Contribution of Agroforestry Systems to Farmer Income in State Forest Areas: A Case Study of Parungpanjang, Indonesia

Abstract

Agroforestry activities in Forest Areas with Special Purpose (FASP) have been implemented since 2000 in Parungpanjang, West Java, which was subsequently reinforced by the Decree of the Minister of Environment and Forestry concerning the Recognition and Protection of Forest Partnerships (Kulin KK) for the Harapan Sejahtera and Guna Bakti Forest Farmer Groups in 2019. This study investigates the contribution of agroforestry systems to farmer income using a household survey in the Parungpanjang Research Forest. The study aims to analyze: 1) the contribution of agroforestry to farmer income from a household structured income analysis; 2) factors of agroforestry that influence total farmer household income using multiple regression analysis. The results show that agroforestry systems contributed 15.8% to farmer household income. The highest agroforestry productivity occurs in the age group of 41-45 years with an average of managed land area of 0.65 hectares and average annual income of IDR 16,780,000 (USD 1,198.6)/farmer/year. The statistical model showed that agroforestry income does not have a significant influence on total farmer household income due to differences in the types of commercial crops, motivation, and skill, as well as age related to physical abilities. There are only two agroforestry factors, namely age and land area, that have a significant influence on total farmer income, whereby the direction of the age variable has a negative influence.

Full text

Forest and Society
Vol. 5(1): 109-119, April 2021
http://dx.doi.org/10.24259/fs.v5i1.11223
Received: 2020-09-08; Accepted: 2021-02-26
Copyright © 2021 by Forest and Society. This work is licensed under a Creative Commons Attribution 4.0 International License.
Regular Research Article
Contribution of Agroforestry Systems to Farmer
Income in State Forest Areas: A Case Study of
Parungpanjang, Indonesia
Desmiwati Desmiwati 1,*, Thomas Oni Veriasa 2, Aam Aminah 1, Anggi Dian Safitri 1 , Kresno Agus
Hendarto 1, Tri Astuti Wisudayati 1, Hasan Royani 1, Kurniawati Hastuti Dewi 3, Sandy Nur Ikfal
Raharjo 3, Dian Ratna Sari 3
1 Forest Tree Seed Technology Research and Development Center, Ministry of Environment and Forestry,
Bogor-Indonesia 16001
2 Center for Regional Systems Analysis Planning and Development (Crestpent/P4W), IPB University, Bogor-
Indonesia 16127.
3 The Center for Political Studies, Indonesian Institute of Science
*Corresponding author: desmiwati.wong@gmail.com; Tel: +62-813-810-94360
Abstract: Agroforestry activities in Forest Areas with Special Purpose (FASP) have been implemented since
2000 in Parungpanjang, West Java, which was subsequently reinforced by the Decree of the Minister of
Environment and Forestry concerning the Recognition and Protection of Forest Partnerships (Kulin KK) for
the Harapan Sejahtera and Guna Bakti Forest Farmer Groups in 2019. This study investigates the contribution
of agroforestry systems to farmer income using a household survey in the Parungpanjang Research Forest.
The study aims to analyze: 1) the contribution of agroforestry to farmer income from a household structured
income analysis; 2) factors of agroforestry that influence total farmer household income using multiple
regression analysis. The results show that agroforestry systems contributed 15.8% to farmer household
income. The highest agroforestry productivity occurs in the age group of 41-45 years with an average of
managed land area of 0.65 hectares and average annual income of IDR 16,780,000 (USD
1,198.6)/farmer/year. The statistical model showed that agroforestry income does not have a significant
influence on total farmer household income due to differences in the types of commercial crops, motivation,
and skill, as well as age related to physical abilities. There are only two agroforestry factors, namely age and
land area, that have a significant influence on total farmer income, whereby the direction of the age variable
has a negative influence.
Keywords: Agroforestry systems; Household income; Research Forest; Social forestry
1. Introduction
In order to address the global challenges of climate change, food security, and rural poverty,
changes in environmental management systems are required. In the forestry sector, agroforestry is
increasingly recognized as a viable option for overcoming these challenges (Mutonyi & Fungo, 2011).
Agroforestry is a system of natural resources management that integrates trees on farms and in the
agricultural landscape to diversify and sustain production (Molla, 2019). Agroforestry is a cost-
effective strategy for climate change mitigation (Baliton et al., 2017), that provides benefits on
carbon sequestration and storage (Zomer et al., 2016; Feliciano et al., 2018), increases ecosystem
services (Shin et al., 2020), simultaneously provides job opportunities (Borrella et al., 2015), and
there is a positive relation between agroforestry and community (Humphries et al., 2012).
In practice, agroforestry is often described as a suitable system for the needs of community in
their land use systems. Several studies of agroforestry systems in Indonesia have shown that it has
brought about several positive impacts particularly because it increases productivity of forest land
(Suryanto et al., 2013), improves soil quality (Mulyono et al., 2019), plays an important role in
maintaining avian diversity (Withaningsih et al., 2020), brings economic benefits for local
communities (Sudaryanto & Variasa, 2018; Kamaluddin et al., 2020), and promotes food security

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(Wulandari et al., 2014). However, agroforestry still faces challenges mainly with regard to the
agriculture expansion caused by commercialization of timber (Kusters et al., 2008), poverty
alleviation and farmer household welfare (Nuryati et al., 2019), community participation (Dwijanti
et al., 2018), and lack of market and community access to finance opportunities (Suyadi et al., 2019).
To date, the Government of Indonesia has established 35 Forest Areas with Special Purpose
(FASP) for research, education, training and religious purposes. FASPs are located in various regions
with a total area of 37,569.05 hectares (Ratina, 2019), one of which is located in Parungpanjang,
Bogor Regency, West Java. FASP Parungpanjang has applied agroforestry systems since 2016, which
was subsequently received strengthened authority by forestry partnerships through the Social
Forestry (SF) model since 2019. The SF provides access for Harapan Sejahtera and Guna Bakti Forest
Farmer Groups (FFG) to manage the forest through an agrosilviculture model for 35 years. It is aimed
at increasing the productivity of research on forest land, such as the quality of shade tree plants, the
productivity of intercropping plants, soil fertility, and on the improvement of local community
welfare (Desmiwati et al, 2018).
As a research forest, various studies on FASP Parungpanjang have already been carried out,
particularly focusing on the technical aspects of silvicutural forest plants. Studies on the social
economic aspects of the FASP, on the other hand, are still very limited and mostly conductive
through qualitative research such as research on community attitudes and behavior (Surati, 2014),
perceptions and participation levels of smallholder farmers (Desmiwati, 2016), social capital of
smallholder farmers (Desmiwati et al, 2018), agroforestry patterns and livelihood strategies of
smallholder farmers (Desmiwati & Nugraheni, 2018) and economic perceptions of smallholder
farmers (Hendarto et al, 2020), and roles and voice of farmers in the “special purpose” forest area:
strengthening gender responsive policy (Dewi et al, 2020).
Referring to the aims of the agroforestry system and SF implementation in FASP Parungpanjang,
this study aims to fill the gap on socio-economic aspects of FASP to complement the baseline data
for impact measurement. The objectives of this study are as follows: first, to calculate the
contribution of agroforestry to farmer income, and second, to analyze agroforestry factors that
influence farmer income. The main research question of the study is: does agroforestry has a
significant contribution to the rural economy?
2. Methods
2.1. Study Area
This study was conducted in the Parungpanjang FASP (106031’06”E, 06022’58,9”S) managed by
the Forest Tree Seed Technology Research and Development Center (FTSTRDC), of the Ministry of
Environment and Forestry (MoEF). The area directly borders four villages namely Jagabaya and
Gintung Cileujet Village, Parungpanjang District, and Tapos and Batok Village, Tenjo District, Bogor
Regency, West Java (Figure 1). Initially, the Parungpanjang FASP was located in the Perum Perhutani
production forest area as stated in the Loan and Use Agreement
1
. Subsequently, the designation
was changed to a FASP in accordance with the Decree of the Minister of Environment and Forestry
in 2019
2
. Furthermore, on 27 August 2019, the Parungpanjang FASP became the first Social Forestry
model implemented by the MoEF out of a total of 35 FASPs in Indonesia. The Social Forestry permit
(35 years) is stipulated through the Decree of the Minister of Environment and Forestry Number SK.
7087/Menlhk-PSKL/PKPS/PSL.0/8/2019 concerning the Recognition and Protection of the Forest
1
The Loan and Use Agreement No.08/044-3/III/1996 and 796/VIII-BTP/12/1996
2
The Decree of the Minister of Environment and Forestry No. SK.169/Menlhk/Setjen/PLA.0/2/2019 dated
February 25, 2019 with an area of ± 100 Ha.

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Partnership (Kulin KK) of the Harapan Sejahtera Forest Farmer Group (FFG) covering an area of 10.7
hectares, which includes 19 members.
On the same date, MoEF also issued the Decree of the Minister of Environment and Forestry
Number SK.7089/Menlhk-PSKL/PKPS/PSL.0/8/2019 concerning the Recognition and Protection of
the Forest Partnership (Kulin KK) of Guna Bakti FFG covering an area of 8.75 hectares with 21
members.
This research provides a baseline of socio-economic data as a parameter to measure forest
management using the Forestry Partnership scheme (Kulin KK).
Figure 1. Location of field study
2.2. Data Collection
The data was collected from September until October 2019 using a household census survey
with a total of 52 respondents consisting of farmer households in the Tapos Village (N=31) and
Jagabaya Village (N=21), Bogor Regency, West Java. The household questionnaires drew from the
National Survey on Socio-economic Issues questionnaire developed by the Indonesia Bureau of
Statistics (BPS), and introduced several modifications. The census method and questionnaire was
used to explore the demographic characteristics of the village and the respondents, as well as
collecting baseline data for further in-depth surveys (Malleson et al., 2008). Meanwhile,
observations and in-depth interviews were conducted to obtain detailed farmer household
socioeconomic dynamics and demographic information.
Furthermore, two focus group discussions (FGD) were conducted in each village with 25 farmer
participants in Tapos Village and 21 participants in Jagabaya Village. The FGDs verified and deepened
information related to agroforestry patterns and types of commercial crops that had been
developed, as well as information on seasonal calendars and agroforestry income referring to each
type of commercial crops cultivated.
2.3. Analysis
2.3.1 Contribution of agroforestry income to total farmer household income

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Total farmer income was analyzed by calculating all activities that generate both cash and in-
kind income. In-kind income is calculated by summing up all the value of products consumed directly
by farmer households (Faße & Grote, 2013; Angelsen et al., 2014). The formula used is as follows:
Total farmers income=Σ (On-farm Income + Off-farm income+Non-farm Income) (1)
In this study, on-farm income activities included agroforestry and livestock, and off-farm income
included work as daily laborers. Non-farm income activities included stalls and hawkers, bike
mechanics, craftmans (Boboko/bamboo craft) and others (service activities and transfers). The
agroforestry contribution was analyzed by calculating agroforestry income to the total farmers
income in a year. The formula used is as follows:
 
 (2)
Where,  = Contribution of agroforestry income to the total farmers income (% in a year);
 = total income from agroforestry activities (IDR/year);  = Total farmers income (IDR/year).
2.3.2 Factors of agroforestry system that influence farmer household income
Multiple linear regression analysis was carried out to determine agroforestry factors that have
a significant influence on farmer income. The equation model (Sarstedt & Mooi, 2014) is as follows:
Y = + 1X1 + 2X2 + 3X3 + 4X4 + 5X5 +  (3)
Where, Y = Farmers income (IDR/year); α = constant; β1- β8 = regression coefficient; X1 =
Agroforestry income (IDR/year); X2 = Age (years); X3 = Education (years); X4 = Family size (person);
X5 = Land area (hectare); e = error. The t test is conducted by comparing the p-value (Sig.) of the
regression test results with the degree of error used in this model i.e. 10% or α = 0.1. The references
of variables can be seen in Table 1 below.
Table 1. References of Variables
No
Variable
Source of References
1.
Age
Suherdi et al., 2014
2
Education
Marschke & Berkes, 2005; Parhusip et al., 2019
3
Family size
Rahman et al., 2017
4
Land area
Nyaga et al., 2015, Van Chu et al., 2019
Due to data limitations (52 farming households), this research conducted several tests on the
regression model to mitigate statistical issues that might arise and ensure the robustness of the
model i.e Normality, Linearity, Heteroscedasticity, Multicollinearity and Regression Spesification
Error Test (RESET).
3. Results and Discussions
3.1 Agroforestry practice
The main tree species that dominate the forest vegetation structure of the Parungpanjang FASP
are mahogany (Swietenia macrophylla), acacia (Acacia mangium), nyamplung (Calophyllum
inophilum), gempol (Nauclea orientalis i Linn), merbau (Intsia bijuga), kepuh (Sterculia foetida),
mindi (Melia azedarach), tisuk (Hibiscus sp) and white jabon (Anthocephalus cadamba).
Intercropped plants were dominted by galangal (Lenguas galangal), chinese potato (Coleus

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tuberosus) and peanut (Arachis hypogaea). Tree plantations in this area are research objects of
FTSTRDC.
Farmer Groups members in Tapos Village and Jagabaya Village have practiced agro-silviculture
by applying alley-cropping techniques in a simple pattern with a limited number of intercropping
cultivated varieties. Alley-cropping techniques allow farmers to plant agricultural crops in alleys in
between woody plants (Shin et al., 2020). The main inter-cropped plant species was galangal
(Lenguas galanga) with other secondary and additional intercropped plants (Table 2).
Table 2. Agroforestry patterns adopted by farmers in FASP Parungpanjang.
Agroforestry
Patterns
Intercropped plants
Primary
Secondary
Additional
Type 1
Galangal (Lenguas galanga)
Pongamia (Pongamia pinnata)
Cassava (Manihot
utilissima)
Banana (Musa sp.)
Type 2
Galangal (Lenguas galanga)
Largeleaf rosemallow (Hibiscus macrophyllus)
Type 3
Galangal (Lenguas galanga)
Peanut (Arachis hypogaea)
Type 4
Galangal (Lenguas galanga)
Chinese potato (Coleus tuberosus)
Type 5
Galangal (Lenguas galanga)
Red Jabon (Anthocephalus macrophyllus)
Type 6
Galangal (Lenguas galanga)
Cheesewood (Nauclea orientalis)
Source: Primary data, 2019
3.2 Contribution of agroforestry to farmer income
Table 3. shows the education level of the respondents in both villages. The majority of the
respondents graduated from elementary school (55.8%), while 36.6% did not graduate from
elementary school, although most of them can read and write. Only 7.6%, or four respondents, had
a higher education level than other respondents. According to age group, respondents over 45 years
old amounted to 67.3%, while 13.4% of respondents were over 60 years old (Table 4).
The study found that the age of respondents ranged from 30–78 years. Table 4 shows that the
age group of 41-45 years (9.6%) managed the largest part of agroforestry land area than other age
groups, namely an average of 0.65 hectares. Out of the total land managed by farmers (22.9
hectares), the average area of managed land is 0.44 hectares per farmer.
Table 3. Education level of farmers
No
Education level
Frequency
Percentage
1
Did not graduate from Elementary School ( < 6 years)
19
36.6
2
Elementary School - SD (6 years)
29
55.8
3
Junior High School – SMP (9 years)
2
3.8
4
Senior High School - SMA (12 years)
2
3.8
Total
52
100
Source: Primary data, 2019; N=52
Table 4. Farmer composition based on age group
Age Group
Farmers Households
Total Land Area
(Hectare)
Land Area per age
group (hectare)
N
Percentage
30 - 35
4
7.7
1.25
0.31
36 - 40
8
15.4
2.90
0.36
41 - 45
5
9.6
3.25
0.65
46 - 50
15
28.9
7.00
0.47
51 - 55
6
11.5
3.00
0.50
56 - 60
7
13.5
3.25
0.46
61 - 65
3
5.7
1.00
0.33
> 65
4
7.7
1.25
0.31
Total
52
100
22.9
0.44
Source: Primary data, 2019

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Table 5 shows that the contribution of agroforestry income to total farmer income was 15.8%
with an average agroforestry income of IDR 3,829,519 (US$ 273.5) per farmer per year. The highest
contribution to total farmer income was from working as daily laborers (33.7%), followed by income
from stall/hawkers (28.9%). The lowest contribution to farmer income is from livestock (1.6%).
Agroforestry is an alternative livelihood option where the main income of farmers are off-farm and
non-farm activities. This is because farmer households are landless and are unable to develop
agricultural activities. Furthermore, low education and poverty have caused them to seek out
selected employment that relies more on physical abilities that do not require large capital, such as
daily laborers and hawkers.
Table 5. Average farmer household income based on income sources per year (in IDR)
No
Source of Income
Total Income
Mean
SD
Income Shared (%)
1
On-farm
Agroforestry
199,135,000
3,829,519
6,255,682
15.8
Livestock
20,800,000
400,000
1,670,505
1.6
2
Off-farm
Daily laborers
424,990,000
8,172,885
13,440,567
33.7
3
Non-farm
Stall/Hawkers
364,565,000
7,010,865
14,345,205
28.9
Bike Mechanic
28,800,000
553,846
3,993,841
2.3
Craft (Boboko)
42,386,500
815,125
2,328,566
3.4
Others
180,080,000
3,463,076
6,646,217
14.3
Total
1,260,756,500
24,245,316
17,743,668
100
Source: Primary Data, 2019 Total N= 52; US$ 1= IDR 14,000
Figure 2. Distribution of farmer income based on land area and age group.
Figure 2 explains that the highest productivity of agroforestry occurs in farmers aged 41-45 years
with an average land area of 0.65 hectares and an average income of IDR 16,780,000 (US$ 1,198.6)
per year per farmer. In the age group 46-50 and above, agroforestry income tends to decrease along
with the area of land being managed. The downward trend of farmer income from agroforestry was
explained in Table 2 and shows that the majority of farmer groups members involved in agroforestry
businesses are over 45 years (67.3%).

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While the age group of 30-40 years manages land with an average area of 0.31-0.36 hectares,
yet, the level of agroforestry income is still relatively low in this group compared to the same level
of land in other older age groups (61-65 years). This is due to the fact that younger farmers are not
as focused on agroforestry, as it is viewed as an additional livelihood that makes the land become
unproductive. The younger farmers earn their main income from other livelihood options such as
daily laborers and hawkers.
In the case of the Parungpanjang FASP, the contribution of agroforestry income to total farmer
household income is 15.8%, with agroforestry income contribution in each farmer household
described in Figure 2. This has been caused by the following 1) different types of intercropping
planted, namely although the main intercropped plants (galangal) are relatively the same and
provide a large share of income, yet other intercropped plants also contribute to increasing farmers
income; 2) farmers motivation and skills, for farmers who regularly apply fertilizer and clean the
land, the results are much better than plants that remain unmanaged after planting; 3) age also
affects the physical ability to cultivate land. The majority of farmer groups members are already
elderly and expressed that they are unable to cultivate larger areas land. These farmers feel that the
land that has been cultivated is sufficient.
According to Brown et al. (2018), there are two important factors as a precondition for success
in adopting an agroforestry system before making further interventions namely, successful
mobilization and engagement of farmers and facilitating farmer capacity development and/or
access to qualified tree/agriculture seeds. Several interventions are needed after the precondition
phases have been met, include providing incentives, facilitating market networks, and institutional
and policy change.
3.3 Factors of agroforestry system that influence on the farmers household income
The agroforestry system factors analyzed in this regression model are explained in Table 6. Of
the five variables analyzed by t-test, there are two variables that have a significant influence on total
farmer income, namely age and land area (Table 7), whereas education, family size, and agroforestry
income variables do not have a significant influence on the total farmers household income.
Table 6. Explanation and summary statistics of variables
Variable
Explanation
Mean
Std. Deviation
N
Farmers Income (Y)
Total farmer income in IDR
per year
24245317.31
17743668.217
52
Age (X1)
Age in years
50.2885
10.55580
52
Education (X2)
Education in years
4.6923
2.96739
52
Family Size (X3)
The family member of
household (person)
3.5000
1.83110
52
Agroforestry Income (X4)
Household annual income
from agroforestry in IDR
3817980.7692
6260676.86152
52
Land Area (X5)
Land area in hectare
.4404
.29952
52
Source: Primary data, 2019.
Age (Sig. 0.007) has a negative influence direction, which means that as age increases, farmer
income will decrease, due to the contribution of agroforestry income also decreasing as farmers get
older and the limited area of land that can be managed. Agroforestry activities require farmers who
are in the productive age (18–50 years) due to intensive workload (Suherdi et al., 2014; Suyadi et
al., 2019). In the Parungpanjang FASP context, farmer physical ability to manage land will determine
the productivity and income received by the farmers. This phenomenon is verified by the findings
listed in Figure 2.

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Table 7. Result of t-test
Model
Standardized Coefficients
t
Sig.
Collinearity Statistics
Beta
Tolerance
VIF
(Constant)
3.250
.002
Age (X1)
-.400
-2.814
.007*
.816
1.226
Education (X2)
-.051
-.364
.718
.827
1.209
Family Size (X3)
-.049
-.369
.713
.926
1.080
Agroforestry Income (X4)
.035
.251
.803
.849
1.178
Land Area (X5)
.282
2.041
.047*
.866
1.155
a. Dependent Variable: Y – Household Income; * sigficant at p value < 0.05
Land area (Sig. 0.047) of the agroforestry system has a significant influence on the total farmer
income. This is consistent with Van Chu et al. (2019), which stated that farmers with larger forestry
land area have more chance to increase their household income. In this case, significant agroforestry
income is obtained from farmers aged 41-45 years with an average land area of 0.65 hectares. Land
productivity is also closely related to farmer capacity and access to resources, as well as access to
markets (Borrella et al., 2015; Brown et al., 2018).
4. Conclusion
Agroforestry practices in the Parungpanjang FASP have contributed to the income of farmer
groups members, but the effects are still imbalanced. This is influenced by the types of plant
cultivated, motivation and skills, and age relative to ability to manage land. Regarding the results of
the regression analysis, there are two agroforestry factors that influence farmer income, namely
age and land area.
In order to optimize the contribution of the agroforestry system to farmer income in the
Parungpanjang FASP, it is necessary to increase land productivity by assessing profitable
intercropped plant types in corresponding soil or land characteristics and minimum requirements
of physical treatments. Furthermore, FTSTRDC need to strengthen the capacity of farmer groups
members by facilitating technical capacity for training of good agricultural practices, including
facilitating the business model and market network of agroforestry products.
Author Contributions: Conceptualization and design of the experiments were conducted by D., and K.A.H.,
who performed the experiments. D and T.O.V analyzed the data and wrote the paper. D, T.O.V, and K.A.H.,
are the main contributors of the paper, and the others are member contributors. All authors have read and
agreed to the published version of the manuscript.
Conflicts of Interest: The authors declare no conflict of interest
Acknowldegement: The authors would like to express heartfelt thanks to the farmers in Tapos and Jagabaya
Village who took part in focus group discussions and informant interviews or respondent survey in our
research. We would like to express our special gratitude to the field officers in Parungpanjang, including Mr.
Adim, Mr. Muhammad, and Mr. Maman, and Dian Anshar for English editing. This paper is one of the joint
outputs of Pusat Unggulan Iptek (PUI) between the Center for Political Studies, Indonesian Institute of Sciences
and Forest Tree Seed Technology Research & Development Center (FTSTRDC/BP2TPTH), Ministry of
Environment and Forestry of the Republic of Indonesia, 2019.
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