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All Journal Ainara Journal (Jurnal Penelitian dan PKM Bidang Ilmu Pendidikan) Devotion: Journal of Research and Community Service Journal of Dinda : Data Science, Information Technology, and Data Analytics
Ramadhan, Ridwan
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Religion Humanities Computer Science & IT Education Languange, Linguistic, Communication & Media Mathematics Social Sciences

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Classification of Indonesian Disasters with Decision Trees Based on Spatial and Text Data Ramadhan, Ridwan; Saputra, Ragil Raditya; Innova, Zacky; Prabowo, Ary
Indonesian Journal of Data Science, IoT, Machine Learning and Informatics Vol 5 No 2 (2025): August
Publisher : Research Group of Data Engineering, Faculty of Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/dinda.v5i2.2006

Abstract

Indonesia is one of the countries with a very high level of natural disaster vulnerability. The types of disasters that frequently occur include earthquakes, floods, landslides, volcanic eruptions, and others. This is because Indonesia is located at a geographical position where three world tectonic plates meet and has tropical climate conditions that make it prone to disasters. Therefore, Indonesia needs a system that can classify disaster types automatically and accurately to help the decision-making process quickly and accurately. This research aims to develop a natural disaster classification model based on information such as location (regency and province), time of occurrence (date), and causes that lead to disasters. The method used for classification in this research is the Decision Tree algorithm, because this algorithm can handle both numerical and categorical data and has high interpretability. Classification processing is also performed using textual cause data using Term Frequency-Inverse Document Frequency (TF-IDF) technique to convert text format into numerical form that can be processed by machine learning algorithms. The dataset obtained from the National Disaster Management Agency (BNPB) is open source. Test results show that the trained Decision Tree model can classify disaster types with an accuracy of 87%. This model also shows good precision, recall, and f1-score values in each disaster category. It is hoped that the results of this research can help in developing historical data-based disaster detection systems and assist government and society in responding to disasters more effectively and efficiently.
The Influence of Gimkit Game Implementation on Students’ Analytical Skills, Engagement, and Satisfaction Levels: Pengaruh Penerapan Game Gimkit terhadap Kemampuan Analitik, Keterlibatan dan Tingkat Kepuasan Mahasiswa Kurniasari, Dwiga; Puspitasari, Shinta; Ramadhan, Ridwan; Ayu, Siska Sukma; Sihombing , Yosepa Juliana; Susilowati, Nurdian
Ainara Journal (Jurnal Penelitian dan PKM Bidang Ilmu Pendidikan) Vol. 6 No. 3 (2025): Ainara Journal (Jurnal Penelitian dan PKM Bidang Ilmu Pendidikan)
Publisher : Lembaga Penelitian dan Pengembangan Sumberdaya Wilayah (elrispeswil)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54371/ainj.v6i3.981

Abstract

This study aimed to analyze the effect of using Gimkit, an interactive game-based learning platform, on students’ analytical skills, engagement, and learning satisfaction in the Introduction to Accounting course. A quasi-experimental design with a Nonequivalent Control Group was employed, involving 80 undergraduate students divided into an experimental class (using Gimkit) and a control class (conventional methods). Research instruments consisted of a 15-item multiple-choice test to measure analytical skills and Likert-scale questionnaires to assess engagement and satisfaction. The instruments were validated using Pearson’s correlation (r > 0.30) and achieved acceptable reliability (Cronbach’s α > 0.70). The results of independent sample t-tests showed no significant differences in analytical skills (t = 0.26, p > .05, d = 0.06) and engagement (t = 0.02, p > .05, d = 0.01) between groups. However, a significant difference was found in learning satisfaction (t = 4.21, p < .001, d = 0.75), with higher satisfaction reported by students in the Gimkit group. These findings suggest that Gimkit is more effective in enhancing affective aspects, particularly satisfaction, rather than cognitive outcomes in the short term. This study provides one of the first empirical insights into Gimkit implementation in accounting education in Indonesia and highlights the need for further longitudinal research to examine its long-term cognitive effects.
The Combination Effect of Plant Standing and Dosage of Manureon Growth and Years of Corn (Zea Mays L.) Cultivar Sweet Lady Wijaya, Wijaya; Faqih, Achmad; Ramadhan, Ridwan; Noviana, Nia; Nurjaman, Jajang; Mutiah, Lili
Devotion : Journal of Research and Community Service Vol. 4 No. 7 (2023): Devotion: Journal of Research and Community Service
Publisher : Green Publisher Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59188/devotion.v4i7.512

Abstract

This study aims to determine: (1) the effect of the combination treatment spacing and manure dosage on the growth and yield of sweet corn, (2) the best combination of spacing treatment and manure dosage on the growth and yield of sweet corn, and (3) correlation between growth components and yield of sweet corn plants. The experiment was carried out in Bakung Kidul Village, Jamblang District, Cirebon Regency from November 2022 to February 2023. The experimental method used was an experimental method using a Randomized Block Design (RBD) with a further test of the Scott Knott Cluster Test at a 5 percent significance level. It consisted of a combination of spacing and manure treatment, and was repeated three times. The treatment combinations were as follows: A (40 cm x 40 cm and 15 tons of manure/ha), B (40 cm x 40 cm and 20 tons of manure/ha), C (40 cm x 40 cm and 25 tons of fertilizer manure/ha), D (50 cm x 40 cm and 15 tons of manure/ha), E (50 cm x 40 cm and 20 tons of manure/ha), F (50 cm x 40 cm and 25 tons of manure/ ha), G (60 cm x 40 cm and 15 tons of manure/ha), H (60 cm x 40 cm and 20 tons of manure/ha) and I (60 cm x 40 cm and 25 tons of manure/ha). The results showed that: (1) the combination of spacing and manure treatment had a significant effect on the growth and yield of sweet corn, (2) a spacing of 50 cm x 40 cm combined with 20 tons of manure per hectare had the best effect on plant height, number of leaves, cob length, weight of cobs with and without husks per plot. Spacing of 50 cm x 40 cm combined with 20 and 25 tons of manure per hectare gave the best effect on cob diameter, cob weight with and without husks per plant, and (3) there was a significant positive relationship between plant height at 42 days old after planting, the number of leaves aged 28 days and 42 days after planting with cob weight without husk per plot.
Co-Authors Ayu, Siska Sukma Faqih, Achmad Innova, Zacky Kurniasari, Dwiga Mutiah, Lili Noviana, Nia Nurdian Susilowati Nurjaman, Jajang Prabowo, Ary Saputra, Ragil Raditya Shinta Puspitasari Sihombing , Yosepa Juliana Wijaya Wijaya