The Application of Weighted Ranking Method Using Combination of ROC and CPI to Select Eligible Family for Keluarga Harapan Program Aids


Aishiyah Saputri Laswi(1*); Ulvah Ulvah(2); Dasril Dasril(3);

(1) Institut Agama Islam Negeri (IAIN) Palopo
(2) University Cokroaminoto Palopo
(3) University Cokroaminoto Palopo
(*) Corresponding Author

  

Abstract


The Keluarga Harapan Program (KHP), a financial assistance, is a program launched by the government to deal with poverty in various regions of Indonesia by conducting direct surveys and collecting data on disadvantaged families in each region. However, the issue is that many recipients do not meet the appropriate criteria or are not categorized as recipients. The Composite Performance Index and Rank Centeroid algorithms are a solution in the selection process for the recipients for the KHP by carrying out the analysis and comparison stages of whether they are categorized as KM (Disadvantage Families) through several stages. The results obtained based on analysis for recipient selection with a minimum performance index coverage value of 70% can be categorized as eligible to receiv assistance. In this study, 50 KM data samples were taken with the highest assessment value 128.41. In the top tenth ranking of the highest score from the 50 data held indicated that they were truly entitled to receive PKH KM financial assistance. Before using this method, only around 40% was eligible recipients.

Keywords


Algorithm; Composite Performance Index; Rank Order Centeriod; Selection Recipients

  
  

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doi  https://doi.org/10.33096/ilkom.v15i3.1614.465-472
  

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References


S. Prabowo and M. Abdurohman, “Studi Perbandingan Performa Algoritma Penjadwalan untuk Real Time Data Twitter pada Hadoop,” Komputika J. Sist. Komput., vol. 9, no. 1, pp. 43–50, 2020, doi: 10.34010/komputika.v9i1.2848.

Hastuti, Ruhmaniyati, and D. Widyaningsih, “Pelaksanaan PKH dan Program Sembako dalam Rangka Mitigasi Dampak Covid-19,” Catatan Penelit. SMERU, no. 2, pp. 1–8, 2020.

D. Domri, R. Ridwan, and M. Jaya, “Evektivitas program keluarga harapan dalam meningkatkan kesejahteraan masyarakat Abstrak Informasi Artikel,” J. Polit. dan Pemerintah. Drh., vol. 1, no. 1, pp. 1–16, 2019.

A. Juri, H. Maksum, W. Purwanto, and E. Indrawan, “Evaluasi Program Praktik Kerja Lapangan dengan Metode CIPP,” J. Penelit. dan Pengemb. Pendidik., vol. 5, no. 3, p. 323, 2021, doi: 10.23887/jppp.v5i3.38439.

A. Simangunsong, R. M. Simanjorang, and H. Fahmi, “Penerapan Metode Composite Performance Index Dalam Seleksi Penerimaan Calon Laboran,” J. Sist. Informasi, Tek. Inform. dan Teknol. Pendidik., vol. 1, no. 2, pp. 41–48, 2022, doi: 10.55338/justikpen.v1i2.8.

I. P. Pertiwi, F. Fedinandus, and A. D. Limantara, “Sistem Pendukung Keputusan Penerima Program Keluarga Harapan (PKH) Menggunakan Metode Simple Additive Weighting,” CAHAYAtech, vol. 8, no. 2, p. 182, 2019, doi: 10.47047/ct.v8i2.46.

Fitri Duwiyanti, “Sistem Pendukung Keputusan Pemilihan Guru Terbaik di SMK Pustek Serpong Dengan Menggunakan Metode TOPSIS,” Int. J. Educ. Sci. Technol. Eng., vol. 2, no. 1, pp. 45–67, 2019, doi: 10.36079/lamintang.ijeste-0201.18.

D. Ayudia, G. W. Nurcahyo, and S. Sumijan, “Optimalisasi Penentuan Kriteria Penerima Bantuan Program Indonesia Pintar dengan Metode TOPSIS,” J. Sistim Inf. dan Teknol., vol. 3, pp. 142–149, 2021, doi: 10.37034/jsisfotek.v3i3.58.

M. O. Esangbedo, J. Xue, S. Bai, and C. O. Esangbedo, “Relaxed Rank Order Centroid Weighting MCDM Method With Improved Grey Relational Analysis for Subcontractor Selection: Photothermal Power Station Construction,” IEEE Trans. Eng. Manag., vol. PP, no. September, pp. 1–18, 2022, doi: 10.1109/TEM.2022.3204629.

M. G. Seok and S. H. Choi, “Practical Simulation Budget Allocation for Ranked Subset Partitioning,” IEEE Access, vol. 11, no. September, pp. 104347–104358, 2023, doi: 10.1109/ACCESS.2023.3317283.

A. U. Haq, D. Zhang, H. Peng, and S. U. Rahman, “Combining Multiple Feature-Ranking Techniques and Clustering of Variables for Feature Selection,” IEEE Access, vol. 7, pp. 151482–151492, 2019, doi: 10.1109/ACCESS.2019.2947701.

I. M. Zubair and B. Kim, “A Group Feature Ranking and Selection Method Based on Dimension Reduction Technique in High-Dimensional Data,” IEEE Access, vol. 10, no. December, pp. 125136–125147, 2022, doi: 10.1109/ACCESS.2022.3225685.

A. I. Lubis, P. Sihombing, and E. B. Nababan, “Comparison SAW and MOORA Methods with Attribute Weighting Using Rank Order Centroid in Decision Making,” Mecn. 2020 - Int. Conf. Mech. Electron. Comput. Ind. Technol., pp. 127–131, 2020, doi: 10.1109/MECnIT48290.2020.9166640.

W. Maryono, E. Diana, Y. Darnita, R. Toyib, and B. Priyopradono, “Implementation of the K-Means Clustering Algorithm for Hope Family Program Participants Using Android-Based Retrofit Library,” 2021 9th Int. Conf. Cyber IT Serv. Manag. CITSM 2021, pp. 1–5, 2021, doi: 10.1109/CITSM52892.2021.9588844.

A. Andiyanto, “Selection Of Receipt Of Bpnt Pkh Aid Using Simple Additive Weight Method (Case Study of Jumo Temanggung District Office),” 2020, [Online]. Available: http://eprints.uty.ac.id/6306/.

T. Tuncer, “Intelligent centroid localization based on fuzzy logic and genetic algorithm,” Int. J. Comput. Intell. Syst., vol. 10, no. 1, pp. 1056–1065, 2017, doi: 10.2991/ijcis.2017.10.1.70.

M. Yedla, S. R. Pathakota, and S. T. M, “Enhancing K-means Clustering Algorithm with Improved Initial Center,” Int. J. Comput. Sci. Inf. Technol., vol. 1, no. 2, pp. 121–125, 2010.

M. Mughnyanti, S. Efendi, and M. Zarlis, “Analysis of determining centroid clustering x-means algorithm with davies-bouldin index evaluation,” IOP Conf. Ser. Mater. Sci. Eng., vol. 725, no. 1, 2020, doi: 10.1088/1757-899X/725/1/012128.

P. L. Kunsch and A. Ishizaka, “A note on using centroid weights in additive multi-criteria decision analysis,” Eur. J. Oper. Res., vol. 277, no. 1, pp. 391–393, 2019, doi: 10.1016/j.ejor.2019.02.021.

M. Tarmizi, L. Atika, and I. Seprina, “Decision Support System For Assessing Teacher Achievement Using The Composite Performance Index Method Bina Darma Conference on Computer Science,” Bina Darma Conf. Comput. Sci., pp. 414–423, 2005.

B. Satria, A. Sidauruk, R. Wardhana, A. Al Akbar, and M. A. Ihsan, “Penerapan Composite Performance Index (CPI) Sebagai Metode Pada Sistem Pendukung Keputusan Seleksi Penerima Beasiswa,” Indones. J. Comput. Sci., vol. 11, no. 2, pp. 566–576, 2022, doi: 10.33022/ijcs.v11i2.3056.

Z. Sipahutar, B. Nadeak, and P. Ramadhani, “Penerapan Metode Composite Performance Index (CPI) Dalam Penerima Bantuan Kelompok Usaha Bersama (KUBE),” J. Sist. Komput. dan Inform., vol. 2, no. 3, p. 255, 2021, doi: 10.30865/json.v2i3.2627.

B. Bin Dahlan, B. Betrisandi, and M. Diange, “Sistem Pendukung Keputusan Seleksi Beasiswa Prestasi Miskin Dengan Metode Composite Performance Index (CPI),” J. Nas. Komputasi dan Teknol. Inf., vol. 5, no. 1, pp. 1–13, 2022, doi: 10.32672/jnkti.v5i1.3849.

I. A. S. Dewi Paramitha, G. M. A. Sasmita, and I. M. S. Raharja, “Analisis Data Log IDS Snort dengan Algoritma Clustering Fuzzy C-Means,” Maj. Ilm. Teknol. Elektro, vol. 19, no. 1, p. 95, 2020, doi: 10.24843/mite.2020.v19i01.p14.

M. Mursalim, P. Purwanto, and M. A. Soeleman, “Penentuan Centroid Awal Pada Algoritma K-Means Dengan Dynamic Artificial Chromosomes Genetic Algorithm Untuk Tuberculosis Dataset,” Techno.Com, vol. 20, no. 1, pp. 97–108, 2021, doi: 10.33633/tc.v20i1.4230.

D. Pratama and A. Basry, “Rancang Bangun Sistem Perekomendasian Lokasi Usaha Menggunakan Metode Composite Performance Index Berbasis Laravel (Studi Kasus : Lokasi Usaha Di Jakarta),” Tekinfo J. Bid. Tek. Ind. dan Tek. Inform., vol. 23, no. 2, pp. 24–38, 2022, doi: 10.37817/tekinfo.v23i2.2594.

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.

A. Primandana, S. Adinugroho, and C. Dewi, “Optimasi Penentuan Centroid pada Algoritme K-Means Menggunakan Algoritme Pillar (Studi Kasus: Penyandang Masalah Kesejahteraan Sosial di Provinsi …,” … Teknol. Inf. dan Ilmu …, vol. 3, no. 11, pp. 10678–10683, 2020, [Online]. Available: http://j-ptiik.ub.ac.id/index.php/j-ptiik/article/download/6748/3264.

M. Mesran, J. Afriany, and S. H. Sahir, “Efektifitas Penilaian Kinerja Karyawan Dalam Peningkatan Motivasi Kerja Menerapkan Metode Rank Order Centroid (ROC) dan Additive Ratio Assessment (ARAS),” Pros. Semin. Nas. Ris. Inf. Sci., vol. 1, no. September, p. 813, 2019, doi: 10.30645/senaris.v1i0.88.

R. Kharisman Ndruru, “Penerapan Metode Additive Ratio Assessment (ARAS) dan Rank Order Centroid (ROC) Dalam Pemilihan Jaksa Terbaik Pada Kejaksaan Negeri Medan,” Semin. Nas. Teknol. Komput. Sains, pp. 367–372, 2020.


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