(IJACSA) International Journal of Advanced Computer Science and Applications,
Vol. 10, No. 10, 2019
232 | P a g e
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Developing Agriculture Land Mapping using
Rapid Application Development (RAD):
A Case Study from Indonesia
Antonius Rachmat Chrismanto
1
, Rosa Delima
4
Program Studi Informatika
Universitas Kristen Duta Wacana
Yogyakarta, Indonesia
Halim Budi Santoso
2
, Argo Wibowo
3
Reinald Ariel Kristiawan
5
Program Studi Sistem Informasi, Universitas Kristen Duta
Wacana, Yogyakarta, Indonesia
Abstract—The use of Information and Communication
Technology (ICT) in agriculture has become one of the steps to
improve agricultural efficiency, effectiveness, productivity, and
also expected to encourage the creation of Precision Agriculture.
Precision agriculture has an impact on the efficiency of
operational costs to increase margins in the production of
agricultural products using ICTs. One of the problems that often
arise in agriculture is related to the management of agricultural
land in each farmer group area. This information is closely
related to the needs of agricultural production facilities and
infrastructure, such as the need for fertilizers, seeds, and other
resources. Web Mapping System is one of the systems to assist in
land or area mapping. In this study, the Web Mapping System is
expected to be used to help at agricultural land mapping, owned
by farmer members of farmer groups. The developed system will
store spatial data from farmland members and farmer groups.
The Web Mapping System was developed using the Rapid
Application Development (RAD) method, where there are several
iterative processes. The result of this study is the Web Mapping
System for agricultural land. With this application, farmers can
find out the status of the land being cultivated or owned. In
addition, the Web Mapping System can record the status of the
existing land in a farmer group and the need for agricultural
production facilities and infrastructure. Further, the Web
Mapping System also provides information in a dashboard that
can help farmer groups to manage the land owned by each
farmer who is a member of the group.
Keywords—Farmland; precision agriculture; land mapping
system; dashboard; software development
I. INTRODUCTION
Agriculture is one of the focused fields of development in
Indonesia. Various technologies in agriculture are developed to
improve agricultural efficiency, effectiveness, and productivity.
Information and communication technology (ICT) is used in
the development of information systems for agriculture.
Agricultural Information System (AIS) covers a variety of
related systems, ranging from land preparation, systems for
farmers’ data collection, agricultural activities, systems for
land management, agricultural activities, crop sales and
purchase systems, learning systems for farmers and farmer
groups. The development of AIS has done quite a lot in various
regions in Indonesia, but most of the existing systems are local
and not integrated.
The development of information systems in agriculture has
been carried out by a development team from the Information
Technology Faculty (FTI) of Duta Wacana Christian
University (UKDW) since 2016. To conduct research related to
the development and application of Information Technology in
agriculture, a study is first carried out to see the readiness of
the Indonesian agricultural community in the use of
Information Technology [1] and several applications in
agriculture that have been carried out [2]. After that, an
integrated SIP blueprint was developed by developing
Architecture Vision [3], Business Architecture [4], and
defining integrated AIS stakeholders [5]. Besides, there are
several systems developed, such as the Agricultural Portal [6],
Farmer and Farmer Groups Information System [7], Farmers
Activity Information System [8], and Information System of
Agricultural Products’ Purchases and Sales [9]. Three of the
four systems developed are ready to be applied in the
community. Three systems that have been developed can be
accessed via the website at http://dutatani.id [6].
Along with the application of the three existing systems,
the next stage of the research to be carried out is to develop a
system for mapping of agricultural land and agricultural
activities carried out by farmers. The development of this
system was carried out because there were problems faced by
farmer groups in processing land ownership data, seed
requirements, and the estimated amount of agricultural
productivity. The manual data processing makes it difficult for
farmer groups to produce information related to land area,
identification of needs, and level of agricultural production in
their area. Indeed, information is needed for a variety of needs
including agricultural quality assurance, preparing the needs of
seeds, fertilizer, and other resources supporting the agricultural
process.
To help farmer groups in overcoming the problem, a
system for land mapping and data collection on agricultural
activities was developed. This system is developed by Rapid
Application Development (RAD) method and is intended to
produce spatial information related to land use and agricultural
activities that are being carried out. The system is able to
integrate various data and display information in spatial form.
Therefore it facilitates the analysis process and helps
agricultural stakeholders to understand the data. The use of
RAD is based on the suitability of sequential and iterative or
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incremental model characteristics in the process of developing
software prototypes. This method is also used in many studies,
as in [10].
This paper specifically discusses the process of developing
agricultural land mapping systems and dashboards as a user
interface between agricultural stakeholders and the system. The
paper consists of five parts, preceded by an introduction,
followed by a literature review in section II. The application of
the RAD method can be seen in Section III, followed by the
results and discussion in section IV, and the paper is closed
with the conclusion and future work in section V.
II. LITERATURE REVIEW
A. Precision Farming
Precision agriculture is one of the capabilities to handle
various activities related to productivity on agricultural land
and increase financial benefits, reduce residual production, and
minimize impacts on the environment by using data collection,
and utilizing the information for strategic decisions on
agricultural management using information and
communication technology [10]. The use of Information and
Communication Technology (ICT) in precision agriculture
supports the determination, analysis, and arrangement of
changes in agriculture for optimal benefits, sustainability, and
preservation for agriculture [11].
Precision agriculture has a good impact on the agriculture
sector. Approaches using precision agriculture help to reduce
costs and maximize yields [12]. Cost reduction and increased
yields encourage increased profits for farmers. The application
of precision agriculture also encourages agricultural
operational efficiency, particularly for the use of fertilizers and
pesticides [13]. This encourages the creation of environmental
sustainability and reduces the adverse effects of the use of
pesticides and fertilizers. The benefits above are also one of the
driving forces that make actors, especially farmers, to
implement precision agriculture [11].
B. Web Mapping System for Indonesian Land Mapping
One application of Information Technology for the
agricultural sector is a system for mapping agricultural land.
With the land mapping system, spatial data generated is needed
for farmers to support the creation of precision agriculture [14].
This system is one step that can be used to map existing
agricultural land. The mapping of agricultural land to support
precision agriculture was started in 2002 to map fertilizer needs
in each of the existing regions [15]. Using this system, fertilizer
needs in each agricultural location can be identified more
easily. This is certainly considered to support efficiency in
managing fertilizer needs [15].
With the development of a mapping system website for
agricultural land, there will be operational cost efficiency and
also the effectiveness of costs incurred [16]. In addition, this
land mapping system can also support land management and
reduce neglected agricultural land [17]. Geospatial analysis
and prediction models can also be produced by land mapping
systems that can be used for agricultural land management
[14]. By using a Land Mapping System (SPL) that has spatial
data, the system can help to give farmers the ability to visualize
their land and crops. The use of spatial data in agriculture can
also help farmers to understand their agricultural land better
and provide information that can support decision making [14].
C. Rapid Application Development (RAD) Methodology
According to Denis [18], RAD is a collection of methods
developed to overcome the weaknesses of traditional
development systems, such as the Waterfall model and its
variants. Through a RAD process, organizations can reduce
development and maintenance costs [19]. The method used in
RAD cycles also provides good software quality compared to
the traditional development method approach.
RAD was first introduced by James Martin in the 90s.
James Martin believes that the RAD model is more flexible
and adaptable to changing user demands and needs and ensures
the quality of rapid development with minimal costs [20]. In its
application, RAD emphasizes a short planning process by
focusing on the software development process, which consists
of the development, testing, and reciprocity [21]. The stages of
developing a RAD – based system can be seen in Fig 1.
D. Convex Hull
A convex polygon, where each inner corner is less than or
equal to 180 degrees, is a simple polygon whose interior is a
convex set. This means that all vertices of the polygon will
point outward, away from the interior of the field [22].
A subset S of a plane is called convex (Fig. 2) if and only if
for each pair of points p, q S the line portion 
is contained
entirely in S. More precisely, as illustrated in Figure. 3.
convex hull is the meeting point of all convex sets containing S
[23]. Besides, the convex hull can also be applied to 3D fields
such as in Fig. 4 which shows the results.
Fig. 1. RAD Development Process.
Fig. 2. Convex Example [23].
Fig. 3. Convex Hull 2D [23].
This research is funded by The Ministry of Research, Technology and
Higher Education.
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Fig. 4. Convex Hull 3D [23].
Calculating the convex hull is one of the problems in the
calculation of geometry. According to Zhongliang Fu, et al.
[24] , practically convex hull is widely used in recognizing
patterns, image processing, statistics, and GIS. It also used to
reconstruct geometric fields. The minimum convex hull of a set
of points is a requirement of a GIS application (Fig. 5), such as
dynamic area calculation, TIN, and area change.
E. Graham’s Scan
The name Graham’s Scan was given in a journal about
efficient algorithms for the planar field case, which was
published in 1972 by a mathematician named Ronald Lewis
Graham. According to a book written by Cormet et al. [25].
The algorithm is a rotational sweep algorithm with good
performance characteristics. Because of its speed, Graham’s
Scan is among the most popular in the search for the convex
hull in the planar field.
The algorithm has several variations, but the original
version runs in 3 phases:
1) Prepare a set of points as input.
2) Calculates the initial hull.
3) Sweeping to check one by one on the points in order
and check whether it is included in the hull.
The first step in preparing a collection of input points is to
choose a pivot point for the algorithm. This pivot is usually at
the lowest point, then the leftmost in the collection. This point
is definitely included in the convex hull [26]. All other points
are then sorted by the pivot point as the center. Points that have
identical angles are eliminated, the initial starting point from
the pivot point is taken, which is the furthest point with the
largest angle from the pivot point [25].
The starting hull is simply calculated starting from the pivot
point and with 2 starting points that are in a collection of saved
and sorted points (P1 and P2). The initial hull was considered
as the current hull, which will be updated throughout the
algorithm. The sweeping phase considers points in a set of
points that have been sorted one by one. For each existing
point, it will be determined whether adding this point to the
current hull will result in a non-left turn. If the point causes a
non-left turn or not, the last point will be removed, and the
direction of the turn will be tested again. Turn points are
illustrated as in Fig. 6. This continues until you get a left turn,
the point will be entered into the current hull. This is repeated
until the saved, and sorted points are finished (Fig. 7.) [25].
This figure is modeled Graham’s Scan Process [27].
Fig. 5. Convex Hull Usage on Application.
Fig. 6. Left Curve and Right Curve [28].
Fig. 7. Graham’s Scan Process [27].
F. Google Maps API
Quoted from Google [28], the Google Map API is a free
virtual world map service available online from Google.
Google Maps can be opened at the following address
https://www.google.com/maps. Google Maps has a feature that
can display maps from all over the world, at various scales, and
photos of the world from satellites for the whole world in the
form of maps. There is also the Google Street View, which
provides services to explore the streets with a series of
photographs. In addition, it also provides location search and
information from a place, travel route, measuring distance from
one point to another, view traffic information, save certain
places, and place ratings and reviews.
The online API map from Google provides variations to be
added to the online map that will be displayed on a web page.
As on the example, it can provide variations such as adding
markers to a point on the map, which will later be used as a
land pointer. The marker can also be added to events, such as if
it’s clicked, it will bring up the info window as an additional
dialog box that points to the marker that was clicked. Then
Google Maps also provides variations to make polyline to
make lines, polygons to create fields that are formed with many
points, other shape fields, and various other variations. The
Polygon will be used to describe agricultural land.
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III. RESEARCH METHODOLOGY
The research carried out applies the RAD software
development model. The way to apply the RAD model is to
combine sequential development techniques and prototyping
systems. The dashboard development process is carried out
through several stages, such as planning, analysis, design, and
manufacture, system testing, and ending with the process of
system integration into the dutatani portal. The stages of
developing a Web Mapping System can be seen in Fig. 8.
In Fig. 8 it can be seen that in general, the process is
divided into 2 stages, such as the sequential development stage,
the initial process of planning, data collection, and user
requirements analysis. After that, the application development
process is continued by means of an iterative and incremental
prototyping system. The prototyping system consists of design,
coding, and testing activities. A system prototype was
produced through this process. As a final activity, an
evaluation of the system and integration of the system into the
main Dutatani portal is carried out.
A. Planning
Planning is the initial stage in the system development
process. This stage consists of planning the time and resources
needed for system development. The system was developed
with PHP and MySQL programming languages as the database
with 5 people involved in this research.
B. Data Collection
The data in this study is used in the information system
website and recording dashboard, including farmer data, farmer
group data, land data, land detail data, species data, land
planting data, farmer membership data, land ownership data,
and user data and user category data. Most of the data obtained
from the database of the main website Dutatani.id system. The
data structure obtained from the Dutatani database is as
follows: farmer data, farmer group data, farmer membership
data, user data, user category data, category type data, plant
species data, and regional data. Most of them already have
data, but for user data, farmer data, farmer group data,
membership data are obtained from Tani Harjo and Tani
Rahayu farmer groups. Land data and data structures were
obtained from data belonging to Tani Harjo and Tani Rahayu
farmers groups.
Land data is also obtained from farmer groups. Using the
data obtained, a data structure is created in the database that
adjusts the data. Land data, land point data, land planting data,
and land photo data are obtained. For land point data and land
point detail, it is done by recording using the application
directly in the rice fields in Gilangharjo, Pandak, Bantul,
Special Region of Yogyakarta, guided by the committee of
Tani Harjo farmer group to identify the land and match it with
the Google Map online map in the system.
The data that has been obtained is then inputted into the
system and then processed by the system to be displayed as a
dashboard for calculating land recording and 2 main types of
land mapping maps, such as a combined land map and a land
distribution map.
Fig. 8. Research Methodology.
C. User Requirements Analysis
The analysis phase is carried out to be able to understand
the conditions that apply and identify the system requirements.
Before conducting the analysis, the process begins with
gathering needs. Techniques used for gathering needs include
interviews, questionnaires, and surveys of land mapping
systems that have been developed before. Interviews were
conducted through small group discussions with system users.
Interviews are intended to get the features and services needed
by users. Interviews were conducted with farmer group
coordinators and farmer group members of Tani Rahayu and
Tani Harjo farmer groups. To get the characteristics of users,
data collection is done through questionnaires. There were 36
respondents who participated in filling out the questionnaire.
After the data is collected, an analysis is carried out to
formulate the functional requirements of the system. The
analysis produces a description of the user’s characteristics and
a list of system requirements. Based on the collected data, the
characteristics of the user of the system is obtained as follows.
1) The average age of farmers is 51 years with experience
working on rice fields of approximately 25 years. This
identifies that the farmer has been trained and has enough
experience in managing agricultural land. The work of farmers
becomes the main work. Only 15 respondents answered that
their job as a farmer is as a side job.
2) Farmers in Gilangharjo manage an average land area of
2000 m2 per farmer. This land is mostly planted with rice
types such as mentik wangi and mentik susu rice. In one year,
farmers have 3 growing seasons, where 2 times are planted
with rice and 1 time planted with corn, soybeans, beans, and
others. This land is mostly privately-owned land with an
income of less than 5 million rupiah.
3) Seen from their educational background indicates that
almost 50% of farmers did not graduate from elementary
school or only graduated from elementary school. This, of
course, will also have an impact on the use and application of
technology to assist production and management in this sector.
It needs to build the system which is user friendly and easy to
use.
D. Main Design
The main design for the development of the Web Mapping
System is the development of use case diagrams based on the
functional requirements of the Web Mapping System, as
follows:
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1) The Web Mapping System is capable of recording and
managing land data, farmer data, and data of planting in that
land.
2) The Web Mapping System has an online map provided
through the API service by Google Maps, which will have
farmers’ land distribution points.
3) The Web Mapping System has info-graphics that
display online maps and distribution data.
4) Web Mapping System has filters that can categorize
data that will come out on maps and info-graphics.
5) The Web Mapping System can provide statistical
calculations from existing land, agriculture, and planting data,
which will then be displayed on an infographic dashboard.
The functional needs as the results of the design process are
illustrated in the Use Case diagram, as shown in Fig. 9.
Fig. 9 explains the use case diagram of the Web Mapping
System for farmland. There are 2 actors, such as the admin
who is the representative or administrator of the farmer groups
and farmers. The admin is actually a farmer who was appointed
to be the committee of a farmer group. As an admin, there are
several functional things that can be done, such as accessing
land combined maps, accessing land distribution maps,
managing land ownership, and accessing the dashboard of the
existing system. Whereas farmers have the functions to make
land arrangements, look at land lists, manage land point details,
record/organize land planting, view land photos, and arrange
land photos. To be able to run the features in the system, you
need to log in first, either as farmer group’s admin or farmer.
E. Detail Design
The detailed design of the system is done by using several
diagrams, such as the Entity Relationship Diagram, Diagram,
and Data Flow Diagram. The Entity Relationship Diagram in
Fig. 10 explains the relationships between entities in the
database used in this study. The schema of the relations in this
diagram is used in the recording system and is used in
determining simple calculations to be displayed in the
Agricultural Land Web Mapping System.
Figure 10 shows the entity relations in the Web Mapping
System. There are 17 tables in the ER Diagram. In carrying out
land recording, the system will relate to the land ownership
recorded in the system. It also relates the land with each detail
point, planting, photos. Planting data also has a relation with
saprotan (infrastructure for agricultural production) unit data to
limit and find out what saprotan (infrastructure for agricultural
production) units are available and can be used in recording
land planting. In planting, it also records plant species that are
related to the information of the plant species that have been
stored previously in the main system.
Relationships between farmers and user accounts and
categories are also interrelated to indicate the category of the
user, whether he is a farmer or an admin who will differentiate
his rights in the application. It also takes note of the
membership of farmers in farmer groups by looking at the
relationship between farmers and their registration in the
farmer groups. In addition, there is also a relationship that
shows the farmer who functions as a contact person of the
farmer group.
Fig. 9. Use Case Diagram.
Fig. 10. Entity Relationship Diagram Web Mapping System.
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F. Data Flow and Process Design
1) Overall process in the system: Fig. 11 explains Data
Flow Diagram Level 0 (Context Diagram) from the Web
Mapping System. Data flow diagram/DFD is used to describe
the data flow in the system. The development of DFD starts
from a context diagram to illustrate the system with entities
outside the system/stakeholder. There are two outside entities,
such as farmers and farmer admin.
Fig. 12 shows Data Flow Diagram Level 1. There are 2
main processes in this diagram, namely the agricultural land
data processing and the process of displaying agricultural land
information on the dashboard. The Level 0 process is divided
into 2 so that the process is clearer. The processes are such as
Recording Agricultural Land and Displaying Land Mapping
Dashboard. Each of these processes can stand alone, but of
course, the dashboard will have results if there has been a
previous land recording before. The process of recording
farmers’ land will be explained in the next section.
2) Recording of farmer’s land: Fig. 13 shows Data Flow
Diagram Level 2 for the process of land data entry. The
process at this level is a more detailed process than the process
of recording farmer's land in DFD level 1. This level 2
diagram is illustrated in Fig. 13. All three stakeholders remain
at this level. Farmers can carry out the process of adding land
directly, while the Admin must make the process of selecting
farmers before they can carry out the process of adding land.
From the process of adding land, there will be 2 data outputs,
such as land data and land ownership data. Then, to go to the
process of adding detail to the point of land, adding land
planting, and adding photos of land, farmers, and admins who
have gone through the process of selecting farmers, must go
through the process of selecting land first.
G. Coding and Testing
System development is done by implementing what already
designed in the previous stage of RAD.
H. Evaluation
An evaluation is carried out to assess the performance of
the system. Evaluation is carried out on the time and memory
needed by the system as well as measuring the level of use and
usability of the system.
Fig. 11. Context Diagram Data Flow Diagram.
Fig. 12. Data Flow Diagram Level 1.
Fig. 13. Data Flow Diagram Level 2 for Land Data Entry.
IV. RESULTS AND DISCUSSION
At this stage, the results of the application of the system
will be explained, which includes an explanation of the process
in the land recording information system and a land mapping
dashboard, which will later be explained more clearly in each
process. This system can be accessed via the URL
http://dutatani.id/si_mapping. A description of the land
recording information system will include an explanation of
how to record the land and record additional data for lands
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such as planting, ownership, and land photos. It is also how the
system displays land data. In the mapping, the dashboard will
explain how the system displays data. The discussion will
include an explanation of the appearance, functions, and
processes that occur in the system, accompanied by pictures to
help explain the steps that occur in the system being applied.
A. Land Recording Information System
Land recording information system is part of the system
used to register the land and additional information for the
land. Additional information for the land is divided into four,
such as the details of land points, details of land planting, land
ownership, and land photo.
1) Land data recording: The first process in
implementing this system is the process of land recording.
This land recording process is important because the land data
obtained will be used for processing and display in the
information system and mapping dashboard on the website.
As well as being used as a reference for recording additional
land data such as land point details, land planting, land
ownership, and land photos.
Fig. 14 shows the farmer data that has been entered into the
Web Mapping System. The list of farmers can be accessed by
selecting the Farmers Land List menu on the side menu. The
page has filters based on the farmer group and the village
where the farmer lives, as well as a search bar for farmers’
name search. In addition, action options are provided for these
farmers, such as adding land and a list of land owned by
farmers. The add land button will immediately take the user to
the land added form, while the Detail button will take the user
to the farm register page of a farmer. In this system, based on
the interview result, the land ownership status consists of 3
choices, i.e. owned, rented, and worked on.
2) Land details: The user can view details of the land that
has been recorded on the detail page after it has been recorded.
The page shows only the basic land data that has been
recorded, while additional detail data is still displayed as not
recorded. Only land ownership data that has been filled but
later it can also be added because the land can be owned or
rented or worked on by more than 1 farmer.
3) Land ownership recording: The next recording in the
land recording information system is the recording of land
ownership. Land ownership data is data that records land
ownership transactions and ownership status of a farmer.
Ownership status is divided into three, namely Owned,
Rented, and Worked On. Ownership status is a status that
indicates that the farmer is the owner of the land. TheRented
Status is a status that indicates that the farmer is a land tenant,
and the worked On Status shows that the farmer is only the
worker of the land. This data recording is also important, it is
necessary to store ownership transactions which also influence
and are used in the process and output of the information
system and land mapping dashboard. If this data is not
recorded, the land would not appear in the list of land
ownership list belongs to 1 farmer, and the land would not be
found.
Fig. 15 shows the page for data entry on agricultural land
ownership. One land can be recorded in an ownership
transaction with more than 1 farmer. Of course, with a different
status, because land tenants can be more than 1 per land.
4) Land planting recording: Detailed land planting data is
additional data for land that records data on the annual cycle
of land about what plants are planted on the land, the seed
requirements for the land, the saprotan (infrastructure for
agricultural production) requirements on the land, then the
saprotan unit, then the planting month and the crop harvest
month, and estimated yields from from one time planting with
the data. Fig.16 shows the page for location data entry from
farmland. Planting data can be added by the user as needed
5) Land photo recording: The next record in the system is
the recording of land photographs. This recording records the
land photo and saves the photo with the name specified by the
system by combining the uploader’s user id and the photo file
name. Fig. 17 shows pages for images from each recorded
land data. To set the land photo, the user can choose the photo
detail button at the top of the land photo section. On this page,
users can also upload photos and record data in a database.
Also shown photos that have been uploaded, and the action to
delete photos that can be done for each photo.
Fig. 14. Farmer Data.
Fig. 15. Farm Land Ownership Data.
Fig. 16. Form Entry Farm Land Location.
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Fig. 17. Farm Land Picture.
6) Land point detail recording: Land point detail data is
coordinate data stored to form fields that will be displayed
through Google’s online maps embedded on this website. The
process of recording details of these land points is the second
most important after land recording because the details of the
points recorded will be used as landforms on the land mapping
dashboard that shows the points and land plots on the online
map.
Figure 18 shows the Farm Land Polygon. In recording the
details of the land points, the user will be asked to select the
detail points sequentially and not crossing diagonally between
points, because the formation of the polygon fields is arranged
sequentially in the order in which the points are recorded. The
point detail of the land is used as a guide to form the outer
point of the field, which was formed using the Polygon feature
provided by Google, as in Fig. 18.
B. Land Mapping Dashboard
The second part of the system is a simple dashboard for
mapping agricultural land which maps land from the existing
data and is recorded in the system database and performs land
calculations. This land mapping uses 3 types of land
distribution maps, namely the Point of Farm Land Distribution
Dashboard, which is the main page of this system, then the
second is the Land Distribution Map, and finally, the Land
Combination Map. Each map has 3 main parts, namely filters,
maps, and land calculation information.
1) Map of land distribution point: Point of Farm Land
Distribution Dashboard is a map displayed on the main page
of the system, which is the distribution of the coordinates of
the midpoints of each land, as in Fig. 19. The statistical
calculation of land under the map is regulated following the
available land data.
2) Map of farm land distribution: Fig. 20 shows a map of
the distribution of agricultural land. The second type of map in
this mapping dashboard is the Land Distribution Map, which
will display all land that has detailed land points and can form
fields on the map. Likewise, the calculations performed on
this page. This condition is exemplified in Fig. 20.
3) Land combined map: The final type of map is the Land
Combined Map. This Land Combined Map is a map that
shows the resulting combined fields of land. The map is
exemplified in Fig. 21, and Graham’s Scan method
implemented in the system uses a library to calculate and
merge land points.
C. System Testing
In this study, a system test was also carried out using a test
scenario. There are 16 test scenarios that categorized into three
categories as seen in Requirement Traceability Matrix (RTM)
in Table I.
Fig. 18. Farm Land Polygon.
Fig. 19. Point of Farm Land Distribution Dashboard.
Fig. 20. Farm Land Distribution Map.
Fig. 21. Land Combined Map
(IJACSA) International Journal of Advanced Computer Science and Applications,
Vol. 10, No. 10, 2019
240 | P a g e
www.ijacsa.thesai.org
TABLE. I. REQUIREMENT TRACEABILITYMATRIX
Req
No
Req Desc
Test
Case ID
1
Login
TA01
TA02
2
Filtering
Maps
TB01,
TB02,
TB03,
TB04
3
Manage
Farmland
Data
TC01,
TC02,
TC03,
TC04,
TC05,
TC06,
TC07,
TC08,
TC09,
TC10
From testing to 30 users, it was found that the results were
quite good with an average success rate of 74.375%. The
results of this test can be seen in Table II and Figure 22.
TABLE. II. TESTING RESULT
Test
Case
ID
Test Case Scenario
Number
Pass
Percentage
%
TA01
TA02
Check Url http://dutatani.id/si_mapping
Check Customer Login with invalid Data
27
22
90
73.33
TB01,
TB02,
TB03,
TB04
Check Maps Filtering Features
Change the Maps Mode
Change back the Maps Mode
Check Points Info
26
19
24
20
86.67
63.33
80
66.67
TC01,
TC02,
TC03,
TC04,
TC05,
TC06,
TC07,
TC08,
TC09,
TC10
Check Menu Daftar Lahan Petani
Add the Farmland Data
Update the Farmland Data
Delete the Farmland Data
Add additional ownership data into a
farmland
Add additional planting data into a
farmland
Add farmland photos
Add Farmland Points
Update Farmland Points
Remove Farmland Points
25
15
22
26
17
26
28
25
16
19
83.33
50
73.33
86.67
56.67
86.67
93.33
83.33
53.33
63.33
Fig. 22. Statistic of Scenario Testing.
Farm Land Web Mapping System that we developed has
some strengths and weaknesses. This system provides
information for farmers and management/representatives of
farmer groups. This information will help farmers and farmer
groups manage land ownership and land processing better. This
information is shown on the dashboard that is provided in this
system. The limitation of developing this system lies in the
mapping of farmland filed formed on the Land Combined Map
which covers areas that should not be included in agricultural
areas. This is due to the use of Convex Hull Graham’s Scan
method on the online Google Maps which only detects the
outermost point, while the inside will be missed. This can
cause data to be biased.
This study gives some practical and academic contributions
in terms of developing the Farm Land Web Mapping System.
First, this system is built using the real data which got from
Tani Harjo and Tani Rahayu Farmer Union. This is a new
approach that researchers want to develop by understanding
from the farmers what kind of data and information they need.
If this system is successful to be built and implemented,
researchers want to propose a local government to implement
the Web Mapping System in order to help the farmer manage
the land well. The developing of Web Mapping System using
Rapid Application Development is an iterative and easy way to
understand the needs of the user (farmers). Iterative
development is needed since farmers do not understand a lot
about Information Technology and some of them are digitally
illiterate. By using Rapid Application Development,
researchers want to understand the business process and farmer
information needs Researchers are succeeded to gather the
requirement from the farmers and farmer union.
V. CONCLUSION
From the results of research on the implementation of the
system that has been done, it can be concluded that:
a) Application of Land Recording Information System
can create a system for recording agricultural land so that the
agricultural land data obtained is structured according to needs
and stored in a database so that it can be used easily if needed.
b) The application can display data on a map in the
dashboard using data that has been recorded in the database by
calling data using the API service and from Google Maps as
needed.
c) The application can do the calculation of farmland,
farmers, regions and farmer groups to meet the calculation
needs that are in the dashboard.
d) The Land Recording Information System application
can also create and determine the relationships between
farmers and farmland related to the farmers as needed by
differentiating land ownership status.
The future works of this research is to measure the level of
user acceptance and usability tests of the system. Both
evaluations are conducted to get feedback for the final system
product before it is implemented to the user. Further
development will be built on a mobile-based application to
facilitate user access to the system.
(IJACSA) International Journal of Advanced Computer Science and Applications,
Vol. 10, No. 10, 2019
241 | P a g e
www.ijacsa.thesai.org
ACKNOWLEDGMENT
The research team would like to thank the Ministry of
Research, Technology, and Higher Education for the funds that
have been given to undertake this research with research
contract number 227 / SP2H / LT / DRPM / 2019. The research
team also thanked the Community Empowerment Research
and Empowerment Institute Universitas Kristen Duta Wacana
for its support so that this research could proceed well.
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