The Utility of Decision Tree and Analytics Hierarchy Process in Prioritizing of Social Aid Distribution due to Covid-19 Pandemic in Indonesia

Saucha Diwandari; Enny Itje Sela; Briyan Efflin Syahputra; Nathaniela Aptanta Parama; Anindita Septiarini

doi:10.5614/itbj.ict.res.appl.2023.17.1.6

Authors

Saucha Diwandari Faculty of Science and Engineering, Universitas Teknologi Yogyakarta, Jalan Siliwangi, Ring Road Road, Jombor, Sleman, Daerah Istimewa, Yogyakarta, 55528, Indonesia
Enny Itje Sela Faculty of Science and Engineering, Universitas Teknologi Yogyakarta, Jalan Siliwangi, Ring Road Road, Jombor, Sleman, Daerah Istimewa, Yogyakarta, 55528, Indonesia
Briyan Efflin Syahputra Faculty of Science and Engineering, Universitas Teknologi Yogyakarta, Jalan Siliwangi, Ring Road Road, Jombor, Sleman, Daerah Istimewa, Yogyakarta, 55528, Indonesia
Nathaniela Aptanta Parama Faculty of Science and Engineering, Universitas Teknologi Yogyakarta, Jalan Siliwangi, Ring Road Road, Jombor, Sleman, Daerah Istimewa, Yogyakarta, 55528, Indonesia
Anindita Septiarini Department of Computer Science, Universitas Mulawarman, Jalan Kuaro, Gn. Kelua, Kec. Samarinda Ulu, Kota Samarinda, Kalimantan Timur, 75123, Indonesia

DOI:

https://doi.org/10.5614/itbj.ict.res.appl.2023.17.1.6

Keywords:

analytical hierarchy process, classification, decision tree, ranking, social aid

Abstract

The Indonesian government provided various social assistance programs to local governments during Covid-19. One of the difficulties for the local governments in determining candidates for social aid is ensuring that the number of candidates is in balance with the available quota. Therefore, the local governments must select the most eligible candidates. This study proposes a priority model that can provide recommendations for candidates who meet the criteria for social assistance. The six parameters used in this study were: number of dependents, occupation, income, age, Covid status, and citizen status. The model operates in two stages, namely classification followed by ranking. The classification stage is conducted using a decision tree, while the ranking stage is performed conducted using the Analytical Hierarchy Process (AHP) algorithm. The decision tree separates two classes, namely, eligible and non-eligible. In addition, the classification process is also used to determine the dominant attributes and played a role in the modeling. The proposed model generates a list of the most eligible candidates based on our research. These are sorted by weight from greatest to most eligible using five dominant parameters: number of dependents, income, age, Covid status, and citizen status.

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