Learning Vector Quantization 3 (LVQ3) Usage To Determine Recipients of the Family Hope Program (Case Study: Tanjung Lubuk District)
Abstract
The problem of poverty is a dilemma that the Government must solve. One of the Government's programs is the welfare program for the Family Hope Program (PKH). Tanjung Lubuk district, implementing the Family Hope Program experienced several obstacles in identifying PKH recipients, one of which was selection, limited, and close to officers so that it could lead to the provision of PKH assistance on target. Another problem is that the recipients of the data used are still using old data that has not been updated regularly, so many people who deserve assistance do not receive assistance. The research variables used were 35 variables. The output categories were entitled to receive and not entitled to receive PKH. The research method uses Learning Vector Quantization (LVQ) 3. The data are from 654 low-income families in Tanjung Lubuk District. The data used are 90:10 for practice data and 80:10 for test data. The learning rate values are 0.1, 0.3, 0.5, 0.7, and 0.9, while the learning rate reduction is 0.1, the minimum learning rate is 0.01, the window is 0.1, 0.5, and the m value is 0.1, 0.5. The accuracy obtained is 94.4%.Downloads
References
D. J. S. K. Kementerian Sosial RI, “pedoman pelaksanaan PKH.pdf.” pp. 7–58, 2021.
V. C. Pamungkas, L. Muflikhah, and R. C. Wihandika, “Klasifikasi Penerimaan Program Keluarga Harapan ( PKH ) Menggunakan Metode Learning Vector Quantization ( Studi Kasus Desa Kedungjati ),” J. Pengemb. Teknol. Inf. dan Ilmu Komput., vol. 3, no. 3, pp. 2659–2666, 2019.
N. Aminudin, I. Ayu, and P. Sari, “Sistem Pendukung Keputusan (Dss) Penerima Bantuaprogram Keluarga Harapan (Pkh) Pada Desa Bangun Rejo Kec.Punduh Pidada Pesawaran Dengan Menggunakan Metode Analytical Hierarcy Process (Ahp),” J. TAM ( Technol. Accept. Model ), vol. 5, no. 2, pp. 66–72, 2015.
E. Y. Anggraeni, “Sistem pendukung Keputusan Penentuan Penerima Bantuan Program Keluarga Harapan (Pkh) Menggunakan Metode Topsis (Studi Kasus pekon Talang padang kabupaten Tanggamus),” J. Cendikia, vol. Vol. 20 No, no. 1, pp. 460–465, 2020.
Muslim Hidaya, “Penentuan Pemberian Bantuan Program Keluarga,” pp. 98–106, 2018.
N. Alfiah, “Klasifikasi Penerima Bantuan Sosial Program Keluarga Harapan Menggunakan Metode Naive Bayes,” Respati, vol. 16, no. 1, p. 32, 2021, doi: 10.35842/jtir.v16i1.386.
M. A. Tanjung, P. P, and H. Qurniawan, “Analisa Kelayakan Penerima Program Keluarga Harapan (PKH) Menggunakan Algoritma C4.5,” Jurasik (Jurnal Ris. Sist. Inf. dan Tek. Inform., vol. 6, no. 1, p. 217, 2021, doi: 10.30645/jurasik.v6i1.286.
A. Bahtiar and P. DP Silitonga, “Penerapan Algoritma Decision Tree Untuk Memprediksi Penerima Bantuan Keluarga Harapan,” J. ICT Inf. Commun. Technol., vol. 19, no. 1, pp. 70–76, 2020, doi: 10.36054/jict-ikmi.v19i1.93.
H. Harliana and S. Kirono, “Penerapan Learning Vector Quantization Dalam Memprediksi Jumlah Rumah Tangga Miskin,” J. Sains dan Inform., vol. 5, no. 2, pp. 118–127, 2019, doi: 10.34128/jsi.v5i2.192.
J. Jasril and S. Sanjaya, "Learning Vector Quantization 3 (LVQ3) and Spatial Fuzzy C-Means (SFCM) for Beef and Pork Image Classification," Indones. J. Artif. Intell. Data Min., vol. 1, no. 2, p. 60, 2018, doi: 10.24014/ijaidm.v1i2.5024.
E. Budianita, N. Azimah, F. Syafria, and I. Afrianty, “Penerapan Learning Vector Quantization 3 (LVQ 3) untuk Menentukan Penyakit Gangguan Kejiwaan,” Semin. Nas. Teknol. Informasi, Komun. dan Ind., no. November, pp. 69–76, 2018.
F. M. Putra and F. Syafria, “Penerapan Learning Vector Quantization 3 (LVQ3) untuk Mengidentifikasi Citra Darah Acute Lymphoblastic Leukemia (ALL) dan Acute Myeloid Leukemia (AML),” J. CoreIT J. Has. Penelit. Ilmu Komput. dan Teknol. Inf., vol. 4, no. 1, p. 27, 2018, doi: 10.24014/coreit.v4i1.6124.
R. Arifando, N. Hidayat, and A. A. Soebroto, “Klasifikasi Calon Penerima Bantuan Keluarga Miskin Menggunakan Metode Learning Vector Quantization ( LVQ ) ( Studi Kasus : Daerah Kecamatan Mlandingan , Situbondo ),” J. Pengemb. Teknol. Inf. dan Ilmu Komput., vol. 2, no. 6, pp. 2173–2181, 2018.
L. V FAUSETT, "Neural networks based on competition," _____. Fundam. Neural Networks Archit. Algorithms Appl. Englewood Cliffs Prentice-Hall, pp. 156–217, 1994.


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