The development of technology in education is increasing. One technology that is often used in education is big data. This research aims to analyze the factors that influence student performance in test scores. Big Data is a collection of very large and complex data that can be analyzed to reveal useful patterns. In this research, qualitative analysis methods are used to collect and analyze data from various sources, including national and international journals, academic publications, reports, and books. Data processing was conducted using the Kaggle Dataset with a data sample of 1000 students who have taken various exams. This research utilizes Big Data in predicting student performance based on parents' educational background, exam preparation courses, and students' lunch portion. The results show that the factor that affects student performance in exam scores is the student's lunch portion. The number of scores of female students with the appropriate meal portion on the Math, Reading, and Writing exams reached 22.413, 24.875, 24.890. The scores of male students with appropriate lunch portions on the Math, Reading, and Writing exams were 22.759, 21.342, and 20.701. Therefore, the conclusion of this research is that appropriate lunch portions play a crucial role in enhancing students' performance in exam results.
{"title":"IMPLEMENTASI PENGGUNAAN BIG DATA DALAM MENGANALISIS FAKTOR YANG MEMPENGARUHI KINERJA SISWA DALAM HASIL UJIAN","authors":"Irika Widiasanti, Jessica Triuli Adelia, Luthfia Rosidin, Maria Felicita Viola, Meyra Daniarista","doi":"10.34005/akademika.v12i01.2607","DOIUrl":"https://doi.org/10.34005/akademika.v12i01.2607","url":null,"abstract":"The development of technology in education is increasing. One technology that is often used in education is big data. This research aims to analyze the factors that influence student performance in test scores. Big Data is a collection of very large and complex data that can be analyzed to reveal useful patterns. In this research, qualitative analysis methods are used to collect and analyze data from various sources, including national and international journals, academic publications, reports, and books. Data processing was conducted using the Kaggle Dataset with a data sample of 1000 students who have taken various exams. This research utilizes Big Data in predicting student performance based on parents' educational background, exam preparation courses, and students' lunch portion. The results show that the factor that affects student performance in exam scores is the student's lunch portion. The number of scores of female students with the appropriate meal portion on the Math, Reading, and Writing exams reached 22.413, 24.875, 24.890. The scores of male students with appropriate lunch portions on the Math, Reading, and Writing exams were 22.759, 21.342, and 20.701. Therefore, the conclusion of this research is that appropriate lunch portions play a crucial role in enhancing students' performance in exam results.","PeriodicalId":486257,"journal":{"name":"Akademika : Jurnal Teknologi Pendidikan","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136064788","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-02DOI: 10.34005/akademika.v12i01.2459
Maria Ana Dwi, Afandi Afandi, Indri Astuti
Digital learning provides various benefits to students, from easy access to materials to giving assignments and quizzes. However, the use of digital learning is influenced by a teacher's decision to use it. Therefore, this factor becomes an obstacle in the transformation of digital learning. This study aims to evaluate the digital competence of teachers at SMKN 1 Kab. Sekadau This research was conducted to determine the awareness of SMK vocational subject teachers in Sekadau in using digital learning, this study analyzed six dimensions of Teacher Digital Competence Belief (TDCB). Data collection involved administering a questionnaire to 25 vocational subject teachers at SMK schools in Sekadau Regency. The results indicated that the average score
for the six TDCB dimensions was 71.28, falling into the "good" category. This suggests that vocational school teachers in Sekadau Regency recognize the importance of using digital technology in education
{"title":"KOMPETENSI DIGITAL GURU DALAM MENINGKATKAN MINAT BELAJAR SISWA SMK DI KABUPATEN SEKADAU","authors":"Maria Ana Dwi, Afandi Afandi, Indri Astuti","doi":"10.34005/akademika.v12i01.2459","DOIUrl":"https://doi.org/10.34005/akademika.v12i01.2459","url":null,"abstract":"Digital learning provides various benefits to students, from easy access to materials to giving assignments and quizzes. However, the use of digital learning is influenced by a teacher's decision to use it. Therefore, this factor becomes an obstacle in the transformation of digital learning. This study aims to evaluate the digital competence of teachers at SMKN 1 Kab. Sekadau This research was conducted to determine the awareness of SMK vocational subject teachers in Sekadau in using digital learning, this study analyzed six dimensions of Teacher Digital Competence Belief (TDCB). Data collection involved administering a questionnaire to 25 vocational subject teachers at SMK schools in Sekadau Regency. The results indicated that the average score
 for the six TDCB dimensions was 71.28, falling into the \"good\" category. This suggests that vocational school teachers in Sekadau Regency recognize the importance of using digital technology in education","PeriodicalId":486257,"journal":{"name":"Akademika : Jurnal Teknologi Pendidikan","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135772062","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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