A Decision Making and Clustering Method Integration based on the Theory of Planned Behavior for Student Entrepreneurial Potential Mapping in Indonesia

Rijati, Nova; Purwitasari, Diana; Sumpeno, Surya; Purnomo, Mauridhi Hery

doi:10.22266/ijies2020.0831.12

Cited by 8 publications

(12 citation statements)

References 15 publications

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“…erefore, in practice, the algorithm must start n indicators of risk assessment system Complexity with the development of the poststructure, insist on analyzing from the background of big data, and at the same time adjust the rationality of space and form, and promote the development of the information industry chain on the basis of effective research and improvement. From a provider to a dominant player at this stage, the network media itself is constantly improving [18]. ey pay attention to the key points of marketing in the era of big data, understand the data and information behind consumers, and do a good job of digging into user needs so as to achieve personalized services and ensure the rationality of construction plans and strategies.…”

Section: Results Analysismentioning

confidence: 99%

A Risk Assessment Algorithm for College Student Entrepreneurship Based on Big Data Analysis

Zhou

Wang

2021

Complexity

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College student entrepreneurship is a complex and dynamic process, in which the potential risks faced by entrepreneurial enterprises are interactive and diverse. The changes in risk assessment for college student entrepreneurship are also dynamic and nonlinear and are affected by many factors, which make the risk assessment process for college student entrepreneurship quite complicated. Big data analysis technology is a new product formed under the background of cloud computing and Internet technology, which has the characteristics of large data scale, multiple data types, and strong data value and provides more technical support for the researches on the risk assessment algorithm for college student entrepreneurship. On the basis of summarizing and analyzing previous research results, this article expounded the research status and significance of the risk assessment algorithm for college student entrepreneurship, elaborated the development background, current status, and future challenges of big data analysis technology, introduced the basic principles of support vector machine (SVM) and hierarchical analytic process, constructed a risk assessment model for college student entrepreneurship based on big data analysis, analyzed the risk factors and assessment indicators of the entrepreneurial model, proposed a risk assessment algorithm for college student entrepreneurship based on big data analysis, performed the discrimination coefficient calculation and comprehensive correlation optimization, and finally conducted a case experiment and its result analysis. The study results show that the risk assessment algorithm for college student entrepreneurship based on big data analysis can effectively realize the comprehensive management of risk factors, make full use of the value of assessment parameter data, and significantly improve the accuracy and efficiency of the risk assessment for college student entrepreneurship, providing more technical support for the researches on the risk assessment algorithm for college student entrepreneurship. The study results of this article provide a reference for further researches on the risk assessment algorithm of college student entrepreneurship based on big data analysis.

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Section: Results Analysismentioning

confidence: 99%

A Risk Assessment Algorithm for College Student Entrepreneurship Based on Big Data Analysis

Zhou

Wang

2021

Complexity

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“…TPB has been integrated with fuzzy logic to measure entrepreneurial interest in the Global Entrepreneurship Monitor (GEM) [16], a survey conducted on adult populations and experts to uncover the entrepreneurial potential of students based on the GEM entrepreneurship process model. In our previous studies, TPB integration with a fuzzy-based approach of the Multi-Attribute Decision Making (MADM) technique in education datasets have been used to map student entrepreneurial potential based on their academic activities [9]. Our studies have displayed that K-Means clustering and Fuzzy MADM produce consistent data interpretations with the GEM dataset.…”

Section: Related Workmentioning

confidence: 90%

“…We have used к-Мeans clustering to observe the behavior of student entrepreneurial potential patterns from an academic database using Simple Multi-Attribute Rating Technique (SMART) preprocessing [19]. Then, preliminary experiments with a defined TPB model have been performed to understand the relation between entrepreneurial potential and student attributes [9].…”

Section: Related Workmentioning

confidence: 99%

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A Rule-Generation Model for Class Imbalances to Detect Student Entrepreneurship Based on the Theory of Planned Behavior

Rijati

Purwitasar

Sumpeno

et al. 2022

Cybernetics and Information Technologies

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The ability to identify the entrepreneurial potential of students enables higher education institutions to contribute to the economic and social development of a country. Current research trends regarding the detection of student entrepreneurial potential have the greatest challenge in the unequal ratio of datasets. This study proposes a rule-generation model in an imbalanced situation to classify student entrepreneurship based on the Theory of Planned Behavior (TPB). The result is a ruleset that is used for the early detection of student entrepreneurial potential. The proposed method consists of three main stages, namely preprocessing data to classify data based on TPB variables, generating a dataset by clustering and selecting attributes by sampling to balance the data, and finally generating a ruleset. Furthermore, the results of the detecting ruleset have been evaluated with actual data from the student tracer study as ground truth. The evaluation results show high accuracy so that the ruleset can be applied to the higher education environment in the future.

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“…The same authors developed a new meta-heuristic called the Lagrangean Relaxation Granular Tabu Search (LRGTS) [7]. Many researchers use clustering methods to assign customers to depots, these technics create the clusters using similarity between the data [10].…”

Section: Introductionmentioning

confidence: 99%

An approach based on Clustering AH and VND for Supply Chain Management

Oudouar¹,

Zaoui²

2021

IJIES

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In this work, we present a new approach to solve the Capacitated Location-Routing Problem (CLRP). The aim of this method is to determine the depot locations, to assign customers to facilities and to define routes for each depot to serve the associated clients. The proposed approach contains two phases, which are the constructive phase and the improvement phase. In the first phase, we select the depots to be opened, allocate the customers to open depots using a Hierarchical Ascendant (HA) method and we solve the vehicle routing problem for each depot using Sweep algorithm. In the second phase, we apply a Variable Neighborhood Descent (VND) with three structures in order to optimize the cost obtained by the first phase. Two sets of well-known instances from the literature are used to evaluate the performance of this method, and the numerical results obtained are compared with the experimental results of other methods. Results show that our method is competitive with respect to the best-known solutions (BKSs) and demonstrate its efficiency in comparison with other approaches.

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A Decision Making and Clustering Method Integration based on the Theory of Planned Behavior for Student Entrepreneurial Potential Mapping in Indonesia

Cited by 8 publications

References 15 publications

A Risk Assessment Algorithm for College Student Entrepreneurship Based on Big Data Analysis

A Risk Assessment Algorithm for College Student Entrepreneurship Based on Big Data Analysis

A Rule-Generation Model for Class Imbalances to Detect Student Entrepreneurship Based on the Theory of Planned Behavior

An approach based on Clustering AH and VND for Supply Chain Management

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