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Cici Cahyati
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Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Library & Information Science Social Sciences

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The Effect of Quartet Nusantara Media on Learning Outcomes of Social Studies on the Diversity of Indonesian Ethnic Groups and Cultures Mahara Arigayo; Cici Cahyati; Neneng Sulastri
JURNAL PENDIDIKAN IPS Vol 13 No 1 (2023): JURNAL PENDIDIKAN IPS
Publisher : STKIP Taman Siswa Bima

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37630/jpi.v13i1.999

Abstract

Social Sciences is a subject that studies social life by integrating various fields of social sciences and humanities. However, students often face difficulties in understanding the concepts taught due to less engaging and interactive teaching methods and learning media. This research aims to examine the effectiveness of using Game-Based Learning (GBL) in enhancing students' proficiency in Social Sciences at MI Matlaul Huda Bandung. The research method employed is Pre-Experiment with a One Group pretest-posttest design. The research subjects are fifth-grade students at Madrasah Ibtidaiyah in Bandung Regency, Indonesia. The experimental group is provided with the treatment using the Game-Based Learning Model, specifically the Nusantara Quartet Card Game. The sample consists of 20 students from MI Matlaul Huda in Bandung Regency, and the data is analyzed using descriptive statistics. Based on the results of inferential statistical analysis using the paired t-test formula, the success rate achieved by the students is that all students obtain scores above 70. Since t-value > t-table at a significance level of 0.05, the null hypothesis (H0) is rejected, and the alternative hypothesis (Ha) is accepted. Therefore, it can be concluded that the model has an impact on students' learning outcomes.
Penerapan Metode Klasifikasi Decision Tree dalam Prediksi Kanker Payudara Menggunakan Algoritma C4.5 Nurjoko, Nurjoko; Hendra, Hendra Kurniawan; Cici Cahyati; Elvira Uthia Rustanti; Hiya Cahya Mujahidah; Amanda Putri Maharani; Rosita; Agus Rahardi
JUPITER (Jurnal Penelitian Ilmu dan Teknologi Komputer) Vol 17 No 2 (2025): Jurnal Penelitian Ilmu dan Teknologi Komputer (JUPITER)
Publisher : Teknik Komputer Politeknik Negeri Sriwijaya

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

Abstract

Breast cancer is a deadly disease that require early detection and accurate prediction to improve recovery chance. This research aims to predict breast cancer using Data Mining technique with Decision Tree C4.5 algorithm. The dataset includes attributes such as tumor size, estrogen status, progesterone status, Progesterone Status, Survival Month, and status. These attributes were selected based on their clinical relevance and predictive potential in the context of breast cancer. The classification results showed a high level of accuracy with a prediction history of 658 surviving breast cancer patients and a precision class of 91.90%. This study has an accuracy rate of 89,81%. These findings have the potential to be developed int a medical decision support system to assist in more objective and efficient.   Keywords—Breast Cancer, Data Mining, Decision Tree, C4.5, Prediction, Accuracy
Co-Authors - Nurjoko Agus Rahardi Amanda Putri Maharani Elvira Uthia Rustanti Hendra, Hendra Kurniawan Hiya Cahya Mujahidah Mahara Arigayo Rosita Sulastri, Neneng