Article Per Year (5 Year)
p-Index From 2019 - 2024
0.444
P-Index
This Author published in this journals
All Journal Publikasi Pendidikan Indonesian Journal of Data and Science
Al Danny Rian Wibisono
UPN "Veteran" Jawa Timur
Computer Science & IT Decision Sciences, Operations Research & Management Education Mathematics

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Peningkatan Keterampilan Mengajar Guru SD/MI melalui Pelatihan Media Pembelajaran Edugames Berbasis Teknologi: Quizizz dan Baamboozle Ilmatus Sa'diyah; Adelia Savitri; Salsa Febiola Gading Widjaya; Falih Wicaksono; Al Danny Rian Wibisono
Publikasi Pendidikan Vol 11, No 3 (2021)
Publisher : Prodi PGSD FIP UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26858/publikan.v11i3.22951

Abstract

The Covid-19 pandemic has changed many things, included learning methods in schools. All learning activities switch to an online system. This change raised several teaching obstacles faced by SD/MI teachers in Indonesia. The obstacle faced was the lack of mastery of technology for teachers so that the learning media used was less attractive. Based on a survey conducted, as many as 79.2% of parents stated that teachers mostly provide explanations of material through videos in WhatsApp groups and 45.8% of teachers provide video links from Youtube. Boredom was experienced by students during learning. Therefore, the community service team collaborates with partner schools to organize educational media training activities. In this case, the edugames taught are Quizizz and Baamboozle. This activity was attended by nine teachers from MI Asshibyan Dampaan, Cerme District, Gresik Regency. Activities taken place in a hybrid (offline and online). Quizizz materials were conducted offline at school on the first day, while bamboozle materials were conducted online through Zoom Meetings on the second day. After the presentation of the material by the team, the teacher also practiced compiling his own learning media with team assistance and then applied it in their respective classes. After the training activities, participants were able to arrange practice questions using the Quizizz learning media. The bamboozle media has not been implemented because the class does not take place via Zoom Meeting. The team hopes that this learning media can be applied continuously in online and offline classes.
Comparison of K-Nearest Neighbor and Decision Tree Methods using Principal Component Analysis Technique in Heart Disease Classification Al Danny Rian Wibisono; Syahrul Hidayat; Humam Maulana Tsubasanofa Ramadhan; Eva Yulia Puspaningrum
Indonesian Journal of Data and Science Vol. 4 No. 2 (2023): Indonesian Journal of Data and Science
Publisher : yocto brain

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56705/ijodas.v4i2.70

Abstract

Heart disease has become a global health issue that can threaten anyone, regardless of age. Numerous research efforts have been made to develop classification methods that can aid in diagnosing heart disease. In this study, we compared two classification methods, namely K-Nearest Neighbor (KNN) and Decision Tree, by applying Principal Component Analysis (PCA) technique to the heart disease classification. The dataset used contains relevant clinical attributes. After analyzing the dataset and performing data preprocessing, we applied PCA to reduce the dataset's dimensions. PCA models with KNN and Decision Tree were implemented and evaluated using performance metrics such as Confusion Matrix, F1 Score, and Accuracy. The analysis results showed that the PCA model with Decision Tree outperformed the PCA model with KNN in terms of accuracy. The Decision Tree model successfully classified all data correctly, while KNN had some misclassifications. This research recommends using the PCA model with Decision Tree for heart disease classification with the best performance. However, further research with larger datasets is needed for a deeper understanding
Co-Authors Adelia Savitri Eva Yulia Puspaningrum Falih Wicaksono Humam Maulana Tsubasanofa Ramadhan Ilmatus Sa’diyah Salsa Febiola Gading Widjaya Syahrul Hidayat