Clustering of Eligibility and Characteristics of Smart Indonesia Card Recipients for College using Agglomerative Hierarchical Clustering

M. Bucci Ryando, Sutarman Sutarman

Abstract


Since 2023, the Smart Indonesia Card or Kartu Indonesia Pintar-Kuliah (KIP-K) has two schemes. Consisting of KIP-K Scheme 1, where scholarship recipients are exempted from tuition fees and receive living allowances during the KIP-K scholarship period and KIP-K Scheme 2, where scholarship recipients are only exempted from tuition fees without receiving living allowances. Lack of information about the characteristics of prospective KIP-K scholarship recipients is a problem in itself. Many universities/institutions are not on target in providing this scholarship. This study aims to obtain clusters of recipients of KIP-K Scheme 1, KIP-K Scheme 2, and Not Eligible who are received and to obtain the characteristics of recipients of KIP-K Scheme 1, KIP-K Scheme 2, and Not Eligible who are received. This research method uses the CRISP-DM (Cross-Industry Standard Process for Data Mining) approach consisting of the stages of Business Understanding, Data Understanding, Data Preparation, Modeling, Evaluation, and Deployment and uses a combined method of Agglomerative Hierarchical Clustering with Average Linkage and uses the Calinski-Harabasz Index to test the validity of the cluster. The results of the study showed that the best cluster to explore was in 10 clusters with a Calinski-Harabasz Index value of 34.88236681148884. It was concluded that the feasibility of Scheme 1 KIP-K in cluster 8, 9 and 10.

Keywords


Scholarship; Clustering; Characteristics; Agglomerative Hierarchical Clustering

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References


M. B. Ryando, A. R. Mariana, and R. A. Hakim, “Sistem Pendukung Keputusan Pemilihan Sepeda Motor Second Terbaik di Kelas Matic 150cc Menggunakan Metode AHP dan TOPSIS,” Acad. J. Comput. Sci. Res., vol. 5, no. 1, p. 47, 2023, doi: 10.38101/ajcsr.v5i1.611.

M. B. Ryando, F. Ferawati, M. Iqbal, and P. Setiawan, “Multifactor Evaluation Process for a Decision Support System for Selecting the Best Students,” J. SISFOTEK Glob., vol. 14, no. 1, p. 22, 2024, doi: 10.38101/sisfotek.v14i1.10879.

D. T. Yuliana, M. I. A. Fathoni, and N. Kurniawati, “Penentuan Penerima Kartu Indonesia Pintar KIP Kuliah Dengan Menggunakan Metode K-Means Clustering,” J. Focus Action Res. Math. (Factor M), vol. 5, no. 1, pp. 127–141, 2022, doi: 10.30762/f_m.v5i1.570.

Hendra Di Kesuma and S. Hamidani, “Penerapan Data Mining Menggunakan Algoritma K- Means Clustering dalam Pengelompokan Penerima Beasiswa KIP Kuliah,” J. Ilm. Bin. STMIK Bina Nusant. Jaya Lubuklinggau, vol. 5, no. 1, pp. 86–92, 2023, doi: 10.52303/jb.v5i1.102.

F. Nuraeni, D. Kurniadi, and G. Fauzian Dermawan, “Pemetaan Karakteristik Mahasiswa Penerima Kartu Indonesia Pintar Kuliah (KIP-K) menggunakan Algoritma K-Means++,” J. Sisfokom (Sistem Inf. dan Komputer), vol. 11, no. 3, pp. 437–443, 2023, doi: 10.32736/sisfokom.v11i3.1439.

M. Iqbal, M. B. Ryando, T. Triono, and N. Nurmaesah, “Clustering of Prospective New Students Using Agglomerative Hierarchical Clustering,” Int. Proceeding Conf. Inf. Technol. Multimedia, Archit. Des. E-bus., vol. 2, no. August, pp. 183–192, 2022.

E. L. Cahapin, B. A. Malabag, C. S. Santiago, J. L. Reyes, G. S. Legaspi, and K. L. Adrales, “Clustering of students admission data using k-means, hierarchical, and DBSCAN algorithms,” Bull. Electr. Eng. Informatics, vol. 12, no. 6, pp. 3647–3656, 2023, doi: 10.11591/eei.v12i6.4849.

F. V. Espiritu, M. C. B. Natividad, and R. A. Velasco, “Data-Driven Decision Making in Scholarship Programs: Leveraging Decision Trees and Clustering Algorithms,” Int. J. Inf. Technol. Governance, Educ. Bus., vol. 6, no. 1, pp. 55–67, 2024, doi: 10.32664/ijitgeb.v6i1.134.

M. J. M. Moningkey, D. R. Kaparang, and H. Sumual, “The Distribution Pattern Of New Students Admissions Using The K-Means Clustering Algorithm,” Int. J. Inf. Technol. Bus., vol. 3, no. 2, pp. 52–60, 2021, [Online]. Available: https://ejournal.uksw.edu/ijiteb/article/view/4632%0Ahttps://ejournal.uksw.edu/ijiteb/article/download/4632/1913%0Ahttps://www.mendeley.com/catalogue/7c357677-698c-3973-ac41-6972c0817f34/?utm_source=desktop

Y. Kustiyahningsih, B. K. Khotimah, D. R. Anamisa, M. Yusuf, and T. Rahayu, “Decision Tree C 4.5 Algorithm for Classification of Poor Family Scholarship Recipients,” IOP Conf. Ser. Mater. Sci. Eng., vol. 1125, no. 1, p. 012048, 2021, doi: 10.1088/1757-899x/1125/1/012048.

M. Sompa and R. Ishak, “Clustering Tingkat Ekonomi Mahasiswa Calon Penerima Kartu Indonesia Pintar (KIP) Kuliah Metode K-Means,” J. Ilm. Ilmu Komput. Banthayo Lo Komput., vol. 1, no. 2, pp. 65–71, 2022, doi: 10.37195/balok.v1i2.175.

M. Chaudhry, I. Shafi, M. Mahnoor, D. L. R. Vargas, E. B. Thompson, and I. Ashraf, “A Systematic Literature Review on Identifying Patterns Using Unsupervised Clustering Algorithms: A Data Mining Perspective,” Symmetry (Basel)., vol. 15, no. 9, pp. 1–44, 2023, doi: 10.3390/sym15091679.

S. Peker and Ö. Kart, “Transactional data-based customer segmentation applying CRISP-DM methodology: A systematic review,” J. Data, Inf. Manag., vol. 5, no. 1, pp. 1–21, 2023, doi: 10.1007/s42488-023-00085-x.

F. Jáñez-Martino, R. Alaiz-Rodríguez, V. González-Castro, E. Fidalgo, and E. Alegre, “Classifying spam emails using agglomerative hierarchical clustering and a topic-based approach,” Appl. Soft Comput., vol. 139, p. 110226, 2023, doi: https://doi.org/10.1016/j.asoc.2023.110226.

A. Sidik, M. Kom, A. Nurrochman, M. Kom, M. Iqbal, and M. Kom, LOGIKA ALGORITMA PEMROGRAMAN DENGAN PYTHON. Purwokerto, Indonesia: PT. Pena Persada Kerta Utama, 2024.

S. P. Lima and M. D. Cruz, “A genetic algorithm using Calinski-Harabasz index for automatic clustering problem,” Rev. Bras. Comput. Apl., vol. 12, no. 3, pp. 97–106, 2020, doi: 10.5335/rbca.v12i3.11117.

J. Brzozowska, J. Pizoń, G. Baytikenova, A. Gola, A. Zakimova, and K. Piotrowska, “Data Engineering in Crisp-Dm Process Production Data – Case Study,” Appl. Comput. Sci., vol. 19, no. 3, pp. 83–95, 2023, doi: 10.35784/acs-2023-26.

W. Y. Ayele, “Adapting CRISP-DM for idea mining a data mining process for generating ideas using a textual dataset,” Int. J. Adv. Comput. Sci. Appl., vol. 11, no. 6, pp. 20–32, 2020, doi: 10.14569/IJACSA.2020.0110603.

J. A. Solano, D. J. Lancheros Cuesta, S. F. Umaña Ibáñez, and J. R. Coronado-Hernández, “Predictive models assessment based on CRISP-DM methodology for students performance in Colombia - Saber 11 Test,” Procedia Comput. Sci., vol. 198, no. 2020, pp. 512–517, 2021, doi: 10.1016/j.procs.2021.12.278.

U. Kannengiesser and J. S. Gero, “Modelling the Design of Models: an Example Using Crisp-Dm,” Proc. Des. Soc., vol. 3, no. JULY, pp. 2705–2714, 2023, doi: 10.1017/pds.2023.271.

E. S. Dalmaijer, C. L. Nord, and D. E. Astle, “Statistical power for cluster analysis,” BMC Bioinformatics, vol. 23, no. 1, pp. 1–28, 2022, doi: 10.1186/s12859-022-04675-1.

F. N. Dhewayani, D. Amelia, D. N. Alifah, B. N. Sari, and M. Jajuli, “Implementasi K-Means Clustering untuk Pengelompokkan Daerah Rawan Bencana Kebakaran Menggunakan Model CRISP-DM,” J. Teknol. dan Inf., vol. 12, no. 1, pp. 64–77, 2022, doi: 10.34010/jati.v12i1.6674.

R. Wirth and J. Hipp, “CRISP-DM: towards a standard process model for data mining. Proceedings of the Fourth International Conference on the Practical Application of Knowledge Discovery and Data Mining, 29-39,” Proc. Fourth Int. Conf. Pract. Appl. Knowl. Discov. Data Min., no. 24959, pp. 29–39, 2000, [Online]. Available: https://www.researchgate.net/publication/239585378_CRISP-DM_Towards_a_standard_process_model_for_data_mining




DOI: http://dx.doi.org/10.38101/sisfotek.v14i2.15707

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