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All Journal International Journal of Evaluation and Research in Education (IJERE) Jurnal Biogenerasi JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Journal of Multidisciplinary Applied Natural Science Bulletin of Information Technology (BIT) EXPLORER Jurnal Pengabdian Masyarakat Gemilang (JPMG) Journal of Scientific Research, Education, and Technology Buletin Ilmiah Informatika Teknologi Prosiding Seminar Nasional Unimus Management of Information System Journal International Conferences On Early Childhood Education Proceedings
Andi Ernawati
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Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Energy Engineering Environmental Science Health Professions Immunology & microbiology Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mathematics Mechanical Engineering Nursing Physics Public Health Social Sciences Other

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Gambaran Konsep Diri pada Klien Gangren Diabetik di Klinik Spesialis Luka Diabetes Diahel Kota Makassar - Idris; Andi Ernawati; Muhammad Arif Mansur; Salki Sasmita
Prosiding Seminar Nasional Unimus Vol 4 (2021): Inovasi Riset dan Pengabdian Masyarakat Post Pandemi Covid-19 Menuju Indonesia Tangguh
Publisher : Universitas Muhammadiyah Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Komplikasi ulkus diabetikum dapat menimbulkan efek pada konsep diri penderita diabetesmellitus. Derajat IV dan V ulkus diabetikum ditadai dengan adanya gangren. Penelitian ini bertujuanuntuk mengetahui gambaran konsep diri pada klien gangren diabetik di klinik spesialis luka diabetesDiahel kota Makassar. Penelitian ini merupakan jenis penelitian kuantitatif dengan menggunakanrancangan penelitian deskriptif. Metode pengambilan sampel menggunakan tehnik accidentalsampling yang berjumlah 5 responden. Alat ukur berupa kuesioner. Pada penelitian ini diperolehbahwa dari keseluruhan responden tersebut memiliki konsep diri yang positif yaitu 5 responden(100%). Seluruh responden tersebut juga memiliki komponen konsep diri yakni citra tubuh, ideal diri,harga diri, identitas diri, dan peran diri yang masing-masing positif (100%). Kata Kunci : konsep diri, gangren, diabetes mellitus.
SCHOOL STAGE IMPLEMENTATION IN DEVELOPING EARLY CHILDREN'S PERFORMING ARTS CREATIVITY Andi Ernawati; Cucum Sumiati; Buton Buton; Mia Sumiani Madi; Durrotul Muniroh Ahdaniyah
International Conferences on Early Childhood Education Proceedings Vol 1 No 2 (2023): International Conference on Early Childhood Proceeding
Publisher : Universitas Panca Sakti Bekasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51714/icec.v1i2.153

Abstract

Performing arts creativity has an important role in the holistic development of early childhood. The implementation of the TV Sekolah stage in schools has been recognized as an effective approach to facilitating the development of early childhood performing arts creativity. The purpose of this research is to explore the implementation of the school stage in developing early childhood performing arts creativity. This study uses a qualitative descriptive method involving participatory observation, interviews, and document analysis. Research participants consisted of early childhood, educators, and parents who were involved in the School TV Sekolah stage program. The results of the study show that the implementation of the School TV Sekolah stage makes a positive contribution in developing early childhood performing arts creativity. Through the TV Sekolah school stage, children have the opportunity to express themselves, hone their performing arts skills, and broaden their knowledge of art and culture.
Pemanfaatan Teknologi Virtual Reality (VR) Dalam Pembelajaran Pada Lembaga Kursus Dan Pelatihan Rumah Tik Labuhanbatu Ernawati, Andi; Sitorus, Zulham; Wijaya, Rian Farta; Aulia, Ananda; Siregar, Andree Risky Yuliansyah; Sofyan, Siti Nurhaliza
Jurnal Pengabdian Masyarakat Gemilang (JPMG) Vol. 4 No. 1 (2024): Januari 2024
Publisher : HIMPUNAN DOSEN GEMILANG INDONESIA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58369/jpmg.v4i1.152

Abstract

Learning using technology continues to develop along with developments in technology itself. One technology that is increasingly being used in learning is virtual reality (VR). Virtual Reality is a technology that produces a digital environment that resembles the real world and allows users to interact with that environment. Including in Labuhanbatu Regency, where virtual reality media has been used as a learning medium. However, if we observe that the use of virtual reality as a learning medium has not been distributed thoroughly to every level of student, only the student level can access learning using virtual reality. And if we look more deeply, the virtual reality media content that is presented is able to improve the quality of student learning for each level because virtual reality media will really help improve the imagination and mindset of students at all levels to become more effective and efficient. In Labuhanbatu Regency there are many course and training institutions, judging from the area and the number of course and training institutions in Labuhanbatu Regency, the introduction of virtual reality learning media in Labuhanbatu Regency should be managed generally for all levels of students as a basis for community service activities (PKM). . This activity aims to provide training to students in Labuhanbatu Regency about learning methods using virtual reality technology through videos on cellphones using the Millea Lab Viewer application and VR Player with a virtual box device. Activities carried out focus on introducing and training virtual reality for learning. The methods used include training for students at all levels at the Labuhanbatu Tik House course and training institution regarding the features and concepts of virtual reality, the goals, benefits and practices of using virtual reality. After attending the training, students at the Tik Labuhabatu home course and training institution experienced an increase in their knowledge about virtual reality, as well as their ability to improve the quality and creative imagination in learning virtual reality media content in Labuhanbatu Regency Keywords: virtual reality; learning; content, lkprumahtik, Labuhanbatu
Implementasi Sistem Pendukung Keputusan dalam menentukan Kecamatan Terbaik Menggunakan Algoritma Entropy dan Additive Ratio Assessment (ARAS) Ernawati, Andi; Ofta Sari, Ayu; Sofyan, Siti Nurhaliza; Aulia, Ananda; Sitorus, Zulham; Khairul
Bulletin of Information Technology (BIT) Vol 4 No 4: Desember 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v4i4.1066

Abstract

In the context of regional development and decision making related to determining the best village, the use of a Decision Support System (DSS) with the application of the Entropy and Additive Ratio Assessment (ARAS) algorithms is a very important approach. The main objective of this research is to propose and implement a method that utilizes the Entropy algorithm to evaluate criteria weights and ARAS to rank villages based on predetermined criteria. This approach begins the process by identifying relevant criteria to determine the best village in an area. Next, the Entropy algorithm is used to measure the level of importance or relative weight of each predetermined criterion. This step helps in assessing how informative each criterion is in the decision-making process regarding determining the best Village. After determining the criteria weights using Entropy, the approach continues with the application of the ARAS method. ARAS is used to rank villages based on normalized values ​​from previously determined criteria. The data normalization process is carried out to ensure the validity of comparisons between villages. The final result of this approach is a ranking of villages indicating the best villages based on the criteria considered. This method was tested in a case study using a dataset involving a number of relevant criteria for assessing village development potential. Experimental results show that the use of the Entropy and ARAS algorithms in the Decision Support System provides an effective and informative framework for decision makers in determining the best Village. In conclusion, this approach provides a solid foundation to support a more effective and precise decision-making process in regional development based on clearly defined criteria.
Implementasi Algoritma Naïve Bayes dalam Menganalisis Sentimen Review Pengguna Tokopedia pada Produk Kesehatan Ernawati, Andi; Sari, Ayu Ofta; Sofyan, Siti Nurhaliza; Iqbal, Muhammad; Wijaya, Rian Farta Wijaya
Bulletin of Information Technology (BIT) Vol 4 No 4: Desember 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v4i4.1090

Abstract

It must be realized that customer satisfaction is the main goal for companies in developing their business. Because customers' opinions written on social media will have a big influence on the company and potential customers. In its development, it is increasingly found in various online media, one of which is Tokopedia. Product reviews are an important source of information regarding quality, service and delivery from both consumers and manufacturers. With a very large amount of data for each product on Tokopedia, analyzing and concluding product review information will definitely take a lot of time if done manually. To overcome this, a sentiment analysis system is needed that can automatically extract important information that can objectively determine product quality and handle large amounts of textual information. The sentiment analysis system consists of several stages, namely crawling, pre-processing, word weighting, and sentiment classification. By applying the Naïve Bayes algorithm through selecting range and frequency features, accuracy, accuracy and recall results will be obtained using the Confusion Matrix test. The dataset used is from the kaggle.com site regarding customer sentiment on health products with the type of mask. using the Naïve Bayes Algorithm Method to determine the sentiment of user reviews by classifying 2 positive and negative classes using the NLP approach produces an accuracy value of 88%.
Application of The Odonga Ronga Kolopua Folklore to The Character of Group B Children at The Pembina Wundulako State Kindergarten Ernawati, Andi; Puridawaty , Brigita
Journal of Scientific Research, Education, and Technology (JSRET) Vol. 3 No. 2 (2024): Vol. 3 No. 2 2024
Publisher : Kirana Publisher (KNPub)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58526/jsret.v3i2.401

Abstract

This research aims to analyze the influence of the application of the Odonga Ronga Kolopua folklore on the character of group B children at the Pembina Wundulako State Kindergarten. The research method used was an experiment with a pretest-posttest design. The research population was all group B students at the Pembina Wundulako State Kindergarten, totaling 30 students, with a sample of 10 students using a purposive sampling technique. Data collection was carried out through observation sheets and checklists. Data analysis was carried out using SPSS 24 and paired sample t-test. The results of the research show that there is a significant influence of the application of the Odonga Ronga Kolopua folklore on the character of group B children, with a significance value (sig) of 0.002. The implication of this research is the importance of using local folklore in early childhood education to strengthen cultural identity and build sensitivity to traditional values. The suggestion put forward is that PAUD teachers and parents can utilize the Odonga Ronga Kolopua folklore in children's learning activities, and further research can explore the impact of the story on other aspects of children's development such as creativity and language skills.
EFEKTIVITAS ANTIBAKTERI EKSTRAK DAUN TEH HIJAU TERHADAP BAKTERI MYCOBACTERIUM TUBERCULOSIS Misnarliah; Ernawati, Andi
Jurnal Biogenerasi Vol. 10 No. 1 (2024): Volume 10 Nomor 1, Agustus 2024 - Februari 2025
Publisher : Universitas Cokroaminoto Palopo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30605/biogenerasi.v10i1.4431

Abstract

Tuberculosis is still a global health problem. Prolonged treatment of tuberculosis and using several anti-tuberculosis drugs (OAT) can cause side effects, one of which is multidrug resistance. Cases of multidrug-resistant (MDR) and extensively drug-resistant (XDR) Mycobacterium strains continue to increase. . Research and development of active compounds from medicinal plants to achieve more effective tuberculosis treatment is still being promoted. This research aims to determine the potential and effectiveness of green tea plant (Camellia sinensis) leaf extract in inhibiting the growth of Mycobacterium tuberculosis strain H37Rv bacteria using the LJ (Lowenstein-Jensen) method in vitro. The research samples used were green tea plant leaves (Camellia sinensis) obtained from the Malino Village Tea Plantation, Tinggi Moncong Regency, Gowa District, South Sulawesi. The leaf extract was made in 4 types of concentrations, namely 10, 20, 50 and 100 µg/ml, each of which was tested against the clinical isolate of Mycobacterium tuberculosis strain H37Rv using the LJ (Lowenstein-Jensen) method as the standard for tuberculosis examination. Of the four extracts tested in vitro, only extract concentrations of 50 and 100 µg/ml were able to very strongly inhibit and kill the growth of Mycobacterium tuberculosis strain H37Rv (inhibition percentage of 100%), not a single bacterial colony growth was found during the observation period. The percentage of inhibition of green tea plant leaves (Camellia sinensis) is the same as the percentage of inhibition of the drug rifampicin. Thus, the leaves of the green tea plant (Camellia sinensis) with concentrations of 50 and 100 µg/ml have potential antituberculosis activity and are prospective to be developed as antituberculosis from natural ingredients, and also as an additional therapeutic complement for TB.
Komparasi Kinerja Algoritma Random Forest dan C4.5 untuk Klasifikasi Harga Mobil Ernawati, Andi; Karim, Abdul
Buletin Ilmiah Informatika Teknologi Vol. 3 No. 1: September 2024
Publisher : AMIK STIEKOM SUMATERA UTARA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58369/biit.v3i1.95

Abstract

Determining car prices is a crucial aspect of the automotive industry that requires accurate data analysis for strategic decision-making. This study aims to compare the performance of the Random Forest and C4.5 algorithms in classifying car prices based on specific features, such as technical specifications, production year, and market conditions. The dataset used in this study consists of [mention the size and source of the dataset if available], analyzed using a cross-validation approach to ensure the accuracy of the results. The performance of both algorithms is evaluated based on several metrics, including accuracy, precision, recall, and F1-score. The results show that the Random Forest algorithm consistently outperforms the C4.5 algorithm across most evaluation metrics, achieving an accuracy of [best Random Forest accuracy] compared to [best C4.5 accuracy]. These findings indicate that the Random Forest algorithm is more effective in handling multivariate data complexity and providing more reliable predictions. The conclusions of this study highlight the potential of Random Forest as the primary method for car price classification, especially in scenarios requiring high accuracy levels. This research also contributes to a comparative understanding of decision-tree-based algorithms for applications in the automotive industry and opens opportunities for further research into developing more adaptive and efficient models.
Analisis Perbandingan Algoritma Klasifikasi Data Mining untuk Penentuan Lokasi Perumahan Ernawati, Andi; Iqbal, Muhammad
Journal of Information System Research (JOSH) Vol 6 No 2 (2025): January 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v6i2.6516

Abstract

This study aims to analyze the application of C5.0 and K-Nearest Neighbor (K-NN) algorithms in the classification process for determining the optimal location for housing. The classification process involves several factors such as land price, accessibility, public facilities, crime rate, infrastructure, land availability, and consumer preferences. The research conducted tests on both algorithms to compare their performance in generating accurate predictions. The results show that the C5.0 algorithm outperforms K-NN, achieving an accuracy rate of 100%, compared to K-NN, which achieved an accuracy of 66.67%. This demonstrates that C5.0 is more effective in modeling data and producing more precise classifications. Therefore, it can be concluded that the use of data mining algorithms, particularly C5.0, greatly assists in the classification process for determining housing locations, providing more optimal results compared to K-NN.
Penerapan Data Mining Untuk Klasifikasi Penduduk Miskin Di Kabupaten Labuhanbatu Menggunakan Random Forest Dan K-Nearest Neighbors Ernawati, Andi; Khairul; Sitorus, Zulham; Iqbal, Muhammad; Nasution, Darmeli
Bulletin of Information Technology (BIT) Vol 6 No 2: Juni 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v6i1.1783

Abstract

This study aims to apply and compare the performance of two data mining algorithms—Random Forest (RF) and K-Nearest Neighbors (KNN)—in classifying poverty status among residents of Labuhanbatu Regency. The dataset includes information on occupation, income, housing, and education from 21,137 individuals. After undergoing preprocessing, model training, hyperparameter optimization, and evaluation, both models were assessed using five key metrics: accuracy, precision, recall, F1-score, and AUC. The results show that Random Forest performed slightly better than KNN, achieving an accuracy of 0.6023, precision of 0.4827, recall of 0.4177, F1-score of 0.4479, and an AUC of 0.5681. In comparison, KNN obtained an accuracy of 0.5990, precision of 0.4771, recall of 0.4006, F1-score of 0.4355, and an AUC of 0.5622. Based on these findings, it can be concluded that Random Forest is more effective for poverty classification on this dataset, although the performance difference is relatively small.
Co-Authors - Idris Abdul Karim Ahmad Johari B. Sihes Alam, Sitti Nur Aris Tri Wahyudi Arridha Zikra Syah Aulia, Ananda Buton Buton Cucum Sumiati Darmeli Nasution Durrotul Muniroh Ahdaniyah Idris Idris Iman Rusmana Iwan Purnama Khairul Mia sumiani Madi Misnarliah Mohd. Anuar B. Abdul Rahman Muhammad Arif Mansur Muhammad Iqbal Ofta Sari, Ayu Parini Puridawaty , Brigita Rolly Yesputra Salki Sasmita Sari, Ayu Ofta Siregar, Andree Risky Yuliansyah Sitorus, Zulham Sofyan, Siti Nurhaliza Sri Budiarti Poerwanto sri murtini . Sugeng Santoso Syahruddin Lasadike Wijaya, Rian Farta Wijaya, Rian Farta Wijaya