Journal of Advances in Information Systems and Technology最新文献_第2页

Prediction of Life Expectancy of Lung Cancer Patients Post Thoracic Surgery using K-Nearest Neighbors and Bat Algorithm 基于k近邻和Bat算法的肺癌胸外科术后预期寿命预测

Journal of Advances in Information Systems and Technology Pub Date : 2023-03-10 DOI: 10.15294/jaist.v4i2.60846

Muhamad Nur Arifiansyah

{"title":"Prediction of Life Expectancy of Lung Cancer Patients Post Thoracic Surgery using K-Nearest Neighbors and Bat Algorithm","authors":"Muhamad Nur Arifiansyah","doi":"10.15294/jaist.v4i2.60846","DOIUrl":"https://doi.org/10.15294/jaist.v4i2.60846","url":null,"abstract":"\u0000 \u0000 \u0000 \u0000Lung cancer is one of the deadliest cancers, accounting for 11.6% of cancer diagnoses in the world. Death in lung cancer patients can occur in various ways and one of the treatments for lung cancer patients that can be done is thoracic surgery. Thoracic surgery is generally considered a medium risk procedure, but thoracic surgery has a high risk, one of the risks is that if the patient loses blood which will result in the death of the patient. In this study, the method used to implement predictive life expectancy in post-thoracic surgery patients is the bat algorithm for feature selection and the KNN algorithm for classifying data. The dataset used in this study was obtained from the UCI Machine Learning Repository, namely the thoracic surgery dataset which contains 470 data with 16 attributes. The results of the study in predicting the life expectancy of patients after thoracic surgery were carried out with 3 tests. The first test is testing the population with the best accuracy of 87.23%, the second test is convergent testing with the best accuracy of 87.23% and the third test is the comparison test of KNN which produces the best accuracy of 87.23%. The bat algorithm succeeded in increasing the accuracy of the KNN classification by 5.23% from 81.91%. \u0000 \u0000 \u0000 \u0000","PeriodicalId":418742,"journal":{"name":"Journal of Advances in Information Systems and Technology","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115789669","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

Implementation of Fuzzy Inference System with Best-Worst Method for Cost Efficiency on Amazon Web Services 基于成本效率的最佳-最差方法的模糊推理系统在Amazon Web Services上的实现

Journal of Advances in Information Systems and Technology Pub Date : 2023-03-10 DOI: 10.15294/jaist.v4i2.60569

Annisya Dira Prastiwi, A. T. Putra

{"title":"Implementation of Fuzzy Inference System with Best-Worst Method for Cost Efficiency on Amazon Web Services","authors":"Annisya Dira Prastiwi, A. T. Putra","doi":"10.15294/jaist.v4i2.60569","DOIUrl":"https://doi.org/10.15294/jaist.v4i2.60569","url":null,"abstract":"This study aims to reduce the cost of using computing services on AWS. Cost reduction is needed because there is a possibility that the total cost of using cloud services exceeds the estimated budget. One type of EC2 that offers a large discount is the Spot Instance. The downside of this type of EC2 is that AWS reserves the right to stop it at any time. The proposed solution is an automation system to select and run EC2 Spot Instance types based on price, discount, amount of memory, and vCPU usage from previous instances. The automation system is built with the implementation of fuzzy inference system and Best-Worst Method (BWM). All input data is obtained using the Boto3 SDK. System deployment is done in Lambda functions. This Lambda function is automatically executed whenever a Spot Instance is terminated by AWS. The EventBridge service will catch the event and then trigger the Lambda to run. System testing was run for 4 (four) days with event simulation using the Send Events feature. From these tests it is known that the automation system can select the appropriate instance and generate a total cost of $3.85 (USD). After calculating the total cost with regular EC2 estimation (On Demand), the cost is reduced by 71.28%. This number proved to be 4.28% greater than previous similar studies.","PeriodicalId":418742,"journal":{"name":"Journal of Advances in Information Systems and Technology","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124472288","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

Improved Accuracy of Naïve Bayes Algorithm and Support Vector Machine Using Particle Swarm Optimization for Menstrual Cup Sentiment Analysis on Twitter 基于粒子群优化的Naïve贝叶斯算法和支持向量机在推特上的月经杯情感分析

Journal of Advances in Information Systems and Technology Pub Date : 2023-03-10 DOI: 10.15294/jaist.v4i2.59561

Dini Shalikha, A. Alamsyah

引用次数: 0

Electric Vehicle Routing Problem with Fuzzy Time Windows using Genetic Algorithm and Tabu Search 基于遗传算法和禁忌搜索的模糊时间窗电动车路径问题

Journal of Advances in Information Systems and Technology Pub Date : 2023-03-10 DOI: 10.15294/jaist.v4i2.62314

Wahyu Syafrizal, E. Sugiharti

{"title":"Electric Vehicle Routing Problem with Fuzzy Time Windows using Genetic Algorithm and Tabu Search","authors":"Wahyu Syafrizal, E. Sugiharti","doi":"10.15294/jaist.v4i2.62314","DOIUrl":"https://doi.org/10.15294/jaist.v4i2.62314","url":null,"abstract":"\u0000 \u0000 \u0000 \u0000The distribution of goods becomes a very calculated thing in the economic aspect, especially in the case of wide and complex distribution. The greater the range of distribution of goods, the more precise, fast, and accurate calculations are needed. Specifically, the calculation of the distribution required starts from mileage, total travel time, customer satisfaction level based on customer time windows, and operational costs. Vehicle Routing Problem (VRP) is a solution to the problem of distributing goods from the depot to its customers. This study aims to determine the optimal route. The methods used for VRP optimization are the Genetic Algorithm (GA) and Tabu Search (TS) methods. Fuzzy logic is used to provide leeway on the limitations of the time windows parameters, thus providing a time tolerance in the event of early arrival of the vehicle or delay in delivery. Data processing using the GA-TS combination was carried out as many as two types of trials, namely trials with the same dataset ten times and trials with various types of datasets ten times. The results of the first trial fitness value on E-VRPFTW average increased by 14.39% compared to the results of the E-VRPTW fitness value that did not use fuzzy. The results of the second trial also experienced an average increase of 8.49% compared to the results of the E-VRPTW fitness value that did not use fuzzy. Therefore, the addition of fuzzy logic has an effect in determining the optimum route of E-VRPTW. \u0000 \u0000 \u0000 \u0000","PeriodicalId":418742,"journal":{"name":"Journal of Advances in Information Systems and Technology","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131514311","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

Detection of the Use of Masks as an Effort to Prevent Covid-19 Using Gray Level Co-Occurrence Matrix (GLCM) Based on Learning Vector Quantization (LVQ) 基于学习向量量化(LVQ)的灰度共生矩阵(GLCM)检测口罩预防Covid-19行为

Journal of Advances in Information Systems and Technology Pub Date : 2023-03-10 DOI: 10.15294/jaist.v4i2.61105

Teguh Pamungkas

{"title":"Detection of the Use of Masks as an Effort to Prevent Covid-19 Using Gray Level Co-Occurrence Matrix (GLCM) Based on Learning Vector Quantization (LVQ)","authors":"Teguh Pamungkas","doi":"10.15294/jaist.v4i2.61105","DOIUrl":"https://doi.org/10.15294/jaist.v4i2.61105","url":null,"abstract":"Covid-19 is a disease caused by the SARS-CoV-2 virus. Transmission of Covid-19 can be through the flow of air (aerosol), splashes of liquid (droplets). One of the prevention efforts to break the chain of transmission is to use a mask when interacting with other people. Monitoring and controlling the use of masks will be safer and more efficient when implementing a mask detection system. This study will analyze GLCM for extraction method and LVQ for classification method. The results of GLCM successfully provide statistical features that represent image characteristics well. While the LVQ can provide classification results with a good percentage of accuracy. The results of the best percentage accuracy for the first rank are 83.15% in the composition ratio of 90: 10. Furthermore, the percentage of accuracy for the second rank is 76.03% at the composition ratio of 70: 30 and the third rank is 72.47% at the composition ratio of 80: 20. This indicates that the composition more training data does not guarantee the level of achievement of a higher percentage of accuracy. There is an optimal maximum number of epochs where the number of epochs that exceeds the optimal number of epochs will not experience a change in the percentage of accuracy. For each value the learning rate (alpha) can give the results of the percentage of accuracy with different graphic patterns and will stop at the optimal maximum number of epochs.","PeriodicalId":418742,"journal":{"name":"Journal of Advances in Information Systems and Technology","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123812216","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

Performance Comparison of SVM, Naïve Bayes, and KNN Algorithms for Analysis of Public Opinion Sentiment Against COVID-19 Vaccination on Twitter 支持向量机、Naïve贝叶斯和KNN算法在Twitter上对COVID-19疫苗接种的民意情绪分析中的性能比较

Journal of Advances in Information Systems and Technology Pub Date : 2023-03-10 DOI: 10.15294/jaist.v4i2.59493

Khafifah Munawaroh, A. Alamsyah

{"title":"Performance Comparison of SVM, Naïve Bayes, and KNN Algorithms for Analysis of Public Opinion Sentiment Against COVID-19 Vaccination on Twitter","authors":"Khafifah Munawaroh, A. Alamsyah","doi":"10.15294/jaist.v4i2.59493","DOIUrl":"https://doi.org/10.15294/jaist.v4i2.59493","url":null,"abstract":"\u0000 \u0000 \u0000 \u0000The emergence of the COVID-19 virus in 2020 has created a new breakthrough in the form of a vaccine as a solution to slow the spread of the virus. However, the COVID-19 vaccine is considered controversial and invites many people to express their views on various media, one of which is social media Twitter. Using Twitter data on the COVID-19 vaccine, sentiment analysis can be performed. Sentiment analysis aims to evaluate whether the tweet contains a positive sentence or sentiment. In this study, the analysis of sentiments on the COVID-19 vaccine on social media Twitter was carried out using the Support Vector Machine (SVM), Naïve Bayes, and k-Nearest Neighbor (KNN) algorithms. SVM has the advantage of being able to identify hyperplanes that maximize the margins between different sentiments. Meanwhile Naïve Bayes is an algorithm that is simple, fast and produces maximum accuracy with training. The KNN algorithm was chosen because it is superior to noise. The performance of the three classification algorithms will be compared, so that it can be seen which algorithm is better in classifying text mining. Sentiment classification results in this study consist of positive sentiment and sentiment classes. The resulting accuracy value will be a benchmark for finding the best test model in the case of sentiment classification. Based on ten tests, the final result of accuracy and best performance using the SVM algorithm with an accuracy value of 96.3% is obtained. Meanwhile, the Naïve Bayes and KNN algorithms have an accuracy of 94% and 91%, respectively. The high accuracy results are supported by the feature extraction TF-IDF the TextBlob library. \u0000 \u0000 \u0000 \u0000","PeriodicalId":418742,"journal":{"name":"Journal of Advances in Information Systems and Technology","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123547554","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

After Sales Business Process Optimization 售后业务流程优化

Journal of Advances in Information Systems and Technology Pub Date : 2022-09-06 DOI: 10.15294/jaist.v3i2.53020

Vivi Aryska, Nabila Zahra Irfany, Dilla Caroline Khairunnisa’

引用次数: 0

Multilayer Perceptron Optimization on Imbalanced Data Using SVM-SMOTE and One-Hot Encoding for Credit Card Default Prediction 基于SVM-SMOTE和One-Hot编码的不平衡数据多层感知器优化信用卡违约预测

Journal of Advances in Information Systems and Technology Pub Date : 2022-09-06 DOI: 10.15294/jaist.v3i2.57061

Adi Sakti Almajid

{"title":"Multilayer Perceptron Optimization on Imbalanced Data Using SVM-SMOTE and One-Hot Encoding for Credit Card Default Prediction","authors":"Adi Sakti Almajid","doi":"10.15294/jaist.v3i2.57061","DOIUrl":"https://doi.org/10.15294/jaist.v3i2.57061","url":null,"abstract":"Credit risk assessment analysis by classifying potential users is an important process to reduce the occurrence of default users. The problems faced from the classification process using real-world datasets are imbalanced data that causes bias-to-majority in model training outcomes. These problems cause the algorithm to only focus on the majority class and ignore the minority class, even though both classes have the same important role. To overcome this problem, a combination of One-hot encoding (OHE) and SVM-Synthetic minority oversampling technique (SVM-SMOTE) techniques are used for the optimization process of the MLP classification algorithm. OHE is used to encode values categorical nominal and SVM-SMOTE for the oversampling. The results of the measurement of the ability of the model generated from the optimized MLP are then compared with the baseline using the AUC score. The data used is the default of credit card client dataset from Taiwan which has 30000 instances. The result of the highest AUC score of the MLP that has gone through optimization is 0.7184, an increase of 0.2179 compared to the baseline.","PeriodicalId":418742,"journal":{"name":"Journal of Advances in Information Systems and Technology","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130572993","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: 3

User Experience Analysis of Satisfaction of Job Seekers (PENCAKER) in the City of Semarang Manpower Department in Using the SIKER Application Using the User Experience Questionnaire (UEQ) Method 用用户体验问卷法分析三宝垄市人力资源部求职者对SIKER应用的满意度

Journal of Advances in Information Systems and Technology Pub Date : 2022-09-06 DOI: 10.15294/jaist.v3i2.53714

Edward Jhonatan, K. Budiman

{"title":"User Experience Analysis of Satisfaction of Job Seekers (PENCAKER) in the City of Semarang Manpower Department in Using the SIKER Application Using the User Experience Questionnaire (UEQ) Method","authors":"Edward Jhonatan, K. Budiman","doi":"10.15294/jaist.v3i2.53714","DOIUrl":"https://doi.org/10.15294/jaist.v3i2.53714","url":null,"abstract":"\u0000 \u0000 \u0000 \u0000The Semarang City Manpower Service or also known as (DISNAKER) is a government agency that can foster and control the manpower sector. The Manpower Office has its website application, namely the work system (SIKER) which is an integrated employee recruitment information system from the Semarang city government, companies, and also the community or job seekers. This study aims to understand the level of comfort in terms of User Experience in using the SIKER application. Analysis of the SIKER website application by applying the User UEQ method approach given to 32 respondents who have used this website. The UEQ assessment focuses on six aspects, namely: efficiency, attractiveness, accuracy, clarity, novelty, and stimulation. The results obtained after conducting the analysis are that the average respondent gives below average results, at the User Experience level the efficiency item gets a sufficient value, on the clarity, accuracy, stimulation, attractiveness, and novelty scales it gets a value below the average. This tends to be the lack of seeker users with this SIKER application. In other words, the reason is that there are still many users who don't understand this application because this application is still relatively new. \u0000 \u0000 \u0000 \u0000","PeriodicalId":418742,"journal":{"name":"Journal of Advances in Information Systems and Technology","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115503455","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

ACCEPTANCE ANALYSIS OF TECHNOLOGY-BASED PERSONNEL MANAGEMENT INFORMATION SYSTEMS (SIMPATIK) IN SUPPORTING THE IMPLEMENTATION OF E-GOVERNMENT IN THE SEMARANG CITY MANPOWER SERVICE 基于技术的人事管理信息系统(simpatik)在三宝朗市人力服务中支持电子政务实施的验收分析

Journal of Advances in Information Systems and Technology Pub Date : 2022-09-06 DOI: 10.15294/jaist.v3i2.53708

Muhammad Majid, K. Budiman

{"title":"ACCEPTANCE ANALYSIS OF TECHNOLOGY-BASED PERSONNEL MANAGEMENT INFORMATION SYSTEMS (SIMPATIK) IN SUPPORTING THE IMPLEMENTATION OF E-GOVERNMENT IN THE SEMARANG CITY MANPOWER SERVICE","authors":"Muhammad Majid, K. Budiman","doi":"10.15294/jaist.v3i2.53708","DOIUrl":"https://doi.org/10.15294/jaist.v3i2.53708","url":null,"abstract":"In this digital era, information technology has an important role for institutions, companies, communities, and governments. In carrying out the main tasks of the Semarang City Manpower Service, one of them is evaluating employee performance. In assessing the performance of the Semarang City Manpower Service employees using SIMPATIK which was developed by the Semarang City BKPP which was launched in 2018. Where the implementation of the new system needs to be evaluated further. This is due to the failure to implement e-government services, not because of the quality and capacity of the system, but because of the low user acceptance of these services. Thus, it is necessary to analyse the level of acceptance in using SIMPATIK services at the Semarang City Manpower Service whether it can be evaluated further. So that SIMPATIK can still exist to be used for various kinds of services contained in the application by ASN at the Semarang City Manpower Service. The method applied to data collection is the interview and questionnaire method. While the method applied to evaluate SIMPATIK is the Technology Acceptance Model (TAM) by applying four research variables, namely perceived usefulness (PU), perceived ease of use (PEOU), attitude toward using (ATU), and behavioural intentions (BI). To examine the data adopted the method of Structural Equation Model-partial Least Square (SEMPLS). The conclusion reached in this study is that all hypotheses developed in this study were accepted, except for PU on BI rejected because the value of T-Statistics (0.846) < T-Table (1.96) and P-Values were more than 0.05 with a value of 0.398 .","PeriodicalId":418742,"journal":{"name":"Journal of Advances in Information Systems and Technology","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128842120","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