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All Journal Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi Early Childhood Research Journal (ECRJ)
Kawuri, Gabriella Vindy
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Humanities Computer Science & IT Education Mathematics Other

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Efektifitas Game Edukasi Belajar Hijaiyah Berbasis Android Dalam Meningkatkan Kemandirian Belajar Bagi Anak Usia 3-5 Tahun Wiratmoko, Galih; Mawsally, Dita Aluf; Faza, Firdaus Aulia; Kawuri, Gabriella Vindy
Early Childhood Research Journal (ECRJ) Vol. 7 No. 1 (2024)
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/ecrj.v7i1.8126

Abstract

Al’Quran merupakan pedoman hidup bagi umat Islam, Agar dapat memahami isi Al’quran perlu dilatih mulai dari mengenal huruf terlebih dahulu yaitu huruf hijaiyah. Tujuan penelitian ini untuk mengasilkan produk berupa game edukasi belajar huruf hijaiyah dalam rangka meningkatkan kemandirian belajar bagi anak usia 3-5 tahun. Penelitian ini menggunakan metode penelitian dan pengembangan (Research and Development) dengan tujuan menghasilkanproduk yang telah diuji kelayakannya. Produk yang dihasilkan dari penelitian ini berupa aplikasi game edukasi dengan langkah penelitian yang mengacu pada desain pengembangan model ADDIE (Analysis, Design, Development, Implementation, Evaluation). Hasil penelitian ini dapat disimpulkan bahwa pengembangan aplikasi game edukasi untuk pengenalan huruf hijaiyah pada anak dikategorikan “Sangat Layak” dengan nilai rata-rata kelayakan sebesar 3,4 yang dihasilkan dari kuisioner. Aplikasi game edukasi "Belajar Hijaiyah" berbasis Android merupakan media yang efektif untuk meningkatkan kemandirian belajar bagi anak usia 3-5 tahun. Aplikasi ini dapat membantu anak belajar mengenal huruf hijaiyah, cara membaca huruf hijaiyah, dan cara menulis huruf hijaiyah secara mandiri. Aplikasi ini juga dapat membantu anak termotivasi belajar secara menyenangkan dan tidak membosankan.
Cluster Analysis of BPJS Kesehatan Claim Data in Madiun City to Identify High Claim Patterns and Fraud Indications Shobri, Muhammad Qolbi; Al-Kubro, Putri Balqis; Kawuri, Gabriella Vindy
Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi Volume 13 Issue 3 December 2025
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/euler.v13i3.35013

Abstract

The increasing number of BPJS Kesehatan (Health Social Security) service claims in Madiun City poses significant challenges to financing efficiency and raises concerns about potential irregular or fraudulent claims. This study aims to identify high-claim patterns and detect indications of fraud using a data mining approach through the K-Means and Hierarchical Clustering methods. The research employed secondary data consisting of 309 hospital claim records from Madiun City in 2025. The primary variables were the number of claims and total claim costs, supported by additional variables such as age, gender, occupation, type of service, and disease diagnosis. Data analysis involved three main stages: preprocessing, clustering, and cluster quality evaluation using the Silhouette Score, Davies-Bouldin Index, and Calinski-Harabasz Index. Ths Study further compared the performance of both clustering methods, revealing that K-Means achieved superior validity scores across major evaluation metrics. The K-Means method produced the best performance, with a Silhouette Score of 0.617 and a Calinski-Harabasz Index of 419.581, reflecting well-separated and compact cluster structures. Three main clusters were identified-low, medium, and high. The high-claim cluster consisted of participants aged 55 years and above, with a claim frequencies of 2 to 7 claims and total claim costs exceeding IDR 20 million. This cluster was dominated by retirees, housewives, and private-sector employees utilizing inpatient services. Although categorized as a high-risk group, verification results revealed no signs of fraud but rather complex medical needs. These findings suggest that integrating clustering analysis into BPJS Kesehatan’s claim monitoring system can support early anomaly detection and enhance both financing efficiency and claim management integrity.
Co-Authors Al-Kubro, Putri Balqis Faza, Firdaus Aulia Mawsally, Dita Aluf Wiratmoko, Galih