Journal of Advances in Information Systems and Technology最新文献_第3页

Design of Attendance System for Pemalang Diskominfo Employees Using Design Thinking Method 运用设计思维方法设计百马郎Diskominfo员工考勤系统

Journal of Advances in Information Systems and Technology Pub Date : 2022-09-01 DOI: 10.15294/jaist.v3i2.53150

Luthfi Ilham Agus Pratama, K. Budiman

{"title":"Design of Attendance System for Pemalang Diskominfo Employees Using Design Thinking Method","authors":"Luthfi Ilham Agus Pratama, K. Budiman","doi":"10.15294/jaist.v3i2.53150","DOIUrl":"https://doi.org/10.15294/jaist.v3i2.53150","url":null,"abstract":"Employees are an important part of carrying out the obligations of the Communication and Information Office (Kominfo) Pemalang Regency. However, the management of employee data for recording attendance at the Department of Communication and Information of Pemalang Regency is still processed manually, so that the attendance process management is considered ineffective and inefficient. Therefore, it is necessary to create an Employee Presence System that can manage employee attendance data. The goal is to facilitate the process of managing employee attendance data and making attendance data more precise. A data collection method is applied in making the system is an interview. In the interview, consultations and direct questions and answers were conducted with the field supervisor regarding the system requirements to be made. The design of this system uses the design thinking method. The design thinking method is carried out sequentially from one stage to another. There are five stages in the design thinking method: empathy, determination, ideas, prototypes, and testing. From making a system with this method, a design for an employee attendance system is produced that is comfortable to look at and easy to use in all circles.","PeriodicalId":418742,"journal":{"name":"Journal of Advances in Information Systems and Technology","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114197007","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

Web-Based Employee Attendance System Development Using Waterfall Method 利用瀑布法开发基于web的员工考勤系统

Journal of Advances in Information Systems and Technology Pub Date : 2022-09-01 DOI: 10.15294/jaist.v3i2.52942

Nafa Fajriati, K. Budiman

{"title":"Web-Based Employee Attendance System Development Using Waterfall Method","authors":"Nafa Fajriati, K. Budiman","doi":"10.15294/jaist.v3i2.52942","DOIUrl":"https://doi.org/10.15294/jaist.v3i2.52942","url":null,"abstract":"Employees are one of the important elements in carrying out the duties and functions of the Pemalang Regency Communication and Information Department (Diskominfo). However, the management of employee data for recording the attendance of Non Pegawai Negeri Sipil (Non PNS) employees at Diskominfo Pemalang Regency is still done manually so it is not effective and efficient. Therefore, it is necessary to create an Employee Presence System that can manage employee attendance data. The goal is to facilitate the process of managing employee attendance data and make attendance data more accurate. The data collection method used in making the system is an interview. In the interview, consultations and direct questions and answers were conducted with the field supervisor regarding the system requirements to be made. Making this system using the waterfall method. The waterfall method is carried out sequentially from one phase to another. There are five phases in the waterfall method, namely requirements analysis, system design, implementation, system testing, and operation and maintenance. From making a system with this method, an employee attendance system is produced that can manage employee attendance data at the Communication and Information Department of Pemalang Regency.","PeriodicalId":418742,"journal":{"name":"Journal of Advances in Information Systems and Technology","volume":"2012 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121502953","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

Comparison of Forecasting Using Fuzzy Time Series Chen Model and Lee Model to Foreign Exchange in EUR/USD and GBP/USD 模糊时间序列Chen模型与Lee模型对欧元/美元、英镑/美元汇率预测的比较

Journal of Advances in Information Systems and Technology Pub Date : 2021-04-14 DOI: 10.15294/jaist.v3i1.49096

Syehudin Syehudin, A. T. Putra

{"title":"Comparison of Forecasting Using Fuzzy Time Series Chen Model and Lee Model to Foreign Exchange in EUR/USD and GBP/USD","authors":"Syehudin Syehudin, A. T. Putra","doi":"10.15294/jaist.v3i1.49096","DOIUrl":"https://doi.org/10.15294/jaist.v3i1.49096","url":null,"abstract":"Each country has a currency value that applies in its territory and can be adjusted to the value of the currency of other countries. In this adjustment, there is a difference in value when the transaction is made, and the difference in profit can be taken, usually referred to as foreign exchange (forex). In forex trading, analytical calculations are needed to plan a decision to get a significant difference so that the profits will increase. One analysis technique that can maximize the search for an enormous profit difference is by using the prediction method using the fuzzy time series. This method is a method that predicts future data based on historical data or past data. The fuzzy time series method has several models, including the Chen model and Lee model. In determining which model is the best, it is necessary to test using the AFER (average forecasting error rate) based on the level of accuracy of the smallest error value. By using historical data of EUR/USD and GBP/USD from 19 February 2019 to 19 February 2020, it is known that Lee’s fuzzy time series method predicts better accuracy because Chen’s model in foreign currency EUR/USD has a more significant error rate of 0.0018 (0.18%) or greater than Lee’s model which only has a value of 0.0016 (0.16%). Then the Chen model in foreign currency GBP/USD has an error rate of 0.00445 (0.445%) or greater than the Lee model, which only has an error rate of 0.00297 (0.297%).","PeriodicalId":418742,"journal":{"name":"Journal of Advances in Information Systems and Technology","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127538983","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

Comparative Analysis of IPv4 and IPv6 OpenVPN Protocol Performance Based on QoS Parameters 基于QoS参数的IPv4和IPv6 OpenVPN协议性能对比分析

Journal of Advances in Information Systems and Technology Pub Date : 2021-04-14 DOI: 10.15294/jaist.v3i1.49095

Pradistia Edo Kristianto, A. T. Putra

引用次数: 0

Diagnosis Using Brain Tumors Two-Dimensional Principal Component Analysis (2D-PCA) with K-nearest Neighbor (KNN) Classification Algorithm 基于k -最近邻(KNN)分类算法的二维主成分分析(2D-PCA)诊断脑肿瘤

Journal of Advances in Information Systems and Technology Pub Date : 2021-04-14 DOI: 10.15294/jaist.v3i1.49013

A. Warsun, A. T. Putra

{"title":"Diagnosis Using Brain Tumors Two-Dimensional Principal Component Analysis (2D-PCA) with K-nearest Neighbor (KNN) Classification Algorithm","authors":"A. Warsun, A. T. Putra","doi":"10.15294/jaist.v3i1.49013","DOIUrl":"https://doi.org/10.15294/jaist.v3i1.49013","url":null,"abstract":"The rapid development of computer technology has brought more and more benefits to human life. Currently, computers can make decisions by imitating the human brain to be used in the health sector to play a role in solving existing problems. One of the technologies used is digital image processing technology on MRI images of brain tumors. Brain tumor images have various variations and large dimensions; therefore, an appropriate method is needed to recognize images maximally. Dimensional reduction uses the Two-Dimensional Principal Component Analysis (2DPCA) method. The classification process uses the K-Nearest Neighbor (KNN) method by calculating the euclidean distance (Euclidean Distance). From 3 tests with the number of data 200 images, the results of the accuracy of the 1st test were 90.0% with 60 test data and 140 training data, the second test was 85.0% with 80 test data and 120 training data, and the 3rd test is worth 83.0% with 100 test data and 100 training data. Based on the research above, it can be concluded that the highest accuracy is obtained in the 1st test, while the lowest accuracy is on the 3rd test. The more amount of training data compared to the test data, the greater the accuracy value obtained. This research is expected to be a reference for further research so that the results obtained are more optimal.","PeriodicalId":418742,"journal":{"name":"Journal of Advances in Information Systems and Technology","volume":"196 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132227386","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

Optimization of the C4.5 Algorithm by Using a Genetic Algorithm for the Diagnosis of Life Expectancy for Hepatitis Patients 基于遗传算法的C4.5算法优化肝炎患者预期寿命诊断

Journal of Advances in Information Systems and Technology Pub Date : 2021-04-14 DOI: 10.15294/jaist.v3i1.49014

Margareta Ayu Riantik, R. Arifudin

引用次数: 1

Accuracy Enhancement in Early Detection of Breast Cancer on Mammogram Images with Convolutional Neural Network (CNN) Methods using Data Augmentation and Transfer Learning 使用数据增强和迁移学习的卷积神经网络(CNN)方法提高乳房x线照片早期乳腺癌检测的准确性

Journal of Advances in Information Systems and Technology Pub Date : 2021-04-14 DOI: 10.15294/jaist.v3i1.49012

Arief Broto Susilo, E. Sugiharti

{"title":"Accuracy Enhancement in Early Detection of Breast Cancer on Mammogram Images with Convolutional Neural Network (CNN) Methods using Data Augmentation and Transfer Learning","authors":"Arief Broto Susilo, E. Sugiharti","doi":"10.15294/jaist.v3i1.49012","DOIUrl":"https://doi.org/10.15294/jaist.v3i1.49012","url":null,"abstract":"The advancement of computer technology has made it possible for computers to imitate the work of the human brain to make decisions that can be used in the healthcare sector. One of the uses is detecting breast cancer by using Machine Learning to increase the sensitivity and or specificity of detection and diagnosis of the disease. Convolutional Neural Network (CNN) is the most commonly used image analysis and classification method in machine learning. This study aims to improve the accuracy of early detection of breast cancer on mammogram images using the CNN method by adding the Data Augmentation and Transfer method. Learning. This study used a mammography image dataset taken from MIAS 2012. The dataset has seven classes with 322 image samples. The results of accuracy tests of early detection process of breast cancer using CNN by utilizing Data Augmentation and Transfer Learning show several findings: Model VGG-16, Model VGG-19, and ResNet-50 produced the same training accuracy rate of 86%, while for validation accuracy, Model ResNet-50 produced the highest level of accuracy (71%) compared to other models (VGG-16=64%, VGG-19=61%). The use of more image datasets may create better accuracy.","PeriodicalId":418742,"journal":{"name":"Journal of Advances in Information Systems and Technology","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114439906","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: 4

Implementation of Expert System to Diagnose Pregnancy Disorders using Fuzzy Expert System Method 用模糊专家系统方法实现妊娠障碍诊断专家系统

Journal of Advances in Information Systems and Technology Pub Date : 2021-04-14 DOI: 10.15294/jaist.v3i1.49093

S. Putri, A. Alamsyah, I. Akhlis

引用次数: 0

The Improvement of C4.5 Algorithm Accuracy in Predicting Forest Fires Using Discretization and AdaBoost 基于离散化和AdaBoost的C4.5算法对森林火灾预测精度的提高

Journal of Advances in Information Systems and Technology Pub Date : 2021-04-14 DOI: 10.15294/jaist.v3i1.49094

Tomi Bagus Nugroho, E. Sugiharti

引用次数: 0

Classification of Movie Review Sentiment Analysis Using Chi-Square and Multinomial Naïve Bayes with Adaptive Boosting 基于卡方和多项Naïve贝叶斯的电影评论情感分析分类

Journal of Advances in Information Systems and Technology Pub Date : 2021-04-14 DOI: 10.15294/jaist.v3i1.49098

Muhamad Biki Hamzah

引用次数: 3