1 10 5 https://repository.horizon.ac.id/files/original/db8f6e8e17a91eda39151a43cc270eee.pdf 80e7cf7ee487c207fed48270e0c3a284 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOL 5 NO 4 DECEMBER 2022 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Software Defect Fault Intelligent Location and Identification Method Based on Data Mining Subject The topic of the resource Software Defect; Data Mining; Fault Location; Data Algorithm Description An account of the resource With the advancement of the times, computer technology is also constantly improving, and people's requirements for software functions are also constantly improving, and as software functions become more and more complex, developers are technically limited and teamwork is not tacitly coordinated. And so on, so in the software development process, some errors and problems will inevitably lead to software defects. The purpose of this paper is to study the intelligent location and identification methods of software defects based on data mining. This article first studies the domestic and foreign software defect fault intelligent location technology, analyzes the shortcomings of traditional software defect detection and fault detection, then introduces data mining technology in detail, and finally conducts in-depth research on software defect prediction technology. Through in-depth research on several technologies, it reduces the accidents of software equipment and delays its service life. According to the experiments in this article, the software defect location proposed in this article uses two methods to compare. The first error set is used as a unit to measure the subsequent error set software error location cost. The first error set 1F contains 19 A manually injected error program, and the average positioning cost obtained is 3.75%. Creator An entity primarily responsible for making the resource Wenhua College, Wuhan, 430074, Hubei, China Date A point or period of time associated with an event in the lifecycle of the resource 2022 Contributor An entity responsible for making contributions to the resource PERI IRAWAN Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource ENGLISH Type The nature or genre of the resource TEXT https://repository.horizon.ac.id/files/original/85da94196ff20a300f98cd3f397ee51d.pdf f34da6b356a9dfab5b786f63993aaf02 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOL 5 NO 4 DECEMBER 2022 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource The Combined Application Technology of the Bank's TwoDimensional Aggregate Payment Code and the Vegetable Field Traceability System Subject The topic of the resource QR Code Aggregation; Green Food; Traceability Description An account of the resource With the rapid development of social economy, people's living standards and quality of life are getting better and better, and food safety is getting more and more attention. Aiming at the problem of vegetable traceability, this paper analyzes the bank's QR code scan code aggregation payment model. Secondly, it designs a green food traceability system and elaborates the realization of the main functions of the system. Practice has proved that the traceability system of green food can allow consumers to consume with confidence, and at the same time, it is convenient for the competent government departments to trace the source in time and control the quality. Creator An entity primarily responsible for making the resource Luyi Zhang Date A point or period of time associated with an event in the lifecycle of the resource 2022 Contributor An entity responsible for making contributions to the resource PERI IRAWAN Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource ENGLISH Type The nature or genre of the resource TEXT https://repository.horizon.ac.id/files/original/669e531b5cc0e9891e573752a7892d2a.pdf eed65864413eb55cdf6fdd9730559c84 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOL 5 NO 4 DECEMBER 2022 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Selection of Suppliers of Building Materials Using the Analytical Hierarchy Process (AHP) Method at PT. Cipta Nuansa Prima Tangerang Subject The topic of the resource Supplier Selection; Methods Analytical Hierarchy Process; Decision Support System Description An account of the resource Supplier is one of the most important parts of a construction services provider company. PT. Nuance Prima Cipta Tangerang is a contracting company that offers construction services. Since the number of suppliers, PT. Nuance Prima Cipta Tangerang difficulty in choosing suppliers with their respective advantages. Therefore, use AHP (Analytical Hierarchy Process) for supplier selection process to make it more objective. Broadly speaking, AHP (Analytical Hierarchy Process) is the process of comparing criteria into alternatives, the greater the value is generated, then the main well to the supplier selected. By using the AHP method obtained the final value for each alternatif Lead A 39%, 12% and Supplier B Supplier C 49%. Creator An entity primarily responsible for making the resource Rani Irma Handayanir Date A point or period of time associated with an event in the lifecycle of the resource 2022 Contributor An entity responsible for making contributions to the resource PERI IRAWAN Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource ENGLISH Type The nature or genre of the resource TEXT https://repository.horizon.ac.id/files/original/580ef83b7286f6f97310376068eb43ff.pdf 61132100e3d3e07cad487ca8f9f0b422 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOL 5 NO 4 DECEMBER 2022 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Analysis of Recommended Mobile Selection Using the Weighted Product Method Subject The topic of the resource Mobile Phones; Criteria; Alternatives; Weighted Products. Description An account of the resource Mobile is an electronic telecommunications device that has become a major requirement at this time, which is equipped with the advantages of the features of each device. The number of outputs or new breakthroughs from mobile phone manufacturers makes consumers have to be observant in choosing the right cellphone to use in their activities. Ignorance of the advantages and disadvantages of selected mobile phones can cause harm to consumers who use them based on their respective levels of interest. In this study, an analysis of the calculation of several alternative cell phone data will be carried out based on the criteria/attributes determined using the weighted product method which can solve the problem by multiplying to connect the attribute rating with the weighted attribute in question. It is hoped that this calculation analysis concept can become the foundation of knowledge about the weighted product method, especially in terms of selecting recommendation cellphones, as well as a basic sketch for developing the implementation of the weighted product method into future decision support system application programs Creator An entity primarily responsible for making the resource Sora Yi 1,*, Yong-Chul Jang Date A point or period of time associated with an event in the lifecycle of the resource 2022 Contributor An entity responsible for making contributions to the resource PERI IRAWAN Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource ENGLISH Type The nature or genre of the resource TEXT https://repository.horizon.ac.id/files/original/5a9e5d7ebc7d8d0dc6bdf2576acc3035.pdf bb2fd7e3fb13a2eee4deab60263718b8 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOL 5 NO 4 DECEMBER 2022 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Comparison of Data Normalization for Wine Classification Using K-NN Algorithm Subject The topic of the resource Normalization, K-fold cross validation, K-NN Description An account of the resource The range of values that are not balanced on each attribute can affect the quality of data mining results. For this reason, it is necessary to pre-process the data. This preprocessing is expected to increase the accuracy of the results from the wine dataset classification. The preprocessing method used is data transformation with normalization. There are three ways to do data transformation with normalization, namely min-max normalization, z-score normalization, and decimal scaling. Data that has been processed from each normalization method will be compared to see the results of the best classification accuracy using the K-NN algorithm. The K used in the comparisons were 1, 3, 5, 7, 9, 11. Before classifying the normalized wine dataset, it was divided into test data and training data with k-fold cross validation. The division of the data using k is equal to 10. The results of the classification test with the K-NN algorithm show that the best accuracy lies in the wine dataset which has been normalized using the min-max normalization method with K = 1 of 65.92%. The average obtained is 59.68%. Creator An entity primarily responsible for making the resource Rohitash Chandra 1,*, Kaylash Chaudhary 2, Akshay Kumar Date A point or period of time associated with an event in the lifecycle of the resource 2022 Contributor An entity responsible for making contributions to the resource PERI IRAWAN Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource ENGLISH Type The nature or genre of the resource TEXT