Available via license: CC BY
Content may be subject to copyright.
ISSN : 2302 - 1590
E-ISSN: 2460 – 190X
Economica: Journal Of Economic And Economic Education
Volume 10, Issue 1, October 2021, pp 23-32
ANALYSIS OF THE EFFICIENCY OF THE MANAGEMENT
OF PRIVATE HIGH SCHOOLS
Aditia Rhomadhani1), Suratno2), Kuswanto3)
1)Study Programme Economic Education, Universitas Jambi, Indonesia.
Email: rhomadaniaditia@gmail.com
2)Study Programme Economic Education, Universitas Jambi, Indonesia.
Email: suratno@unja.ac.id
3)Study Programme Economic Education, Universitas Jambi, Indonesia.
Email: kuswanto.fkip@unja.ac.id
Submitted: 2020.05.31 Reviewed: 2020.10.19 Accepted:2020.10.30
https://doi.org/10.22202/economica.2021.v10.i1.4901
Abstract
The number of private high schools even makes parents reluctant to enroll their children in private high schools,
due to several conditions such as the condition of facilities and infrastructure are alarming and the number of
students is constantly decreasing each year. This study aims to analyze factors or inputs that affect the number of
graduates of private high schools in Jambi City and measure the level of technical efficiency of private high
schools in Jambi City. The results showed that the factors or inputs that influenced the number of private high
school graduates in Jambi city from 2015-2019 were students and classrooms. While the factors or inputs that do
not affect the number of graduates are study groups, teachers, administrative personnel, and support rooms. The
technical efficiency level of 27 private high schools in Jambi city from 2015-2019, the highest in 2015 reached
0,78 = 78%, the lowest figure occurred in 2019 only 0,27 = 27% and the average only reached0,49 = 49%, this
explains that the efficiency of managing private high schools in Jambi city has not been efficient. The results of
the study recommended that private high schools in Jambi city be technically efficient by optimizing the
achievement of graduate competencies consisting of qualification criteria of learners' abilities that are expected
to be achieved after completing their studies in the secondary education unit and the addition of classrooms is
necessary to create a comfortable and disciplined learning atmosphere, orderly, anti-smoking and drugs,
harmony between teachers, students and parents and maintain optimal conditions in the learning process.
Jel Classification:
F49; C67; C67.
Keywords: Technical Efficiency, School Input, School Output
©2021Economic Education Study Program STKIP PGRI WEST Sumatera, Indonesia.
Aditia Rhomadhani
24
Economica: Journal Of Economic And Economic Education
Volume 10, Issue 1, October 2021, pp 23-32
INTRODUCTION
Education is one of the instruments in shaping quality human resources. The
educational unit that plays an important role in improving the quality of human resources is
formal education. High School is part of the education unit of formal education providers. High
School is divided into two, namely public high school and private high school. The
management of public high schools is currently implemented by the Local Government. Based
on the Directorate of High School Development of the Ministry of Education and Culture
(Menteri Pendidikan dan Keb, 2017) in line with the reform era in which regional autonomy
occurred, management was carried out by the Central and Regional Governments following
their authority. Based on Government Regulation of the Republic of Indonesia Number 28 of
1981 concerning The Provision of Assistance to Private Schools in article 1 mentioned that
private schools are schools established and organized by people or private entities of charitable
nature. Based on the Law of the Republic of Indonesia Number 20 of 2003 concerning the
National Education System in article 51 paragraph 1 mentioned that the management of
secondary education units is carried out based on minimum service standards with school-
based management principles. To optimize the management of secondary education units,
quality education management is required (Marzuki, 2012). Based on the Directorate of High
School Development of the Ministry of Education and Culture (Direktorat Pembinaan SMA,
Direktorat Jenderal Pendidikan Dasar dan Menengah, n.d. 2018) the quality of education is a
comprehensive picture and characteristic of goods or services that demonstrate its ability to
satisfy expected needs that include inputs, processes, and educational outputs. Efficiency is
defined as the comparison between output and input (Rizky Yudaruddin, 2017) Based on the
Directorate of High School Development of the Ministry of Education and Culture (Direktorat
Pembinaan SMA, Direktorat Jenderal Pendidikan Dasar dan Menengah, n.d.2018: 16 2018)
especially related to the quality of school output, it is said to be quality when school
performance in this case students show high achievement in academic achievement. Input-
output research looks for ways educational inputs are converted into educational outcomes
(Marini, 2012).
At this time, private high schools face a big challenge, namely with free schools. Where
the data of Jambi City High School in 2021. Private high schools are much more numerous
with a total of 33 schools, while public high schools only number 13 schools. The number of
private high schools even makes parents reluctant to enroll their children in private high
schools, due to several conditions such as the condition of facilities and infrastructure are
alarming and the number of students is constantly decreasing each year. To know that the
management of the school is managed appropriately or efficiently to be in demand by all
parties, private high schools must make efficient. The only exception is private schools, which
are positively related to efficiency and equality (Woessmann, 2011). Efficient in this case is in
the use of school inputs to produce maximum school output. (Mulyati, 2013) in his literature
studies suggests that the calculation of improvement of each school can help the relevant parties
to determine the number of inputs and output targets used in achieving efficient conditions.
School inputs in this study are students, study groups, teachers, administrative personnel,
classrooms, and support rooms. The school output in this study was the number of graduates.
So that if the management of school inputs is carried out to the maximum, then the output of
the school produced is technically correct. Measurement of technical efficiency of schools
using multi-input and multi-output is expected to provide a new nuance of school performance
and can explain school performance in real time (Mulyadi JMV, 2016).
Research conducted by (Decker, 2014) the number of graduates at various levels is by
far the most commonly used output variable included in the analysis of efficiency estimates. In
Aditia Rhomadhani
25
Economica: Journal Of Economic And Economic Education
Volume 10, Issue 1, October 2021, pp 23-32
addition, there is also research on the ratio of students per class, Indriati, (2014) determination
of priority scale, identification and synchronization of data on physical facilities and
infrastructure, whether held new procurement, new buildings, rehab or routine maintenance.
The same is revealed (Mulyadi JMV, 2016: 21) factors that cause schools to be inefficient are
the ratio of students to administrative personnel and the ratio of students to teachers. Based on
the explanation above, it is necessary to conduct an assessment on the efficiency of school
management, which is expected later with each input can explain the performance of the school
in a rill and can help the school in achieving efficient school conditions.
This study aims to analyze factors or inputs that affect the number of graduates of
private high schools in Jambi City and measure the level of technical efficiency of private high
schools in Jambi City. The results showed that the factors or inputs that influenced the number
of private high school graduates in Jambi city from 2015-2019 were students and classrooms.
METHODS
This research uses a quantitative approach. The research method used is descriptive
method. The samples in this study amounted to 27 private high schools in Jambi City. The data
source in the study came from the Ministry of Education and Culture from 2015-2019. This
study uses panel data which is a combination of cross section data with periodic data (time
series). (Mulyati, 2018) measures the efficiency of public high school education using data
analysis envelopment analysis (DEA) and variable return to scale (VRS). (Togatorop, 2017)
measures the cost of education against the quality of private high schools using track analysis.
In addition, there is also about the ratio of perelas students, (Indriati, 2014) priority scale
determination, identification and synchronization of data regarding physical facilities and
infrastructure, whether new procurement, new buildings, rehab or routine maintenance.
(Indriati, 2014) the number of graduates at various levels is by far the most commonly used
output variable included in the efficiency estimation analysis.
The school's efficiency measurements are carried out using Stochastic Frontier Analysis
(SFA). Stochastic Frontier Analysis (SFA) is one of the parametric approaches used for
technical efficiency measurement. The advantage of this approach is that the hypothesis can be
tested statistically and the relationship between input and output follows a known function
(Putri, 2019). Output research assumes that school performance results are directly linked to
inputs such as: expenses for each student, teacher characteristics, teacher-student ratio, and
characteristics of students and their families, the result of which is a score from the test (A
Marini, 2016).
RESULTS AND DISCUSSION
Analysis of the production function of SFA (Stochastic Frontier Analysis) used in
testing the efficiency of the management of private high schools in Jambi City from 2015-2019
is a production function Cobb-Douglas conducted simultaneously using the software program
Frontier Version 4.1C consisting of 6 variables of descriptors, namely: students, study groups,
teachers, administrative personnel, classrooms, and support rooms. The results of the analysis
are described in Table 1, the following:
Aditia Rhomadhani
26
Economica: Journal Of Economic And Economic Education
Volume 10, Issue 1, October 2021, pp 23-32
Tabel 1. Estimation of Parameters and t Ratio of SFA Production Function Model
(Stochastic Frontier Analysis)Using MLE
Variable
Parameters
Coefficient
t-ratio
School Input
Interception
β0
3,77
0,47
Students
β1
0,23
5,22***
Study Groups
β2
-0,43
-0,23
Teachers
β3
0,04
0,09
Administrative Personnel
β4
-0,29
-0,21
Classrooms
β5
3,86
2,72***
Support Rooms
β6
-1,16
-0,68
Variant Parameters
Sigma-squared
662,38
1,96
Gamma
0,41
1,24
Log-Likelihood OLS
-601,06
Log-Likelihood MLE
-600,11
LR
1,90
Mean TE
0,49
Source: Primary data, 2021 (processed)
Information:
*** : real at ɑ = 1%; ** : real at ɑ = 5%; * : real at = 10%
Table 1, shows that the signs and magnitude of parameters in the cobb-Douglas
production function have been following the desired expectations. Positive signs indicate a
direct relationship between school inputs and the number of graduates. Negative signs indicate
a decrease in the number of graduates in line with the increase in variables. Based on the results
of the estimated production function of Cobb-Douglas, two school inputs affect the number of
graduates, namely: students, and classrooms. Students and classrooms have a very real effect
on the 99% level of trust. Mathematically the Cobb-Douglas production function model is
described in the following equation:
Ln Q = 3,77 + 0,23InPd − 0,43InRb + 0,04InG − 0,29InTa + 3,86InRk − 1,16InRp + vᵢ − uᵢ
Based on the results of efficiency tests with frontier version 4.1C software program, the
technical efficiency level of private high schools in Jambi City from 2015-2019 is described in
Table 2, the following:
Aditia Rhomadhani
27
Economica: Journal Of Economic And Economic Education
Volume 10, Issue 1, October 2021, pp 23-32
Table 2. Technical Efficiency Levels of Private High Schools
in Jambi City from 2015-2019
No.
School Name
Technical Efficiency Level
2015
2016
2017
2018
2019
1
Xaverius Private High School 2 Jambi
1
1
1
1
1
2
Private High SchoolNusantara Jambi
1
1
1
1
1
3
AttaufiqPrivate High School
1
1
1
1
1
4
Jambi IX LurahPrivate High School
1
1
1
1
1
5
Private High SchoolSuryaIbu
1
1
1
1
0,88
6
Al-Falah Islamic Private High School
1
1
1
1
0,21
7
Private High SchoolUnggulSakti
1
1
1
1
0,2
8
XaveriusPrivate High School 1 Jambi
1
1
1
0,92
0,16
9
Ferdy Ferry PutraPrivate High School
1
1
1
0,51
0,17
10
PGRIPrivate High School 2 Jambi
1
1
1
0,15
0,15
11
PurnamaPrivate High School 2 Jambi
1
1
1
0,12
0,16
12
Sariputra National Private High School
1
1
0,79
0,14
0,15
13
MuhammadiyahPrivate High School
1
1
0,42
0,13
0,14
14
MegatamaPrivate High School
1
1
0,11
0,11
0,12
15
Private High SchoolDua Mei Jambi
1
0,1
0,08
0,09
0,09
16
Dharma BhaktiPrivate High School3
1
0,07
0,08
0,08
0,09
17
YadikaPrivate High School
1
0,07
0,08
0,08
0,09
18
NomensenPrivate High School
0,98
0,07
0,08
0,08
0,09
19
Dharma BhaktiPrivate High School 4
0,76
0,07
0,07
0,08
0,08
20
Dharma BhaktiPrivate High School 2
0,69
0,07
0,07
0,08
0,08
21
Al-Azhar Integrated Islamic Private
High School Jambi City
0,67
0,06
0,07
0,08
0,08
22
Pelita RayaPrivate High School
0,48
0,07
0,07
0,08
0,08
23
AdhyaksaPrivate High School 1 Jambi
0,43
0,07
0,07
0,08
0,08
24
PGRIPrivate High School 3 Jambi
0,11
0,06
0,06
0,07
0,07
25
Private Christian High School Bina
Kasih
0,03
0,03
0,03
0,03
0,03
26
YPWIPrivate High School
0,005
0,005
0,01
0,01
0,01
27
PertiwiPrivate High School
0,003
0,003
0,003
0,003
0,004
Average
0,78
0,55
0,48
0,37
0,27
Source: Primary data, 2021 (processed)
In Table 3, the level of technical efficiency of private high schools in Jambi city from
2015-2019, the highest in 2015 reached 0,78, in 2016 reached 0,55, in 2017 only reached 0,48
and 0,37 occurred in 2018 and the lowest number occurred in 2019 only 0,27. From 27 private
high schools in Jambi City from 2015-2019 obtained 4 efficient (14,81 percent), namely:
XaveriusPrivate High School 2 Jambi, Private High SchoolNusantara Jambi, Attaufiq Private
High School, and Jambi IX Lurah Private High School. While from 2015-2019 there were 23
private high schools (85,19 percent) that were inefficient, namely: Private High School Surya
Ibu, Al-Falah Islamic Private High School, Private High School UnggulSakti, Xaverius Private
High School 1 Jambi, Ferdy Ferry Putra Private High School, PGRI Private High School 2
Jambi, Purnama Private High School 2 Jambi, Sariputra National Private High School,
Aditia Rhomadhani
28
Economica: Journal Of Economic And Economic Education
Volume 10, Issue 1, October 2021, pp 23-32
Muhammadiyah Private High School, Megatama Private High School, Private High School
Dua Mei Jambi, Dharma Bhakti Private High School 3, Yadika Private High School,
Nomensen Private High School, Dharma Bhakti Private High School 4, Dharma Bhakti Private
High School 2, Al-Azhar Integrated Islamic Private High School Jambi City, Pelita Raya
Private High School, Adhyaksa Private High School 1 Jambi, PGRI Private High School 3
Jambi, Private Christian High School BinaKasih, YPWI Private High School and Pertiwi
Private High School.
DISCUSSION
Cobb Douglass parameter testing is done in two stages. The first stage uses the ordinary
least square(OLS) method and the second stage uses the maximum likelihood estimation(MLE)
method. In Table 2, the log-likelihood value by using the MLE method (-600,11) is greater
than the log-likelihood value by using the OLS method (-601,06), thus the production function
by the MLE method is good and appropriate field conditions. The gamma value (0,41) is
interpreted that all term errors are a result of a random model (Vi) error, hence the inefficiency
coefficient parameter becomes meaningless. The ratio generalizalized-likelihood (LR-test) is
(1,90).
According to (Kuswanto, 2019) conducted a study through his research on the impact
of rubber production efficiency on the welfare of farmers in Jambi Province analyzed using the
approach of the stochastic frontier production function the results showed that the value of log-
likelihood with MLE method (-29,39) is greater than the value of log-likelihood with OLS
method (-38,47), thus the production function with MLE method is better and following the
conditions in the field. (Kuswanto, 2019) conducted a study through his research on analysis
efficiency of learning students Bidikmisi analyzed using the approach of the stochastic
production function frontier results showed that the value of log-likelihood with the MLE
method (85,52) is greater than the value of log-likelihood with OLS method (55,52), thus the
production function with MLE method is better and following the conditions in the field.
Based on the results of the analysis as shown in Table 2, the student's variable
coefficient value (0,23) was obtained and had a very real effect on the level of trust of 99
percent of the number of graduates. This explains that increasing the number of students will
increase the number of graduates by 0,23 percent. Based on the Directorate General of Teachers
and Educational Personnel of the Ministry of Education and Culture (Morphology, n.d. 2019:
8) the purpose of student management is to organize student activities so that all activities can
lead to the achievement of competencies for each level and type of school. The student
component is indispensable in school because the learner is both a subject and an object in the
learning process (Perdana, 2018: 2). Previous research relevant to these results is as conducted
by (Umi et al., 2020), that student management can be used to help the development and growth
of students optimally through the educational process in schools.
Based on the results of the analysis as shown in Table 2, the study group statistically
had no real effect on both the 90 percent and 95 percent confidence levels. The coefficient
value indicates a negative value, indicative of this condition is the role of the study group is
not ideal to increase the number of graduates. To achieve a quality school, the learning process
must be effective, one way to achieve this is by arranging the number of students in the study
group (Perdana, 2018). Research conducted by (Islakhudin, 2020) in the results of his research
suggests that the number of students in a study group is very influential on the learning process.
Similarly, the research conducted by (Perdana, 2018), that at the high school level on the island
of Sumatra, among the ten provinces that have an average ratio of high school students above
the ratio of national students ramble is the provinces of North Sumatra, South Sumatra, and
Lampung.
Aditia Rhomadhani
29
Economica: Journal Of Economic And Economic Education
Volume 10, Issue 1, October 2021, pp 23-32
Based on the results of the analysis as shown in Table 2, the role of teachers statistically
has no real effect on both the 95 percent and 90 percent confidence levels. Although the
coefficient shows a positive value, the increase does not represent an increase in the number of
graduates each year. Previous research relevant to this result is as done by (Susanti & Sa'ud,
2016), that after training many teachers have not been able to apply the results of professional
development into real practice. While the research conducted by (Herawati, 2018) that
professional teacher management in the future requires a change in strategy so that the
Provincial Government can carry out its duties as needed. Indriati, (2014) in his research results
suggested that to improve efficiency in the field of education, schools are allowed to appoint
Teachers Not Permanent (TNP) who are paid with school operational funds.
Based on the results of the analysis as shown in Table 2, the role of administrative
personnel statistically has no real effect on both the level of trust of 95 percent and 90 percent.
The coefficient value indicates a negative value, indications of this condition is the role of
administrative personnel has not been ideal to increase the number of graduates. Currently,
employees who serve administrative jobs or educational personnel do not have provisions that
can be used as a basis for the requirements of the number of educational personnel (Helianty,
2014: 251). Previous research relevant to these results is as done by (Dr. Mulyadi JMV, 2016)
that the variable ratio of student-administrative employees negatively affects school
performance. Similarly, the research conducted by (Bafadal, 2018), that the projected data of
administrative personnel of high schools and vocational schools in Ngawi District in the last
ten years was reviewed from the ratio of students experiencing shortages. While the research
conducted by (Bachtiyar, 2017), that the needs of school administration personnel in each
school has a certain amount of accumulation in each year.
Based on the results of the analysis as shown in Table 2, a classrooms variable
coefficient value of (3,86) was obtained and had a very real effect on the level of trust of 99
percent of the number of graduates. This explains that a 1 percent increase in the number of
classrooms will increase the number of graduates by 3.86 percent. Classroom management is
an activity to create and maintain optimal conditions in the learning process (Rosidah, 2018:
211). Previous research relevant to this result is as done by (Hajeriani, 2019) that class
management positively affects learning outcomes. Similarly, research conducted by (Arumsari,
2017), that classroom management skills have a significant influence on learning
achievements. The results of research conducted by (Yuliani & Sucihatiningsih, 2014), that
class management directly affects the results of learning.
Based on the results of the analysis as shown in Table 2, the value of the support rooms
variable coefficient (-1,16) and statistically has no real effect on both the 90 percent and 95
percent confidence levels. This explains that the more support rooms in this case the library
room and laboratory room in one school will reduce the level of the number of graduates.
Support rooms management in the world of education is important in supporting the learning
process in schools (Perdana, 2018). Previous research relevant to this result is as conducted by
Yuliani & Sucihatiningsih, (2014), that learning facilities have an indirect effect on learning
outcomes. While the research conducted by (Anas, 2016) that input in education does not have
to be learners but includes infrastructure facilities that can be used for education. Similarly,
research conducted by Indriati, (2014) determined priority scale, identification, and
synchronization of data on physical facilities and infrastructure, whether held new
procurement, new buildings, rehab, or routine maintenance.
Aditia Rhomadhani
30
Economica: Journal Of Economic And Economic Education
Volume 10, Issue 1, October 2021, pp 23-32
CONCLUSION
Based on the results of the analysis of the efficiency of the management of private high
schools in Jambi City from 2015-2019 using the Stochastic Frontier Analysis (SFA) method,
it can be concluded that: factors or inputs that affect the number of graduates of private high
schools in Jambi City from 2015-2019 are students and classrooms. While the factors or inputs
that do not affect the number of graduates are study groups, teachers, administrative personnel
and support rooms. (Mulyati, 2018) conducted a study through his research on the efficiency
analysis of public high school education in Semarang Regency analyzed using data
envelopment analysis (DEA) methods the results showed that the factors that affect input
quality are the ratio of students per teacher, the ratio of students per administrative employee,
and the influence of quality of output is the percentage of graduation. The technical efficiency
level of 27 private high schools in Jambi City from 2015-2019, the highest in 2015 reached
0,78 = 78%, the lowest figure occurred in 2019 with 0,27 = 27%, and the average only reached
0,49 = 49%. This explains that the efficiency of managing private high schools in Jambi city
has not been efficient. (Isa, 2011) conducted a study through his research on the technical
efficiency of education in surakarta city analyzed using data envelopment analysis (DEA)
methods the results showed that 70.73 percent of high schools in Surakarta were efficient and
another 29.27 percent inefficient.
Efforts that must be made so that private high schools in Jambi City are technically
efficient by combining factors or inputs in accordance with Government Regulation of the
Republic of Indonesia Number 19 of 2005 on National Standards of Education in article 2
paragraph 1 mentioned that the scope of national standards of education includes: graduate
competency standards, facilities and infrastructure standards, namely (1) optimizing the
achievement of graduate competence consisting of qualification criteria for participants'
abilities. Students who are expected to be achieved after completing their study period in the
secondary education unit, (2) the addition of classrooms is needed to create a comfortable and
disciplined learning atmosphere, orderly, anti-smoking and drug, harmony between teachers,
students and parents and maintain optimal conditions in the learning process.
Aditia Rhomadhani
31
Economica: Journal Of Economic And Economic Education
Volume 10, Issue 1, October 2021, pp 23-32
REFERENCES
Anas, M. (2016). 2. Anas Publised 2016 vol 2. 1(2), 47–58.
Arumsari, D. (2017). Pengaruh Media Pembelajaran Dan Keterampilan Pengelolaan Kelas
Terhadap Prestasi Belajar Siswa SMK Negeri 5 Madiun. Assets: Jurnal Akuntansi Dan
Pendidikan, 6(1), 13. https://doi.org/10.25273/jap.v6i1.1290
Bachtiyar, Y. (2017). Analisis Kebutuhan Tenaga Administrasi Sekolah ( Tas ). Jurnal
Manajemen Dan Supervisi Pendidikan, 1(3), 196–200.
Bafadal, I. (2018). Analisis kebutuhan tenaga administrasi sekolah pada jenjang sma dan
smk. 1, 388–399.
Decker, B. R. (2014). Estimating the Efficiency of Four-year Public Master’s Universities in
Arkansas Using Data Envelopment Analysis. Dissertation Abstracts International, A:
The Humanities and Social Sciences, 76(01).
Direktorat Pembinaan SMA, Direktorat Jenderal Pendidikan Dasar dan Menengah, K. P. dan
K. (n.d.). Manajemen Berbasis Sekolah (MBS) SMA.
Dr. Mulyadi JMV. (2016). Aplikasi Data Envelopment Analysis. 13, 83.
Hajeriani, S. (2019). Phinisi Integration Review Pengaruh Pengelolaan Kelas , Pemanfaatan
Sarana Dan Prasarana Se-Kecamatan Belawa Kabupaten Wajo. 2(1).
Helianty, Y. (2014). Analisis Kebutuhan Jumlah Pegawai Berdasarkan Analisis Beban Kerja.
Jurnal Reka Integra, 01(04), 250–258.
Herawati, N. R. (2018). Analisis Politik Alih Kewenangan Pengelolaan Guru Sma/Smk Dari
Pemerintah Kabupaten/Kota Kepada Pemerintah Provinsi. Jurnal Ilmu Sosial, 16(2), 72.
https://doi.org/10.14710/jis.16.2.2017.72-93
Indriati, N. E. (2014). Analisis Efisiensi Belanja Daerah di Kabupaten Sumbawa (Studi Kasus
Bidang Pendidikan dan Kesehatan). Jesp, 6(2), 192–205.
Isa. (2011). Efisiensi Teknis Pendidikan di Kota Surakarta: Aplikasi Data Envelopment
Analysis (DEA). Jurnal Manajemen Dan Bisnis, 3(2), 14–22.
https://doi.org/http://journals.ums.ac.id/index.php/benefit/article/view/1303
Islakhudin, M. (2020). Pengaruh Rombongan Belajar Siswa Terhadap Perkembangan
Kognitif Sosial Peserta Didik Di Mi Ma ’ Arif Ngampeldento Salaman. 8, 139–158.
Kuswanto, K. (2019). The Analysis of the Learning Efficiency of Bidikmisi Students. Jurnal
Pendidikan Ekonomi Dan Bisnis (JPEB), 7(1), 10–21.
https://doi.org/10.21009/jpeb.007.1.2
Kuswanto Kuswanto, Zulkifli Alamsyah, Armandelis Armandelis, Z. Z. (2019). The Impact
of the Efficiency of Rubber Production on the Welfare of Rubber Farmers in Jambi
Province. International Journal of Economics and Financial Issues, 9(2), 80–86.
https://doi.org/10.32479/ijefi.7503
Marini, A. (2016). Manajemen Pendidikan Teori dan Aplikasinya. Ombak.
Marini, Arita. (2010). Teori dan Aplikasinya. Jakarta: Rineka Cipta.
Menteri Pendidikan dan Keb. (2017). Salinan Menteri Pendidikan Dan Kebudayaan Republik
Indonesia Peraturan Menteri Pendidikan Dan Kebudayaan Republik Indonesia Nomor
17 Tahun 2017 Tentang Penerimaan Peserta Didik Baru Pada Taman Kanak-Kanak,
Aditia Rhomadhani
32
Economica: Journal Of Economic And Economic Education
Volume 10, Issue 1, October 2021, pp 23-32
Sekolah Dasar, Sekolah Menengah Pertama, Sekolah . Kementerian Pendidikan Dan
Kebudayaan, 1(1), 1–20.
Morphology, T. C. (n.d.). Modul Pelatihan Penguatan Kepala Sekolah Pengelolaan Peserta
Didik (MPPKS - DIK).
Mulyati. (2018). Analisis Efisiensi Pendidikan Sekolah Menengah Atas Negeri (SMAN) di
Kabupaten Semarang. Economics Development Analysis Journal, 7(2).
https://doi.org/https://doi.org/10.15294/edaj.v7i1.21936.
Mulyati, S. (2013). Economics Development Analysis Journal. 2(4), 446–455.
Perdana, N. S. (2018). Analisis Capaian Rombongan Belajar Di Provinsi Lampung Tahun
2018 Dalam Upaya Implementasi Permendikbud Nomor 17 Tahun 2017. Dewantara, V,
1–16.
Putri, T. A., Kusnadi, N., dan Rachmina, D. (2019). Efisiensi Teknis Usaha Penggilingan
Padi di Kabupaten Cianjur: Pendekatan Stochastic Frontier Analysis. Jurnal AGRISEP,
18(2), 203–218.
https://doi.org/https://ejournal.unib.ac.id/index.php/agrisep/article/view/7419
Rizky Yudaruddin. (2017). JURNAL AKUNTANSI & EKONOMI FE. UN PGRI Kediri Vol. 2
No. 1, Maret 2017. 2(1), 1–11.
Rosidah, R. (2018). Strategi Pengelolaan Kelas Efektif dan Efisien Dalam Proses
Pembelajaran. Jurnal Teknologi Pendidikan Madrasah, 1(2), 208–217.
https://doi.org/10.5281/zenodo.1421013
Soedibyo. (2003). Undang-Undang Republik Indonesia Nomor 20 Tahun 2003 Tentang
Sistem Pendidikan Nasional. Teknik Bendungan, 1.
Susanti, A., & Indonesia, U. P. (2016). EFEKTIFITAS PENGELOLAAN PENGEMBANGAN.
2, 37–51.
Togatorop, M. (2017). Pengaruh Biaya Pendidikan Terhadap Mutu Sekolah SMA Swasta.
Jurnal Pendidikan Dan Kebudayaan, 7(3).
https://doi.org/https://garuda.ristekbrin.go.id/documents/detail/623273
Umi, F., Marsidin, S., & Sabandi, A. (2020). Analisis Kebijakan dan Pengelolaan terkait
Peserta Didik di Sekolah Dasar. Edukatif : Jurnal Ilmu Pendidikan, 2(2), 128–133.
https://doi.org/10.31004/edukatif.v2i2.114
Woessmann, L. (2010). Institutional determinants of school efficiency and equity: German
states as a microcosm for OECD countries. Jahrbucher Fur Nationalokonomie Und
Statistik, 230(2), 234–270. https://doi.org/10.1515/jbnst-2010-0206
Yuliani, P., & Sucihatiningsih, D. W. P. (2014). Pengaruh Fasilitas Belajar, Pengelolaan
Kelas, Dan Lingkungan Keluarga Terhadap Hasil Belajar Ekonomi Melalui Motivasi
Belajar Siswa Kelas Xi Ma Al-Asror Kota Semarang. Economic Education Analysis
Journal, 3(1), 24–30.
