Seleksi Penerima Bantuan Pangan Non Tunai di Desa Menggunakan Metode Naïve Bayes dan Simple Additive Weighting
DOI:
https://doi.org/10.30646/sinus.v19i1.525Keywords:
naïve bayes, simple additive weighting, bantuan pangan non tunaiAbstract
Poverty is one of the problems experienced by some developing countries, including Indonesia. There are many ways to mitigate poverty, for example, Indonesian government policy overcome this situation by Non-Cash Food Aid Program (BPNT). The electoral candidate for BPNT in the rural area is carried out by Poverty Reduction Team (SATGASKIN). To avoid uneven and untargeted assistance with the process, a system is capable for addressing the matter. The selection methods in this research were Naive Bayes and Simple additive weighting. The purpose of this research was to design and build an application that provided convenience to SATGASKIN in determining the eligibility of prospective beneficiaries and prioritizing beneficiaries. As a result of the study, the system can be used by SATGASKIN to help determining the recipients’ eligibility with 85% accuracy value, 85.71% Precision, and 92.31% Recall. Naive Bayes and Simple Additive Weighting (SAW) methods reached 100% according to the results by manual calculations.
References
Annur, H. (2018). Klasifikasi Masyarakat Miskin Menggunakan Metode Naive Bayes. ILKOM Jurnal Ilmiah, 10(2), 160–165. https://doi.org/10.33096/ilkom.v10i2.303.160-165
Arianto, S. R., Siswanti, S., & Saptomo, W. L. Y. (2020). Sistem Pendukung Keputusan Penerima Bantuan Pangan Non Tunai Dengan Metode Hybrid AHP - SAW. Jurnal Transformatika, 17(2), 200. https://doi.org/10.26623/transformatika.v17i2.1733
Kusumadewi, S., Hartati, S., Harjoko, A., & Wardoyo, R. (2006). Fuzzy Multi-Attribute Decision Making (Fuzzy MADM). Graha Ilmu. https://opac.perpusnas.go.id/DetailOpac.aspx?id=718512
Lestari, U., & Kristiyana, S. (2013). Rancang Bangun Mobile Tracking Application Module untuk Pencarian Posisi Benda Bergerak Berbasis Short Massage Service (SMS). Seminar Nasional Teknologi Informasi Dan Komputasi 2013 (SENASTIK 2013), 2013, 30–31.
Nasution, S. R., Andreswari, D., & Wahyu, T. (2019). Implementasi Naïve Bayes Classifier dan Simple Additive Weighting (SAW) untuk Pemilihan Menu Diet Penyakit Diabetes Mellitus. Jurnal Rekursif, 7(1). http://ejournal.unib.ac.id/index.php/rekursif/1
Nofriansyah, D., & Nurcahyo, G. W. (2019). Algoritma Data Mining Dan Pengujian. Deepublish. https://books.google.co.id/books/about/Algoritma_Data_Mining_Dan_Pengujian.html?id=Fn-QDwAAQBAJ&redir_esc=y
Pedoman Umum Bantuan Pangan Nontunai 2019. (2019). Kementerian Koordinator Bidang Pembangunan Manusia dan Kebudayaan.
https://www.kemsos.go.id/uploads/topics/15767284433221.pdf
Saleh, A. (2015). Implementasi Metode Klasifikasi Naïve Bayes Dalam Memprediksi Besarnya Penggunaan Listrik Rumah Tangga. Citec Journal, 2(3), 207–217. https://citec.amikom.ac.id/main/index.php/citec/article/view/49
Downloads
Published
How to Cite
Issue
Section
License
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).
Â
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
