.19% and a lift ratio of 0.93. Furthermore \"if you order Kopsus Overlimit then you will order tofu at grandma's house\", from the rule it will produce a support value of 34.69%, with a specified confidence value of 59.76%, so the lift ratio value is 1.15. The last rule \"if you order tofu at grandma's house, the customer orders Kopsus Overlimit\", from the rule that occurs, the support value is 34.69%, with a confidence value of 66.7% and a lift ratio of 1.15. The results of the study found the two best rules, namely \"if the customer orders over-limit Kopsus, he will order tofu at grandma's house\" and \"if he orders tofu at grandma's house, the customer orders over-limit Kopsus\". Based on the results of the rules formed, it can be concluded that only two rules can be categorized as valid and can be used as a reference in food and beverage menu recommendations at MSME Cafe Over Limit. So the results of this study can be useful to be applied to MSMEs, especially in terms of menu recommendations.","PeriodicalId":364657,"journal":{"name":"MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer","volume":"15 12","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132644983","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

Support Vector Machine for Predicting Candlestick Chart Movement on Foreign Exchange 预测外汇烛台图运动的支持向量机

MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Pub Date : 2023-03-31 DOI: 10.30812/matrik.v22i2.2676

Annisa Nurul Puteri, Suryadi Syamsu, Topan Leoni Putra, Andita Dani Achmad

{"title":"Support Vector Machine for Predicting Candlestick Chart Movement on Foreign Exchange","authors":"Annisa Nurul Puteri, Suryadi Syamsu, Topan Leoni Putra, Andita Dani Achmad","doi":"10.30812/matrik.v22i2.2676","DOIUrl":"https://doi.org/10.30812/matrik.v22i2.2676","url":null,"abstract":"Foreign Exchange, commonly called Forex, is a form of investment in the non-real sector in great demand. Forex is a marketplace that specializes in foreign exchange trading. Technology advancements have made it easy to monitor investment conditions in real time and present them in an easyto - understand graphical form. As a result, predictions are closely related to investment, starting from market sentiment and economic conditions to technical matters. One of the Artificial Intelligence methods that can be used in classifying is the Support Vector Machine (SVM). SVM is a machine learning classification method based on the Structural Risk Minimization (SRM) principle to find the best hyperplane that separates two classes in the input space that determines the classification decision function by minimizing empirical risk. This study used candlestick patterns to predict foreign exchange chart movements using the Support Vector Machine (SVM) classification method. The purpose of this study was to measure the accuracy of the Support Vector Machine method in making predictions using candlestick patterns so that it can assist traders in making decisions in forex trading. The accuracy level obtained from the data classification results reached 90.72% with a precision of 87.69%. With a relatively good level of accuracy, the Support Vector Machine (SVM) method can be used to predict chart movements in foreign exchange using candlesticks to indicate the current trend’s direction.","PeriodicalId":364657,"journal":{"name":"MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer","volume":"18 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":"116480604","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

The UTAUT Model for Measuring Acceptance of the Application of the Patient Registration System 用于测量患者登记系统应用接受度的UTAUT模型

MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Pub Date : 2023-03-30 DOI: 10.30812/matrik.v22i2.2844

Tugiman Tugiman, H. Herman, A. Yudhana

引用次数: 0

Convolutional Neural Network for Colorization of Black and White Photos 卷积神经网络用于黑白照片的着色

MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Pub Date : 2023-03-30 DOI: 10.30812/matrik.v22i2.2652

S. Masruroh, Andrew Fiade, M. I. Tanggok, Rizka Amalia Putri, Luigi Ajeng Pratiwi

{"title":"Convolutional Neural Network for Colorization of Black and White Photos","authors":"S. Masruroh, Andrew Fiade, M. I. Tanggok, Rizka Amalia Putri, Luigi Ajeng Pratiwi","doi":"10.30812/matrik.v22i2.2652","DOIUrl":"https://doi.org/10.30812/matrik.v22i2.2652","url":null,"abstract":"People today are very fond of capturing moments by taking pictures. Various photo functions are used to document all forms of information that you want to store. In photos with digital images that have black and white, the information obtained is less than optimal, so an image processing process is needed to get color photos. Based on this, the author wants to change photos from black and white to color photos. The method used in this research is Convolutional Neural Network (CNN). This study uses Atlas 200 DK hardware and Ascend 310 processor. The data used in this study are 32 black and white photos in .jpg format as training data and perform 6 experimental scenarios with different numbers of black and white photos in each experiment. The total black and white photos used to experiment were 81 photos. The results obtained are models that successfully perform processing in the form of color photos with the appropriate color results in predicting the possible color of the object in each pixel in the photo. Based on this research, the trend of artificial intelligence can be implemented in changing the color of photos according to color predictions.","PeriodicalId":364657,"journal":{"name":"MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115879837","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

A Novel Algorithm of Distance Calculation Based-on Grid-Edge-Depth-Map and Gyroscope for Visually-Impaired 一种基于网格边缘深度图和陀螺仪的视障距离计算新算法

MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Pub Date : 2023-03-28 DOI: 10.30812/matrik.v22i2.2757

Budi Rahmani, Ruliah Ruliah

{"title":"A Novel Algorithm of Distance Calculation Based-on Grid-Edge-Depth-Map and Gyroscope for Visually-Impaired","authors":"Budi Rahmani, Ruliah Ruliah","doi":"10.30812/matrik.v22i2.2757","DOIUrl":"https://doi.org/10.30812/matrik.v22i2.2757","url":null,"abstract":"This paper presented a new algorithm for determining the distance of an object in front of a stereo camera placed on a helmet. By using a stereo camera with a Sum of Absolute Difference with a Sobel edge detector, our previous Grid-Edge-Depth map algorithm could calculate the objects’ distance up to 500 cm. The problem started when a vision disability person used the device with an unfixed stereo camera angle. The unspecified angle caused by the helmet’s movement influenced the distance calculation result. This novel process started with calculating the distance from a Grid-Edge-Depth map considering unfixed angle data of the x-axis from a gyroscope sensor placed on the stereo camera using the trigonometry formula. The angle data used was the x-axis data. The distance measurement results by the system were then computed based on the unfixed angle compared to the actual distance. The test was carried out with three scenarios which required the user to stand at a distance of 100 cm, 125 cm, and 150 cm from a table, chair, or wall, with 30 tests for each scenario. The test results showed an average accuracy of 96.05% with three experimental scenarios, which meant that this machine was feasible to implement.","PeriodicalId":364657,"journal":{"name":"MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114973213","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