Penentuan Prioritas Kesejahteraan Keluarga Menggunakan Metode the Extended Promethee II

Masna Wati(1*); Ferry Miechel Lubis(2); Andi Tejawati(3);

(1) Universitas Mulawarman
(2) Universitas Mulawarman
(3) Universitas Mulawarman
(*) Corresponding Author



Indonesia is a developing country in which poverty is one of the problems faced by each province. The government continues to strive to overcome this problem of poverty to be able to create conditions for a prosperous society. The government's efforts to poverty alleviation are by providing some assistance programs. Therefore, it is necessary to build a decision support system that is useful to help the government to make a decision. This decision support system applies the EXPROM II (The Extended Promethee II) method with the weight of objective criteria. There are 15 criteria used based on SUSENAS data from the Statistics Indonesia of East Kalimantan Province. This research resulted in a decision support system that can give priority order of the level of family welfare so that it can be considered or referred by the local government or related agencies in distributing assistance to the society.


Poverty; family welfare; assistance; decision support system; EXPROM II


Full Text:


Article Metrics

Abstract view: 57 times
PDF view: 20 times

Digital Object Identifier




M. Wati and B. Cahyono, “Aplikasi Multi-Criteria Decision Making Penentuan Penerima Bantuan Sosial Santunan Warga Tidak Mampu Menggunakan PROMETHEE,” J. Rekayasa Teknol. Inf., vol. 2, no. 2, pp. 208–217, 2018.

E. Budiman, N. Dengen, Haviluddin, and W. Indrawan, “Integrated multi criteria decision making for a destitute problem,” Proceeding - 2017 3rd Int. Conf. Sci. Inf. Technol. Theory Appl. IT Educ. Ind. Soc. Big Data Era, ICSITech 2017, vol. 2018-Janua, pp. 342–347, 2018.

A. Kurniawan and Rianto, “Implementasi Sistem Pendukung Keputusan Penentuan Warga Miskin Menggunakan Metode Simple Additive Weighting (SAW) Seri Sains dan Teknologi E-ISSN 2615-4765,” J. Siliwangi Seri Sains dan Teknol., vol. 4, no. 2, pp. 72–77, 2018.

B. P. S. Samarinda, Kota Samarinda Dalam Angka 2018. Samarinda: BPS Kota Samarinda, 2018.

D. A. Ramdhan, D. Setyadi, and A. Wijaya, “Faktor-faktor yang mempengaruhi tingkat pengangguran dan kemiskinan di kota samarinda,” Inovasi, vol. 13, no. 1, p. 1, 2018.

M. Wati, “Analisis Metode Weighted Product dan Promethee Dalam Pemilihan Penerima Santunan Warga Tidak Mampu,” J. Rekayasa Teknol. Inf., vol. 3, no. 1, pp. 96–105, 2019.

S. Sarwosri, D. Sunaryono, R. J. Akbar, and R. D. Setiyawan, “Poverty Classification Using Analytic Hierarchy Process and K-Means Clustering,” in International Conference on Information, Communication Technology and System (ICTS), 2016, pp. 266–269.

A. Rusnawati, M. Wati, and H. J. Setyadi, “Sistem Pendukung Keputusan Penentuan Penerima Bantuan Sosial Daerah Kutai Kartanegara Menggunakan Metode TOPSIS,” JURTI, vol. 1, no. 2, pp. 160–169, 2017.

M. A. Saputera, A. Tejawati, and M. Wati, “Sistem Pendukung Keputusan Penentuan Penerima Bantuan Daerah Menggunakan Weighted Product,” Pros. Semin. Ilmu Komput. dan Teknol. Inf., vol. 2, no. 1, pp. 76–80, 2017.

A. Rambe, Alokasi Pengeluaran Rumah Tangga dan Tingkat Kesejahteraan. Medan: Universitas Sumatera Utara, 2011.

B. P. S. BPS, Indikator Kesejahteraan Rakyat 2018. 2018.

E. Budiman and N. Dengan, “Performance of Decision Tree C4.5 Algorithm in Student Academic Evaluation,” Lect. Notes Electr. Eng., vol. 488, pp. 380–389, 2018.

K. D. Maisari, D. Andreswari, and R. Efendi, “Pembobotan Entropy Untuk Penentuan Calon Penerima Bantuan Siswa Miskin (BSM) APBD Kota Bengkulu ( Studi Kasus : SMAN 8 Kota Bengkulu ),” vol. 5, no. 2, 2017.

M. Wati, N. Novirasari, and H. S. Pakpahan, “Evaluation of scholarly performance student using multi-criteria decision-making with objective weight,” Int. Electron. Symp. Knowl. Creat. Intell. Comput. IES-KCIC 2018 - Proc., pp. 56–61, 2019.

M. Wati, N. Novirasari, E. Budiman, and Haeruddin, “Multi-Criteria Decision-Making for Evaluation of Student Academic Performance Based on Objective Weights,” in the Third International Conference on Informatics and Computer, 2019, no. 11, pp. 1–5.

D. M. B. Tarigan, D. Palupi Rini, and Sukemi, “Particle Swarm Optimization – Based on Decision Tree of C4.5 Algorithm for Upper Respiratory Tract Infections (URTI) Prediction,” J. Phys. Conf. Ser., vol. 1196, no. 1, 2019.

Y. Gong, Y. Yu, K. Huang, J. Hu, and C. Li, “Evaluation of lithium-ion batteries through the simultaneous consideration of environmental, economic and electrochemical performance indicators,” J. Clean. Prod., vol. 170, pp. 915–923, 2018.

N. Dicky, Multi Criteria Decision Making (MCDM) pada Sistem Pendukung Keputusan. Yogyakarta: Deepublish, 2017.

L. T. Sianturi, A. Karim, A. Putera, and U. Siahaan, “Best Student Selection Using Extended Promethee II Method,” Int. J. Recent Trends Eng. Res., vol. 3, no. 8, pp. 21–29, 2017.

K. Palczewski and W. Sałabun, “Influence of various various normalization normalization methods methods in in PROMETHEE PROMETHEE II: an empirical study on the selection of the airport location an empirical study on the selection of the airport location,” Procedia Comput. Sci., vol. 159, pp. 2051–2060, 2019.

Y. Silalahi, M. Mesran, T. Zebua, and S. Suginam, “Penerapan the Extended Promethee II ( Exprom II) Untuk Penentuan Produk Diskon,” KOMIK (Konferensi Nas. Teknol. Inf. dan Komputer), vol. I, no. 1, 2017.

M. Wati, H. S. Pakpahan, and N. Novirasari, “Comparative Analysis of Multi-Criteria Decision Making for Student Degree Completion Time based on Entropy Weighted,” Proc. ICAITI 2018 - 1st Int. Conf. Appl. Inf. Technol. Innov. Towar. A New Paradig. Des. Assist. Technol. Smart Home Care, pp. 56–61, 2019.

M. Wati, Haeruddin, and W. Indrawan, “Predicting degree-completion time with data mining,” Proceeding - 2017 3rd Int. Conf. Sci. Inf. Technol. Theory Appl. IT Educ. Ind. Soc. Big Data Era, ICSITech 2017, vol. 2018-Janua, pp. 732–736, 2018.

Z. Saringat, A. Mustapha, R. R. Saedudin, and N. A. Samsudin, “Comparative Analysis of Classification Algorithms for Chronic Kidney Disease Diagnosis,” Bull. Electr. Eng. Informatics, vol. 8, no. 4, pp. 1496–1501, 2019.

S. Tabassum, M. B. B. G, and J. Majumdar, “Analysis and Prediction of Chronic Kidney Disease using Data Mining Techniques,” Int. J. Eng. Res. Comput. Sci. Eng., vol. 4, no. 9, pp. 25–32.


  • There are currently no refbacks.

Copyright (c) 2020 Masna Wati, Ferry Miechel Lubis, Andi Tejawati

Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

 ILKOM Jurnal Ilmiah indexed by


ILKOM Jurnal Ilmiah
ISSN 2548-7779
Published by Teknik Informatika Fakultas Ilmu Komputer Universitas Muslim Indonesia
W :
E :

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0