Introduction. Music is one of the areas of expertise and skills existing in vocational schools in Indonesia, where students must master music in theory and practice. Due to the COVID-19 pandemic, music teachers are encouraged to design alternative learning methods in order to facilitate the students to learn music. This challenges the music teachers to provide interesting and well-delivered material during online learning since the teachers of vocational education have to adapt quickly and prepare the students to be ready in facing the today’s challenges. In addition, the use of information and communication technology in teaching and performing music is growing rapidly, thus, the music teachers must master computer technology to address the complexities of today’s music industry, and support the music learning process in theory and practice. The heutagogical approach is believed to be an innovative and trending approach to be applied in the music learning process, since it can adapt to the current changing times. It can also assist teachers to guide music theory and practice, develop and deliver direction and discussion through technology assistance with learning materials agreed in the classroom.The aim of this article is to analyse the application of a heutagogical approach that focuses on improving learning, overall learning opportunities, and developing independent skills with technology assistance on music subjects in vocational schools in Bandung (West Java, Indonesia).Methodology and research methods. This research employs grounded theory method by providing explicit analytical strategies with the ultimate goal of obtaining theories about certain processes, actions, or interactions that come from the teacher’s point of view in teaching music in vocational schools.Results and scientific novelty. It was found that teaching processes with heutagogical approach tend to be student-centred, enabling students to learn independently through self-determination, since it is the real implementation of student-centred educational theory that can help students hone skills and metacognition and reflect their own learning experience faster.Practical significance. The current research aims at helping students studying music in vocational schools to apply self-determined learning, hence they can determine what to learn, how to learn it, when to learn, and where to get information to achieve the learning objectives.Thus, students can decide when the best time to study music, explore their musical knowledge, and practice their music skills. In addition, students can be trained to design music lessons, build space patterns and learning opportunities, and develop themselves individually; hence that they can be responsible for the learning objectives they designed for themselves. As for the teachers, they can play their role as a guide and facilitator who can direct students in achieving their learning objectives.
Determination of recipients of the Non-Cash Food Assistance Program (BPNT) is a matter that causes problems if it is not carried out in an objective, transparent, and targeted manner. Previous studies on BPNT were based on a specific method, which did not use a negative trend in the criteria. In this study, the Multi-Criteria Decision Making (MCDM) approach was used to recommend the recipients of the BPNT program. Two MCDM models were used in this study, COPRAS and CODAS methods. Spearman's rank correlation method was used to determine the best model and measure the degree of similarity between the results obtained from different models. Spearman rank correlation shows that COPRAS and CODAS have a strong positive correlation of 0.89899. The combined COPRAS-CODAS ranking model produces a very strong positive correlation value of 0.9744 for both methods, so the model is used for recommendations for BPNT program recipients.
<p>Bantuan Langsung Tunai Dana Desa (BLT-DD), or known as Village Fund Direct Cash Assistance is assistance from the Indonesian government which causes problems and conflicts in the community when the assistance is not on target. The classification algorithm is proven to use in determining BLT-DD recipients. In this study, the radial basis function (RBF) and elman recurrent neural network (ERNN) models compare to classify the eligibility of BLTDD recipients. In the experiment, the optimal performance of the RBF and ERNN compare in determining the eligibility of BLT-DD recipients. Also, it’s compared with the classification algorithm that implements the same data, namely BLT-DD data for Kubu Raya District. The experimental results show the effectiveness of the RBF model in recognizing test data, while the ERNN model is effective in identifying test data. The RBF and ERNN models can achieve the same total accuracy of 98.10%.</p>
This conceptual framework of piano etudes is arranged in accordance with the phenomena that occur today, that there are still many students which study piano both in music schools and in international standard music courses in Indonesia, not sensitive to the musical sense of Indonesian traditional music, especially Sundanese. This is due to the lack of piano teaching materials based on Sundanese scale. In addition, the tendency of children, even teenagers and adults, are less interested in learning traditional music. In fact, Sundanese music has its own uniqueness that can be seen in its musical instrument, namely gamelan degung, laras or scales, and structure of degung music which is different from other gamelan. Therefore, this study using piano to introduce the scales of degung and some piece that are designed so the students can understand the tune that resembles degung which is adapted to the Western music approach. It is because students tend to find it easier to learn the piece with media conventional music background, one of them is the piano. This research used a literature review analysis that produces a conceptual framework to develop the piano etudes based on degung scale. From the result of the research, four ideas of piano etudes were produces, each of which has different levels of difficulty.
Purpose: Cervical cancer is one of the most common types of cancer that kills women worldwide. One way for early detection of cervical cancer risk is by looking at human behavior determinants. Detection of cervical cancer based on behavior determinants has been researched before using Naïve Bayes and Logistic Regression but has never using ADALINE Neural Network. Methods: In this paper, ADALINE proposes to detect early cervical cancer based on the behavior on the UCI dataset. The data used are 72 data, consisting of 21 cervical cancer patients and 51 non-cervical cancer patients. The dataset is divided 70% for training data and 30% for testing data. The learning parameters used are maximum epoch, learning rate, and MSE. Result: MSE generated from ADALINE training process is 0.02 using a learning rate of 0.006 with a maximum epoch of 19. Twenty-two test data obtained an accuracy of 95.5%, and overall data got an accuracy value of 97.2%. Novelty: One alternative method for early detection of cervical cancer based on behavior is ADALINE Neural Network.
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