ENHANCING EFFICIENCY IN DETERMINING QURAN LEARNING GROUPS: A WEBSITE-BASED K-MEANS ALGORITHM APPROACH AT NURUL JADID ISLAMIC BOARDING SCHOOL

  • Ikhwan Abdillah Department of Informatics Engineering, Faculty of Engineering, Universitas Nurul Jadid, Indonesia
  • Andi Wijaya Department of Informatics Engineering, Faculty of Engineering, Universitas Nurul Jadid, Indonesia
  • Kamil Malik Department of Informatics Engineering, Faculty of Engineering, Universitas Nurul Jadid, Indonesia
Keywords: Data Mining, K-Means, Quran Coaching, Student Clustering, Website Technology

Abstract

This research aims to develop a web-based application system using the K-Means algorithm to group students in Quran coaching at the Nurul Jadid Islamic Boarding School in Paiton, Probolinggo. The need for this system is based on the importance of efficiency and accuracy in determining student coaching groups based on their abilities in reading the Quran, including Tajweed, fluency, and memorization scores. This research method involves data analysis from 412 students. The data is processed using the K-Means algorithm to group students into three skill categories: "Good", "Sufficient", and "Poor". The grouping results provide objective and accurate guidance in determining suitable coaching groups for each student. The research results show that the K-Means algorithm is effective in grouping students, thereby improving the efficiency and accuracy of the coaching process. The implementation of web-based technology facilitates access and use of the system by administrators and coaching participants, ensuring that the grouping and coaching processes become faster, more accurate, and more objective. In conclusion, this research successfully develops a more responsive and efficient Quran coaching system, which not only solves specific problems at the Nurul Jadid Islamic Boarding School but also makes a significant contribution to the development of similar systems in other Islamic educational institutions.

Downloads

Download data is not yet available.

References

M. Syafiih and N. Hatima Indah Arifin, “Sistem Informasi Monitoring Target Capaian Pembinaan Al-Qur’an Di Wilayah Pondok Pesantren Nurul Jadid Berbasis Web,” Jar’s, vol. 1, no. 2, p. 23, 2023, [Online]. Available: https://www.ejournalwiraraja.com/index.php/JARS

J. Hutagalung, “Pemetaan Siswa Kelas Unggulan Menggunakan Algoritma K-Means Clustering,” JATISI (Jurnal Tek. Inform. dan Sist. Informasi), vol. 9, no. 1, pp. 606–620, 2022, doi: 10.35957/jatisi.v9i1.1516.

S. Santi and H. Februariyanti, “Implementation of Clustering on Tweet Uploading Side Effects of Covid-19 Post Vaccination Using K-Means Algorithm,” J. Tek. Inform., vol. 4, no. 4, pp. 779–786, 2023, doi: 10.52436/1.jutif.2023.4.4.704.

S. N. Br Sembiring, H. Winata, and S. Kusnasari, “Pengelompokan Prestasi Siswa Menggunakan Algoritma K-Means,” J. Sist. Inf. Triguna Dharma (JURSI TGD), vol. 1, no. 1, p. 31, 2022, doi: 10.53513/jursi.v1i1.4784.

D. Adillah, N. Manurung, and ..., “Implementation of K-means Clustering Analysis to Determine Barriers to Online Learning Case Study: Swasta Yapendak Tinjowan Junior High School,” J. Tek. Inform. …, vol. 3, no. 3, pp. 519–525, 2022, [Online]. Available: http://jutif.if.unsoed.ac.id/index.php/jurnal/article/view/189%0Ahttp://jutif.if.unsoed.ac.id/index.php/jurnal/article/download/189/100

I. Soliani and S. Juanita, “Grouping the Prevalence of Disease Cases By Age in Bandung City Hospitals Using K-Means,” J. Tek. Inform., vol. 3, no. 6, pp. 1647–1654, 2022, doi: 10.20884/1.jutif.2022.3.6.430.

M. Syafiih et al., “Pembuatan Website Biro Pendidikan Nurul Jadid dengan Sistem Framework sebagai Media Informasi Pendidikan di Pesantren,” GUYUB J. Community Engagem., vol. 2, no. 1, pp. 157–169, 2021, doi: 10.33650/guyub.v2i1.2120.

N. Mirantika, “Penerapan Algoritma K-Means Clustering Untuk Pengelompokan Penyebaran Covid-19 di Provinsi Jawa Barat,” Nuansa Inform., vol. 15, no. 2, pp. 92–98, 2021, doi: 10.25134/nuansa.v15i2.4321.

Esmi Nur Fitri et al., “Performance of K-Means Clustering and Knn Classifier in Fish Feed Seller Determination Models,” J. Tek. Inform., vol. 4, no. 3, pp. 485–491, 2023, doi: 10.52436/1.jutif.2023.4.3.725.

Z. Subecz, “Web-development with Laravel framework,” Gradus, vol. 8, no. 1, pp. 211–218, 2021, doi: 10.47833/2021.1.csc.006.

Z. D. Montero, “Customer Grouping for Customer Relationship Management Optimization with the K-Means Algorithm,” J. Comput. Scine Inf. Technol., pp. 98–105, 2022, doi: 10.35134/jcsitech.v8i4.46.

S. Likmi and J. Barat, “APPLICATION OF DATA MINING TO MEASURE THE EFFECTIVENESS OF THE ISLAMIC BOARDING SCHOOL ’ S INDEPENDENT CURRICULUM BASED ON LEARNING ACHIEVEMENT USING THE CLUSTERING METHOD,” vol. 3, no. 5, pp. 514–519, 2024, doi: 10.58344/jws.v3i5.595.

A. Rohmah, F. Sembiring, and A. Erfina, “Implementasi Algoritma K-Means Clustering Analysis untuk Menentukan Hambatan Pembelajaran Daring (Studi Kasus: SMK Yaspim Gegerbitung),” Semin. Nas. Sist. Inf. dan Manaj. Inform., pp. 290–298, 2021, [Online]. Available: https://sismatik.nusaputra.ac.id/index.php/sismatik/article/view/32

D. P. Sari, “Implementasi Algoritma K-Means Dalam Menentukan Tingkat Penyebaran Pandemi Covid-19 Di Sumatera Barat,” Comput. Based Inf. Syst. J., vol. 9, no. 1, pp. 50–56, 2021, doi: 10.33884/cbis.v9i1.3646.

A. Dimyati, “E-ISSN : XX-XX-XX ejurnal . itsnupekalongan . ac . id / sandtree E-ISSN : XX-XX-XX,” vol. 1, no. 1, pp. 39–54, 2023.

R. Anggara1, S. Defit, B. Hendrik3, and F. I. Komputer, “Implementasi K-Means Clustering Dalam Analisa Soal Ujian CBT Universitas Baiturrahmah,” vol. 5, no. 2, pp. 577–586, 2024.

N. Hendrastuty, “Penerapan Data Mining Menggunakan Algoritma K-Means Clustering Dalam Evaluasi Hasil Pembelajaran Siswa,” J. Ilm. Inform. Dan Ilmu Komput., vol. 3, no. 1, pp. 46–56, 2024, [Online]. Available: https://doi.org/10.58602/jima-ilkom.v3i1.26

M. R. Palevi and Z. Indra, “Implementasi Algoritma K-Means Clustering Dengan Pendekatan Active Learning Pada Siswa SMA Untuk Menentukan Jurusan Ke Perguruan Tinggi,” J. SAINTIKOM (Jurnal Sains Manaj. Inform. dan Komputer), vol. 23, no. 1, p. 26, 2024, doi: 10.53513/jis.v23i1.9553.

R. Novita, A. N. Khomarudin, R. Aulia, J. Jamaluddin, A. Yuditihwa, and A. Ayuri, “Penerapan Algoritma K-Means dan Analisisnya untuk Menentukan Kebijakan Strategis Penyelesaian Studi Mahasiswa,” J. SAINTIKOM (Jurnal Sains Manaj. Inform. dan Komputer), vol. 22, no. 2, p. 401, 2023, doi: 10.53513/jis.v22i2.8461.

E. Ramadanti and M. Muslih, “Penerapan Data Mining Algoritma K-Means Clustering Pada Populasi Ayam Petelur Di Indonesia,” Rabit J. Teknol. dan Sist. Inf. Univrab, vol. 7, no. 1, pp. 1–7, 2022, doi: 10.36341/rabit.v7i1.2155.

K. P. Sinaga and M. S. Yang, “Unsupervised K-means clustering algorithm,” IEEE Access, vol. 8, pp. 80716–80727, 2020, doi: 10.1109/ACCESS.2020.2988796.

M. M. Hidayat, “Data Mining Data mining,” Min. Massive Datasets, vol. 2, no. January 2013, pp. 5–20, 2015, [Online]. Available: https://www.cambridge.org/core/product/identifier/CBO9781139058452A007/type/book_part

B. Juli, “Jurnal Kajian dan Terapan Matematika,” vol. 8, pp. 114–128, 2023.

Z. Nabila, A. R. Isnain, Permata, and Z. Abidin, “Analisis Data Mining Untuk Clustering Kasus Covid-19 Di Provinsi Lampung Dengan Algoritma K-Means,” J. Teknol. dan Sist. Inf., vol. 2, no. 2, p. 100, 2021, [Online]. Available: http://jim.teknokrat.ac.id/index.php/JTSI

M. R. Muttaqin and M. Defriani, “Algoritma K-Means untuk Pengelompokan Topik Skripsi Mahasiswa,” Ilk. J. Ilm., vol. 12, no. 2, pp. 121–129, 2020, doi: 10.33096/ilkom.v12i2.542.121-129.

G. Gustientiedina, M. H. Adiya, and Y. Desnelita, “Penerapan Algoritma K-Means Untuk Clustering Data Obat-Obatan,” J. Nas. Teknol. dan Sist. Inf., vol. 5, no. 1, pp. 17–24, 2019, doi: 10.25077/teknosi.v5i1.2019.17-24.

Published
2024-08-21
How to Cite
[1]
Ikhwan Abdillah, Andi Wijaya, and Kamil Malik, “ENHANCING EFFICIENCY IN DETERMINING QURAN LEARNING GROUPS: A WEBSITE-BASED K-MEANS ALGORITHM APPROACH AT NURUL JADID ISLAMIC BOARDING SCHOOL”, J. Tek. Inform. (JUTIF), vol. 5, no. 4, pp. 559-577, Aug. 2024.