IJIIS: International Journal of Informatics and Information Systems最新文献_第6页

Cyber Democracy Versus Controlling Shareholders: The Implications of E-Voting System for Corporate Governance 网络民主与控股股东:电子投票系统对公司治理的影响

IJIIS: International Journal of Informatics and Information Systems Pub Date : 2019-12-01 DOI: 10.47738/ijiis.v2i3.97

Kuo-Pin Yang

引用次数: 2

Electronic Banking in Opinion of Young Customers in Poland 波兰年轻客户对电子银行的看法

IJIIS: International Journal of Informatics and Information Systems Pub Date : 2019-12-01 DOI: 10.47738/ijiis.v2i1.88

E. Wyslocka

引用次数: 0

Naive Bayes Algorithm Using Selection of Correlation Based Featured Selections Features for Chronic Diagnosis Disease 基于相关性特征选择特征的朴素贝叶斯算法用于慢性诊断疾病

IJIIS: International Journal of Informatics and Information Systems Pub Date : 2019-09-01 DOI: 10.47738/IJIIS.V2I2.14

Irfan Santiko, Ikhsan Honggo

{"title":"Naive Bayes Algorithm Using Selection of Correlation Based Featured Selections Features for Chronic Diagnosis Disease","authors":"Irfan Santiko, Ikhsan Honggo","doi":"10.47738/IJIIS.V2I2.14","DOIUrl":"https://doi.org/10.47738/IJIIS.V2I2.14","url":null,"abstract":"Chronic kidney disease is a disease that can cause death, because the pathophysiological etiology resulting in a progressive decline in renal function, and ends in kidney failure. Chronic Kidney Disease (CKD) has now become a serious problem in the world. Kidney and urinary tract diseases have caused the death of 850,000 people each year. This suggests that the disease was ranked the 12th highest mortality rate. Some studies in the field of health including one with chronic kidney disease have been carried out to detect the disease early, In this study, testing the Naive Bayes algorithm to detect the disease on patients who tested positive for negative CKD and CKD. From the results of the test algorithm accuracy value will be compared against the results of the algorithm accuracy before use and after feature selection using feature selection Featured Correlation Based Selection (CFS), it is known that Naive Bayes algorithm after feature selection that is 93.58%, while the naive Bayes without feature selection the result is 93.54% accuracy. Seeing the value of a second accuracy testing Naive Bayes algorithm without using the feature selection and feature selection, testing both these algorithms including the classification is very good, because the accuracy value above 0.90 to 1.00. Included in the excellent classification. higher accuracy results.","PeriodicalId":229613,"journal":{"name":"IJIIS: International Journal of Informatics and Information Systems","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129127144","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

Decision Support System to Determine the Achievement of Students Using Simple Multi-Attribute Rating Technique (SMART) 基于简单多属性评定技术(SMART)的学生成绩判定决策支持系统

IJIIS: International Journal of Informatics and Information Systems Pub Date : 2019-09-01 DOI: 10.47738/ijiis.v2i2.12

Abdul Jahir, I. Setiawan, Anisa Dayu Arta

引用次数: 4

Comparison of Cart and Naive Bayesian Algorithm Performance to Diagnose Diabetes Mellitus Cart与朴素贝叶斯算法诊断糖尿病的性能比较

IJIIS: International Journal of Informatics and Information Systems Pub Date : 2019-09-01 DOI: 10.47738/ijiis.v2i1.9

Irfan Santiko, Pungkas Subarkah

{"title":"Comparison of Cart and Naive Bayesian Algorithm Performance to Diagnose Diabetes Mellitus","authors":"Irfan Santiko, Pungkas Subarkah","doi":"10.47738/ijiis.v2i1.9","DOIUrl":"https://doi.org/10.47738/ijiis.v2i1.9","url":null,"abstract":"Based on Indonesia's health profile in 2008, Diabetes Mellitus is the cause of the ranking of six for all ages in Indonesia with the proportion of deaths of 5.7% under stroke, TB, hypertension, injury and perinatal. This is reinforced by WHO (2003), Diabetes Mellitus disease reached 194 million people or 5.1 percent of the world's adult population and in 2025 is expected to increase to 333 million inhabitants. In particular, in Indonesia, people with Diabetes Mellitus are increasing. In 2000, Diabetes Mellitus sufferers have reached 8.4 million people and it is estimated that the prevalence of Diabetes Mellitus in 2030 in Indonesia reaches 21.3 million people.This allows researchers and practitioners to focus their attention on detecting/diagnosing diabetes mellitus and to prevent it because the disease can cause complications. The method used in this research was problem identification, data collection, pre-processing stage, classification method, validation and evaluation and conclusion. The algorithm used in this research was CART and Naïve Bayes using dataset taken from UCI Indian Pima database repository consisting of clinical data ofpatients who detected positive and negative diabetes mellitus. Validation and evaluation method used was 10-crossvalidation and confusion Matrix for the assessment of precision, recall and F-Measure. The result of calculation has been done, got the accuracy result on CART algorithm equaled to 76.9337% with precision 0.764%, recall 0.769%, and F-Measure 0.765%. Whilethe diabetes dataset was tested with the Naïve Bayes algorithm, got an accuracy of 73.7569% with precision 0.732%, recall 0.738%, and F-Measure 0.734%. From these results it can be concluded that to diagnose diabetes mellitus disease it is suggested to use CART algorithm.","PeriodicalId":229613,"journal":{"name":"IJIIS: International Journal of Informatics and Information Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129172739","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: 5

Sentiment Analysis of Product Reviews as A Customer Recommendation Using the Naive Bayes Classifier Algorithm 基于朴素贝叶斯分类器的产品评论情感分析

IJIIS: International Journal of Informatics and Information Systems Pub Date : 2019-09-01 DOI: 10.47738/ijiis.v2i2.13

T. Hariguna, Wiga Maaulana Baihaqi, Aulia Nurwanti

{"title":"Sentiment Analysis of Product Reviews as A Customer Recommendation Using the Naive Bayes Classifier Algorithm","authors":"T. Hariguna, Wiga Maaulana Baihaqi, Aulia Nurwanti","doi":"10.47738/ijiis.v2i2.13","DOIUrl":"https://doi.org/10.47738/ijiis.v2i2.13","url":null,"abstract":"In an e-commerce Shopee, the process of selling and buying continues to run every day, and the comments given by consumers will increase more and more. Comments given by consumers will be the reference/review of a product that has been purchased by consumers. Consumers freely provide a review containing positive comments and negative comments in the Comments field listed on the Shopee e-commerce website. With the above problems, researchers will do a research with the method of sentiment analysis to distinguish classes in product review comments that include positive comment class or negative comment class using a combination of K-means and naive Bayes classifier. K-means used to determine the grouping of classes; naive Bayes classifier used to get the value of accuracy. The results obtained based on clustering K-means include getting 116 negative comments on product reviews and 37 negative comments product reviews. Accuracy results obtained from product review comment data of 77.12%. Thus, the accuracy value using K-means and naive Bayes classifier without manual data get a higher accuracy value is compared using K-means, Naive Bayes classifier, and manual data get results lower accuracy of 56.86%. From the results above the most comments is a negative comment of 116 data review comments product, from the results of the study can be concluded that one of the products of Spatuafa named high heels women know the Ribbon Ikat FX18 the condition of the product is not good enough due to the high negative comments compared to positive comments","PeriodicalId":229613,"journal":{"name":"IJIIS: International Journal of Informatics and Information Systems","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126737642","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: 14

Comparative Method of Weighted Product and TOPSIS to Determine The Beneficiary of Family Hope Program 加权乘积与TOPSIS比较法确定家庭希望计划受益人

IJIIS: International Journal of Informatics and Information Systems Pub Date : 2019-09-01 DOI: 10.47738/ijiis.v2i2.16

Didit Suhartono, Tika Sari

{"title":"Comparative Method of Weighted Product and TOPSIS to Determine The Beneficiary of Family Hope Program","authors":"Didit Suhartono, Tika Sari","doi":"10.47738/ijiis.v2i2.16","DOIUrl":"https://doi.org/10.47738/ijiis.v2i2.16","url":null,"abstract":"The Family Hope Program (PKH) is a government program that provides cash assistance to impoverished households. The implementation of PKH in Cimrutu Village has not been implemented optimally, namely prioritizing the targets of PKH participants who are not yet on targets. This happened because the officers in registering the poor were still using manual methods. To simplify the work and avoid miscalculation of data with the old system, a decision support system was built that could help make decisions on PKH recipients quickly and more accurately. The calculation method used is the Weighted Product (WP) method. Data collection methods used in this study were interviews and documentation. System development in this study uses waterfall through black-box testing. System design tools in the form of DFD and ERD. The software used in making this application is Visual Studio 2012, Xampp, and Crystal Reports. The programming language used is Java with its supporting database using MySQL. This decision support system is expected to be able to help officers in Cimrutu Village in selecting and determining communities that are eligible for PKH.","PeriodicalId":229613,"journal":{"name":"IJIIS: International Journal of Informatics and Information Systems","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116208242","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: 6

Product Review Sentiment Analysis by Artificial Neural Network Algorithm 基于人工神经网络算法的产品评论情感分析

IJIIS: International Journal of Informatics and Information Systems Pub Date : 2019-09-01 DOI: 10.47738/ijiis.v2i2.15

Tri Astuti, Irnawati Pratika

引用次数: 3

Analysis of Sequential Book Loan Data Pattern Using Generalized Sequential Pattern (GSP) Algorithm 基于广义顺序模式(GSP)算法的顺序图书借阅数据模式分析

IJIIS: International Journal of Informatics and Information Systems Pub Date : 2019-03-01 DOI: 10.47738/ijiis.v2i1.10

T. Astuti, Lisdya Anggraini

{"title":"Analysis of Sequential Book Loan Data Pattern Using Generalized Sequential Pattern (GSP) Algorithm","authors":"T. Astuti, Lisdya Anggraini","doi":"10.47738/ijiis.v2i1.10","DOIUrl":"https://doi.org/10.47738/ijiis.v2i1.10","url":null,"abstract":"As a center for learning and information services, STMIK Amikom Purwokerto Library is a source of learning and a source of intellectual activity that is very important for the entire academic community in supporting the achievement of the college Tridharma program. Book lending transaction data, can produce information that is important as supporting decision making when further analyzed. One useful information is that it can provide information in the form of user behavior patterns in borrowing books that are used to maintain the availability of related book stocks to be balanced. This study uses the Generalized Sequential Pattern (GSP) algorithm, which can be used to determine the behavior patterns of users in each transaction and can show relationships or associations between books, both requested simultaneously and sequentially. From the calculations that have been done, 295 frequent sequences are consisting of 3 sequence patterns that are formed from the minimum support of 0.53% or the minimum number of books borrowed, namely 2 books. Three book items have very strong linkages in book lending transactions, namely book code 6690, 2026, and 8131.","PeriodicalId":229613,"journal":{"name":"IJIIS: International Journal of Informatics and Information Systems","volume":"143 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116373729","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

Expert System for Simulation of Pest and Disease Diagnosis in Onion Plant Using Putty Shafer Method and Rule-Based Approach 基于Putty Shafer法和基于规则的洋葱病虫害诊断模拟专家系统

IJIIS: International Journal of Informatics and Information Systems Pub Date : 2019-03-01 DOI: 10.47738/ijiis.v2i1.8

Melia Dianingrum, Nandang Hermanto, Mohamad Iqbal Rifa'i

{"title":"Expert System for Simulation of Pest and Disease Diagnosis in Onion Plant Using Putty Shafer Method and Rule-Based Approach","authors":"Melia Dianingrum, Nandang Hermanto, Mohamad Iqbal Rifa'i","doi":"10.47738/ijiis.v2i1.8","DOIUrl":"https://doi.org/10.47738/ijiis.v2i1.8","url":null,"abstract":"The expert system is trying to adopt a system of human knowledge into a computer so that the computer can solve problems like the experts. The expert system is well designed in order to solve a particular problem by mimicking the work of the expert. The development of an expert system is expected to be resolved problems with the help of experts. The problems addressed by an expert not only the problems that rely on algorithms but sometimes elusive problems. An expert with knowledge and experience can overcome these problems. The application of an expert system in this study is made to diagnose pests and diseases in onion plants based on the web. The Data Collection method used is literature studies, interviews and observation. The stages of research used are literature review, data processing analyst, and Onion analyzed and photographed which then is uploaded and analyzed, Dempster Shafer method, application development, evaluation. In the last stage is the pilot study conducted using a Blackbox method and testing to the user. The result of the research is in the form of an expert system application that can diagnose pests and diseases of onion as many as 7 types of diseases. The output system is in the form of onion disease searching result obtained based on the symptoms inputted by the user. The result of Blackbox Testing is all functions of the application successfully run well. Testing to the users rated well both appearance and information of the application.","PeriodicalId":229613,"journal":{"name":"IJIIS: International Journal of Informatics and Information Systems","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128548579","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