PENGEMBANGAN E-MODUL BERBASIS DISCOVERY LEARNING PADA PEMBELAJARAN TEMATIK TEMA 6 SUBTEMA 1 HEWAN DI SEKITAR KU SD KELAS II

This study aims to produce an E-Module based on discovery learning in thematic learning of theme 6 sub-theme 1 for class II SD which is valid and practical and to determine the potential effects of development. This research is included in research and development, referring to the development of ADDIE. The research took place at SDN 199 Palembang. The research subjects were 24 second grade elementary school students. Data collection was carried out by means of a media and language expert validation questionnaire, material expert, mathematics teacher questionnaire, student response questionnaire, and student test result data. The data were analyzed quantitatively and qualitatively. The results showed that the validation of the validators got an average validation score of 88.66% with a valid category. The results of student responses based on trials got an average score of 91.58% in the practical category. The results of the test questions distributed to 24 students contained 21 students who completed and 3 students did not complete, the average student score was 84.50% in the very good category or had a potential effect on student learning outcomes. Keywords: E-Module, ADDIE, Discovery Learning, Thematic Theme 6 Sub-theme 1

Development of Learning Devices Using Creative Problem Solving (CPS) Models on Static Electricity Material

The learning tools developed are science learning tools using creative problem solving models on static electricity material in the ninth grade of junior high school, in the form of lesson plans, student worksheet and test instruments. The purpose of this research is to produce science learning products with creative problem solving models that are valid and suitable for use in school. The data analysis technique in this study used descriptive analysis, by calculating the validation score for each assessment indicator. The results showed that the value of the validity of science learning tools using creative problem solving models was declared valid with an overall average score of 4.44 very valid categories. Likewise, the empirical validity of the test instrument obtained valid results for each item and was reliable at a value of 0.844 in the high category

Virtual Physics Laboratory with Real World Problem Based on Ngada Local Wisdom in Basic Physics Practicum

This research is based on the problem where practical activities in the Basic Physics Practicum course can no longer be carried out optimally due to changes in the learning model from face-to-face (offline) to online (online) during the COVID-19 pandemic. The purpose of this study was to develop a virtual physics laboratory as a medium in carrying out practical activities and to analyze the feasibility of the product through the validation results of experts and the results of product trials on prospective users. This type of research is Research & Development with ADDIE development model. The subjects of this study were 12 lecturers and 47 students of the STKIP Citra Bakti science education study program. Data collection techniques using validation sheets and questionnaires. The data collection instruments are in the form of validation assessment sheets and response questionnaires of prospective users. The data from this study were analyzed qualitatively descriptive to decide the feasibility of the product being developed. The results of the research showed that the average validation score of the material expert was 4.63, the media expert was 4.41, the learning design expert was 4.30, and the linguist was 4.51. The validation results of the four validators are in the very good category. Meanwhile, the results of product trials to lecturers and students as potential users are in the very good category with an average score of 4.53 and 4.57, respectively. Based on these data, this virtual physics laboratory product with real world problems based on Ngada local wisdom is recommended to be applied to the Basic Physics Practicum course and to help students in their independent practicum activities.

Irrationality of Attitudes toward Safety under Complexity and Uncertainty Leading to Asymmetry of Information

This study investigated how complexity and uncertainty, the probability of accidents, and the probability of financial trouble affected individuals’ recognition of validity of irrational risk-seeking decisions. As a result of conducting a multiple regression analysis on the validation score for irrational risk-seeking alternative obtained by a questionnaire survey, we found that the validity score for an irrational risk-seeking alternative was higher when both complexity and uncertainty were high than when both complexity and uncertainty were low, which means that high complexity and high uncertainty in the situation of decision making more readily leads to an irrational risk-seeking behavior that might trigger a major accident. Beyond complexity and uncertainty, the damage of major accident α, the decrease of the probability of major accidents and the increase of the probability of financial trouble (economic factor) were also found to promote the choice of irrational risk-seeking alternatives. Some implications for safety management under high complexity and uncertainty are discussed.

Pengembangan Modul Elektronik Menulis Teks Tanggapan Berbasis LMS Moodle dengan Muatan Ekoliterasi untuk Kelas 9

This research purposed to produce a Moodle module based ecoliteracy for 9th grade. This study used five methods, (1) preliminary analysis, (2) product development, (3) expert validation and revision, (4) small-scale field trials and revision, and (5) large scale product trial. This research produces a Moodle module with ecoliteracy in its content and presentation which has been validated by material, media, and language expert with certain qualifications. This study result is suitable product that get validation score 87.5% for material, 92.5% for media, and 70.5% for language. The result from small field trials is 75%, and 87.5% for large field trials, the product declared as suitable to use. This study ecoliteracy in the module content is contained in its themes, learning objectivities, materials, exercise, and cases that students must responses. Ecoliteracy in the module presentation is include in text, images, audios, and videos.

DEVELOPMENT OF SELF-REFLECTION INSTRUMENTS OF RIAS LEARNING MODEL IN STUDENTS OF ENVIRONMENTAL EDUCATION COURSE

<span class="fontstyle0">It is necessary to measure student spiritual and social attitudes to find out their attitude development in students ofenvironmental education course. The research aims to develop instruments utilized in measuring student spiritual and social attitudes in RIAS (Reading, Identification, Analysis, and Self-reflection) learning model implementation. Theresearch procedures consist of 1) needs analysis and literature study; 2) instrument design; 3) instrument development; 4) expert assessment; 5) instrument revision; and 6) instrument dissemination. The research instruments utilized include content validity sheets and construct validity instruments with assessment scale score of 1-4 consisting of (1) not feasible; (2) less feasible; (3) feasible; and (4) very feasible. The research results indicate that 1) the instruments of<br />spiritual and social attitudes measurement in the RIAS learning model implementation are feasible to be utilized in measuring student spiritual and social attitudes. It is indicated by validation score of 3.8 and 2) further research and development includes portfolio development to measure spiritual and social attitudes. The research implications become a practical reference for teachers and lecturers in measuring spiritual and social attitudes in learning.</span>

DEVELOPING RELIGIOUS BASED HOTS ASSESMENT BOOK IN SCIENCE SUBJECT TO INCREASE TEACHERS’ COMPETENCE IN DESIGNING HOTS ASSESSMENT AT ELEMENTARY SCHOOL

The purpose of this study was to determine: 1) the development of a religious-based HOTS assessment book; 2) the effectiveness of the book to improve teachers’ competence in preparing religious-based HOTS assessments for grade 4 elementary school in science subject content. This research was a development research (RnD) adapted from Borg and Gall development model with the following procedures: 1) Identification of Potentials and Problems; 2) Data Collection; 3) Product Design; 4) Design Validation; 5) Product Revision I; 6) Product Trial; 7) Product Revision II; 8). Trial Use; 9) Revision of the End Product; and 10) Product Dissemination. The product of this research was religious based HOTS assessment book in science subject content for grade IV SD. The feasibility of the book was shown through validation (material and media testing) by two material and media experts, getting an average validation score of 80.49 with very good category. The effectiveness of using books was proven by the t test which obtained t count = -9.892 < t table = 1.72 so that Ha was accepted. The conclusion of this study was religious-based HOTS assessment book increased teachers’ competence in compiling HOTS assessments at elementary schools. Suggestions in this study included that teachers should use this HOTS-based assessment book to improve their competence in HOTS assessments.

Potential of Rule-Based Methods and Deep Learning Architectures for ECG Diagnostics

The main objective of this study is to propose relatively simple techniques for the automatic diagnosis of electrocardiogram (ECG) signals based on a classical rule-based method and a convolutional deep learning architecture. The validation task was performed in the framework of the PhysioNet/Computing in Cardiology Challenge 2020, where seven databases consisting of 66,361 recordings with 12-lead ECGs were considered for training, validation and test sets. A total of 24 different diagnostic classes are considered in the entire training set. The rule-based method uses morphological and time-frequency ECG descriptors that are defined for each diagnostic label. These rules are extracted from the knowledge base of a cardiologist or from a textbook, with no direct learning procedure in the first phase, whereas a refinement was tested in the second phase. The deep learning method considers both raw ECG and median beat signals. These data are processed via continuous wavelet transform analysis, obtaining a time-frequency domain representation, with the generation of specific images (ECG scalograms). These images are then used for the training of a convolutional neural network based on GoogLeNet topology for ECG diagnostic classification. Cross-validation evaluation was performed for testing purposes. A total of 217 teams submitted 1395 algorithms during the Challenge. The diagnostic accuracy of our algorithm produced a challenge validation score of 0.325 (CPU time = 35 min) for the rule-based method, and a 0.426 (CPU time = 1664 min) for the deep learning method, which resulted in our team attaining 12th place in the competition.

Application of a Machine Learning Algorithms in a Wrist-Wearable Sensor for Patient Health Monitoring during Autonomous Hospital Bed Transport

Smart sensors, coupled with artificial intelligence (AI)-enabled remote automated monitoring (RAMs), can free a nurse from the task of in-person patient monitoring during the transportation process of patients between different wards in hospital settings. Automation of hospital beds using advanced robotics and sensors has been a growing trend exacerbated by the COVID crisis. In this exploratory study, a polynomial regression (PR) machine learning (ML) RAM algorithm based on a Dreyfusian descriptor for immediate wellbeing monitoring was proposed for the autonomous hospital bed transport (AHBT) application. This method was preferred over several other AI algorithm for its simplicity and quick computation. The algorithm quantified historical data using supervised photoplethysmography (PPG) data for 5 min just before the start of the autonomous journey, referred as pre-journey (PJ) dataset. During the transport process, the algorithm continued to quantify immediate measurements using non-overlapping sets of 30 PPG waveforms, referred as in-journey (IJ) dataset. In combination, this algorithm provided a binary decision condition that determined if AHBT should continue its journey to destination by checking the degree of polynomial (DoP) between PJ and IJ. Wrist PPG was used as algorithm’s monitoring parameter. PPG data was collected simultaneously from both wrists of 35 subjects, aged 21 and above in postures mimicking that in AHBT and were given full freedom of upper limb and wrist movement. It was observed that the top goodness-of-fit which indicated potentials for high data accountability had 0.2 to 0.6 cross validation score mean (CVSM) occurring at 8th to 10th DoP for PJ datasets and 0.967 to 0.994 CVSM at 9th to 10th DoP for IJ datasets. CVSM was a reliable metric to pick out the best PJ and IJ DoPs. Central tendency analysis showed that coinciding DoP distributions between PJ and IJ datasets, peaking at 8th DoP, was the precursor to high algorithm stability. Mean algorithm efficacy was 0.20 as our proposed algorithm was able to pick out all signals from a conscious subject having full freedom of movement. This efficacy was acceptable as a first ML proof of concept for AHBT. There was no observable difference between subjects’ left and right wrists.

Development of Mixed Learning Media (MLM) Assisted by Student Worksheet on The Topic of The Effect of Molarity on Light Index

The purpose of this study was to develop mixed learning media (MLM) and test the feasibility of learning media. The study was conducted using the research and development method which refers to the ADDIE model with four main steps, analysis, design, development, and implementation. The instrument used is a questionnaire consisting of a learning media questionnaire, student worksheet questionnaire, and student response questionnaire. Respondents in this study were 4 eleventh grade students. The results showed the feasibility of learning media with a score of 92.5%; in the aspect of serving by 93.3%; on the aspect of the feasibility of the content of 91.6%; on the language aspect by 91.5%; 95.8% on the concept and task aspects. Based on the results of the validation score, the student worksheet was declared very valid. Based on the results of student questionnaire data, an average score of 94.9%. The results showed that the learning media were valid and practical to use for virtual experiments.