Bencoolen Journal of Science Education and Technology

Development of E-Module Concerning The Effect of Solid Lipid Nanoparticle on Blood Glucose Mus musculus to Improve Students' Critical Thinking Skills

2020-10-18T11:45:55+00:00

This study aims to develop an electronic module of teaching material supplements on the effect of solid lipid nanoparticle kebiul extract on blood glucose of Mus musculus to improve critical thinking skills of undergraduate students of Chemistry Education, Faculty of Teacher Training and Education University of Bengkulu. This type of research is Research and Development (R&D) based on the ADDIE model (Analysis, Design, Development, Implementation, and Evaluation). The research was conducted by analyzing student needs for the development of e-module teaching material supplements and continued at the validation stage. The result of the validation of the 3D PageFlip Professional e-module was 89.78% in the very suitable category for use as a teaching material supplement. The validation of the test instrument for critical thinking was 88% with a very valid category and could be tested on students. The N-Gain result data was 0.68 in the medium category, so that the e-module developed is able to improve students' critical thinking skills. The result of the assessment on the student response questionnaire has a score of 89.8% with a very good category and can be disseminated online.

In-Situ Conservation of Siebenrockiella crassicollis to develop the Psycomotors and Environmental Awareness of Students

2021-12-10T04:10:44+00:00

This research aims to study the weight growth, eyes and neck health of S. crasiicollis in the conservation areas of SMAN (High School) Sukakarya and Balong Swamp, Sukakarya District, Musi Rawas Regency, South Sumatra Province. Data collection was carried out by means of observation for 8 weeks in the conservation areas of SMAN Sukakarya and Balong Swamp. The research results showed that the average weight growth of S. crassicollis for eight weeks was seen from the sex. Male S. crassicollis (ABP tagging code) grew 6.25 grams and female S. crassicollis (ACI tagging code) 1.37 grams. Whereas, in the Balong swamp the average body weight growth of S crassicollis for eight weeks was also seen from the sex. Male S. crassicollis (AHJ tagging code) grew 4.62 grams in weight and female S. crassicollis (ABQ tagging code) at 4.00 grams. Eye and neck health in both locations showed that all S. crassicollis eyes were clean, there was no dirt, clear glow and wide open and the neck was erected and looked up with very good / healthy criteria. Biotic components found were pandanus water, algae, ferns and grasses. Animals found include small fish, small shrimp, and water snails. While the abiotic component results of the environmental temperature measurement, and water temperature range from 27⁰C to 32⁰C, the pH of water between 6.5 to7. Based on observations, it can be concluded that the tortoise's body weight has increased and decreased according to the nature of the tortoise's body weight which is reversible, the eyes and neck health of the S. crassicollis shows very good results, where the healthy tortoise's eyes can be seen from clear, non-dirty eyes, wide open and not swollen, while the healthy neck can be seen from frequent lifting of the neck / looking up.

Expert System In Predicting COVID-19 Using Certainty Factor Method

2021-12-10T04:17:28+00:00

During this pandemic, the people of Mukomuko Regency, Bengkulu Province are having problems knowing whether they have the common cold or COVID-19 because the symptoms of COVID-19 are similar to the common cold. Meanwhile, visiting the hospital requires a fee which causes some people to be unable to carry out further examinations. With these conditions, it is difficult to make early predictions of COVID-19. Therefore, the researcher made a system that can predict the possibility of contracting someone with an artificial intelligence concept by using the certainty factor method. The design of this application is quite simple so that it is easy for users to use. The users simply click the "consultation" button and select the symptoms they are experiencing and their conditions. Then the system will calculate what percentage of the user is likely to be exposed to COVID-19.