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All Journal International Journal of Evaluation and Research in Education (IJERE) Indonesian Journal of Electrical Engineering and Computer Science
Omar Chamorro-Atalaya
Universidad Nacional Tecnológica de Lima Sur
Education

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Quadratic vector support machine algorithm, applied to prediction of university student satisfaction Omar Chamorro-Atalaya; Guillermo Morales-Romero; Yeferzon Meza-Chaupis; Elizabeth Auqui-Ramos; Jesús Ramos-Cruz; César León-Velarde; Irma Aybar-Bellido
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 1: July 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i1.pp139-148

Abstract

This study aims to identify the most optimal supervised learning algorithm to be applied to the prediction of satisfaction of university students. In this study, the IBM SPSS - 25.0 software was used to test the reliability of the satisfaction questionnaire and the MATLAB R2021b software through the classification learner technique to determine the supervised learning algorithm. The experimental results determine a Cronbach's Alpha reliability of 0.979, in terms of the classification algorithm, it is validate d that the quadratic vector support machine (SVM) has better performance metrics, being correct in 97.8% (a ccuracy) in the predictions of satisfaction of university students, with a r ecall (sensitivity) of 96.5% and an F1 score of 0.968. Likewise, when eva luating the classification model by means of the receiver operating characteristic curve (ROC) technique, it is identified that for the three expected classes of satisfaction the value of the area under the curve (AUC) is equal to 1, in such sense the pred ictive model through the SVM Quadratic algorithm, has a high capacity to distinguish between the 3 classes ; i) d issatisfied, ii) s atisfied and iii) v ery satisfied of satisfaction of university students.
Functionality of the learning platform and its effect on the satisfaction of students in the online teaching environment Omar Chamorro-Atalaya; Guillermo Morales-Romero; César León-Velarde; Lourdes Quevedo-Sánchez; Yurfa Medina-Bedón; Abel Tasayco-Jala; Maritte Fierro-Bravo
Indonesian Journal of Electrical Engineering and Computer Science Vol 26, No 2: May 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v26.i2.pp1073-1081

Abstract

The objective of this article is to identify the results of the functionality of the learning platform and its effect on the satisfaction of mechanical and electrical engineering students, the results will serve as a basis for the continuous improvement of teaching-learning online from the higher institution. The research findings indicate that the indicators that present a better perception regarding the functionality of the learning platform are related to the design and ease of navigation. However, 21.4% of the students are not entirely satisfied with its functionality due to the technical problems presented when downloading the study material. According to the results, we can point out that the functionality of the learning platform generates an effect of 70.87% on student satisfaction, the relationship was validated through the Chi-square test, in which it is determined that the indicators that generate a Greater satisfaction in students refers to the design, availability (connectivity) and the ease of communication and interaction with the teacher and classmates.
Collaborative learning through virtual tools: Analysis of the perception of student satisfaction of teaching performance Omar Chamorro-Atalaya; Belmira Marcelo-Veliz; Guillermo Morales-Romero; Nicéforo Trinidad-Loli; Darío Villar-Valenzuela; Beatriz Caycho-Salas; César León-Velarde
Indonesian Journal of Electrical Engineering and Computer Science Vol 26, No 2: May 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v26.i2.pp1082-1090

Abstract

The objective of this article is to identify the results of the evaluation of collaborative learning through technological tools as part of the pedagogical strategies in the virtual teaching process. For the evaluation, the SERVQUAL model was used, through which it was identified that 97.73% satisfactorily evaluate the reliability and security of pedagogical strategies through technological tools used in collaborative learning in the teaching process in virtual environments. The optimal evaluation regarding the reliability of collaborative learning is 100% related to compliance with the syllable, to the teacher's disposition to help them in the use of technological tools and to the conformity of the technological tools used in the subject. Regarding the security of collaborative learning, 100% of the satisfactory evaluation is related to the trust and kindness that the teacher transmitted with the use of technological tools in teaching in virtual environments.
Teaching through virtual tools and its effect on the perception of student satisfaction Omar Chamorro-Atalaya; Guillermo Morales-Romero; Adrián Quispe-Andía; Darío Villar-Valenzuela; Alicia Jeri-Sandoval; César León-Velarde; Irma Aybar-Bellido
Indonesian Journal of Electrical Engineering and Computer Science Vol 26, No 3: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v26.i3.pp1599-1606

Abstract

In this context of virtualization, the educational sector has seen the need to make use of technological advances, for this reason it is important to know the perception of students, after having fully adapted distance learning through tools. virtual, which have allowed teachers and students to maintain the pedagogical link at a distance, either through the virtual classroom or through the use of simulation software. In this sense, the objective of this article is to identify the perception of teaching through virtual tools in university students and determine its level of effect or relationship in student satisfaction. This research is approached from a qualitative approach using the Likert measurement method and a content analysis methodology using virtual instruments. The results of the study indicate that 92.9% and 89.3% of the students are satisfied, these results focus on the indicators "absolves the questions asked regarding the use of virtual tools" and "knowledge shown by the teacher in the development of the sessions through virtual tools”. Likewise, the correlational analysis, through Spearman's Chi square test, establishes that there is a high relationship or significant effect of 0.850 between the perception of teaching through virtual tools with student satisfaction.
Vector support machine algorithm applied to the improvement of satisfaction levels in the acquisition of professional skills Omar Chamorro-Atalaya; Orlando Ortega-Galicio; Guillermo Morales-Romero; Darío Villar-Valenzuela; Yeferzon Meza-Chaupis; César León-Velarde; Lourdes Quevedo-Sánchez
Indonesian Journal of Electrical Engineering and Computer Science Vol 26, No 1: April 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v26.i1.pp597-604

Abstract

The study carried out identifies the metricss of the predictive model obtained through the support vector machine (VSM) algorithm, which will be applied in the satisfaction of the acquisition of professional skills of the students of the Professional Engineering Career. As part of the development, the statistical classification tool is used, during the development of the research, it was identified that the predictive model presents as general metrics an accuracy of 82.1%, a precision of 70.72%, a sensitivity of 91.06% and a specificity of 87.60%. Through this model, it contributes significantly to decision-making in relation to improving satisfaction related to the acquisition of professional skills in engineering students, since decision-making by university authorities will have a scientific basis, to take early and timely actions in relation to the predictive elements.
Sentiment analysis through twitter as a mechanism for assessing university satisfaction Omar Chamorro-Atalaya; Dora Arce-Santillan; Guillermo Morales-Romero; César León-Velarde; Primitiva Ramos-Salaza; Elizabeth Auqui-Ramos; Miguel Levano-Stella
Indonesian Journal of Electrical Engineering and Computer Science Vol 28, No 1: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v28.i1.pp430-440

Abstract

Currently, the data generated in the university environment related to the perception of satisfaction is generated through surveys with categorical response questions defined on a Likert scale, with factors already defined to be evaluated, applied once per academic semester, which generates very biased information. This leads us to wonder why this survey is applied only once and why it only asks about some factors. The objective of the article is to demonstrate the feasibility of a proposal to determine the degree of perception of student satisfaction through the use of data science and natural language processing (NLP), supported by the social network twitter, as an element of data collection. As a result of the application of this proposal based on data science, it was possible to determine the level of student satisfaction, being 57.27%, through sentiment analysis using the Python library "NLTK"; Thus, it was also possible to extract texts linked to the relevant factors of teaching performance to achieve student satisfaction, through the term frequency and inverse document frequency (TF-IDF) approach, these being those linked to the use of tools of simulation in the virtual learning process.
Automated drainage system for thermoelectric power plant Max Melgarejo-Jara; Omar Chamorro-Atalaya; Florcita Aldana-Trejo; Nestor Alvarado-Bravo; José Farfán-Aguilar; Erika Zevallos-Vera; Evelyn Anicama-Navarrete
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 3: March 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i3.pp1393-1401

Abstract

The Chilca 2 thermoelectric power plant, located in the province of Lima, Peru, has an open cycle gas turbine and a combined cycle steam turbine, whose combined capacity is 112.8 MW (Mega Watts). This plant requires auxiliary equipment for its operation, which is why it consists of electrical systems, lubrication system, hydraulic ventilation, pumps, vacuum systems and drainage of condensate generated by the difference in temperature in the steam conductor. Said drainage system is inside a 5-meter-deep basement that, being exposed to the elements, is exposed to falling drops of water that are generated by the vapors that are released due to the difference in temperature, repeatedly flooding and exposing to hazards that affect the normal operation of the thermoelectric plant. The proposed solution is based on the philosophy of a feedback control system, which uses a programmable logic controller (PLC) Siemens 1214AC/DC/Relay programmable logic controller, which, through a frequency inverter, activates the drainage pumps; the frequency range at which the variator works is linked to a 4-position level sensor. The result shows that it was possible to activate the frequency variator in a controlled manner through frequencies of 10 Hz, 30 Hz and 60 Hz, in this way a sustained operation of the drainage system is guaranteed.
Supervised learning through k-nearest neighbor, used in the prediction of university teaching performance Omar Chamorro-Atalaya; Nestor Alvarado-Bravo; Florcita Aldana-Trejo; Claudia Poma-Garcia; Carlos Aliaga-Valdez; Gutember Peralta-Eugenio; Abel Tasayco-Jala
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 3: September 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i3.pp1625-1634

Abstract

This study initially seeks to identify the most optimal supervised learning algorithm to be used in predicting the perception of teacher performance, and then to evaluate its performance indicators that validate its predictive capacity. For this, the Matlab R2021a software is used; the experimental results determine that the supervised learning algorithm K-Nearest Neighbor Weighted (Weighted KNN) will be correct in 98.10% in predicting the perception of teaching performance, this has been validated by carrying out two evaluations through its performance indicators obtained in the confusion matrix and the receiver operating characteristic (ROC) curve, in the first evaluation an average sensitivity of 97.9%, a specificity of 99.1%, an accuracy of 98.8% and a precision of 96.7% are observed, thus validating the ability of the Weighted KNN model to correctly predict the perception of teacher performance; while in the receiver operating characteristic (ROC) curve, values of the area under the curve (AUC) equal to 0.99 and 1 are obtained, with this it is possible to validate the capacity that the model will have to distinguish between the 4 classes of the perception of the university teaching performance.
Supervised learning using support vector machine applied to sentiment analysis of teacher performance satisfaction Omar Chamorro-Atalaya; Dora Arce-Santillan; José Antonio Arévalo-Tuesta; Lilia Rodas-Camacho; Ronald Fernando Dávila-Laguna; Rufino Alejos-Ipanaque; Lilly Rocío Moreno-Chinchay
Indonesian Journal of Electrical Engineering and Computer Science Vol 28, No 1: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v28.i1.pp516-524

Abstract

Satisfaction with teaching performance is an important measurement process in higher education institutions, for this reason, applying sentiment analysis to the opinions of university students through the support vector machine (SVM) Fine Gaussian supervised learning algorithm represents an important contribution to the academic literature. This article identifies the best classification algorithm according to performance parameters for predicting student satisfaction with teaching performance through sentiment analysis; the subsequent implementation of the research has the purpose of strengthening teaching practices, in addition to allowing continuous training of teaching for the benefit of student learning. This article has provided a compact predictive model, with literature review based on SVM and sentiment analysis techniques. Through the machine learning classification learner technique, it is identified that the SVM algorithm: Fine Gaussian SVM is the one with the best accuracy equal to 98.3%. Likewise, the performance metrics for the four classes of the model were identified, which have a sensitivity equal to 88.89%, a specificity of 98.04%, a precision of 99.21% and an accuracy of 98.85%.
Automation and electrical control of a mortising machine with 12 synchronous perforations in the manufacture of stairs Daniel López-Borjas; Omar Chamorro-Atalaya; Florcita Aldana-Trejo; Vidalina Chaccara-Contreras; Nestor Alvarado-Bravo; Erika Zevallos-Vera; Evelyn Anicama-Navarrete
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 3: March 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i3.pp1364-1373

Abstract

With the constant technological development, industries have been incorporating technologies into their manufacturing processes, which generate benefits in the productive field. In the manufacturing process of wooden stairs, the faults of the products, generates that an adequate homogeneity is not achieved, often because the manual operation is carried out without having established parameters in the handling of the mortiser. In this sense, the present article develops an automatism and electrical control of a 12 synchronous perforation mortiser, in order to improve the productivity of the perforation stage in the manufacture of wooden stairs. As part of the development, the electrical, pneumatic and mechanical control system is carried out using Autodesk Inventor software, while the KOP programming is carried out in Tía Portal V14 with connection to S7 PLCSIM V14 using the programmable logic controller (PLC) 1214C. Once the automation has been implemented, a reduction in the processing time per wooden strip of 74.68% is obtained. Likewise, with the automatic process, it is possible to produce 2,460 units of slats, that is, the monthly production increases by 294.9%, in other words, the productivity is 58 units of slats manufactured per hour.
Co-Authors Abel Tasayco-Jala Abel Tasayco-Jala Ademar Vargas-Díaz Adrián Quispe-Andía Alicia Jeri-Sandoval Beatriz Caycho-Salas Belmira Marcelo-Veliz Carlos Aliaga-Valdez César León-Velarde César León-Velarde Claudia Poma-Garcia Daniel López-Borjas Darío Villar-Valenzuela Dora Arce-Santillan Elizabeth Auqui-Ramos Elizabeth Auqui-Ramos Erika Zevallos-Vera Evelyn Anicama-Navarrete Florcita Aldana-Trejo Genaro Sandoval-Nizama Guillermo Morales-Romero Guillermo Morales-Romero Gutember Peralta-Eugenio Irma Aybar-Bellido Irma Aybar-Bellido Jesús Ramos-Cruz José Antonio Arévalo-Tuesta José Farfán-Aguilar Lilia Rodas-Camacho Lilly Rocío Moreno-Chinchay Lisle Sobrino-Chunga Lourdes Quevedo-Sánchez Maritte Fierro-Bravo Max Melgarejo-Jara Miguel Levano-Stella Nestor Alvarado-Bravo Nicéforo Trinidad-Loli Orlando Ortega-Galicio Primitiva Ramos-Salaza Risley Rengifo-Tello Ronald Fernando Dávila-Laguna Rosa Valle-Chavez Rosemary Guerrero-Carranza Rufino Alejos-Ipanaque Teresa Guía-Altamirano Vidalina Chaccara-Contreras Yadit Rocca-Carvajal Yeferzon Meza-Chaupis Yeferzon Meza-Chaupis Yurfa Medina-Bedón