scholarly journals Data Similarity Filtering of Wartegg Personality Test Result using Cosine-Similarity

2018 ◽  
Vol 6 (3) ◽  
pp. 19
Author(s):  
Rosihan Ari Yuana ◽  
Dewanto Harjunowibowo ◽  
Nugraha Arif Karyanta ◽  
Cucuk Wawan Budiyanto
Keyword(s):  
Graphical Representation ◽  
Cosine Similarity ◽  
Potential Contribution ◽  
Personality Test ◽  
Evaluation Instrument ◽  
Technical Procedure ◽  
Data Similarity ◽  
Identification Technique ◽  
Similarity Method ◽  
The Ideal

Wartegg test is a widely adopted personality evaluation instrument known for its drawing completion technique.  Employee personality data, for instance, can be sorted by the closest similarity with the expected characters. Whereas, Wartegg test plays a significant role in data similarity filtering. Despite the potential contribution of personal characters identification technique, practical guidance is rarely found in the literature. This paper demonstrates the usage of cosine-similarity method for data similarity filtering on Wartegg personality test. The method used in this study is a case study, in which will be selected several Wartegg test subjects. By using the value of each character aspect derived from the Wartegg test, the cosine-similarity value will be calculated against the expected/ideal aspect character. Based on this value, the Wartegg test subjects will be filtered based on similarity to the expected/ideal character aspects. A technical procedure to perform the method is also presented in this paper. In order to find out the effectiveness, sample data scores of each character aspect from five test subjects, and also the ideal scores of the expected characters are given. By using FWAT, a graphical representation of the test subjects' characters to the ideal characters is generated. Then, this graph was compared to the results obtained from the cosine-similarity method. Drawn from the results, the cosine-similarity is effectively applied for Wartegg test data similarity filtering.

scholarly journals Some Similarity and Distance Measures between Complex Interval-Valued q-Rung Orthopair Fuzzy Sets Based on Cosine Function and their Applications

2021 ◽  
Vol 2021 ◽  
pp. 1-25
Author(s):  
Harish Garg ◽  
Zeeshan Ali ◽  
Tahir Mahmood ◽  
Sultan Aljahdali
Keyword(s):  
Decision Making ◽  
Solution Method ◽  
Similarity Measures ◽  
Cosine Similarity ◽  
Distance Measures ◽  
Uncertain Information ◽  
Cosine Similarity Measures ◽  
Complex Valued ◽  
Interval Valued ◽  
The Ideal

The purpose of this paper is to present a new method to solve the decision-making algorithm based on the cosine similarity and distance measures by utilizing the uncertain and vague information. A complex interval-valued q-rung orthopair fuzzy set (CIVQROFS) is a reliable and competent technique for handling the uncertain information with the help of the complex-valued membership grades. To address the degree of discrimination between the pairs of the sets, cosine similarity measures (CSMs) and distance measures (DMs) are an accomplished technique. Driven by these, in this manuscript, we defined some CSMs and DMs for the pairs of CIVQROFSs and investigated their several properties. Choosing that the CSMs do not justify the axiom of the similarity measure (SM), then we investigate a technique to developing other CIVQROFSs-based SMs using the explored CSMs and Euclidean DMs, and it fulfills the axiom of the SMs. In addition, we find the cosine DMs (CDMs) by considering the inter-relationship between the SM and DMs; then, we have modified the procedure for the rank of partiality by similarity to the ideal solution method for the CDMs under investigation, which can deal with the associated decision-making problems not only individually from the argument of the opinion of geometry but also the fact of the opinion of algebra. Finally, we provide a numerical example to demonstrate the practicality and effectiveness of the proposed procedure, which is also in line with existing procedures. Graphical representations of the measures developed are also used in this manuscript.

Assessing the Validity of the Semantic Differential Portion of the Apperceptive Personality Test

2001 ◽  
Vol 88 (3_suppl) ◽  
pp. 1235-1244 ◽  
Author(s):  
David J. Palmiter ◽  
David E. Silber
Keyword(s):  
Discriminant Analysis ◽  
Social Desirability ◽  
Semantic Differential ◽  
Personality Test ◽  
Ideal Self ◽  
Social Desirability Scale ◽  
Strong Negative Correlation ◽  
Discriminant Analyses ◽  
The Difference ◽  
The Ideal

This study investigated the validity of the semantic differential portion of the Apperceptive Personality Test with 225 undergraduates who completed the Marlowe-Crowne Social Desirability scale, actual-self and ideal-self semantic differential scales (e.g., Actual-self and Ideal-self), and either the Apperceptive Personality Test or a modified version. A projected-self score was calculated using the semantic differential ratings of the hero(ine) character on the test, e.g., Projected-self. A strong negative correlation indicated that, as the difference between the Ideal-self and Actual-self decreased, the difference between the Actual-self and Projected-self increased. Discriminant analyses indicated that highly guarded participants, e.g., high Social Desirability scores, showed more congruency between Ideal-self and Actual-self and less congruency between Actual-self ratings and Projected-self on the APT than did less guarded participants. When the difference scores incorporated only those semantic differential items that loaded on an Evaluative factor, the same result of discriminant analysis was found when participants who completed the modified version were included. These findings support the validity of the test's semantic differential items and suggest that guardedness tends to promote more similarity between Actual-self and Ideal-self and less similarity between Actual-self and Projected-self.

Positive Psychology in SLA

2017 ◽  
Vol 40 (2) ◽  
pp. 108-120 ◽  
Author(s):  
Sarah Mercer
Keyword(s):  
Positive Psychology ◽  
Language Learning ◽  
Language Learners ◽  
Language Teaching ◽  
Language Education ◽  
Psychological Wellbeing ◽  
Potential Contribution ◽  
Positive Education ◽  
Specific Approach ◽  
The Ideal

Abstract This article begins with an outline of the developments in Positive Psychology (PP) generally and specifically within SLA focusing on theoretical, empirical and practical developments. It moves on to consider PP’s potential contribution to language teaching focusing on how it can help promote emotional, social and psychological wellbeing for language learners and teachers. It explores the concept of ‘Positive Education’ and reflects on possible lessons from these broader developments for a specific approach to ‘Positive Language Education’. It is argued that PP facilitates new ways of thinking about language learning and can provide the ideal vehicle from which to foreground wellbeing as a concept and dual aim in language education.

scholarly journals Recites fidelity detection system of al-Kautsar verse based on words using mel frequency cepstrum coefficients and cosine similarity

2019 ◽  
Vol 8 (1) ◽  
pp. 27-35
Author(s):  
Jans Hendry ◽  
Aditya Rachman ◽  
Dodi Zulherman
Keyword(s):  
Feature Extraction ◽  
Word Recognition ◽  
Test Data ◽  
Extraction Method ◽  
Detection System ◽  
Test Word ◽  
Word Segmentation ◽  
Cosine Similarity ◽  
Feature Extraction Method ◽  
Similarity Method

In this study, a system has been developed to help detect the accuracy of the reading of the Koran in the Surah Al-Kautsar based on the accuracy of the number and pronunciation of words in one complete surah. This system is very dependent on the accuracy of word segmentation based on envelope signals. The feature extraction method used was Mel Frequency Cepstrum Coefficients (MFCC), while the Cosine Similarity method was used to detect the accuracy of the reading. From 60 data, 30 data were used for training, while the rest were for testing. From each of the 30 training and test data, 15 data were correct readings, and 15 other data were incorrect readings. System accuracy was measured by word-for-word recognition, which results in 100 % of recall and 98.96 % of precision for the training word data, and 100 % of recall and 99.65 % of precision for the test word data. For the overall reading of the surah, there were 15 correct readings and 14 incorrect readings that were recognized correctly.

scholarly journals Aplikasi Pendeteksi Plagiasi pada Universitas Indo Global Mandiri Berbasis Web

2019 ◽  
Vol 10 (2) ◽  
Author(s):  
Dhamayanti Dhamayanti ◽  
Lidia Permata Sari
Keyword(s):  
Information Systems ◽  
Cosine Similarity ◽  
Plagiarism Detection ◽  
Original Source ◽  
Final Project ◽  
Processing And Storage ◽  
And Storage ◽  
Popular Texts ◽  
Similarity Method ◽  
Student Thesis

<p align="center"><strong>ABSTRACT</strong><em></em></p><p><em>Thesis is a final project that must be taken by students to complete their studies at the Indo Global Mandiri University in Palembang. Thesis data processing and storage, especially in the Information Systems department is still done conventionally, so checking the similarity of the title even the contents of the student thesis is difficult to detect. Difficulties in detecting the title and content of the thesis cause students to easily and freely plagiarize the proposal preparation and thesis report from beginning to end without being known by the lecturer and the Information System department. Plagiarism is the act of a shortcut that steals ideas, takes the work, and recognizes the work of others as their own without including references from the original source. This research will discuss the problem of plagiarism in the Information Systems department through making applications that can detect the plagiarism of titles and contents of the thesis especially in the information systems department so as to overcome the plagiarism problems faced by the information systems department. This plagiarism detection application is built using the cosine similarity method</em><em>. </em><em>Cosine similarity is a method for calculating similarity (level of similarity) between two object. In testing the similarity of documents with the results of the study, cosine similarity has a higher degree of accuracy. Cosine similarity is used to calculate the similarity value by equating said words and become one of the techniques to measure the similarity of popular texts. Plagiarism detection application using cosine similarity method which is implemented with PHP and MySQL as the database can help efforts to reduce the occurrence of plagiarism in the title and contents of the thesis in the Information Systems department.</em></p><pre> </pre><p><em> </em></p><pre><strong><em>Keywords :</em></strong><em> </em><em>P</em><em>lagiarism</em><em>, </em><em>P</em><em>lagiarism </em><em>D</em><em>etection </em><em>A</em><em>pplication</em>, <em>Cosine Similarity, PHP</em></pre><p align="center"><strong>ABSTRAK</strong></p><p><em>Skripsi merupakan tugas akhir yang wajib ditempuh mahasiswa untuk menyelesaikan studi di Universitas Indo Global Mandiri Palembang</em><em>.</em><em> Pengolahan dan penyimpanan data skripsi  khususnya pada program studi Sistem Informasi masih dilakukan secara konvensional, sehingga pengecekan kemiripan judul bahkan isi skripsi mahasiswa sulit untuk dideteksi. Kesulitan pendeteksian judul dan isi skripsi menyebabkan mahasiswa dengan mudah dan bebas melakukan plagiasi pada pembuatan proposal maupun laporan skripsi dari awal hingga akhir tanpa diketahui oleh dosen dan pihak program studi. Plagiasi merupakan tindakan sebuah jalan pintas yang mencuri ide, mengambil hasil karya, dan mengakui hasil karya orang lain sebagai miliknya sendiri tanpa mencantumkan referensi dari sumber aslinya.</em><em> </em><em>Penelitian ini akan membahas permasalahan plagiasi pada program studi Sistem Informasi melalui pembuatan aplikasi yang dapat mendeteksi plagiasi judul dan isi skripsi khusunya pada program studi </em><em>sistem informasi sehingga dapat mengatasi permasalahan plagiasi yang dihadapi oleh program studi sistem informasi. Aplikasi pendeteksi plagiasi ini dibagun  dengan menggunakan metode cosine similarity. Cosine similarity adalah metode untuk menghitung similarity (tingkat kesamaan) antar dua buah objek. Pada pengujian kesamaan dokumen dengan hasil penelitian menunjukkan cosine similarity memiliki tingkat akurasi yang lebih tinggi. Cosine similarity digunakan untuk menghitung nilai kemiripan dengan menyamakan kata perkata dan menjadi salah satu teknik untuk mengukur kemiripan teks yang popular.</em><em> </em><em>Aplikasi pendeteksi plagiasi dengan menggunakan metode </em><em>cosine similarity yang diimplemntasikan dengan PHP dan MySQL sebagai databasenya dapat membantu upaya mengurangi terjadinya plagisi pada judul dan isi skripsi di program studi Sistem Informasi.</em></p><strong><em>Kata kunci</em></strong><em> : Plagiasi, Aplikasi Pendeteksi Plagiasi, Cosine Similarity, PHP</em>

scholarly journals Prediction of E-Commerce Product Ratings Based on Similar Users

2021 ◽  
Vol 10 (6) ◽  
pp. 25347-25351
Author(s):  
Shashank Pola ◽  
Venkatesh M ◽  
Ravi Chandra Reddy K ◽  
Indira Priyadarsini P
Keyword(s):  
High Efficiency ◽  
Cosine Similarity ◽  
The Internet ◽  
Huge Amount ◽  
Simple Manner ◽  
User Expertise ◽  
Primary Key ◽  
Item Scores ◽  
Product Ratings ◽  
Similarity Method

Together with the fast advancement of continuous expansion and the Internet of E-commerce scope, product quantity, as well as assortment, boost fast. Merchants offer many goods via going shopping customers and websites generally consider a huge amount of moment to discover the products of theirs.Within e-commerce sites, the item rating is among the primary key ingredients of an excellent pc user expertise. Many methods are working with whose users to consider the goods they wish. A comparable item suggestion is among the favorite modes working with whose customers look for items in line with the item scores. In general, the suggestions aren't personalized to a particular pc user. Exploring a great deal of solutions tends to make customers runoff as a result of the info clog but not offering proper reviews for solutions.Traditional algorithms has data sparsity and cold start issues. To overcome these problems we use cosine similarity method to identify the similarity between those vectors. The nearest similar vector ratings will be used during the estimation of the unknown ratings.The proposed methodology records ratings of each product from users and those are represented by a vector, and the cosine similarity is used a measure to identify the similarity between those vectors. The nearest similar vector ratings will be used during the estimation of the unknown ratings.Hence, By using the above approach it can overcome the above problems and also it can achieve high efficiency and accuracy in a simple manner.

scholarly journals Analisis Metode Cosine Similarity Pada Aplikasi Ujian Online Otomatis (Studi Kasus JTI POLINEMA)

2021 ◽  
Vol 8 (2) ◽  
pp. 343
Author(s):  
Eka Larasati Amalia ◽  
Angelita Justien Jumadi ◽  
Irsyad Arif Mashudi ◽  
Dimas Wahyu Wibowo
Keyword(s):  
Cosine Similarity ◽  
Term Frequency ◽  
Long Time ◽  
E Learning ◽  
Exam System ◽  
Similarity Method ◽  
Learning Concept ◽  
Word Frequencies ◽  
F Measure

<p>Dalam konsep <em>e-learning</em> pelaksanaan ujian dilakukan secara online salah satunya ujian esai. Ujian esai online merupakan ujian yang menggunakan metode online dan mewajibkan siswa menjawab dengan kalimat mereka sendiri. Namun, dalam ujian esai online ini memerlukan waktu yang lama untuk mengoreksi jawaban jika dikerjakan secara manual. Agar tidak memakan banyak waktu untuk mengoreksi jawaban siswa maka dalam sistem terdapat penilaian kemiripan jawaban untuk penilaian. Pada penelitian ini dilakukan pembuatan sistem ujian esai online dengan penilaian kemiripan jawaban menggunakan metode <em>Cosine Similarity</em> dan persamaan <em>Term Frequency</em> (TF) untuk menyamakan frekuensi setiap kata yang terdapat dalam kalimat. Suatu faktor yang menentukan bobot kata berdasarkan pada jumlah frekuensi kata dalam sebuah dokumen disebut dengan<em> Term Frequency</em>. Untuk pengujian akurasi metode dilakukan pengujian <em>precision, recall</em>, dan <em>f-measure</em> dan berdasarkan hasil analisis dengan menggunakan metode yang telah dicoba diperoleh rata-rata 81%.</p><p> </p><p><em>Abstract</em></p><p> </p><p><em>In the e-learning concept, the implementation of exams is carried out online, one of which is an essay exam. The online essay exam is an exam that uses an online method and requires students to answer in their own sentences. However, in this online essay exam, it takes a long time to correct answers if done manually. In order not to take a lot of time to correct student answers, the system has an assessment of the similarity of answers for the assessment. In this study, an online essay exam system was made with the similarity of answers using the Cosine Similarity method and the Term Frequency (TF) equation to equalize the frequency of each word contained in a sentence. Term Frequency is a factor that determines word weight based on the number of word frequencies in a document. To test the accuracy of the method, precision, recall, and f-measure tests were carried out and based on the results of the analysis using the method that had been tried, an average of 81% was obtained.</em></p>

scholarly journals Product Codefication Accuracy With Cosine Similarity And Weighted Term Frequency And Inverse Document Frequency (TF-IDF)

2021 ◽  
Vol 2 (2) ◽  
pp. 62-69
Author(s):  
Sintia Sintia ◽  
Sarjon Defit ◽  
Gunadi Widi Nurcahyo
Keyword(s):  
Information System ◽  
Cosine Similarity ◽  
Search Process ◽  
Inverse Document Frequency ◽  
Term Frequency ◽  
Product Code ◽  
Document Frequency ◽  
Similarity Method

In the SiPaGa application, the codefication search process is still inaccurate, so OPD often make mistakes in choosing goods codes. So we need Cosine Similarity and TF-IDF methods that can improve the accuracy of the search. Cosine Similarity is a method for calculating similarity by using keywords from the code of goods. Term Frequency and Inverse Document (TFIDF) is a way to give weight to a one-word relationship (term). The purpose of this research is to improve the accuracy of the search for goods codification. Codification of goods processed in this study were 14,417 data sourced from the Goods and Price Planning Information System (SiPaGa) application database. The search keywords were processed using the Cosine Similarity method to see the similarities and using TF-IDF to calculate the weighting. This research produces the calculation of cosine similarity and TF-IDF weighting and is expected to be applied to the SiPaGa application so that the search process on the SiPaGa application is more accurate than before. By using the cosine sismilarity algorithm and TF-IDF, it is hoped that it can improve the accuracy of the search for product codification. So that OPD can choose the product code as desired

Modeling Effects of Faking on an Objective Personality Test

2011 ◽  
Vol 32 (4) ◽  
pp. 210-218 ◽  
Author(s):  
Martin Arendasy ◽  
Markus Sommer ◽  
Margit Herle ◽  
Bettina Schützhofer ◽  
Dagmar Inwanschitz
Keyword(s):  
Item Response ◽  
Test Scores ◽  
Latent Trait ◽  
Personality Test ◽  
Personality Tests ◽  
Naturally Occurring ◽  
Subject Design ◽  
Personality Questionnaires ◽  
Clear Description ◽  
The Ideal

The article investigated the effect of faking on the dimensionality and mean scores of an objective personality test measuring subjectively accepted level of risk. Various studies conducted with standardized personality questionnaires have demonstrated that faking may distort both the dimensionality and mean scores. In contrast, the empirical evidence on the effect of faking on the dimensionality and mean scores obtained with objective personality tests is still sparse. In the first study, we evaluated the effect of naturally occurring faking on the dimensionality and mean scores using a between-subject design that compared professional driver applicants to volunteers matched according to relevant sociodemographic characteristics. The results indicated that the objective personality test measures the same latent trait in both samples. Furthermore, we failed to observe a significant mean difference between volunteers and professional driver applicants. Furthermore, we failed to observe any mean score differences between both samples. The second study experimentally evaluated the effect of individual differences in respondents’ ability to infer the ideal level of the latent trait on the dimensionality and mean scores using a combined between- and within-subject design. Using modern item response theory techniques we found that a less clear description of the ideal level of the latent trait prevented a successful faking attempt. In contrast, a more clear and less difficult to implement a description of the ideal level of the latent trait allowed respondents to successfully increase their test scores. The results are discussed in light of current models of applicants response processes when working personality tests.

Sign in / Sign up

Export Citation Format

Share Document