• International Journal of Technology (IJTech)
  • Vol 13, No 7 (2022)

Utilizing Building Information Modelling in the Tax Assessment Process of Apartment Buildings

Utilizing Building Information Modelling in the Tax Assessment Process of Apartment Buildings

Title: Utilizing Building Information Modelling in the Tax Assessment Process of Apartment Buildings
Mohammed Ali Berawi, Mustika Sari, Adinda Alya Salsabila, Bambang Susantono, Roy Woodhead

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Cite this article as:
Berawi, M.A., Sari, M., Salsabila, A.A., Susantono, B., Woodhead, R., 2022. Utilizing Building Information Modelling in the Tax Assessment Process of Apartment Buildings. International Journal of Technology. Volume 13(7), pp. 1515-1526

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Mohammed Ali Berawi 1. Department of Civil Engineering, Faculty of Engineering, Universitas Indonesia, Depok, 16424, Indonesia 2. Center for Sustainable Infrastructure Development (CSID), Universitas Indonesia, Depok, 1
Mustika Sari Center for Sustainable Infrastructure Development (CSID), Universitas Indonesia, Depok, 16424, Indonesia
Adinda Alya Salsabila Center for Sustainable Infrastructure Development (CSID), Universitas Indonesia, Depok, 16424, Indonesia
Bambang Susantono Center for Sustainable Infrastructure Development (CSID), Universitas Indonesia, Depok, 16424, Indonesia
Roy Woodhead Sheffield Business School, Sheffield Hallam University, Sheffield, S1 1WB, United Kingdom
Email to Corresponding Author

Abstract
Utilizing Building Information Modelling in the Tax Assessment Process of Apartment Buildings

The increasing demand for vertical residential development, particularly in urban areas, contributes to regional income growth through the collection of building taxes. In Indonesia, the vertical building is one of the non-standard objects applying an individual tax building assessment based on the building component cost list (BCCL) table in determining the value of the payable tax. However, the existing assessment system still cannot show the actual value of the building due to its limitations. Consequently, the building tax assessment process is ineffective and inefficient regarding assessment time and value accuracy. This study investigates the utilization of Building Information Modelling (BIM) in the assessment process of building taxation, considering a high-rise apartment building in Indonesia as the case study. The findings show that compared to the existing system, the final building value used as the basis in the tax assessment can be generated more accurately, involving a detailed calculation of dimensions and variations of building materials. It can be concluded that BIM’s capability to recognize building objects, extract quantity, and calculate automatically can help improve the objectivity of the assessment results and time efficiency in the tax assessment process.

Apartment; Building Information Modeling; Tax assessment

Introduction

The high rate of urbanization has increased the demand for housing in urban areas. However, this growth faces some challenges regarding physical infrastructure development, one of which is limited land availability (Qin & Wang, 2019; Habibi & Asadi, 2011). Some major cities in developing countries develop residential buildings in a vertical direction as one of the strategies to meet the housing needs of city inhabitants (Lau, 2011; Wong, 2004). In addition to solving the housing demand problem, these developments also bring a stream of income for regional governments through the tax on buildings (Berawi et al., 2021; Cho & Choi, 2014).

Based on the Law of the Republic of Indonesia Number 28 of 2009 concerning Regional Taxes and Levies, a vertical housing unit is indicated as a tax object, the tax imposition of which is determined through an individual assessment scheme. This building tax assessment is based on the building component cost list (BCCL), carried out by involving several documents, such as Tax Object Notification Letters, Tax Object Notification Letters’ Attachments, and Tax Object Worksheets. This assessment process needs to be conducted at least every three years to renew the selling value of the building (Asher, 2002). However, assessments are only done for new tax objects due to limited resources (Anwar, 2019).

Implementing the individual building tax assessment reports used by the appraisers from relevant agencies in the BCCL method is expected to enable the assessment results to be followed by performing the steps of the appraisal process. However, this assessment method has not fully answered the needs of appraisers or surveyors in following and reconstructing the assessment process because, in reality, the delivery of assessment results is still limited to verbal descriptions, writing, and images (Hendriatiningsih et al., 2019; Haldenwang et al., 2015). Furthermore, assessment using 2D images lacks accurate projection for the 3D physics of a building (Rajabifard et al., 2018; Shojaei et al., 2013).

3D visualization has been widely known to have the ability to show better accuracy in understanding and interpreting data, as well as displaying a more solid form, improving the delivery of information from existing physical buildings (Seipel et al., 2020; Hassan et al., 2008). Previous studies have supported this statement; Atazadeh et al. (2016) demonstrate how 3D digital data associated with various complex ownership spaces can be visualized and managed by developing a prototype Building Information Modelling (BIM) model for a multi-story building. Moreover, Atazadeh et al. (2021) also proposed a prototype BIM model showcasing that land administration and its registry information can be mapped into a 3D BIM environment.

Correspondingly, the building information’s completeness and disclosure from the 3D visualization can be utilized to improve the accuracy of the individual building tax assessment reports (Isikdag et al., 2014). On top of that, an assessment system with a high-speed updating process is required to support the accuracy of tax revenue assessment. Therefore, this study attempts to investigate the solution to the need for a relatively faster and more accurate updating process of building tax assessments by utilization of BIM technology. The fifth dimension of BIM was employed, which has the capability of design planning, cost estimation, and scheduling of a construction project (Kisel, 2021).

Previous studies have also explored the use of BIM-based 3D visualization in various areas of building cost estimation. El Yamani et al. (2019) demonstrated the potential of BIM as an emerging technology to improve the housing valuation system based on the hedonic approach, arguing that 2D applications are limited in communicating the complexity of a 3D building structure. Furthermore, Sladi? et al. (2020) proposed a more efficient process model for building a public registry in Serbia incorporating BIM-based 3D information. On the city scale, Arcuri et al. (2020) developed an automated calculation of the depreciated reconstruction cost (DRC) by integrating geographic information systems (GIS) technology and BIM 5D. However, minimal studies have been found to have compared the calculation of building valuation between the manual and BIM-based assessment methods. This study is expected to contribute to building valuation and tax assessment literature. 

Experimental Methods

    This study was conducted in two steps to obtain its research objective, adopting both qualitative and quantitative approaches. In the first step, the qualitative method was carried out through a literature study and in-depth interviews with experts to identify the variables from individual building tax assessments that can be integrated into BIM. Accordingly, the second step used the quantitative approach to utilize the BIM application as an alternative for apartment building tax assessments. The variables identified in the first step were used to perform cost calculations and BIM model prototyping, applied to the case study, an apartment building in Jakarta, Indonesia, called the MS apartment.

        The information from the BIM model is used as the basis for the building value calculation, conducted in several steps as implemented in Hendriatiningsih et al. (2019):

1)     Determining the construction work type based on data from the construction work unit, completed with material composition and coefficients.

2)     Specifying the cost of work types based on the volume calculated from the BIM model

3)     Selecting the building facilitiesprocurement cost from the information in BIM.

4)    Calculating the building’s Replacement Cost New (RCN), an estimate of the construction cost based on current labor and material prices for new construction of the same usability, size, and design. The construction work units issued by the Indonesian Ministry of Public Works were used to determine the price of building materials for each building component. The value obtained from the RCN calculation is then reduced by the depreciation value to get the final building value. The process is explained in Figure 1.

5)    Calculating the depreciation value (DV) using the Straight Line Method (SLM), based on the number of months computed using the following Equation (1):



6)        Calculating the building’s practical life (BPL) as one factor of physical depreciation, using Equation (2) below:          



 

7)        Calculating the final value of the building that becomes the building’s Sales Value of the Tax Object (SVTO), which is calculated using Equation (3).



After the building costs had been calculated using the BIM 3D model, a comparative analysis between conventional BCCL and the BIM-based methods was conducted. The collected primary and secondary data used in this study include:

1)    The apartment building’s tax assessment reports were obtained from the Office of Regional Tax and Levy Service at the sub-district level, where the apartment is located

2)    Building historical data of the case study in the form of geometric and non-geometric data obtained from the project construction service company

3)    Field survey data are taken from surveys and field documentation to supplement building information

Finally, in-depth interviews were conducted to validate and obtain feedback from building tax professionals (Berawi et al., 2019), particularly regarding the proposed BIM-based building tax assessment approach. Figure 1 shows the research workflow.


Figure 1 Research Workflow


Results and Discussion

3.1. Building Components for Tax Assessment Integrated into BIM

        The literature study conducted to determine the variables of building tax assessments that can be integrated into BIM examines the literature discussing the use of 3D variables in property valuation. The variables obtained are classified into indoor and outdoor variables. However, it was found that the BIM model is more suitable for reviewing indoor variables because it has semantic and geometric capabilities at the scale of building elements (Zhao, 2017; Domínguez et al., 2011). Therefore, the 3D building variables modeled in BIM significantly affect the building value for tax assessment were focused on indoor variables. It is in line with previous research on 3D modeling for property valuation, stating that 3D building variables considered in tax assessments were indoor structural variables, namely property geometry, size, level, cost, and quality. In contrast, the outdoor building variable is generally used for land tax assessment (Yamani et al., 2021; Arcuri et al., 2020).

        Moreover, a comparison between the data structure of the Tax Object Notice and the BIM model in Autodesk Revit was carried out to identify 3D building components for tax assessment handled in BIM applications. The specified building components and the identity data in the BIM model are summarized in Tables 1 and 2, respectively.

Table 1 Building Components for Tax Assessment in BIM Autodesk Revit

Building Components

1

Air terminals

11

Basement Floor Area

21

Gate

2

Ceilings

12

Flooring

22

Hot water system

3

Communication devices

13

Roof

23

Sewage treatment system

4

Electrical power

14

Structural column material

24

Artesian Aquifer

5

Genset equipment

15

Exterior wall material

25

Reservoir

6

Fire protection

16

Interior wall material

26

Swimming Pool

7

Lightning rod

17

Exterior wall coating material

27

Tennis Court

8

Number of building floors

18

Interior wall coating material

28

Road Pavement

9

Number of basements

19

Type and number of lifts

29

Sound System

10

Building area

20

Type and number of escalators

30

TV System

Table 2 Components’ Identity Data in BIM Autodesk Revit

Identity Data

1

Area

6

High

11

Type

2

Cost

7

ID Material

12

Volume

3

Count

8

Length

13

Work Breakdown Structure

4

Family

9

Level

14

Width

5

Family and Type

10

Material: Name

15

Total Cost (Customize)

3.2. Utilizing BIM for Tax Assessment of Apartment Building

3.2.1.  Developing 3D Model in BIM for Property Value

Historical data of the investigated apartment building, results of field surveys, and additional data collected were then inputted as the basis for developing a 3D model in Autodesk Revit as the BIM tool used in this study. In the early modeling stages, the BIM model’s objectives and detail need to be defined. In this study, BIM modeling is intended to estimate the RCN of a building; therefore, the approach used is the BIM 5D, which can estimate building costs (Reizgevi?ius et al., 2018). The accuracy of the information used and the model’s ability to meet this objective need to be adjusted to a specific Level of Development (LOD) (Latiffi et al., 2015). Therefore, the LOD 300 was used in this study for its ability to define the approximate quantity, size, shape, and location, making its model components expressed with the correct dimensions in a precise position.

The BIM model development was started by determining the constituents of building information, which include the main building components, material components, facility components, datum elements, and annotation elements. Consequently, data on the determined components and features were then collected from the 2D and 3D technical drawing documents of the MS Apartment project. The identities of building components used in the BIM modeling in this study include the size data of the building components, work unit price analysis, Material ID, and the WBS code. Building component size data were obtained automatically from the BIM model quantity extraction results. Meanwhile, the identity data for analysis of work unit prices, Material IDs, and WBS codes used were generated from the MS Apartment project documents.

In the BCCL assessment, the structural component of a building has become an integral part of the main building; therefore, the structure’s modeling for the building valuation was not carried out in this study. Furthermore, there was a lack of information obtained for facility components. Consequently, the values for the main structure and facility components used as the assumption were adopted from the assessment reports manually submitted in the BCCL method. Hence, the comparative data in this study was conducted for the value of building components consisting of inner wall materials, inner wall cladding, outer wall materials, outer wall cladding, ceilings, roof coverings, and ceiling coverings. Figure 2 shows the process of developing the BIM model.


Figure 2 The Process of 3D Modeling in BIM Revit

The BIM model was developed starting from the building components, such as walls, floors, and the roof system, followed by the identity data. The 3D model of three apartment floors being developed in BIM with its identity data is shown in Figure 3.

 

 

Figure 3 Inputting identity data to the floor components of the 3D model in BIM Revit

Moreover, the BIM 5D can estimate building costs through automatic quantity extraction in Revit and can be used to display information on the take-off material from 3D models. The non-graphical data from the 3D model was extracted and generated as tabular data, which was then exported into a spreadsheet application. Figure 4 shows the information display generated for the floor material from the third basement to the ground floor.


Figure 4 Information display for the floor material in BIM Revit

Figure 5 shows the 3D model fully developed in BIM 5D. The utilization of a BIM-based 3D model in calculating the building value based on its geometric form in the model and the cost aspect is discussed in the next section.


Figure 5 3D Model of MS apartment building developed in BIM Revit

3.2.2.  Comparative Analysis of Property Value Between BIM-based and Manual Methods

        The building component costs in the BIM method were calculated based on their volume on the BIM 3D model. The comparative analysis of the building component costs from both the BCCL and BIM-based calculations is detailed in Table 3 below.

Table 3 The Calculation of Building Component Cost

BCCL

 

BIM

Material Name

Total Cost

 

Material Name

Total Cost

Interior Wall Material

 

Interior Wall Material

Half Brick Wall

IDR 8,234,284,604

 

75mm lightweight brick

IDR 3,899,640,972

 

100mm lightweight brick

IDR 5,354,063,067

 

125mm lightweight brick

IDR 734,828,187

 

6mm Calciboard

IDR 29,900,811

 

GRC

IDR 31,536,741

 

9mm Gypsum

IDR 14,200,268

 

9mm Gypsum WR

IDR 810,925

Interior Wall Coating Material

 

Interior Wall Coating Material

Paint

IDR 868,624,750

 

Interior Paint

IDR 1,588,205,928

 

Oil Paint

IDR 305,409,148

 

Ceramics

IDR 27,074,143

 

Homogeneous Tiles 1

IDR 28,531,748

 

Homogeneous Tiles 2

IDR 7,006,202,673

 

Homogeneous Tiles 3

IDR 39,906,667

Granite

IDR 329,440,860

 

Metal Ceiling

IDR 106,887,500

 

Teracota

IDR 426,462,636

 

Andesite

IDR 221,935,248

 

Marble

IDR 2,683,915,511

 

Artificial Wood

IDR 218,917,455

Exterior Wall Material

 

Exterior Wall Material

Precast Concrete

IDR 36,029,657,496

 

Precast Concrete

IDR 15,562,370,996

 

8mm GRC Panel

IDR 6,998,061,906

Exterior Wall Coating Material

 

Exterior Wall Coating Material

Paint

IDR 3,146,615,010

 

Exterior Paint

IDR 659,703,270

Ceiling

 

Ceiling

Gypsum

IDR 25,129,980,120

 

9mm Gypsum

IDR 9,419,550,533

 

9mm Gypsum WR

IDR 2,739,888,661

 

Skimcoat

IDR 533,879,627

 

Aluminium Composite

IDR 279,303,712

 

Metal Ceiling 1

IDR 7,202,301,600

 

 

 

Metal Ceiling 2

IDR 482,104,714

Roof

 

Roof

Concrete

IDR 357,347,956

 

Concrete

IDR 1,105,887,724

Flooring

 

Flooring

Cement

IDR 469,759,360

 

Andesite

IDR 1,393,777,170

Loka Marble

IDR 1,410,347,500

 

Coral Stone

IDR 16,084,813

Stone CERAMICS

IDR 7,388,719,632

 

Cement

IDR 698,769,837

 

Ceramics 1

IDR 153,310,189

 

Ceramics 2

IDR 43,764,400

 

Floor Hardener 1

IDR 221,489,592

 

Floor Hardener 2

IDR 455,135,570

 

Homogeneous Tiles 1

IDR 8,028,604,946

 

Homogeneous Tiles 2

IDR 56,977,275

 

Homogeneous Tiles 3

IDR 5,328,471

 

Pebble Stone

IDR 414,315

 

Artificial Wood

IDR 27,092,428

 

Marble

IDR 506,883

 

Gutter Grill

IDR 17,261,100

        Table 4 compares the component costs of the building’s RCN value used as a constituent of the building tax expected value and the existing BCCL method.

Table 4 Comparison of Apartment’s RCN Value between BCCL and BIM-Based Methods

No.

Building Component

Building’s RCN Value

BCCL Method

BIM-Based Method

1

Main components

IDR 253,933,278,610

IDR 253,933,278,610

2

Interior wall material

IDR 8,234,284,604

IDR 10,064,980,971

3

Interior wall coating material

IDR 1,198,065,610

IDR 12,653,448,657

4

Exterior wall material

IDR 36,029,657,496

IDR 22,560,432,902

5

Exterior wall coating material

 IDR 3,146,615,010

IDR 659,703,270

6

Ceiling

IDR 25,129,980,120