Research Article

Assessing the Adoption of Superior Pepper Variety in Increasing the Efficiency: An Evidence of Pepper Farming in West Kalimantan, Indonesia

Rakhmad Hidayat1,2*, Dwidjono Hadi Darwanto3, Lestari Rahayu Waluyati3 and Jangkung Handoyo Mulyo3

1Faculty of Agriculture, Universitas Tanjungpura, Pontianak, Indonesia; 2Doctoral Program, Faculty of Agriculture, Universitas Gadjah Mada, Yogyakarta, Indonesia; 3Department of Agricultural Socioeconomics, Faculty of Agriculture, Universitas Gadjah Mada, Yogyakarta, Indonesia.

Received | March 14, 2024; Accepted | December 30, 2024; Published | January 28, 2025

*Correspondence | Rakhmad Hidayat, Faculty of Agriculture, Universitas Tanjungpura, Pontianak, Indonesia; Email: [email protected]

Citation | Hidayat, R., D.H. Darwanto, L.R. Waluyati and J.H. Mulyo. 2025. Assessing the adoption of superior pepper variety in increasing the efficiency: An evidence of pepper farming in West Kalimantan, Indonesia. Sarhad Journal of Agriculture, 41(1): 234-247.

DOI | https://dx.doi.org/10.17582/journal.sja/2025/41.1.234.247

Keywords | Efficiency, Stochastic frontier, Bengkayang pepper, Pepper farming, Farmer, Superior variety

Copyright: 2025 by the authors. Licensee ResearchersLinks Ltd, England, UK.

This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).

Introduction

Pepper (Piper nigrum L) is a vital spice plant extensively utilized across diverse industries. Its applications span various sectors, including the food, soft drinks, and cake industries. Pepper and its processed products are also utilized in the perfume, herbal medicine, and cosmetics industries (Khew et al., 2022; Saju and Ramadevi, 2023; Suwarto, 2016; Takooree et al., 2019). As a plantation commodity, pepper contributes significantly to a country’s foreign exchange and job provider (Semuroh and Sumin, 2021). The number of Indonesian pepper exports in 2020 reached US$ 160,388, with an export volume of 58,378 tons (Directorate General of Estate Crops, 2022). Opportunities for developing the pepper commodity in Indonesia remain promising due to its reputation as a high-value product and the expanding areas dedicated to pepper farming (Suwarto, 2016). The availability of land, favorable soil, climate conditions, and product diversification, particularly during declining pepper prices, have heightened farmers’ motivation to cultivate pepper.

In contrast, Indonesian statistical data recorded a decrease in productivity in pepper farming by 2.29% per year in 2014-2020. A quite significant productivity decline occurred in 2014-2015, with a drop of 10%, and in 2018, pepper productivity dropped to the lowest value, 789 kg/ha (Directorate General of Estate Crops, 2022). This situation aligns with Indonesia’s decline in pepper export volume in 2015-2019 (Directorate General of Estate Crops, 2022). Low production and farmers bargaining positions are also problems in the pepper marketing system in Indonesia (Zarliani et al., 2023).

West Kalimantan is recognized as one of the pepper-producing regions in Indonesia, characterized by smallholder plantations managing pepper cultivation. Statistical data records an increase in pepper area in West Kalimantan by 3.8% per year in 2014-2020, followed by a rise in farmer numbers (Central Bureau of Statistics, 2021). However, the increase in farm size and farmer number is not in line with the increase in pepper production, resulting in the decline of pepper productivity in West Kalimantan. Low productivity is the main problem in the pepper industry (Ee and Shang, 2017). Previous studies have gathered several issues regarding the decline of pepper productivity due to plant disease, especially foot rot disease, the use of local varieties, simple cultivation techniques, and the low application of fertilizers (Azri and Hatta,

2021; Ee and Shang, 2017; Suhaendah et al., 2020).

Low productivity indicates low farming efficiency, which refers to the quantity of output generated from a specific input. Previous studies have proven that farming activities in developing countries have not achieved efficiency (Asadullah and Rahman, 2009; Ureta et al., 2007). Farmers have only achieved efficiency ranging from 60-70% or inefficiency between 30-40% (Akamin et al., 2017; Ureta et al., 2007). Achieving technical, allocative, and economic efficiency is a significant factor in accelerating the growth of the agricultural sector and, at the same time, increasing farmers’ productivity and income.

Pepper farmers in West Kalimantan use a superior pepper variety called Bengkayang pepper. This variety is one of ten pepper varieties developed in Indonesia and issued by the Indonesian Center for Plant Variety Protection and Agricultural License (Meilawati et al., 2020; Prayoga et al., 2020). The Bengkayang pepper variety is claimed to be tolerant to foot rot and yellowing disease (Prayoga et al., 2020) and has higher production. Adopting this superior variety can increase the pepper productivity in West Kalimantan compared to the local variety. Local pepper varieties refer to pepper propagation seedlings cultivated by farmers from previous plants, with conditions and production not yet assured.

The study of farming efficiency is crucial as an indicator of farmers’ success in managing their farming activity. Farm sustainability is also reflected in farming efficiency. Technical efficiency in crop production is also essential to pursuing growth in small-scale agricultural output (Omar and Fatah, 2021). The problem of farming efficiency become the main focus in developing countries, including Indonesia, partly due to the low technical, allocative, and economic efficiency. Previous research on farming efficiency has been carried out on food crops (Ali et al., 2019; Biswas et al., 2023; Mulyani et al., 2020), horticulture (Hoque et al., 2019, 2021), livestock (Batzios et al., 2023; Junaidi et al., 2023), and fisheries (Islam et al., 2023). In the plantation sector, studies have been recorded regarding the efficiency of coffee (Tamirat and Tadele, 2023) and palm oil (Abdul et al., 2022).

This research aims to see the effect of adopting superior varieties of Bengkayang pepper on increasing production and efficiency and assess the technical, economic, and allocative efficiency of pepper farming in West Kalimantan. The novelties offered by this study are: (1) identifying the efficiency of pepper farming as a high-value product that is still promising for farmers, (2) emphasizing the influence of adopting the Bengkayang pepper variety in increasing production and efficiency of pepper farming, as well as including several variables others as predictors of farming efficiency. The findings of this study hold significant value for the government and stakeholders in shaping policy recommendations aimed at advancing the development of Bengkayang pepper varieties, intending to enhance efficiency and productivity in pepper farming.

Materials and Methods

Study area

The research area was decided purposively in West Kalimantan Province with consideration as one of the prominent pepper-producing centres in Indonesia with the most significant farm area and production on Kalimantan Island (Directorate General of Estate Crops, 2022). The selected districts were Bengkayang, Sanggau, and Sambas. One sub-district was chosen within each district: Selebar, Sekayam, and Galing sub-districts (Figure 1). Next, the centre village was chosen, namely the Sahan, Bungkang, and Ratu Sepudak villages. The sample consisted of 180 pepper farmers, selected based on having productive trees. Respondents were chosen using proportional random sampling. The research was carried out between October 2022 and May 2023.

 

Data analysis

Analysis of factors influencing pepper production using the Stochastic Frontier Analysis (SFA) into natural logarithm as follows:

Where Y is production, β0 is the intercept, β1–β9 are the coefficients of each independent variable, X1 is the farm size, X2 is the pepper tree, X3 labor, X4 is urea fertilizer, X5 is NPK fertilizer, X6 is manure, X7 is a herbicide, X8 is a fungicide, X9 is pepper age, and e is an error term. The formula resolves using the Maximum Likelihood Estimation (MLE) method. The use of the Cobb-Douglas function has been practiced in the agricultural sector, for example, in food crop production (Biswas et al., 2023; Tadesse et al., 2021; Zhang et al., 2020), fisheries (Yang et al., 2022), and livestock (Khan et al., 2022; Kibona et al., 2022). The next stage uses the SFA to measure technical, allocative, and economic efficiency.

Technical efficiency

Measuring the technical efficiency of pepper production uses the following equation (Coelli, 1998):

Where TEi denotes the technical efficiency of the ith farmer, Yi is output observed of farmer-ith, Yi* signifies output frontier estimated, exp(-ui) is the expected mean of the inefficiency effect (ui). Testing of the stochastic frontier efficiency parameter estimator is carried out in two stages, namely (1) estimating the β parameter using the OLS method, (2) estimating all parameters β0, β1–β9, variations of µi and vi simultaneously using the MLE method with the Frontier program version 4.1 (Coelli et al., 2005). The parameter test results will provide the following parameter variance estimation values (Aigner et al., 2023; Coelli, 1996).

Where; σ2 is the variance of the normal distribution, σμ2 is the variance µi, σv2 is the variance of vi. The value of the gamma parameter (γ) is the contribution of technical efficiency to the residual error (ε), with values ranging between zero and one. Parameter values γ that are close to zero indicate that deviations from the frontier increasingly lead to residual effects (error). In contrast, values that approach one indicate that deviations increasingly lead to inefficiency effects (Ogundari and Ojo, 2006).

The technical efficiency obtained is inversely correlated with the technical inefficiency. In this research, the technical inefficiency effect model refers to (Coelli et al., 1998). Variables to measure technical inefficiency are assumed to be independent and have a normal N distribution (µi, σ2). Determining the distribution parameter (µi) of the technical inefficiency effects uses the formula:

Where µi is the technical inefficiency effect, δ0 is intercept, δ10-δ14 is the coefficent, D1 Dummy of Bengkayang pepper, X10 farmers age, X11 education, X12 experience, X13 family size, and X14 frequency of extension. The decision-making criteria are: (1) If Xi < 0 = The higher the factor, the lower the inefficiency, and (2) If Xi > 0 = The higher the factor, the higher the inefficiency. Technical inefficiency is measured using the MLE method. Data analysis using Frontier software version 4.1.

Economic efficiency

Measuring economic efficiency uses input price information by deriving the dual cost function from the production function. In the SFA model it is formulated:

Where; C is production cost, γ0 is constant, γ0-γ8 is coefficient, P1 is the price of seed, P2 is the wage of labor, P3 is the price of urea fertilizer, P4 is the price of NPK fertilizer, P5 is the price of manure, P6 is the price of herbicide, P7 is the price of fungicide, Y is the production and vi - µi is error term (µj = inefficiency effect).

Jondrow et al. (1982) define economic efficiency as the ratio between the observed minimum total costs (C*) with the total actual production costs of farming (C), formulated:

According to Ogundari and Ojo (2006), the cost function can technically be analyzed using frontier 4.1 software, and the cost efficiency value will be obtained. Furthermore, economic efficiency is acquired as the inverse of cost efficiency.

Economic efficiency can be calculated as the product of technical efficiency and allocative efficiency, expressed by the following formula:

Results and Discussion

Table 1 provides descriptive statistics of the variables. 53% of farmers have adopted the Bengkayang pepper variety, and the remainder (47%) use local pepper. Bengkayang pepper is one of the superior pepper varieties in Indonesia, originating from Bengkayang Regency, West Kalimantan. This variety has received seed certification from the Ministry of Agriculture of the Republic of Indonesia with No. 466/Kpts/TP.240/7/1993 and No. 10/Permentan/OT.140/1/2013. The Bengkayang pepper variety is claimed to have high production and is resistant to stem rot disease (Prayoga et al., 2020). Local pepper is developed independently by farmers or other farmers obtained from previous crops whose quality and production results are not yet guaranteed.

Regarding input use, the average farmer has 800 pepper trees with an average farm size of 0.72 hectares. In other words, a farmer has an average of 1,108 pepper trees in a one-hectare area. This number follows technical recommendations for pepper cultivation, namely 1100-1600 trees per hectare with planting distances ranging from 2.5m x 2.5m to 3m x 3m (Suwarto, 2016). Regarding labor allocation, the most significant labor absorption is for harvest and post-harvest activities. Fertilizers in pepper farming are urea, NPK, and manure. The average use of urea fertilizer is 246.3 kg/year or 340,87 kg/ha/year following the recommended recommendations, namely 200–400 kg/ha/year (Suwarto, 2016). The average use of NPK fertilizer is 658.8 kg/year or 911,82 kg/ha/year, exceeding the recommended recommendation of 400-600 kg/ha/year (Mandiri, 2017). The average use of manure is 1,178.03 kg/year or 1,630.48 kg/ha/year, less than the recommended recommendation, namely 5-10 kg/plant/year or around 5,500-11,000 kg/ha/year (Mandiri, 2017).

Factors affecting pepper farming production

The results of the Cobb-Douglas stochastic frontier production are identified in Table 2. The variables that significantly and positively affect pepper production are the farm size, pepper tree, labor, urea fertilizer, fungicide, and pepper age. The farm size

 

Table 1: Description and unit measurement of variables.

Variables	Description and unit measurement	Mean	Std. dev.
Dependent variables
Pepper production	Amount of pepper production (kg/year)	549.44	97.56
Independent variables
Pepper farm characteristic
Farm size	Pepper farm size (hectare)	0.72	0.21
Pepper age	Age of pepper plants (year)	8.28	1.02
Pepper farm managerial
Bengkayang pepper variety	Use of Bengkayang pepper (1=use, 0=no)	0.53	0.50
Farmer age	Farmer age (year)	45.91	7.24
Education	Formal education (year)	9.29	2.48
Family size	Number of family members (person)	4.24	0.98
Experience	Farmer experience in pepper farming (year)	15.81	4.37
Frequency of extension	Frequency of extension (time)	1.83	0.61
Input variables
Pepper tree	Amount of pepper tree (unit/year)	800.22	119.81
Labor	Amount of labor working day (working day/year)	455.75	234.46
Urea fertilizer	Amount of urea fertilizer (kg/year)	246.28	41.65
NPK fertilizer	Amount of NPK fertilizer (kg/year)	658.79	161.81
Manure	Amount of manure (kg/year)	1178.03	288.71
Herbicide	Amount of herbicide (litre/year)	5.03	1.52
Fungicide	Amount of fungicide (kg/year)	3.64	1.08
Price of input variables
Price of seed	Price of seed fertilizer (IDR/kg)	1.455	330
Price of labor wage	Price of labor wage (IDR/working day)	59,333	8,363
Price of urea fertilizer	Price of urea fertilizer (IDR/kg)	9,284	2,097
Price of NPK fertilizer	Price of NPK fertilizer (IDR/kg)	15,248	4,424
Price of Manure	Price of manure (IDR/kg)	529	191
Price of herbicide	Price of herbicide (IDR/litre)	83,903	8,713
Price of fungicide	Price of fungicide (IDR/kg)	114,628	4,040

Source: primary data analysis (2023).

 

Table 2: Estimation of stochastic frontier production with the MLE.

Variable	Expected sign	Coefficient	Std error	t-ratio
Constanta	+/-	3.709***	0.435	8.536
Farm size	+	0.185***	0.029	6.374
Pepper tree	+	0.261***	0.061	4.296
Labor	+	0.029*	0.015	1.878
Urea fertilizer	+	0.148**	0.071	2.092
NPK fertilizer	+	-0.080 **	0.033	-2.408
Manure	+	0.013 ns	0.025	0.506
Herbicide	+	-0.012 ns	0.220	-0.563
Fungicide	+	0.051**	0.025	2.029
Pepper age	+	0.254***	0.075	3.383
Sigma-square		0.003***	0.0003	9.460
Gamma		0.999***	0.060	16.578
Log-likelihood MLE		258.522
LR test		34.38

*p < α = 10%, ** p < α = 5%, *** p < α = 1%, Source: primary data analysis (2023).

 

positively and significantly affects pepper production at α = 1% with a coefficient of 0.185, which means that increasing farm size by 1% will increase pepper production by 0.185%. Respondent farmers own 0.72 ha of private farm area, so they have full rights to make farming decisions, including the input and technology adoption. The positive influence of farm size on production was discusssed in previous studies (Andaregie et al., 2020; Ghimire et al., 2023; Mulyani et al., 2020; Omar and Fatah, 2021; Osti et al., 2017).

The pepper tree positively and significantly affects pepper production at α=1% with a coefficient of 0.261, which means that increasing the number of pepper trees by 1% will increase pepper production by 0.261%. This variable has the highest coefficient value among other significant independent variables, so it is the most responsive variable in increasing pepper production. The number of pepper trees varies, depending on the planting distance and farm size. The planting distance is generally 3m x 3m, with an average number of 800 trees per 0.72 ha, equivalent to 1,107 trees per ha. The positive influence of the number of pepper trees on production was also found in previous studies (Kumar et al., 2018; Verma et al., 2021; Edison, 2022).

The labor has a positive and significant effect at α= 10% with a coefficient of 0.028, which means that increasing the labor positively and significantly impacts increasing pepper production. The labor generally comes from family members with productive age. Outside labor is usually used in certain activities that require much labor, such as harvest and post-harvest activities. Previous studies also show that increasing labor has a positive effect on production (Osti et al., 2017; Andaregie et al., 2020; Wijayanti et al., 2020; Tadesse et al., 2021; Verma et al., 2021; Edison, 2022; Ghimire et al., 2023).

The urea fertilizer has a positive and significant effect at α = 5% with a coefficient of 0.148, which means that increasing the urea fertilizer positively influences rising production. Pepper is a commodity that requires sufficient nutrition to provide substantial production results. Urea fertilizer is essential to strengthen plant roots and accelerate the growth of new shoots. Previous studies are in line with these results and state a positive response of fertilizer on production (Osti et al., 2017; Kumar et al., 2018; Chandio et al., 2019; Zhang et al., 2020; Omar and Fatah, 2021; Verma et al., 2021).

The NPK fertilizer has a negative and significant effect at α= 5% with a coefficient of -0.080. In contrast to urea fertilizers, NPK fertilizers negatively affect production, which means that increasing the NPK fertilizers can reduce pepper production. It means that the use of NPK fertilizer has exceeded the recommended dose. The average use of NPK fertilizer by respondent farmers is 911,82 kg/ha/year, while the recommended dose is 400-600 kg/ha/year (Suwarto, 2016). Respondent farmers have pepper trees in productive age, using more NPK fertilizer to stimulate and accelerate the growth of flowers and fruit. However, the use of NPK fertilizer becomes excessive and has a negative impact on decreasing production.

The fungicide has a positive and significant effect at α= 10% with a coefficient of 0.051, which means that increasing fungicides has a positive impact on increasing pepper production. The primary disease that attacks pepper plants is foot rot, which is led by Phytophthora capsici (Vandana et al., 2014). This disease reduces productivity and even causes the death of pepper plants (Vandana et al., 2014; Nysanth et al., 2022). In several cases, the death rate of pepper trees due to the Phytophthora capsici virus reached 100% (Anh et al., 2018). Farmers treat pepper plant diseases using fungicides or destroy diseased plants by burning them, then treat the soil with bokashi fertilizer and Trichoderma sp. or provide lime to suppress the development of viral pathogens. They used fungicides and biopesticides, which have also proven effective in treating Phytophthora capsici infections in pepper plants (Rini and Remya, 2020).

The pepper age has a positive and significant effect at α = 5% with a coefficient of 0.253, which means that increasing the pepper age will increase pepper production. The lifespan of productive pepper plants ranges from 3-8 years (Suwarto, 2016). However, with good maintenance, this plant can still produce up to 15 years of age. Respondents have an average of 8.28 years of pepper trees and are in the productive category, positively impacting the increase of pepper production.

Analysis of technical efficiency and inefficiency

Table 3 displays the results of technical efficiency using the SFA production function. The estimation results describe the respondent farmers best performance at the existing technology level. The gamma (γ) value is 0.9999 and significant at α= 1%, indicating that technical inefficiency variables cause 99.99% of the error variation. The remaining 0.01% is caused by stochastic effect random variables, such as climate risk, natural disasters, pests, and diseases (Coelli et al., 2005; Ureta et al., 2020).

 

Table 3: Estimation of technical inefficiency.

Variable	Expected sign	Coefficient	Std error	t-ratio
Constanta	+/-	0.589***	0.128	4.586
Bengkayang pepper variety	-	-0.040***	0.009	-4.098
Farmer’s age	-	-0.007 ns	0.033	-0.211
Education	-	-0.072***	0.024	-3.048
Experience	-	-0.050**	0.020	-2.513
Family size	-	-0.011 ns	0.023	-0.479
Frequency of extension	-	-0.004 ns	0.015	-0.256

*p < α = 10%, ** p < α = 5%, *** p < α = 1%; Source: primary data analysis (2023).

 

The sigma square (σ2) value is 0.00332 and significant at α= 1%, indicating that the model used is appropriate and the inefficiency error terms (vi and ui) are normally distributed. The Log-likelihood values are 258.522, meaning the model can describe the farming conditions. The LR test value of 34.38 is greater than X2 in the table (Kodde and Palm, 1986) at α = 1%, and the value of limit 6 is 16.07, indicating that the SFA function can describe the existence of technical efficiency and inefficiency in the pepper farming production.

The analysis results in Table 3 show that farming management and socio-economic variables mainly contribute to technical inefficiency in pepper farming. The influence of farming management variables on farming efficiency was also reported in prior research (Hoque et al., 2019, 2021; Ghimire et al., 2023; Tamirat and Tadele, 2023).

Bengkayang pepper variety has a negative and significant effect at α = 1% on farming inefficiency, which indicates that using the Bengkayang pepper variety can reduce technical inefficiency or, in other words, increase the technical efficiency. The negative influence of using superior seeds on inefficiency was also reported in previous studies (Ali et al., 2019; Hoque et al., 2019, 2021; Mulyani et al., 2020; Ghimire et al., 2023).

The Bengkayang variety has been adopted by 52.77% of respondents, and the remaining 47.23% used local seeds. Farmers obtain Bengkayang pepper variety by buying from seed breeders or getting assistance from the government. This variety is claimed to be tolerant to foot rot and yellowing disease (Prayoga et al., 2020). The Bengkayang pepper variety has been proven to produce higher production than local varieties. The study results confirm the earlier research that stated that choosing a suitable seed will be the primary determinant of production (Andaregie et al., 2020; Baser and Bozoglu, 2020; Zulfiqar et al., 2021; Tadesse et al., 2021; Li, 2023). The study by Kumar et al. (2021) stated that pepper productivity optimization can be achieved by developing superior varieties that are tolerant to foot rot disease and can adapt to shade. Improved varieties reflect farmers adaptability to information and technology, leading to increased production (Imelda et al., 2023).

Socio-economic factors that negatively and significantly influence the inefficiency of pepper farming are education and farming experience, which means that increasing education and experience will decrease inefficiency or increase its technical efficiency. These findings are in line with prior studies which show the influence of education and experience on farming efficiency (Ajapnwa et al., 2017; Ali et al., 2019; Hoque et al., 2019; Andaregie et al., 2020; Omar and Fatah, 2021; Ghimire et al., 2023; Islam et al., 2023; Junaidi et al., 2023; Workneh and Kumar, 2023). Based on these results, increasing farming efficiency can be done by increasing informal education, for example, by providing extension and training to farmers.

The different values of technical efficiency in Bengkayang and local pepper are presented in Table 4. Farmers with Bengkayang variety adoption have achieved a technical efficiency value (0.80) of 61.05%, while for local varieties, it is only 29.42%. The average technical efficiency for the adopters of the Bengkayang pepper variety is 0.81, and for local pepper is 0.77. These results indicate that not all pepper farming activities are carried out efficiently. The implementation of farming activities that are not yet fully efficient was also found in various agricultural sectors (Hoque et al., 2019; Omar and Fatah, 2021; Workneh and Kumar, 2023). Inefficient farming activities indicate a chance to increase efficiency through better resources and technology. Farming management and better use of resources are determining factors for farming efficiency (Kumar et al., 2018).

 

Table 4: Distribution of value and criteria technical efficiency.

Interval	Bengkayang pepper		Local pepper
	Frequency	%	Frequency	%
0.20-0.39	0	0.00	0	0.00
0.40-0.59	0	0.00	0	0.00
0.60-0.79	37	38.95	60	70.58
0.80-1.00	58	61.05	25	29.42
Total	95	100.00	85	100.00
Min	0.71		0.63
Max	0.97		0.93
Mean	0.81		0.77

Source: primary data analysis (2023).

 

Next, the cost efficiency using the SFA cost function is detailed in Table 5. The analysis obtained a sigma-square (σ2) value of 0.03896, significant at α = 1%, which means the model and distribution are appropriate. The gamma parameter (γ) 0.94211 indicates that inefficiency factors influence 94.21% of the variation in the error term, while variables outside the model cause 5.79%. In the cost function, the MLE log-likelihood values are 234.42, indicating that the value is better and more precise in describing farming conditions.

 

Table 5: Estimation of cost inefficiency.

Variable	Expected sign	Coefficient	Std. error	t-ratio
Constanta	+	3.995**	2.012	1.985
Price of seed	+	0.326***	0.072	4.472
Price of labor wage	+	0.075 ns	0.088	0.857
Price of urea fertilizer	+	0.526***	0.077	6.830
Price of NPK fertilizer	+	0.785***	0.046	16.846
Price of manure	+	0.043 ns	0.028	1.546
Price of herbicide	+	-0.187*	0.103	-1.824
Price of fungicide	+	-0.314*	0.185	-1.697
Production	+	0.306***	0.065	4.669
Function of cost inefficiency
Constanta		-0.107 ns	0.486	-0.220
Bengkayang pepper variety	-	-0.402**	0.161	-2.487
Farmer’s age	-	0.334**	0.139	2.404
Education	-	-0.197**	0.096	-2.051
Experience	-	-0.582ns	0.070	-0.827
Family size	-	-0.662***	0.233	-2.840
Frequency of extension	-	-0.382**	0.157	-2.429
Sigma-square		0.038***	0.012	3.172
Gamma		0.942***	0.019	47.275
Log-likelihood function MLE		234.425
LR test of the one-side error		51.969

*p < α =10%, ** p < α = 5%, *** p < α = 1%; Source: primary data analysis (2023).

 

The LR test value of 51.96 is greater than X2 in the table (Kodde and Palm, 1986) at α = 1%, and the value of limit 6 is 16.07, indicating that the SFA cost function can describe the existence of cost efficiency and inefficiency in pepper farming. The stochastic cost function shows that the input prices (seed, urea fertilizer, NPK fertilizer) and production are positive and significant at α = 1%. It indicates that the increase in seed prices, urea fertilizer prices, NPK fertilizer prices, and production caused a rise in production costs. An increase in input price has a high potential to increase input costs because mature trees with ages over three years require more fertilizer than immature trees. Hence, the production costs are more significant (Sulok et al., 2018). These results align with the study of Islam et al. (2023), stating that high input prices positively correlate with increased production costs.

Further, a study from Biswas et al. (2023) also noted that high input prices were a problem in farming efficiency. In studies by Zulfiqar et al. (2021), the input cost is the most significant factor in reducing farming efficiency. One of the causes of high input costs is farmers difficulty in accessing inputs, so it is necessary to ensure farmers input access. Prior studies also explained that farmers access to inputs increases farming efficiency (Ajapnwa et al., 2017; Junaidi et al., 2023). Maintaining input availability is also essential to improving the resilience of smallholder plantations (Andani et al., 2022).

The herbicide and fungicide prices have a negative and significant coefficient at α= 10%. It shows that increased prices will reduce the use of herbicides and fungicides, reducing production costs. Herbicides are used to treat weeds, while fungicides are used to treat fungi that cause foot rot disease. Farmers constrained by capital generally deal with weeds mechanically (cutting the weeds). Farmers typically use chemical methods with fungicides or mechanical methods for foot rot disease, such as replanting or replacing infected plants with healthy plants.

Managerial and socio-economic factors that negatively and significantly affect cost inefficiency are Bengkayang pepper variety, education, family size, and frequency of extension. The Bengkayang pepper variety can adapt to the environment, is resistant to disease, and has the potential for high production, which can reduce cost inefficiencies. Regarding farmer education, the higher the education, the more rational farmers are in using inputs to reduce cost inefficiencies. The negative influence of education on cost inefficiency was also reported in prior research (Andaregie et al., 2020; Islam et al., 2023).

Increasing the family size can reduce cost inefficiencies because the family size reflects the size of the assets owned by the farmers’. Having more family members who can help in farming can reduce labor costs, reducing cost inefficiencies. In line with this study, research from Biswas et al. (2023) also stated that the scarcity of human labor could reduce farming efficiency. Studies from Zulfiqar et al. (2021) also suggest the importance of involving family labor rather than hiring labor.

The frequency of extension indicates that increasing the frequency of extension will reduce cost inefficiencies. On average, respondent farmers participated in two extension activities organized by Field Agricultural Extension Officers. The extension material is related to cultivation techniques and government programs. Previous studies also reported the importance of extension in farming activities, which stated that farming inefficiencies can be minimized through good extension and market information support (Hoque et al., 2021). Mahmood et al. (2020) also reported a positive influence between farmer participation in extension activities and cost efficiency. Further, the study by Zozimo et al. (2023) also recommended increasing field school activities to increase farming efficiency. Through extension activities and field school activities, it is hoped that farmers can increase knowledge about Good Agricultural Practices (GAP). GAP is needed to increase production and efficiency of farming businesses (International Pepper Community, 2007; Krasachat, 2023; Al-Aziz and Suryani, 2024).

Economic and allocative efficiency analysis

Economic efficiency combines technical and allocative efficiency (Ali et al., 2017). Farmers are economically efficient if they can simultaneously achieve technical and allocative efficiency. Allocative efficiency describes the most efficient use of production costs to produce a specific output. The allocative efficiency is a comparison between economic efficiency and technical efficiency. The distribution of economic and allocative efficiency is presented in Table 6.

The research results show that farmers adopting Bengkayang pepper varieties have higher economic and allocative efficiency than local pepper. The Bengkayang pepper variety has achieved an economic efficiency value of 0.6-0.79, as much as 33.68%, while the local variety is only 21.17%. In addition, the Bengkayang pepper varieties have achieved an allocative efficiency value of 0.80, as much as 17.89%, while for local pepper, it is 10.58%.

The distribution values show that the average economic and allocative efficiency of the Bengkayang pepper is 0.56 and 0.69, respectively, higher than the local pepper’s 0.52 and 0.67. The Bengkayang variety’s lowest economic efficiency was 0.36, and the highest was 0.75. Farmers can reach maximum efficiency by saving 25.33% (1-0.56/0.75). The lowest economic efficiency for local varieties was 0.26, and the highest was 0.74. Farmers can reach maximum efficiency by saving 29.73% (1-0.52/0.74) (Ogundari and Ojo, 2006).

The distribution value of allocative efficiency for the Bengkayang pepper was the lowest at 0.42 and the highest at 0.92. It indicates that, on average, farmers can reach the maximum level of allocative efficiency by saving costs of 25% (1-0.69/0.92). The lowest allocative economic for local pepper was 0.31, and the highest was 0.83. Farmers can reach the maximum allocative efficiency by saving 19.27% (1-0.67/0.83).

 

Table 6: Estimate of economic and allocative efficiencies.

Interval	Economic efficiency				Allocative efficiency
	Bengkayang pepper		Local pepper		Bengkayang pepper		Local pepper
	Freq.	%	Freq.	%	Freq.	%	Freq.	%
0.20-0.39	2	2.11	6	7.05	0	0.00	3	3.52
0.40-0.59	61	64.21	61	71.76	26	27.37	9	10.58
0.60-0.79	32	33.68	18	21.17	52	54.74	64	75.29
0.80-1.00	0	0.00	0	0.00	17	17.89	9	10.58
Total	95	100.00	85	100.00	95	100.00	85	100.00
Minimum	0.36		0.26		0.42		0.31
Maximum	0.75		0.74		0.92		0.83
Mean	0.56		0.52		0.69		0.67

Source: primary data analysis (2023).

 

Conclusions and Recommendations

The study concludes that adopting Bengkayang pepper positively influences production, technical, economic, and allocative efficiency in pepper farming. Other factors contributing to increased pepper production include farm size, number of pepper trees, labor, urea fertilizer, and fungicides. Despite generally low-efficiency levels in pepper farming in West Kalimantan, adopting Bengkayang Pepper has been proven to enhance efficiency. This is evidenced by higher technical, economic, and allocative efficiency values for Bengkayang Pepper than local pepper. Opportunities to enhance the efficiency of pepper farming remain open through interventions in various factors. Identifying influential factors reveals that education and experience can mitigate technical inefficiency, while education, family size, and frequency of extension services can reduce cost inefficiencies. However, the study results underscore the importance of adopting superior varieties such as Bengkayang pepper among pepper farmers. This adoption positively influences production efficiency and contributes to improvements in technical, economic, and allocative efficiency, ultimately enhancing overall farm profitability and sustainability. Therefore, promoting the adoption of superior pepper varieties emerges as a critical strategy for maximizing efficiency and productivity in pepper farming.

The government plays a vital role in supporting the development of superior pepper varieties and promoting cultivation techniques aligned with Good Agricultural Practices (GAP) to enhance production and efficiency in pepper farming. Additionally, efforts to increase farmers capacity through extension services and training activities are essential. These initiatives aim to enhance farmers skills in input usage and decision-making related to farming practices, thereby improving overall farm management and efficiency. Furthermore, optimizing inputs such as urea fertilizer and fungicides according to recommended dosages is vital. By adhering to proper application rates, farmers can maximize the benefits of these inputs and potentially boost pepper production while minimizing costs and environmental impact.

Acknowledgements

The authors gratefully acknowledge the support provided by the Ministry of Finance through the LPDP for the BUDI-DN scholarship, which facilitated the pursuit of the Doctoral Program at Gadjah Mada University, Yogyakarta, Indonesia.

Novelty Statement

Previous research on farming efficiency has predominantly focused on food crops, horticulture, livestock, and fisheries, with limited attention to the plantation sector. This study introduces two novel aspects: firstly, it examines the efficiency of pepper farming, a high-value product in agriculture; secondly, it emphasizes the impact of adopting the Bengkayang pepper variety on enhancing both production and efficiency in pepper farming.

Author’s Contributions

Rakhmad Hidayat: Research framework, methodology, collect data, data tabulation and analysis, results interpretation, manuscript writing, review and editing.

Dwidjono Hadi Darwanto: Research framework, methodology, questionnaire, data analysis, manuscript writing and review.

Lestari Rahayu Waluyati and Jangkung Handoyo Mulyo: Research framework, methodology, questionnaire, manuscript review and editing.

All authors read and approved the final manuscript

Conflict of interest

The authors have declared no conflict of interest.

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