A Web-based System of Precision Farming based Agricultural ...ijens.org/Vol_16_I_06/161406-9292-IJECS-IJENS.pdf · Blora is one of the biggest rice producers in Indonesia, and the

International Journal of Electrical & Computer Sciences IJECS-IJENS Vol:16 No:06 1

161406-9292-IJECS-IJENS © December 2016 IJENS I J E N S

Abstract—The lack for agricultural information or limited

information received by most farmers generally in

developing countries including Indonesia especially in

Blora regency has caused that the farming of paddy field is

performed in a speculative way. As a consequence, the

product is not maximal. In order to cope with these

problems, a fast emerging technology ICT (Information

and Communication Technology) is utilized to provide and

distribute information starting from a macro plan

nationally down to micro level in farming regions. There

have been several systems developed by utilizing this

technology to provide and give information to farming

consultants, and even farmers.

This research is about developing a web based integrated

system that consists of several modules with their each

functionality in assisting farmers to perform and manage

their farming activities refered as precision farming or

precision agriculture. The simple GIS is one example of

the system's modules used to display maps of farm fields

deviation, and others (i.e., recommendation modules) are

developed by implementing either a DSS or an expert

system approaches (or methods). The developed system is

intended to assist farming consultants in lecturing and

giving information to farmers.

The system was tested using black box testing method to

see whether its functionalities meet the specifications. The

testing was performed for all modules of the system, and

the result says that all of them satisfy the specification.

Index Term-- IntelligentInformation, ICT, system, module,

precision farming, decision support system

I. INTRODUCTION

Nowadays, Indonesian farmers as the main actor of farming

have not been able to access information relating to farming.

Even though many of them have used modern information

technologies such as, smart phones, televisions, computers

from their places in villages, they have not use it optimally in

doing their farming activities. This is because of the lack of

information availabiliy, as well as the limited access to

information for farmers. On the other hand, the farming

consultants do not function as what farmers expect to do. The

poor performance of the farming consultants might be caused

by their worthless salary, as well as both their agricaltural

equipments and technology have been out of date.

The lack of or limited information received by most farmers in

Indonesia especially in Blora regency have caused almost all

the paddy field farming in Blora regency is done in a way of

either a gambling or speculation. It means they do their

farming activities based on the lack of knowledge. For

instance, they often do planting onan inappropriate time, do

pesting using wrong type of pesticide, and so fort. Moreover,

season anomaly frequenlty happens lately with long either dry

or wet season plus uncertain climate condition as a

consequence of el nina or el nino fenomenon. Therefore, they

can no longer perform a traditional farming, it must be done

with precise plan.

In order to cope with these problems, a fast emerging

technology (i.e., ICT) may take an important role starting from

the macro plan nationally down to micro level in farming

regions. The usage of ICT makes farmers to do their farming

activities refered as precision farming or precision agriculture.

Precision farming is a collection of several computer-based

technologies designed to assist farmers in doing control more

on the management of farming activities [4]. Some

technologies mentioned in precision farming are GPS (global

position system), GIS (geographic information system), DSS

(decision support system), remote sensing and monitoring in

harvest. Precision farming provides information to farmers in

building database for their farm fields, increases the accuracy

of decision making, expands their product's market, improves

quality of farming product by giving precise fertilizer, right

cultivating time, and so fort. The main purpose is that by

implementing precision farming, farmers will obtain the

maximal profit from their farming's products. In addition, by

implementing it the risk of environment destruction can be

reduced significantly.

In this research was developed an integrated web-based

system of Precision Farming based agricultural information

that allows users (i.e., rice farming field consultants and

farmers) to find accurate, complete and up to date information.

The farming location in Blora regency is selected because

Blora is one of the biggest rice producers in Indonesia, and the

most farm fields in Blora are raining-dependent [6]. In

addition, the farming sector gives the biggest contribution in

Blora regency since 2005.

II. RELATED WORKS

There have been some related works perfomed by some

researches beforehand. For example, the paper talked about

information system networking and services of farming in

India [2]. The networking covers a number of problems

relating to Agricultural Research Information System - ARIS

A Web-based System of Precision Farming based

Agricultural Information for Rice Farming Field

Consultant in Blora Regency Suprapto, Anny Kartika Sari, Janoe Hendarto, Medi and Guntur Budi Herwanto

Departement of Computer Science and Electronics

Faculty of Mathematics and Natural Sciences, Universitas Gadjah Mada

Yogyakarta, Indonesia

{ sprapto, a_kartika, janoe, medi and gunturbudi }@ugm.ac.id



in India. And according to [5], in order to increase the farming

product, the representative building for farming consultance

with information technology devices was highly required. The

implementation of precision farming to increase productivity,

decrease production cost and minimize environment's

influence toward farming. The research concentrates on

productivity, income, empowering and adopting technology

behavior in farming. The development of web based

information system used to market farming products in Midle

Java. The objective of this research is to help farmers

especially in Midle Java marketing their farming product

easily and effectively. Another research mentioned that

farmers must have access to important information (especially

one they need) about how to manage their farms to increase

their farming products [9]. This kind of information can be

easily obtained from Internet and other resources either from

private or state institutions. A review about how to generate

(extract) information from a map to develop an information

system that provides location based contextual information on

a map [15]. The reviewed system implements mobile

application technology integrated with GIS, GPS, wireless

communication network and Internet.

There are many potential impacts from precision agriculture.

Some of the primary impacts are costreduction and more

efficient use of production inputs, use of information

technology to increase the size and scope of farming

operations without increasing labor requirements, improved

site selection and control of production processes that help in

the production of higher value or specialty products, improved

recordkeeping and production tracking for food safety, and

environmental benefits [14].

An application of information technology in agriculture,

precision farming is a feasible approach forsustainable agri-

culture. Precision farming makes use of remote sensing to

macro-control of GPS to locate precisely ground position and

of GIS to store ground information. It precisely establishes

various operations, such as the best tillage, application of

fertilizer, sowing, irrigation, harvesting etc., and turns tradi-

tional extensive production into intensively production

according to space variable data.

Precision farming may not only utilize fully resources, reduce

investment, decrease pollution of the of the environment and

get the most of social and economic efficiency, but also makes

farm products, the same as industry, become controllable, and

be produced in standards and batches [8].

Precision agriculture will have a marked impact on traditional

approaches to farming land. Applying technological advances

in data collection and geolocation, precision agriculture uses

technology to optimize yield and detect operating efficiency:

this is technology that will tell farmers when is the best time to

plant and when is the right time to start harvesting; that will

take input costs down, negate environmental impact, reduce

fuel and cut down on fatigue. Farmers across the globe are

going to be challenged by this innovation in agriculture [12].

There, farmers and practitioners have overcome the challenges

associated with precision nutrition management and converted

them into opportunities by harnessing the global information

and developing local precision techniques suitable for their

region, operation and resources. Precision agriculture manage-

ment coupled with genetic improvements in crop traits will

play a crucial role in meeting global demand for food, feed,

fiber and fuel in the near and distant future [11].

An automated guidance of agricultural vehicles (i.e., tractors,

combines, sprayers, spreaders) has been motivated by a

number of factors, but the most important is to relieve the

operator from continuously making steering adjustments while

striving to maintain field equipment or implement perform-

ance at an acceptable level. This is not surprising, considering

the many functions an operator must monitor, perform, and

control while operating the vehicle [13].

Hence, in order to achieve the objective of using ICT in

precision farming needs requirements as follows, availability

of complete and well managed agricultural database, avail-

ability of reliable agricultural information system, availability

of spatial database comprising farming field mapping, type

and characteristic of soil, soil topograhpy also seeding and

fertilizer usages, availability of computer based methods

especially DSS, GIS and so fort, availability of service system

about production equipment's inquiry capable of doing

inventory of farming production devices, and availability of

agricultural networking that easily accessed by both farming

consultant as well as farmers.

III. DISCUSSION

As already mentioned in the research's objective, it must be

clear that the result of the research is an integrated web based

system of precision farming-based agricultural information

for rice field farming consultants in Blora regency. The

application and database server are located in an agricultural

institution of Blora regency, while farming consultants might

have on-line access to the application. The system has two

external entities, i.e., university partner and farming con-

sultants. The external architecture of system showing the

relation with external entities is shown in Fig. 1.

Fig. 1. The External's Architecture of System

The system is designed to be one whose many modules, i.e.,

agricultural information module - one that provide almost any

information associated with agriculture or farming, simple GIS

predicts planting calendar dynamically plus displays farm's

locations on a map, dynamical planting calendar, paddy's

variety recommendation gives priority value of each variety,

planting time recommendation - gives suggestions to farmers

when they should do planting, irrigation usage recommend-

ation suggests the water's consumption distribution, fertilizer

usage recommendation, pestiside usage recommendation and

agricultural networking. The list of system's modules and the

descriptions of their functions are shown in Table I.



Tabel I

The list of modules in the System

A. The Architecture of System

The system is a web-based built by integrating several

modules (or subsystems) with their associated functions. Some

modules are related, and some are not. For example, simple

GIS module and dynamical planting calendar are related since

the predicted results from simple GIS are used by dynamical

planting calendar to produce an advice for farmers or the

farming field consultant in making the cultivating plan. It is

seen from Table I that most modules building the system are

recommendation system. Furthermore, these modules (i.e., the

recommendations) are developed as the DSS (decision support

system) by implementing either AHP (analytical hierarchy

process), SAW (simple addative weighting) or profile

matching methodology.

The system utilizes two databases, i.e., agricultural was

designed to stores agricultural data and information required

by all modules in the system except agricultural networking.

This module uses database networking that is sparated from

agricultural. In addition, the system also requires special data

taken from an Indonesia institution BMKG (Badan Meteoro-

logi Klimatologi dan Geofisika) especially used by the simple

GIS module. Hopefully, data or information obtained from

BMKG is dynamic (almost real time), since it should represent

thecurrent conditions (i.e., weather, temperature, humidity,

wind speed, etc.) of location. So that, the planting calendar

predicted by simple GIS is becoming more dynamic and

accurate.

The integration of system's modules relationship architecture

is therefore shown in Fig. 2.

Fig. 1. The Internal's Architecture of System

B. Database

The data model used in this database is relational, which is

one widely used in database application development.

Generally, relational model database is built by first

identifying entity sets with their reasonable attributes, and the

relationship sets among them (if any). If all necessary entity

sets and relationship sets with their attributes have been

identified, they would have been represented in a diagram

called by ER (entity relationship). This kind of diagram

actually belongs to another data model in database, which is

Entity Relationship model. The relationship sets defined in ER

diagram relate two or more entity sets also explain type of

relationship, either one-to-many or many-to-one. These types

of relationship are derived from the existing or the defined

business rules. Once the diagram has been generated, it can be

transformed (or converted) into a set of relations (or tables),

and creates a relational model database.

Data and information used to design database in this research

are obtained from field observations, informal conversations

or interviewing farmers, a collection of forms and documents

borrowed from data center office of Dinas Pertanian and

BAPEDA in Blora regency. Data and information are then

analyzed in order to identify entity sets, relationship sets and

set of busines rules that must be satisfied in the system. This

analysis needs enough knowledge and understanding toward

problem to be solved in order to obtain a complete and

efficient database. By the carefully analysis, eventually the

collection of entity sets together with their attributes,

relationship sets and a set of business rules was derived. The

collection of entity sets and relationship sets were named

according to their usages, however, for the shake of ease in

remembering and using, their names were given in

Indonesian's terms. While the defined business rules mention

that every Provinsi (province) has many Kabupaten

(regencies), every Kabupaten has many Kecamatan (districts),

every Kecamatan has many Kelurahan (subdistricts), and in

turn every Kelurahan has many farm fields. Paddy has two

varieties, i.e., hybrid and nonhybrid, every variety has

different types of paddies, types of paddies determinepest

type, and pest type determines type of pesticide. There are

three types of farm field, i.e., raining-dependent (depends on

rain), irrigating-dependent (depends on irrigation) and

swamming-dependent (depends on swam water). Every farm

field has different type ofsoil, every type of soil has different

composition. There are two types of fertilizer, i.e., organic and

unorganic. Temperature, humidity and others are measured



daily (from BMKG). Based on the collection of entity sets and

relationship sets plus these business rules, the entity-

relationship diagram can be generated. In this discussion,

however, the E-R diagram was intentionally excluded for

simplicity reasons. Furthermore, once the E-R diagram is

generated, it can be transformed (or converted) into a

relational model represented by table inter-relation diagram.

As already mentioned in the previous paragraph, each entity

set and relationship set occurs in E-R diagram corresponds to

a relation (or table) in the relational model database. The list

of entity sets with their corresponding relations (tables) is

shown in Table II.

Tabel II

The list of used relations

The relational model as the result of the transformation (or

convertion) from E-R diagram for database is represented as a

table inter-relation diagram. Since the size of diagram is too

big to fit in one page, only part of it will be presented in this

article. A part of the table inter-relation diagram is shown in

Fig. 3.

Fig. 3. A part of table inter-Relation diagram of Database

The diagram shown in Fig. 3 is only about 35% of the entire

table inter-relation diagram. Even so, it has already explaned

type of relation between two related tables. For example, the

type of relation between ref_kecamatan (name of table

associated with entity set Kecamatan) and ref_kelurahan is

one-to-many, so is with one between ref_kelurahan and

ref_sawah, and so forth. These relations are derived from the

business rules defined above.

C. Implementation

Considering the location in which the system will be operated

(i.e., Blora, Indonesia), so that most of terms, descriptions and

helps used in this system are in Indonesian. For instance, on

the main page of the system are displayed part of systems

features, i.e., Referensi for reference, Data Pertanian for

agricultural data and Katam for planting calendar (see Fig. 4).

Fig. 4. System Main Page Screenshot

Referensi menu allows users to view Kecamatan (District)

and Kelurahan (Subdistrict) are in Blora regency. It is very

usefull in searching location, and entering the new data. Data

Pertanian menu enables users to display many sorts of

agricultural data, such as farms, fertilizers, pesticides, paddy,

and so fort. While Katam menu capable of displaying the

deviation of paddy fields in Blora regency that is represented

as a map. Fig. 5 shows an example of the display of small part

of the map.

Fig. 5. A part of the farms distribution Map

From this map, users also capable of obtaining detail

information of farms, such as the owner, area of paddy field

history of cultivating times, and so fort. There are still some

usages can be taken from this map.

Beside the main page, system also provide the index page that

allows users to see all stored data in the system (database).

With this page, user not only capable of seeing but also in-

serting some new data by selecting action with label Tambah

Pemakaian Pestisida. This action allows users to insert new

data about pesticide usages. In addition, for each stored data is

associated with two icons on the right side representing sub-

action update and delete respectively. The implementation of

index page is shown in Fig. 6.



Fig. 6. Index page of data about pesticide usages

In sone subsequent subsections will be discussed only the

selected modules build the system. They are mostly recom-

mendation systems.

D. Recommendation of Most Suitable Rice Variety

This module is used to recommend farmers about most

suitable rice variety for their farms. It is a recommendation

system (or to be precise, a decision support system - DSS)

implemented using AHP methodology. In order to build this

AHP decision support system, first is defining a decision

hierarchy as shown in Fig. 7.

The decision hierarchy begins with the objectives, continues to

the intermediate levels called criteria, and then the subcrieria

(if criteria has one). The lowest level should show all alterna-

tives (i.e., rice varieties), however, because there are too many

number of alternatives to fit on page, in this case they are only

represented by three alternatives (symbolized by A, B and C)

as in Fig. 7. Hence, the system uses four criteria, and ten

subcriteria, with Water Supply does not have any subcriteria.

Fig. 7. The Decision Hierarchy

1) Water Supply: Water is one of the critical inputs for

rice production systems [16]. In general, the volume of water

required by rice is different in each phase of growth. In

addition, variations in water demand depend also on rice

varieties and wetland management system.

2) Pest Resistance: Rice and pests are two things that

can hardly be separated. Planting rice is also meant to be

prepared against pests that would threaten rice crops [17]. The

better resistance of rice variety to pests, the higher priority of

the rice to be an alternative. In accordance with Fig. 7, pest

resistance has subcriteria named by four common rice pests as

the following.

Planthoppers. Brown planthopper (or Nilaparvata lu-

gens) is a type of insect that has potential as the most

dominant pests attacking rice plants in Indonesia and Asia.

This pest attacks the stalks of rice with rice straw to suck

fluid. As a result, the rice becomes yellow, dry out or

dwarf [18]. In addition, planthopper can transmit viruses

damaging rice plants.

Rats. In rice cultivation, rats are relatively difficult to

control [19]. It is because of their adaptability, mobility,

and they multiply rapidly, as well as their high destructive

power. Therefore, rats always be a threat for rice

cultivation. In addition, because they attack rice from the

early season until the harvest, the negative impacts caused

by rats is considered as the big one.

Snails. These animals breed with remarkable speed in

areas with lots of puddles. No wonder if they feel like at

home when they are in the fields being supplied with

continuous irrigation. They have already become pests by

eating the rice plants even they are still young. As a result,

farmers must replant their crops [20].

Stem borer. It is a pest that attacks the rice plant at

allphases of plant growth, ranging from seedlings to

harvest [22]. They feed upon tillers and causes dead-

haearts or drying of the central tiller, during vegetative

stage; and cuases whiteheads at reproductive stage.

Deadhearts or dead tiller that can be easily pulled from the

base during the vegetatives stages.

3) Soil Characteristics: Soil is a natural growing medium

which provides food (i.e., nutrients) to the survival of the

plant. So that, in order to obtain optimal rice products, soil

quality must be maintained. Any mistakes in the processing of

the soil can result in damage to the land, and will result in a

decrease in plant productivity [21].

pH. The level of pH is the soil chemical characteristics,

that becomes a very important factor in determining the

fertility of the soil due to association with the availability

of plant nutrients. The higher value of the pH means that

the soil is more acidic. As a result, the plant is unable to

absorb nutrients properly.

Moisture. Moisture is a measurement of the amount of

water contained in the soil [23]. The water content in the

soil expressed in volume percentage. Water has an

important function in the ground, such as the process of

mineral weathering and soil organic matter. The process is

the reaction for preparing soluble nutrient for plant growth.

In addition, water also serves as a medium of motion

nutrients to plant roots. However, if too much water is

available, nutrients can be leached out of the root zone

areas or when high evaporation, dissolved salts may be



lifted above the ground. Excessive water also restricts air

movement in the soil, plant roots impede acquire O2 so

can result in plant death. Different varieties of rice may

have needs different soil water content. The moisture

content condition can be the factor for selecting the mos

suitable rice variety.

Carbon. Carbon is a constituent of organic materials,

hence its circulation during the weathering of plant tissue

is very important. Most of the energy needed by the flora

and fauna are originated from the oxidation of soil carbon,

and therefore CO2 continue to be formed. The content of

carbon is an element that can determine the level of soil

fertility. Carbon is one of the nutrients that plants need.

4) Pest Supply: Nitrogen, phosphorus and potassium, or

NPK, are the primary nutrients in commercial fertilizers. Each

of these fundamental nutrients plays a key role in plant

nutrition [24].

Nitrogen. Nitrogen is considered to be the most important

nutrient, and plants absorb more nitrogen than any other

element. Nitrogen is essential to in making sure plants are

healthy as they develop and nutritious to eat after they are

harvested. That is because nitrogen is essential in the

formation of protein, and protein makes up much of the

tissues of most living things.

Phosphorus. Phosphorus is linked to a plant’s ability to

use and store energy, including the process of

photosynthesis. It is also needed to help plants grow and

develop normally. Phosphorus in commercial fertilizers

comes from phosphate rock.

Potassium. Potassium is the third key nutrient of

commercial fertilizers. It helps strengthen plants abilities to

resist disease and plays an important role in increasing

crop yields and overall quality [25]. Potassium also

protects the plant when the weather is cold or dry,

strengthening its root system and preventing wilt.

The AHP’s computations for finding the value of suitability of

each rice variety for the given farm are initialized by giving

the criteria values of each variety being ranked. These values

should be given by people whose expertise in rice farming, or

ones who have enough experiences in agriculture especially

rice farming. An example of these values is shown in Fig. 8.

Fig. 8. An example of criterion’s values of each variety

The subsequent step is creating matrix of pairwise compa-

rison, and the result is shown in Fig. 9.

Fig. 9. Matrix of Pairwise Comparison

The inputs (or entries) for the pairwise comparison matrix

should be given by an expert in agricultural or people whose

enough experiences in agricultural in order to obtain a correct

comparison among criteria. This matrix is used to compute

eigen vector that indicates the relative ranking of used criteria.

This is why it is known that the criterion pest resistance is

determined as the most important one (as mentioned above).

In this case, the suitability values of each rice variety were

visualized as a bar chart depicted in Fig. 10. The rice variety

whose the biggest value is one that most suitable. According

to the obtained results in this example, INPARI 22 is the most

suitable variety for the given farm.

Fig. 10. A Result represented in Bar chart

E. Recommendation of Irrigation

This is another module in the system, Rekomendasi Irigasi

(recommendation of irrigation). It is used to compute the

water volume required by farm daily. The water volume is

computed based on the inputs data, such as farm’s name, date

when water is required, evaporated water volume, volume of



water absorbed by soil, rain fall, height of drainage from the

farm, height of flash board (if uses one), irrigation’s

efficiency, and plant’s efficiency. The page used to input these

data is shown in Fig. 11.

Fig. 11. Set of Data Inputs for Irrigation Recommendation

While Fig. 12 shows an example of irrigation recommendation

required by a farm Sawah for three subsequent days, i.e.,

12/03/2016, 13/03/2016 and 14/03/2016.

Fig. 12. An Example of Irrigation Recommendation

In order to obtain the recommendation of water requirement

on the following day, simply using a feature Create Rekomen-

dasi Irigasi. Fig. 13 shows the irrigation recommendation

produced by the system.

Fig. 13. A page displays result of irrigation recommendation

F. Agricultural Networking

The Agricultural Networking’s module is equipped with a

database that contains collection of publications, documents,

images relating to rice field farming.

In addition, a spatial database is also included in the module,

holding spatial data about rice field farming in Indonesia. In

order to use this module, one must have an account that

connected to others, and every account is associated with a

profile. Once users have accessed to this module, they can

share recent information especially issues of the rice field

farming. They can even promote thier agricultural’s products.

Moreover, it is accessible from mobile devices. The display of

the forum feature’s page is shown in Fig. 14.

Fig. 14. A page displays a forum feature

On the first page there is an authentication form together with

several discussion forms according to user’s needs. Topics of

discussion are set by forum admin. Fig. 15 shows a page for

discussion forum.

Fig. 15. A page displays a forum of discussion

Each forum has a thread as a topic of discussion inter users.

Fig. 16 shows a nonadmin users adding topic while having a

discussion.

Fig. 16. Adding topic while having a discussion

In addition, users are able to add attachment to topic of

discussion as well as reply it. Fig. 17 shows a page displaying

discussion has been made by users.



Fig. 17. A page is displaying a discussion

IV. CONCLUSION

The developed system, namely an integrated web-based of

precision farming based agricultural informatics has several

functionalities corresponds to modules build the system. Most

of modules in the system are the recommendation systems.

They were implemented as the decision support system with

several methodologies such as, AHP (analytical hierarchy

process), SAW (simple additive weighting) and Profile

matching.

The system testing was carried out by applying a dynamic

black box approach, i.e., it was run by using some data sets as

the inputs to verify whether each function satisfies its

specification. Based on the testing, the function’s satisfaction

is about 85 percent.

For the future work, this number can be increased by per

forming some revisions in the maintenance phase. In addition,

the system can be extended in order to be accessible via

mobile devices.

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