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All Journal Ceddi Journal of Information System and Technology (JST) Lestari: Jurnal Pengabdian Kepada Masyarakat Jurnal Abdimas Cendekiawan Indonesia
Abigail, Omita
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Humanities Computer Science & IT Decision Sciences, Operations Research & Management Education Engineering Environmental Science Health Professions Library & Information Science Nursing Public Health Social Sciences Other

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Application of the Adaptive Boosting Method to Increase the Accuracy of Classification of Type Two Diabetes Mellitus Patients Using the Decision Tree Algorithm Hao Chieh Chiua; Robbi Rahim; Mahmud Mustapa; Kamaruddin; Akbar Hendra; Asnimar; Abigail, Omita
Ceddi Journal of Information System and Technology (JST) Vol. 2 No. 2 (2023): December
Publisher : Yayasan Cendekiawan Digital Indonesia (CEDDI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56134/jst.v2i2.47

Abstract

One of the data mining processes that is often used in machine learning is the data classification process. A decision tree is a classification algorithm that has the advantage of being easy to visualize because of its simple structure. However, the decision tree algorithm is quite susceptible to incorrect classification calculations due to the presence of noise in the data or imbalance in the data, which can reduce the overall level of accuracy. Therefore, the decision tree algorithm should be combined with other methods that can increase the accuracy of classification performance. Machine Learning is used through an artificial intelligence approach to solve problems or carry out optimization. Adaptive Boosting is used to optimize classification calculations. This study aims to examine the performance of Adaptive Boosting in the process of classifying second-degree diabetes mellitus patients using the Decision Tree algorithm. Diabetes mellitus is known as a chronic condition of the human body, the cause of which is an increase in the body's blood sugar levels because the body is unable to produce insulin or is unable to utilize insulin effectively, which is usually referred to as hyperglycemia.. By using a 60:40 data split, the Decision Tree algorithm produces an accuracy value of 95.71%, while the Adaptive Boosting-based Decision Tree results reach a value of 98.99%.
Pendampingan Dalam Pembuatan Presentasi Kepada Guru SMAS Kristen Soleman Makassar Menggunakan Platform Canva A, Andryanto; Bara, Rivanky Valensius; Abigail, Omita; Muchtar, Nur Azizah; Apriliani, Nurlinda; B, Angelin Marici; Syamsu, Suryadi; Nurzaenab, Nurzaenab; Butsiarah, Butsiarah; Ratnawati, Ratnawati; Angriawan, Randy
LESTARI : Jurnal Pengabdian Kepada Masyarakat Vol 1 No 1 (2023): Lestari : Jurnal Pengabdian Kepada Masyarakat
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat (LPPM) Universitas Muslim Maros

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46918/lestari.v1i1.1999

Abstract

Pengabdian masyarakat menjadi fokus utama dalam upaya meningkatkan pendidikan di lingkungan sekolah. Melalui PKM-PM ini bertujuan mengatasi kendala metode pembelajaran tradisional yang dapat menghasilkan kebosanan dan kehilangan minat belajar siswa. Sebagai solusi, kami mengusulkan pemanfaatan teknologi pembelajaran animasi melalui aplikasi Canva dalam pengembangan bahan ajar interaktif, memanfaatkan fasilitas laboratorium sekolah dan memberikan pelatihan serta pendampingan kepada guru-guru. Hasil evaluasi menunjukkan bahwa, meskipun sebagian besar guru belum memiliki pengalaman dengan Canva, setelah pelatihan, mereka menganggap Canva lebih efisien dalam menciptakan bahan ajar yang menarik dan interaktif, yang pada gilirannya meningkatkan efektivitas pembelajaran dan pemahaman materi yang diajarkan. Dari hasil pre-test, kami mencatat bahwa 84,6% dari guru yang kami ajarkan belum pernah menggunakan Canva, sementara 92,3% dari mereka sudah pernah mendengar tentang platform Canva sebelumnya. Hasil post-test juga mengindikasikan perubahan positif dalam persepsi guru terhadap keefisienan Canva dalam pembuatan bahan ajar interaktif, yang dapat memberikan variasi dalam penyajian informasi dalam bahan ajar.
Utilization of Learning Animation Technology in Assisting the Creation of Interactive Teaching Materials for Teachers at SMAS Kristen Soleman Anugraha, Nurhajar; Bara, Rivanky Valensius; Abigail, Omita; Muchtar, Nur Azizah; Aprialliani, Nurlinda; Marici B, Angelin; Aman, Andryanto; Qadri, Muhammad; Wardhani, Dyah Utari Yusa
Jurnal Abdimas Cendekiawan Indonesia Vol. 1 No. 1 (2024): January
Publisher : Yayasan Cendekiawan Digital Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56134/jaci.v1i1.75

Abstract

The teacher's job is to increase student interest in learning with the aim of improving student achievement in the learning process. One of the problems faced by teachers at SMAS Kristen Soleman is the lack of knowledge and skills in the use of animation learning technology, so that the teaching materials produced are less attractive and become one of the factors in decreasing student interest in the learning process. The purpose of this community service is to improve knowledge and skills through training and mentoring in making interactive teaching materials using animated learning technologies such as Canva, Kahoot, and Powtoon to teachers at SMAS Kristen Soleman. The implementation method is carried out starting from the preparation stage (field observation, literature study, and partner identification), the implementation stage (training and mentoring), to the evaluation stage using pre-test and post-test before and after training and mentoring is carried out. Based on the evaluation results of training and mentoring teachers in making interactive teaching materials using animated learning technology, it shows an increase in knowledge from 41.7% to 100%, where teachers already knew interactive teaching materials using animation learning technology. Meanwhile, teachers' skills increased from 12.5% to 91.7%.
Co-Authors A, Andryanto Akbar Hendra Aman, Andryanto ANGRIAWAN, RANDY Aprialliani, Nurlinda Apriliani, Nurlinda Asnimar B, Angelin Marici Bara, Rivanky Valensius Butsiarah Dyah Utari Yusa Wardhani Hao Chieh Chiua Kamaruddin Mahmud Mustapa Marici B, Angelin Muchtar, Nur Azizah Nurhajar Anugraha NURZAENAB, NURZAENAB Qadri, Muhammad Ratnawati Ratnawati Robbi Rahim Suryadi Syamsu, Suryadi