Decision Support System for House Hunting: A Case Study in Chittagong

Mahmud, Tanjim; Sikder, Juel; Naher, Sultana Rokeya

doi:10.1007/978-3-030-63089-8_44

Cited by 13 publications

(14 citation statements)

References 3 publications

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“…We found that 80% of house hunters failed to meet the following criteria: pleasant neighborhood, proximity to stores, proximity to bus and rail stations, proximity to recreation center, police precincts, property insurance, and population density [2]. Qualitative and quantitative parameters such as proximity to a main road, a hospital, an office, a school, and cost per square foot [1] impact house hunting.…”

Section: Ahp For House Huntingmentioning

confidence: 99%

“…We just need to fill up the upper triangular matrix because the diagonal components of the matrix are always 1. The following two rules [1,20] are used to fill the upper triangular matrix:…”

Section: Ahp For House Huntingmentioning

confidence: 99%

“…It necessitates the measurement and evaluation of a large number of criteria at the same time. Because several of these criteria are linked, they frequently collide, with one improvement usually resulting to a decrease in another [1]. Furthermore, because house features are quantifiable and qualitatively expressed, decision-makers must consider both quantitative and subjective data [2].…”

Section: Introductionmentioning

confidence: 99%

“…Furthermore, because house features are quantifiable and qualitatively expressed, decision-makers must consider both quantitative and subjective data [2]. House hunting in Bangladesh is a terrible since various real estate businesses employ static ways to find houses in databases [1], such as the typical search methodology as shown in Fig. 1.…”

Section: Introductionmentioning

confidence: 99%

“…Many concepts have been proposed to address the home hunting dilemma but no model provides proper ranking or human level accuracy due to some limitation. Analytical Hierarchical Process technique can handle both quantitative and qualitative information [1,2]. A multiple criteria decision model with a hierarchical structure is provided for the house-buying process, in which both quantitative and qualitative information is represented in a combined manner [3,4].…”

Section: Introductionmentioning

confidence: 99%

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A Decision Concept to Support House Hunting

Mahmud¹,

Islam²,

Begum³

et al. 2022

IJACSA

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House hunting, or the act of seeking for a place to live, is one of the most significant responsibilities for many families around the world. There are numerous criteria/factors that must be evaluated and investigated. These traits can be both statistically and qualitatively quantified and expressed. There is also a hierarchical link between the elements. Furthermore, objectively/quantitatively assessing qualitative characteristics is difficult, resulting in data inconsistency and, as a result, uncertainty. As a result, ambiguity must be dealt with using the necessary processes; otherwise, the decision to live in a particular property would be incorrect. To compare criteria, the Analytic Hierarchy Process (AHP) is employed, evidential reasoning is used to evaluate houses based on each criterion, and TOPSIS is used to rank house sites for selection. It was necessary to analyze qualitative and quantitative elements, as well as economic and social features of these residences, in order to arrive at the final order of houses, which was not an easy process. As a result, the authors developed a decision support model to aid decision makers in the management of activities related to finding a suitable dwelling. This study describes the development of a decision support system (DSS) capable of providing an overall judgment on the location of a house to live in while taking into account both qualitative and quantitative factors.

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Section: Ahp For House Huntingmentioning

confidence: 99%

Section: Ahp For House Huntingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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