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IMPLEMENTATION OF E-LEARNING USING THE MOODLE Melyanti, Rika; Febriani, Anita
Jurnal Pendidikan Teknologi Kejuruan Vol 4 No 3 (2021): Regular Issue
Publisher : Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/jptk.v4i3.17223

STAI Tuanku Tambusai Pasir Pangaraian is a high school for Islamic religious education, which in the Teaching and Learning Process (PBM) is currently trying to apply the concept of blended learning by using e-learning. The purpose of this research is to build a Learning Management System (LMS) that can assist lecturers and students in conducting PBM with the help of computer technology. This is felt to have become a necessity during the pandemic and industrial revolution 4.0, STAI should have an e-larning that is able to answer challenges. The online learning system service architecture (e-learning) can be used as an appropriate design in the development of learning methods where the level of flexibility, scalability and functionality can make PBM easier to do anywhere and anytime. The designed online learning system (e-learning) at STAI Tuanku Tambusai is used by two actors, namely students and lecturers.

Improved Hybrid Machine and Deep Learning Model for Optimization of Smart Egg Incubator Febriani, Anita; Wahyuni, Refni; Mardeni, Mardeni; Irawan, Yuda; Melyanti, Rika
Journal of Applied Data Sciences Vol 5, No 3: SEPTEMBER 2024
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v5i3.304

This research develops a Smart Egg Incubator that integrates IoT technology, fuzzy logic, and the YOLOv9-S Deep Learning model to enhance the efficiency and accuracy of hatching chicken eggs. The system automatically regulates temperature and humidity, maintaining temperature between 34.3°C and 39.5°C and humidity between 57% and 68% with a fuzzy logic success rate of 90%. The YOLOv9-S model enables realtime chick detection and classification with mAP50 of 93.7% and mAP50:95 of 71.3%. Efficiency improvements are measured through the success rate of fuzzy logic and improved detection and classification accuracy. This research also uses CNN for high-accuracy object classification, with model optimization performed using SGD to accelerate convergence and improve accuracy. The results indicate significant potential in improving the egg hatching process. The high accuracy and robustness of the YOLOv9-S model enhance real-time monitoring and decision-making in hatcheries, leading to higher hatching success rates, reduced chick mortality, and increased operational efficiency. Future designs can leverage these technologies to create more intelligent, automated systems requiring minimal human intervention, enhancing productivity and scalability. Additionally, IoT and deep learning integration can extend to other poultry farming areas, such as broiler production and disease monitoring, providing a comprehensive approach to farm management. Future research could focus on integrating the YOLOv10 model for even higher accuracy and efficiency, exploring diverse data augmentation techniques, optimizing fuzzy logic algorithms, and integrating additional sensors like CO2 and advanced humidity sensors to improve environmental regulation. These advancements would benefit not only smart incubator applications but also broader poultry farming areas.

Analisis Sentimen Kurikulum Merdeka Menggunakan Klasifikasi Naïve Bayes Dan Support Vector Machine: - Eka, Eka Sabna; Anita Febriani; Rika Melyanti
SATIN - Sains dan Teknologi Informasi Vol 10 No 1 (2024): SATIN - Sains dan Teknologi Informasi
Publisher : STMIK Amik Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33372/stn.v10i1.1121

Media sosial adalah sebuah media yang digunakan untuk bersosialisasi dan bertukar informasi oleh para pengguna dengan menggunakan internet. Beberapa kegunaan media sosial seperti berkenalan dengan teman baru, mengetahui informasi olahraga, ekonomi, pariwisata dan juga Pendidikan. Terkait Pendidikan banyak masyarakat memberikan pendapat dan membicarakan Program Kurikulum Merdeka, terdapat pro dan kontra tentang Program ini. Informasi opini masyarakat diperoleh dari salah satu media sosial yaitu twitter. Penelitian ini bertujuan membangun model analisis sentiment terhadap Program Kurikulum Merdeka . Sumber informasi diperoleh dari Twitter sebanyak 399 data. Penelitian ini mengggunakan 2 (dua) algoritma yaitu Naïve Bayes dan Support Vector Machine (SVM). Hasil penelitian didapatkan opini masyarakat dengan Kategori Positif sebanyak 319 (79,9%) orang dan Kategori Negatif sebanyak 80 (20,1%). Nilai akurasi Naïve Bayes sebesar 71,68% dan SVM 82,80%. Dari hasil akurasi dapat dinyatakan bahwa Model SVM lebih baik dibandingkan dengan Naïve Bayes.

A Comprehensive Stacking Ensemble Approach for Stress Level Classification in Higher Education Fonda, Hendry; Irawan, Yuda; Melyanti, Rika; Wahyuni, Refni; Muhaimin, Abdi
Journal of Applied Data Sciences Vol 5, No 4: DECEMBER 2024
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v5i4.388

This research focuses on developing a comprehensive ensemble stacking model for the classification of student stress levels in higher education environments, specifically at Hang Tuah University Pekanbaru. Using a physiological dataset that includes parameters such as SPO2, heart rate, body temperature, systolic, and diastolic pressure, this research categorizes the condition of college students into four main categories: anxious, calm, tense, and relaxed. The data taken from public health centers in the period 2021 to 2024 was processed using the SMOTE technique to overcome data imbalance and K-Fold Cross Validation for model validation. In model development, a combination of basic algorithms such as SVM, Logistic Regression, Multilayer Perceptron, and Random Forest is used which is enhanced by boosting techniques through ADABoost, and XGBoost as a meta model. The test results show that the proposed stacking model is able to achieve 95% accuracy, with an AUC of 0.95, which indicates excellent performance in classification. The model not only excels in detecting more extreme stress conditions such as anxiety, but also shows reliable ability in classifying more difficult to distinguish conditions such as tense and relaxed. The conclusion of this study shows that the applied stacking ensemble approach significantly improves prediction accuracy and stability compared to traditional models. For future research, it is recommended to explore the use of deep learning-based meta-models such as LSTM and BiLSTM as well as rotation techniques in stacking to improve model performance and flexibility. The findings are expected to contribute significantly to the development of more sophisticated and effective stress detection models.

Inovasi Teknologi Dalam Pendidikan Dengan Penerapan Aplikasi Fuzzy Logic Untuk Identifikasi Belajar Di Sekolah Menengah Kejuruan Melyanti, Rika; Yulanda, Yulanda; Fonda, Hendry; Muhardi, Muhardi
INTECOMS: Journal of Information Technology and Computer Science Vol 8 No 1 (2025): INTECOMS: Journal of Information Technology and Computer Science
Publisher : Institut Penelitian Matematika, Komputer, Keperawatan, Pendidikan dan Ekonomi (IPM2KPE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31539/intecoms.v8i1.14569

Penelitian ini bertujuan untuk mengembangkan dan mengimplementasikan aplikasi berbasis fuzzy logic untuk mengidentifikasi gaya belajar siswa di SMK Perbankan Riau. Ruang lingkup penelitian mencakup analisis gaya belajar siswa dan penerapan teknologi fuzzy logic dalam proses identifikasi tersebut. Metode yang digunakan meliputi pengembangan aplikasi menggunakan algoritma fuzzy logic dan uji coba pada sampel siswa di SMK Perbankan Riau. Hasil penelitian menunjukkan bahwa aplikasi ini mampu mengidentifikasi gaya belajar siswa dengan tingkat akurasi yang tinggi. Selain itu, aplikasi ini juga membantu guru dalam menyesuaikan metode pengajaran sesuai dengan gaya belajar siswa yang teridentifikasi. Penerapan teknologi ini menunjukkan peningkatan dalam keterlibatan siswa dan pemahaman materi pembelajaran. Simpulan dari penelitian ini menyatakan bahwa penggunaan fuzzy logic dalam identifikasi gaya belajar merupakan inovasi yang efektif dan efisien. Implikasi dari hasil riset ini memberikan kontribusi signifikan bagi pengembangan ilmu pengetahuan di bidang pendidikan, khususnya dalam penerapan teknologi informasi untuk meningkatkan kualitas proses pembelajaran. Penggunaan aplikasi ini juga diharapkan dapat diaplikasikan pada tingkat pendidikan lainnya di masa depan.

Enhancing Educational Practices through Simple Online Learning Applications for Vocational Teachers at Abdurrab Pekanbaru Melyanti, Rika; Yulanda, Yulanda; Fonda, Hendry
Pengabdian: Jurnal Abdimas Vol. 3 No. 2 (2025)
Publisher : Yayasan Pendidikan Islam Daarut Thufulah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/abdimas.v3i2.1388

ABSTRACTBackground. The rapid advancement of technology in education necessitates the adoption of digital tools to facilitate effective teaching and learning processes. Purpose. The primary objective of this community service activity is to empower vocational teachers with an easy-to-use online learning platform that enhances their instructional methods and improves student engagement.Method. The application was developed using user-centered design principles to ensure it meets the specific needs of the teachers. Training sessions were conducted to familiarize the teachers with the application, followed by a pilot phase to gather feedback and make necessary adjustments. Results. The implementation of the online learning application resulted in increased teacher satisfaction, improved student participation, and a more interactive learning environment. Conclusion. The project demonstrates that simple, user-friendly digital tools can significantly enhance educational practices in vocational schools. Future community service activities should explore the long-term impacts of such applications on teaching efficacy and student outcomes.

Analisis Sentimen Kurikulum Merdeka Menggunakan Klasifikasi Naïve Bayes Dan Support Vector Machine: - Eka, Eka Sabna; Anita Febriani; Rika Melyanti
SATIN - Sains dan Teknologi Informasi Vol 10 No 1 (2024): SATIN - Sains dan Teknologi Informasi
Publisher : STMIK Amik Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33372/stn.v10i1.1121

Media sosial adalah sebuah media yang digunakan untuk bersosialisasi dan bertukar informasi oleh para pengguna dengan menggunakan internet. Beberapa kegunaan media sosial seperti berkenalan dengan teman baru, mengetahui informasi olahraga, ekonomi, pariwisata dan juga Pendidikan. Terkait Pendidikan banyak masyarakat memberikan pendapat dan membicarakan Program Kurikulum Merdeka, terdapat pro dan kontra tentang Program ini. Informasi opini masyarakat diperoleh dari salah satu media sosial yaitu twitter. Penelitian ini bertujuan membangun model analisis sentiment terhadap Program Kurikulum Merdeka . Sumber informasi diperoleh dari Twitter sebanyak 399 data. Penelitian ini mengggunakan 2 (dua) algoritma yaitu Naïve Bayes dan Support Vector Machine (SVM). Hasil penelitian didapatkan opini masyarakat dengan Kategori Positif sebanyak 319 (79,9%) orang dan Kategori Negatif sebanyak 80 (20,1%). Nilai akurasi Naïve Bayes sebesar 71,68% dan SVM 82,80%. Dari hasil akurasi dapat dinyatakan bahwa Model SVM lebih baik dibandingkan dengan Naïve Bayes.

Applications to Support Smart Learning Environments in Project-Based Cooperative Learning Models in Java Programming Courses and Applied in Science Melyanti, Rika; Ayu, Fitri; Mardainis, Mardainis; Henda, Zupri; Herianto, Herianto
Jurnal Penelitian Pendidikan IPA Vol 10 No 6 (2024): June
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v10i6.7141

This research paper proposes the development of an application to support an intelligent learning environment in a project-based cooperative learning model on Java programming courses. The application is built using the Laravel framework where the end result later lecturers can easily see the student portfolio of each learning access on the java programming course. An intelligent learning environment will enable students to learn from their experiences, adapt to new input, and perform project tasks already assigned to lecturers. This application will also help teachers in groups that are adapted from the cooperative learning model of the STAD type. The proposed application will be designed to make it easier for teachers to form groups based on the ability of students from high, medium and low, so that the groups formed are not homogeneous groups. This application will be useful for a variety of study programmer that have practical programming courses devised. This paper will discuss the benefits of cooperative learning, project-based learning, and intelligent learning environments in the context of Java programming courses. It will also provide insights into the proposed application development process. This application facilitates communication and discussion among students in a group that is easily connected with their lecturer, so that the lecturer can also monitor the activity of the group members. This paper will conclude with a discussion of the potential impact of the proposed applications on the field of education and the future in the learning environment.

IMPLEMENTATION OF E-LEARNING USING THE MOODLE Melyanti, Rika; Febriani, Anita
Jurnal Pendidikan Teknologi Kejuruan Vol 4 No 3 (2021): Regular Issue
Publisher : Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/jptk.v4i3.17223

STAI Tuanku Tambusai Pasir Pangaraian is a high school for Islamic religious education, which in the Teaching and Learning Process (PBM) is currently trying to apply the concept of blended learning by using e-learning. The purpose of this research is to build a Learning Management System (LMS) that can assist lecturers and students in conducting PBM with the help of computer technology. This is felt to have become a necessity during the pandemic and industrial revolution 4.0, STAI should have an e-larning that is able to answer challenges. The online learning system service architecture (e-learning) can be used as an appropriate design in the development of learning methods where the level of flexibility, scalability and functionality can make PBM easier to do anywhere and anytime. The designed online learning system (e-learning) at STAI Tuanku Tambusai is used by two actors, namely students and lecturers.

Monitoring Water Quality in The Well-Water Processing System to Make Drinkable Water Based on IoT Ponda, Hendry; Rahmalisa, Uci; Saputra , Haris Tri; Melyanti, Rika
JURNAL TEKNOLOGI DAN OPEN SOURCE Vol. 7 No. 2 (2024): Jurnal Teknologi dan Open Source, December 2024
Publisher : Universitas Islam Kuantan Singingi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36378/jtos.v7i2.4271

Indonesia is also inseparable from problems related to clean water. The city of Pekanbaru is currently experiencing rapid growth. In some big cities, the difficulty of clean water suitable for consumption is commonly felt by some residents, for example in Tuah Karya district – Pekanbaru. Moreover, this area is prone to flooding so the quality is getting worse because it smells and is cloudy. To produce clean water suitable for drinking that can be consumed by all levels of society. Water quality monitoring is also easy to do with IoT-based water quality monitoring tools. The goal of developing this prototype is to improve the healthy standard of living of the community by meeting the clean water needs of the prototype to be built. Seen from the main indicators, TDS and PH = TMS (Not Eligible) were obtained and followed by several other indicators that were still TMS. The results of the sample test showed that the water did not belong to the category of clean water and was suitable for consumption. After the water source of the drilled well is filtered using a tool made (without a manganese filter), the main indicators of TDS and pH are qualified.

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