The objective of this research is to reduce the dropout rate students in Faculty Systems Engineering and Informatics Universidad Nacional Mayor de San Marcos – FISI-UNMSM, through implementation an intelligent system with a data mining approach autonomous learning algorithm (decision trees) that predicts which are at risk dropping out. It was developed Python free software Weka, for purpose stu...

This research paper combines the data mining with natural language processing to extract the nuggets of knowledge from massive volume of student feedback dataset on faculty performance. The main objective is to compare two renowned association rule mining and sequential pattern mining algorithms namely Apriori and Generalized Sequential Pattern (GSP) mining in the context of extracting frequent...

Meta decision trees (MDTs) are a method for combining multiple classifiers. We present an integration of the algorithm MLC4.5 for learning MDTs into the Weka data mining suite. We compare classifier ensembles combined with MDTs to bagged and boosted decision trees, and to classifier ensembles combined with other methods: voting, grading, multi-scheme and stacking with multi-response linear regr...

We analyze the breast Cancer data available from the WBC, WDBC from UCI machine learning with the aim of developing accurate prediction models for breast cancer using data mining techniques. Data mining has, for good reason, recently attracted a lot of attention, it is a new Technology, tackling new problem, with great potential for valuable commercial and scientific discoveries. The experiment...

This study proposes an expert system, which is called the hybrid Kansei engineering system (HKES) based on multiple affective responses (MARs), to facilitate the development of product form design. An HKES is consists of two sub-systems, namely the forward Kansei engineering system (FKES) and the backward Kansei engineering system (BKES). The FKES is utilized to generate product alternatives an...

Packaging is one of the keys to maintaining product quality, packaging involves designing and producing activities, protect product. always design so that message can be conveyed consumers, current function as well an effective marketing medium. The method used in this study kansei engineering data were obtained from distributing questionnaires lasted for 1 month with aim research, namely, obta...

New food product development is so often confronted with failure in the market. One of the significant reasons is, nowadays, the customer preference is no longer simply only determined by a few factors rather a combination of various needs. This article presents an affective engineering methodology “Kansei Engineering” which can tailor the product by the customer need. This methodology is able ...

Kansei Engineering (KE) is a technique used to incorporate emotions in the product design process. Its basic purpose is discovering in which way some properties of a product convey certain emotions in its users. It is a quantitative method, and data is typically collected using questionnaires. Japanese researcher Mitsuo Nagamachi is the founder of Kansei Engineering. Products where KE has been ...

The aesthetic and pleasing properties of a product are important and add significantly to themeaning and relevance of a product. Customer sensation andperception are largely about psychological factors. There has been a strong industrial and academic need and interest formethods and tools to quantify and link product properties to thehuman response but a lack of studies of the impact of surface...