Aplikasi K-Means berbasis Web untuk Klasifikasi Kelas Unggulan
DOI:
https://doi.org/10.30812/matrik.v21i1.1473Keywords:
Data Mining, K-Means, Klasifikasi, Kelas UnggulanAbstract
MAN-1 Mataram merupakan sekolah yang berada di kota Mataram, Sekolahan ini memiliki 2 kelas yaitu kelas unggulan dan kelas biasa. Setiap tahunnya MAN-1 Mataram mengalami peningkatan penerimaan pendaftaran siswa baru diperkiran tahun kedepan siswa barunya akan mengalami peningkatan yang banyak. Banyaknya siswa yang mendaftar membuat bagian kesiswaan MAN-1 Mataram mengalami kesulitan dalam penentuan kelas, apalagi ditemuakan siswa yang dikelas unggulan didapatkan prestasi dan nilai kurang standar. Berdasarkan permasalahan tersebut tujuan dari penelitan ini adalah mewujudkan pengelompokan kelas belajar berdasarkan nilai dan prestasi siswa baru sehingga diperoleh klasifikasi kelas unggulan. Metode penelitian yang digunakan adalah algoritma K-Means yang dilengkapi dengan program aplikasi berbasis web. Hasil dari penelitian ini menunjukan bahwa algoritma k-means mampu menghasilakan pemilihan dan pembagian kelas unggulan bagi calon siswa baru sesuai dengan nilai kemampuan siswa. Penerapan kelas unggulan berdampak positif bagi peningkatan pendidikan.
Downloads
Download data is not yet available.
References
[1] P. R. Indonesia, Undang-Undang Republik Indonesia Nomor 20 Tahun 2003 Tentang Sistem Pendidikan Nasional, no. 1. 2003, pp. 1–33.
[2] R. Murphy and F. Weinhardt, “Top of the Class: The Importance of Ordinal Rank,†Review of Economic Studies, vol. 87, no. 6, pp. 2777–2826, 2020, doi: 10.1093/restud/rdaa020.
[3] K. P. Sinaga and M.-S. Yang, “Unsupervised K-Means Clustering Algorithm,†in IEEE Access, 2020, vol. 8, pp. 80716–80727, doi: 10.1109/ACCESS.2020.2988796.
[4] C. Yuan and H. Yang, “Research on K-Value Selection Method of K-Means Clustering Algorithm,†Multidisciplinary Scientific Journal, vol. 2, no. 2, pp. 226–235, 2019, doi: 10.3390/j2020016.
[5] M. Z. Hossain, M. N. Akhtar, R. B. Ahmad, and M. Rahman, “A dynamic K-means clustering for data mining,†Indonesian Journal of Electrical Engineering and Computer Science, vol. 13, no. 2, pp. 521–526, 2019, doi: 10.11591/ijeecs.v13.i2.pp521-526.
[6] D. Neha and B. M. Vidyavathi, “A Survey on Applications of Data Mining using Clustering Techniques,†International Journal of Computer Applications, vol. 126, no. 2, pp. 7–12, 2015, doi: 10.5120/ijca2015905986.
[7] Ediyanto, N. Mara, and N. Satyahadewi, “Pengklasifikasian Karakteristik Dengan Metode K-Means Cluster Analysis,†Buletin Ilmiah Mat. Stat. dan Terapannya (Bimaster), vol. 02, no. 2, pp. 133–136, 2013.
[8] C. Wu et al., “k-Means Clustering Algorithm and Its Simulation Based on Distributed Computing Platform,†Journal of Wiley, vol. 2021, pp. 1–10, 2021, doi: 10.1155/2021/9446653.
[9] E. Harli, A. Fauzi, and T. H. Kusmanto, “Pengelompokkan Kelas Menggunakan Self Organizing Map Neural Network pada SMK N 1 Depok,†Jurnal Edukasi dan Penelitian Informatika (JEPIN), vol. 2, no. 2, pp. 90–95, 2016, doi: 10.26418/jp.v2i2.17574.
[10] E. B. Sambani and F. Nuraeni, “Penerapan Algoritma C4.5 Untuk Klasifikasi Pola Penjurusan di Sekolah Menengah Kejuruan (SMK) Kota Tasikmalaya,†CSRID (Computer Science Research and Its Development Journal), vol. 9, no. 3, p. 144, 2018, doi: 10.22303/csrid.9.3.2017.144-152.
[11] W. Purba, S. Tamba, and J. Saragih, “The effect of mining data k-means clustering toward students profile model drop out potential,†Journal of Physics: Conference Series, vol. 1007, no. 1, 2018, doi: 10.1088/1742-6596/1007/1/012049.
[12] A. Mahmudan, “Clustering of District or City in Central Java Based COVID-19 Case Using K-Means Clustering,†Jurnal Matematika, Statistika dan Komputasi, vol. 17, no. 1, pp. 1–13, 2020, doi: 10.20956/jmsk.v17i1.10727.
[13] N. Dwitri, J. A. Tampubolon, S. Prayoga, F. Ilmi Zer, and D. Hartama, “Penerapan Algoritma K-Means Dalam Menentukan Tingkat Kepuasan Pembelajaran Online Pada Masa Pandemi Covid-19 di Indonesia,†Jti (Jurnal Teknologi Informasi), vol. 4, no. 1, pp. 101–105, 2020.
[14] H. J. de P. Alves, F. A. F. Henrique José de Paula Alves, K. P. de Lima, B. D. de O. Batista, and T. J. Fernandes, “The COVID-19 pandemic in Brazil an application of the k-means clustering method,†Research, Society and Developmen, vol. 9, no. 10, pp. 1–21, 2020.
[15] N. A. Khairani and E. Sutoyo, “Application of K-Means Clustering Algorithm for Determination of Fire-Prone Areas Utilizing Hotspots in West Kalimantan Province,†International Journal of Advances in Data and Information Systems, vol. 1, no. 1, pp. 9–16, 2020, doi: 10.25008/ijadis.v1i1.13.
[16] A. Heryati and M. I. Herdiansyah, “The Application of Data Mining by using K-Means Clustering Method in Determining New Students’ Admission Promotion Strategy,†International Journal of Engineering and Advanced Technology, vol. 9, no. 3, pp. 824–833, 2020, doi: 10.35940/ijeat.c5414.029320.
[17] C. A. Sugianto, T. Pratiwi, and O. Riska, “K-Means Algorithm For Clustering Poverty Data in Bangka Belitung Island Province Journal of Computer Networks , Architecture and High Performance Computing,†Journal of Computer Networks , Architecture and High Performance Computing, vol. 3, no. 1, pp. 58–67, 2021.
[18] N. Chawla, “Discovering Knowledge in Data: An Introduction to Data Mining,†Briefings in Bioinformatics, vol. 6, no. 4, pp. 411–412, 2005.
[2] R. Murphy and F. Weinhardt, “Top of the Class: The Importance of Ordinal Rank,†Review of Economic Studies, vol. 87, no. 6, pp. 2777–2826, 2020, doi: 10.1093/restud/rdaa020.
[3] K. P. Sinaga and M.-S. Yang, “Unsupervised K-Means Clustering Algorithm,†in IEEE Access, 2020, vol. 8, pp. 80716–80727, doi: 10.1109/ACCESS.2020.2988796.
[4] C. Yuan and H. Yang, “Research on K-Value Selection Method of K-Means Clustering Algorithm,†Multidisciplinary Scientific Journal, vol. 2, no. 2, pp. 226–235, 2019, doi: 10.3390/j2020016.
[5] M. Z. Hossain, M. N. Akhtar, R. B. Ahmad, and M. Rahman, “A dynamic K-means clustering for data mining,†Indonesian Journal of Electrical Engineering and Computer Science, vol. 13, no. 2, pp. 521–526, 2019, doi: 10.11591/ijeecs.v13.i2.pp521-526.
[6] D. Neha and B. M. Vidyavathi, “A Survey on Applications of Data Mining using Clustering Techniques,†International Journal of Computer Applications, vol. 126, no. 2, pp. 7–12, 2015, doi: 10.5120/ijca2015905986.
[7] Ediyanto, N. Mara, and N. Satyahadewi, “Pengklasifikasian Karakteristik Dengan Metode K-Means Cluster Analysis,†Buletin Ilmiah Mat. Stat. dan Terapannya (Bimaster), vol. 02, no. 2, pp. 133–136, 2013.
[8] C. Wu et al., “k-Means Clustering Algorithm and Its Simulation Based on Distributed Computing Platform,†Journal of Wiley, vol. 2021, pp. 1–10, 2021, doi: 10.1155/2021/9446653.
[9] E. Harli, A. Fauzi, and T. H. Kusmanto, “Pengelompokkan Kelas Menggunakan Self Organizing Map Neural Network pada SMK N 1 Depok,†Jurnal Edukasi dan Penelitian Informatika (JEPIN), vol. 2, no. 2, pp. 90–95, 2016, doi: 10.26418/jp.v2i2.17574.
[10] E. B. Sambani and F. Nuraeni, “Penerapan Algoritma C4.5 Untuk Klasifikasi Pola Penjurusan di Sekolah Menengah Kejuruan (SMK) Kota Tasikmalaya,†CSRID (Computer Science Research and Its Development Journal), vol. 9, no. 3, p. 144, 2018, doi: 10.22303/csrid.9.3.2017.144-152.
[11] W. Purba, S. Tamba, and J. Saragih, “The effect of mining data k-means clustering toward students profile model drop out potential,†Journal of Physics: Conference Series, vol. 1007, no. 1, 2018, doi: 10.1088/1742-6596/1007/1/012049.
[12] A. Mahmudan, “Clustering of District or City in Central Java Based COVID-19 Case Using K-Means Clustering,†Jurnal Matematika, Statistika dan Komputasi, vol. 17, no. 1, pp. 1–13, 2020, doi: 10.20956/jmsk.v17i1.10727.
[13] N. Dwitri, J. A. Tampubolon, S. Prayoga, F. Ilmi Zer, and D. Hartama, “Penerapan Algoritma K-Means Dalam Menentukan Tingkat Kepuasan Pembelajaran Online Pada Masa Pandemi Covid-19 di Indonesia,†Jti (Jurnal Teknologi Informasi), vol. 4, no. 1, pp. 101–105, 2020.
[14] H. J. de P. Alves, F. A. F. Henrique José de Paula Alves, K. P. de Lima, B. D. de O. Batista, and T. J. Fernandes, “The COVID-19 pandemic in Brazil an application of the k-means clustering method,†Research, Society and Developmen, vol. 9, no. 10, pp. 1–21, 2020.
[15] N. A. Khairani and E. Sutoyo, “Application of K-Means Clustering Algorithm for Determination of Fire-Prone Areas Utilizing Hotspots in West Kalimantan Province,†International Journal of Advances in Data and Information Systems, vol. 1, no. 1, pp. 9–16, 2020, doi: 10.25008/ijadis.v1i1.13.
[16] A. Heryati and M. I. Herdiansyah, “The Application of Data Mining by using K-Means Clustering Method in Determining New Students’ Admission Promotion Strategy,†International Journal of Engineering and Advanced Technology, vol. 9, no. 3, pp. 824–833, 2020, doi: 10.35940/ijeat.c5414.029320.
[17] C. A. Sugianto, T. Pratiwi, and O. Riska, “K-Means Algorithm For Clustering Poverty Data in Bangka Belitung Island Province Journal of Computer Networks , Architecture and High Performance Computing,†Journal of Computer Networks , Architecture and High Performance Computing, vol. 3, no. 1, pp. 58–67, 2021.
[18] N. Chawla, “Discovering Knowledge in Data: An Introduction to Data Mining,†Briefings in Bioinformatics, vol. 6, no. 4, pp. 411–412, 2005.
Downloads
Published
2021-11-26
Issue
Section
Articles
How to Cite
[1]
C. Satria and A. Anggrawan, “Aplikasi K-Means berbasis Web untuk Klasifikasi Kelas Unggulan”, MATRIK, vol. 21, no. 1, pp. 111–124, Nov. 2021, doi: 10.30812/matrik.v21i1.1473.
Similar Articles
- Abdurraghib Segaf Suweleh, Dyah Susilowaty, Hairani Hairani, Khairan Marzuki, Penanganan Ketidak Seimbangan Kelas Menggunakan Pendekatan Level Data , MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer: Vol. 20 No. 1 (2020)
- Hadi Santoso, Hilyah Magdalena, Helna Wardhana, Aplikasi Dynamic Cluster pada K-Means BerbasisWeb untuk Klasifikasi Data Industri Rumahan , MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer: Vol. 21 No. 3 (2022)
- Pardomuan Robinson Sihombing, Istiqomatul Fajriyah Yuliati, Penerapan Metode Machine Learning dalam Klasifikasi Risiko Kejadian Berat Badan Lahir Rendah di Indonesia , MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer: Vol. 20 No. 2 (2021)
- Fadhilah Dwi Ananda, Yoga Pristyanto, Analisis Sentimen Pengguna Twitter Terhadap Layanan Internet Provider Menggunakan Algoritma Support Vector Machine , MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer: Vol. 20 No. 2 (2021)
- Pungkas Subarkah, Enggar Pri Pambudi, Septi Oktaviani Nur Hidayah, Perbandingan Metode Klasifikasi Data Mining untuk Nasabah Bank Telemarketing , MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer: Vol. 20 No. 1 (2020)
- Christofer Satria, Peter Wijaya Sugijanto, Anthony Anggrawan, I Nyoman Yoga Sumadewa, Aprilia Dwi Dayani, Rini Anggriani, Multi-Algorithm Approach to Enhancing Social Assistance Efficiency Through Accurate Poverty Classification , MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer: Vol. 24 No. 1 (2024)
- Supangat Supangat, Mohd Zainuri Bin Saringat, Mochamad Yovi Fatchur Rochman, Predicting Handling Covid-19 Opinion using Naive Bayes and TF-IDF for Polarity Detection , MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer: Vol. 22 No. 2 (2023)
- Donny Kurniawan, Anthony Anggrawan, Hairani Hairani, Graduation Prediction System on Students Using C4.5 Algorithm , MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer: Vol. 19 No. 2 (2020)
- Erlin Erlin, Yenny Desnelita, Nurliana Nasution, Laili Suryati, Fransiskus Zoromi, Dampak SMOTE terhadap Kinerja Random Forest Classifier berdasarkan Data Tidak seimbang , MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer: Vol. 21 No. 3 (2022)
- Annisa Nurul Puteri, Arizal Arizal, Andini Dani Achmad, Feature Selection Correlation-Based pada Prediksi Nasabah Bank Telemarketing untuk Deposito , MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer: Vol. 20 No. 2 (2021)
1-10 of 239
Next
You may also start an advanced similarity search for this article.
Most read articles by the same author(s)
- Anthony Anggrawan, Analisis Deskriptif Hasil Belajar Pembelajaran Tatap Muka dan Pembelajaran Online Menurut Gaya Belajar Mahasiswa , MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer: Vol. 18 No. 2 (2019)
- Lusiana Efrizoni, Sarjon Defit, Muhammad Tajuddin, Anthony Anggrawan, Komparasi Ekstraksi Fitur dalam Klasifikasi Teks Multilabel Menggunakan Algoritma Machine Learning , MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer: Vol. 21 No. 3 (2022)
- Anthony Anggrawan, Satuang Satuang, Mokhammad Nurkholis Abdillah, Sistem Pakar Diagnosis Penyakit Ayam Broiler Menggunakan Forward Chaining dan Certainty Factor , MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer: Vol. 20 No. 1 (2020)
- Anthony Anggrawan, Mayadi Mayadi, Christofer Satria, Menentukan Akurasi Tata Letak Barang dengan Menggunakan Algoritma Apriori dan Algoritma FP-Growth , MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer: Vol. 21 No. 1 (2021)
- Lalu Ganda Rady Putra, Anthony Anggrawan, Pengelompokan Penerima Bantuan Sosial Masyarakat dengan Metode K-Means , MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer: Vol. 21 No. 1 (2021)
- Bambang Krismono Triwijoyo, Ahmat Adil, Anthony Anggrawan, Convolutional Neural Network With Batch Normalization for Classification of Emotional Expressions Based on Facial Images , MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer: Vol. 21 No. 1 (2021)
- Putu Tisna Putra, Anthony Anggrawan, Hairani Hairani, Comparison of Machine Learning Methods for Classifying User Satisfaction Opinions of the PeduliLindungi Application , MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer: Vol. 22 No. 3 (2023)
- Anthony Anggrawan, Raisul Azhar, Bambang Krismono Triwijoyo, Mayadi Mayadi, Developing Application in Anticipating DDoS Attacks on Server Computer Machines , MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer: Vol. 20 No. 2 (2021)
- Anthony Anggrawan, Mayadi Mayadi, Application of KNN Machine Learning and Fuzzy C-Means to Diagnose Diabetes , MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer: Vol. 22 No. 2 (2023)
- Donny Kurniawan, Anthony Anggrawan, Hairani Hairani, Graduation Prediction System on Students Using C4.5 Algorithm , MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer: Vol. 19 No. 2 (2020)
.png)
