Total Dissolved Solids (TDS) and turbidity of water are parameters to determine the quality of water. In this research, instruments development and study of accuracy level for TDS meter and turbidimeter have been made. Instruments were made using TDS sensor and turbidity sensor that were inexpensive and available on the market. The samples used for instruments examination were water with dye (Rhodamine B) and powder of coffee as impurities. The results showed that the sensors worked properly and provided a better accuracy in measuring water samples with coffee impurities than dye impurities. The inaccuracy on the determination of water samples with dye impurities due to dye particles which have soluble properties on water and microscopic size than particles of coffee.
Education has a very important role in educating the life of the nation. Education should not only give birth to someone who is an expert in a particular field, but also includes how someone is able to bring themselves in a community, nation and state environment in accordance with applicable norms and rules. Therefore, the character of responsibility and attitude towards subjects is very important for every individual. However, education that is happening at this time still does not provide space for students to behave honestly because the learning process tends to teach moral education and character limited to the knowledge written in the text. Therefore this study was designed to see how the relationship between attitude and student responsibility towards science subjects especially junior high students. This study is a mix of correlational type associative method research. The procedure of this study began by following the procedure in stages. In the preparation stage, it is done by formulating the problem and its variables. Then a literature review is conducted, looking for supporting theories and deepening the discussion of the problem under study in order to obtain an overview of the research to be carried out as well as the instruments needed. At the stage of questionnaire data questionnaire data collection was given to 136 students in Adhyaksa 1 Junior High School, Jambi City. From the data, data analysis is then carried out, namely data coding, proper data collection and analysis of the data. The data analysis technique uses correlational tests to find out whether there is a relationship between attitude and responsibility. The results of this study indicate a relationship between attitude and responsibility with a Pearson Correlation value of 0.000 0.05 so that it can be concluded that there is a relationship between attitude and responsibility in Adhyaksa 1 Junior High School, Jambi City
The purpose of this study was to describe the process skills of Muaro Jambi Senior High School 8 students on temperature and heat material. The research used in this study is research that uses research methods that use research This research. The sample used in this study was the students of Muaro Jambi High School 8, which collected 96 students of Class XI MIPA 1 to XI MIPA 3 odd semester 2019/2020. Data collection techniques in this study were observation and interviews. The results of observations of students' mastery of process skills in the material practicum of temperature and heat (change in form) showed a percentage of 55.2% classified in the bad category. I hope students have a low process. Low student learning process. Student-oriented learning process material.
Bean seed classification is critical in determining the quality of beans. Previously, the same dataset was tested using the MLP, SVM, KNN, and DT algorithms, with SVM producing the best results. The purpose of this study is to determine the most effective model through the use of the BoxCox transformation selection feature and the random forest (RF) algorithm, as well as the gradient boosting machine (GBM), light GBM, and repeated k-folds evaluation model. The bean dataset is available on the UCI Repository website. The BoxCox transformation and repeated k-folds improved the classification prediction's accuracy. The model is used in the optimal training phase for a random forest with decision tree parameters 50 and depth 10, a gradient boosting machine model with a learning rate of 1, and a light gradient boosting machine model with a learning rate of 0.5 and estimator of 500. The best training accuracy results are obtained with light GBM. which is 99 percent accurate, but only 91 percent accurate in terms of validation. According research, the Barbunya, Bombay, Cali, Dermason, Horoz, Seker, and Sira beans classes provided accuracy values of 91 percent, 100 percent, 92 percent, 92 percent, 95 percent, 94 percent, and 84 percent, respectively.
This study aimed to determine the effects of the generative learning model for learning temperature and heat on science learning outcomes. This study was quasi-experimental research and used a non-equivalent control group design involving control and treatment groups. This research investigated class seven Islamic Junior High School students in Jambi Province, Indonesia. Random cluster sampling was used to select the control and treatment classes. The data were collected by the science learning outcomes test with the pretest and posttest. The data were analyzed using a t-test. The results of the t-test showed tcount= 2.74 > ttable with a significance level of 5%. Therefore, the H0 is rejected. The generative learning model significantly affected students' science learning outcomes when discussing temperature and heat. The science learning outcomes of the treatment class were higher than those of the control class.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.