Decision Support System for Community Housing Subsidy Recipients

Adhi Nugraha a*, Alvian Widianto b, M. Irfan b, M. Nasar b, Merinda Lestandy c a Jurusan Teknik Industri, Fakultas Teknik, Universitas Muhammadiyah Malang, Indonesia Jl. Raya Tlogomas No. 246 Malang, Jawa Timur, Indonesia b Jurusan Teknik Elektro, Fakultas Teknik, Universitas Muhammadiyah Malang, Indonesia Jl. Raya Tlogomas No. 246 Malang, Jawa Timur, Indonesia c Jurusan D3 Teknik Elektronika, Fakultas Teknik, Universitas Muhammadiyah Malang, Indonesia Jl. Raya Tlogomas No. 246 Malang, Jawa Timur, Indonesia *Corresponding author: adhinugraha@umm.ac.id


Introduction
House is an essential primary need for humans. People think that owning a house is a long-term investment [1] [2]. The higher demand for housing has an impact on the higher house prices. This phenomenon decreases the purchasing power of people with income below the average. This problem has prompted the government to create a subsidized housing program. However, the implementation of the subsidized housing program often does not go according to plan. Identification and accuracy of recipients are the main problematic factors [3]. Most of the houses in the subsidy program were occupied by upper to middle-class owners. The main target of subsidized recipients is the lowermiddle class. An appropriate system for determining subsidy recipients is needed to assist in determining the recipient of subsidies. Therefore, the government is urged to find the proper procedure in determining the recipient of the subsidy. The use of the proper method can provide an alternative in making decisions. One alternative that can be developed is Human needs consist of primary, secondary, and tertiary needs. In primary needs, the house is one of the most critical primary needs in supporting one's life. However, not all residents in Indonesia can meet these needs. Therefore, the government provides subsidized housing ownership programs for people with low income. This study aims to propose a decision support system in determining the proper housing subsidy recipients. The method used in weighting is Analytic Hierarchy Process (AHP). Previous research was still limited to the selection of subsidized housing for developers and potential buyers. This method is projected to provide results in the form of a priority sequence of alternative solutions based on test results. The results were considered capable of providing a better solution for selecting prospective recipients of the housing subsidy program. Several previous studies have been very limited in discussing DSS issues in the housing sector as well as in terms of subsidy recipients. Nasibu [1] solved selecting mortgages using the Analytic Hierarchy Process (AHP) method. Oei [2] used the AHP and Borda methods in solving the DSS for home purchases. Another study was conducted by Hudaya [9], who discussed determining the eligibility of subsidies using the Adaptive Neuro-Fuzzy Inference System method.  [15] utilized AHP and Simple Additive Weight to select the best cost. AHP was then used by Rais [16] for the determination of strategic housing locations. Based on previous research, most studies generally discuss the problem of house selection. To the researchers' knowledge, there has been no research discussing DSS in the selection of recipients of subsidized housing assistance. Therefore, this study proposes a DSS to provide a solution to selecting subsidized housing recipients.
In DSS, the popular method used is AHP [2] [17]. AHP method is carried out based on Pairwise comparisons and a hierarchy of criteria [18]. This method is chosen because this method can solve complex problems with structured procedures. AHP aims to distribute subsidized housing assistance more targeted to the middle to lower economic class. The AHP method is implemented with the PHP programming language using three criteria: family dependents, income, and occupation. PHP programming is implemented to produce the right decision support application system for web-based subsidized home subsidy receivers [11] [19]. With the development of this DSS, it is hoped that housing subsidy recipients' selection process will be more straightforward and more targeted. This paper's composition is presented as follows: Research method and data collection are presented in section 2. Results and discussion, as well as system testing, are presented in section 3. Meanwhile, section 4 discusses the conclusions of the entire study.

Methods
At present, the process of allocating subsidized housing from the government is still not optimal. The selection process is considered to be unable to reach the people who need it. Many houses should be allocated to the middle to lower economic class but owned by the middle and upper economic classes. This case occurred because of the lack of data management carried out by the developers and government. Therefore, a DSS is needed so that subsidy recipients are more targeted. This subsidized housing selection process is a case study involving a variety of complex instruments. Seeing the urgency of this problem, a DSS is needed to help make appropriate decisions. AHP method is the proper method to be applied in problems with multi-object properties such as this problem [8]. This method can solve problems that have many alternatives and criteria that produce the best decisions.

Problem Analysis
In this subsection, this study proposes a block diagram to illustrate the pattern of the proposed DSS. The initial stage is determining criteria and identifying data. Some of the data required are National Identity Card Number, No-House Owning Certificate, Letter of Assistance Recipient, Taxpayer Identification Number, and Family Card Number. If the participant does not meet the initial qualifications, the participant cannot continue to the next stage. The second stage is filling out forms related to the criteria for selecting beneficiaries. In stage 2, several criteria and sub-criteria are used concerning the selection of housing subsidies. The criteria used are Family Dependents, which have five sub-criteria, income has three sub-criteria, and occupation has four sub-criteria. A more detailed description regarding the AHP process diagram can be seen in Fig. 1.
If the input process is correct and the applicable provisions can execute the AHP calculation process. The final result of the calculation is the ranking of potential beneficiaries.
The data processed in this study were derived from a questionnaire related to the process of selecting beneficiaries. The data were then converted into a Pairwise Comparison table by the provisions of Saaty [18]. For more apparent data, see Table 1 to Table 4.

Results and Discussion
This section describes implementing and testing the DSS for subsidized housing recipients using the AHP method. This section consists of program implementation, the weighting of criteria and sub-criteria, and system testing.
After the DSS was created, the next step was to implement a web-based application. Fig. 2 describes the user's home page. The homepage display has a menu of profiles (personal identity), documents (requirements for submitting subsidized housing), criteria (system support using the AHP method), and announcements (results of calculations carried out with several alternative recipients).

Fig. 2. User Home Page Eligibility (in Indonesian version)
The further stage was to fill in the user assessment page based on the existing selection criteria. There was a menu of options regarding Family, Income, and Occupation of Dependents on this page. Each of these menus has a choice of sub-criteria used. Users were asked to choose according to circumstances. This procedure is described in Fig. 3.
Using the web-based AHP program that has been created, this study determined each criterion and sub-criteria's weight. The results of weighting the criteria and subcriteria can be seen in Fig. 4 to Fig. 7. Fig. 4 shows that the "income" criterion was the criterion with the heaviest weight. The second rank was occupied by the criterion "Family dependents" and in the last rank was occupied by the criterion "Employment/Occupation". This result shows that income is the main criterion in selecting recipients of subsidized housing assistance.  Based on Fig. 5 to Fig. 7, subsidized assistance recipients were prioritized for communities with less than 1.5 million incomes with dependent children of more than 3. In addition, the selected occupation as a laborer was prioritized as a recipient. This of course illustrates that the target of the government is those who need assistance.

Weights of Criteria and Sub-Criteria
The application testing phase was carried out to determine the accuracy of the DSS design that has been utilized. This test required identity data. Identity data for DSS testing is presented in Table 5. Furthermore, the DSS determined alternative rankings as presented in Table 6.  Based on Table 6. the results of the subsidy acceptance test are represented in Fig.  8. The test is used to select seven primary candidates for subsidized housing recipients.

Conclusion
This study discusses the DSS in the selection of housing subsidies. This study implemented the Analytic Hierarchy Process (AHP) method based on the web. The results showed that income was the main criterion in selecting subsidized housing recipients, followed by family dependents and occupation criteria. The results also suggested that the DSS could be applied in the selection of subsidized housing assistance recipients. The future researcher suggests that it is necessary to consider other relevant criteria to select subsidized housing recipients. Furthermore, the characteristics of the information on the selection of subsidized housing recipients need to be considered in a fuzzy environment.