Salah satu metode pembelajaran berbasis mahasiswa yaitu adalah PBR atau Pembelajaran Berbasis Riset. Pada metode ini, mahasiswa dituntut aktif untuk mengetahui metodologi penelitian yang digunakan untuk membuat model, lalu mereka mengaplikasikannya dalam case - case tertentu, salah satunya adalah kasus BPJS ini.

1. SYSTEM MODELLING PROJECT
- Aisha Adilla
- Givanny Permata Sari
- Hanny Riana
- Latifa Ayu Lestari
- Salma Nabila Hadi
- Sarah Marsha Davinna
SquadBPJ

2. • BPJSquad consists of 6 female students from the Department of Industrial Engineering, Universitas Indonesia. This
team was formed for the project of Systems Modeling class taught by Mr. Arry Rahmawan. In this project, we were
asked to do research on the system of the BPJS Program in a public hospital, in our case RSUD Pasar Minggu.
Salma Nabila
Givanny Permata
Latifa Ayu
Aisha Adilla
Sarah Marsha
Hanny Riana
TEAM PROFILE
SquadBPJ

3. DETERMINE THE PROBLEM
MODEL CONCEPTUALIZATION
DATA GATHERING AND ANALYSISIS
MODEL CONSTRUCTION
VALIDATION AND VERIFICATION
QUESTIONS
ANSWERS
CONCLUSION
AND
SUGGESTION
OUTPUT ANALYSIS
OUTLINE

4. 01
• Defining the problem, objectives, actual
condition, and scope of our research project
DEFINE THE PROBLEM

5. What?
Service and
queue system
PROBLEM DEFINITION
Who?
BPJS Patients
(Both new and
old members)
When?
During peak time
(Monday, Wednesday,
and Thursday)
Where?
RSUD Pasar
Minggu
Why?
Massive number
of BPJS patients in
Jakarta
5
• Defining the problem with 5W tools

6. 6
PROBLEM DEFINITION
• Defining the hypothesis of the problem
And how it will affects?
If the management of RSUD Pasar
Minggu ignores this problem, the BPJS
patient will feel uncomfortable while
treating their disease in this hospital
due to dissatisfaction of the hospital’s
BPJS system.
What are the symptoms?
Since RSUD Pasar Minggu has accepted
BPJS patients, there have been problems in
the form of a massive amount of BPJS
patients resulting in a long queueing time
in the registration, polyclinic, and
pharmacy lines that makes patients
dissatisfied.

7. 7
RESEARCH OBJECTIVES
• Defining the objectives of our research project
• Reducing the queuing time
of BPJS at RSUD Pasar
Minggu
• Reducing the service time of
BPJS at RSUD Pasar Minggu
• Increasing customer
satisfaction
• Answering the questions that
have been given in class

8. 02
• Representing the real BPJS system at RSUD
Pasar Minggu as a flowchart
MODEL
CONCEPTUALIZATION

9. MODEL CONCEPTUALIZATION
• Using a flowchart as a representation of the real system
9

10. 03
• Explaining the method used for data
collection, the types of data, and analysis of
the data using StatFit
DATA GATHERING
AND ANALYSIS

11. DATA
COLLECTION

12. DATA COLLECTION
• Explaining the data collection method and the data types
12
Direct
observation
Interview Direct
Measurement
Books / Journals

13. Inter-arrival Time
13
DATA COLLECTION
• Explaining about the data that we collected
Arrival Rate
Service Time and
Service Rate
Queue Time
Registration Time

14. DATA COLLECTION
• Explaining how we know the peak days of the system and the sampling method
14
We used direct observation and
interview to know what the peak days
are of the BPJS system at RSUD Pasar
Minggu
From direct observation, we got Monday, Wednesday,
and Thursday as a peak day. This was also proven by
the result of interviews with hospital management. The
average population observed in Monday, Wednesday,
and Thursday is 222 patients (the population from
polyclinics are most influential). We get 144 samples
from Slovin’s Formula.
We used stratified random sampling because the
difference of cumulative from each registration and
polyclinic.
Stratified Random Sampling
From 144 samples,
Registration Samples
• BPJS Lama= 84% from population (121 patients)
• BPJS Baru= 16% from population (23 patients)
Polyclinics Samples
• Penyakit Dalam= 44% from population (63 patients)
• Jantung= 36% from population (51 patients)
• Syaraf= 20% from population (29 patients)

15. • Based on direct observation (service time and arrival rate), 80% of the service
time and arrival rate comes from 20% of the polyclinics:
Penyakit Dalam, Jantung, and Syaraf
DATA COLLECTION
• Using pareto diagram to know which polyclinic should be observed
15
0%
20%
40%
60%
80%
100%
120%
0%
5%
10%
15%
20%
25%
30%
35%
40%
Jumlah Kedatangan Per Periode Waktu
% Kumulatif %
0%
20%
40%
60%
80%
100%
120%
0%
5%
10%
15%
20%
25%
Waktu Pelayanan
% Kumulatif %

16. DATA COLLECTION
• Summing up all data to find mean and standard deviation
16
REG BPJS LAMA
Mean Standar Dev
Detik Menit Detik Menit
Waktu antar Kedatangan 27.3 0.46 20 0.33
Waktu Pelayanan (4 server) 65.1 1.09 20.2 0.34
Waktu Tunggu 6694 111.57 278.8 4.65
REG BPJS LAMA
Jumlah Orang/Jam
Mean
Waktu antar Kedatangan 131.87
Waktu Pelayanan 55.30
REG BPJS BARU
Mean Standar Dev
Detik Menit Detik Menit
Waktu antar Kedatangan 224.30 3.74 213.30 3.56
Waktu Pelayanan (3 server) 199.3 3.32 58.7 0.98
Waktu Tunggu 1413.9 23.565 766.6 12.78
REG BPJS BARU
Jumlah Orang/Jam
Mean
Waktu antar Kedatangan 16.05
Waktu Pelayanan 18.06
FARMASI
Mean Standar Dev
Detik Menit Detik Menit
Waktu antar Kedatangan 163.5 2.73 154.4 2.57
Waktu Pelayanan
Scan Barcode 9.201 0.15 4.091 0.07
Pelayanan Memberi Obat 139.6 2.33 30.16 0.50
Waktu Tunggu 5890 98.16667 2482 41.37
FARMASI
Jumlah Orang/Jam
Mean
Tingkat Kedatangan 22.02
Tingkat Pelayanan
Server 1 391.26
Server 2 25.79

17. DATA COLLECTION
• Summing up all data to find mean and standard deviation
17
POLI JANTUNG
Mean Standar Dev
Detik Menit Detik Menit
Waktu antar Kedatangan 178 2.97 116 1.93
Waktu Pelayanan (2 server) 330.4 5.51 56.8 0.95
Waktu Tunggu 9204 153.4 1796 29.93
POLI JANTUNG
Jumlah Orang/Jam
Mean
Tingkat Kedatangan 20.22
Tingkat Pelayanan 10.90
POLI PENYAKIT DALAM
Mean Standar Dev
Detik Menit Detik Menit
Waktu antar Kedatangan 160.1 2.67 163.6 2.73
Waktu Pelayanan (2 server) 578.7 9.65 192.1 3.20
Waktu Tunggu 4349 72.48 1893 31.55
POLI PENYAKIT DALAM
Jumlah Orang/Jam
Mean
Waktu antar Kedatangan 22.49
Waktu Pelayanan 6.22
POLI SYARAF
Mean Standar Dev
Detik Menit Detik Menit
Waktu antar Kedatangan 233.28 3.89 197.66 3.29
Waktu Pelayanan (2 server) 333.3 5.56 55.57 0.93
Waktu Tunggu 4526.0 75.43 695.80 11.60
POLI SYARAF
Jumlah Orang/Jam
Mean
Tingkat Kedatangan 15.43
Tingkat Pelayanan 10.80

18. DATA
ANALYSIS

19. DATA ANALYSIS
• Identifying the type of distribution of each data
19
Normal
Normal
BPJS Lama
Inter-arrival
TimeServiceTime

20. DATA ANALYSIS
• Identifying the type of distribution of each data
20
Normal
WaitingTime

21. DATA ANALYSIS
21
Exponen
tial
Exponen
tial
BPJS Baru
• Identifying the type of distribution of each data
Inter-arrival
TimeServiceTime

22. DATA ANALYSIS
• Identifying the type of distribution of each data
22
Normal
WaitingTime

23. DATA ANALYSIS
23
Normal
Normal
Poli Penyakit Dalam
• Identifying the type of distribution of each data
WaitingTimeServiceTime

24. DATA ANALYSIS
• Identifying the type of distribution of each data
24
Normal
Normal
Poli Jantung
WaitingTimeServiceTime

25. DATA ANALYSIS
25
Normal
Normal
• Identifying the type of distribution of each data
WaitingTimeServiceTime
Poli Syaraf

26. DATA ANALYSIS
26
Normal
Normal
Farmasi
• Identifying the type of distribution of each data
WaitingTime
ServiceTime
ofScanning
Barcode

27. DATA ANALYSIS
27
Normal
• Identifying the type of distribution of each data
ServiceTime
ofGiving
Medicine

28. 04
• Illustrating about how a ProModel model is
built to represent the real system
MODEL CONSTRUCTION

29. MODEL CONSTRUCTION
Illustrating how a ProModel model is built represent the real system
29
ENTITIES

30. MODEL CONSTRUCTION
30
Illustrating how a ProModel model is built represent the real system
LOCATIONS

31. MODEL CONSTRUCTION
31
Illustrating how a ProModel model is built represent the real system
ARRIVALS

32. MODEL CONSTRUCTION
32
Illustrating how a ProModel model is built represent the real system
PROCESSING

33. MODEL CONSTRUCTION
33
Illustrating how a ProModel model is built represent the real system
ARRIVAL
CYCLES

34. MODEL CONSTRUCTION
34
Illustrating how a ProModel model is built represent the real system
ATTRIBUTES

35. MODEL CONSTRUCTION
35
Illustrating how a ProModel model is built represent the real system
USER
DISTRIBUTION

36. MODEL CONSTRUCTION
36
Illustrating how a ProModel model is built represent the real system
• Final ProModel for the BPJS system of RSUD Pasar Minggu
When model pause When model run

37. 05
• The validation and verification of model
conceptualization and computer model
VALIDATION AND
VERIFICATION

38. VALIDATION

39. VALIDATION
• Model conceptualization validation
39
Trace Validity Face Validity
Trace in Promodel
Using a feature in ProModel
(trace) to trace the truth of the
model logic and computer
model (debugging)
Validity in Real Life
Checking the validity of model
conceptualization by asking
people who know the system
well and trusted
Determining the truth of model
flow diagram or model logic
mechanism

40. VALIDATION
• Model conceptualization validation
40
Trace Validity

41. VALIDATION
• Model conceptualization validation
41
We interviewed people from
information centre and also security
who is on duty and always observe the
queuing system of BPJS patients in
RSUD Pasar MingguFace Validity
Interview recording attached

42. VALIDATION
• ProModel validation
42
Comparing with
Queuing Theory
Watching the
Animation
Extreme
Condition Test
Running
Traces
Comparing output from
the simulation with
queuing theory
Watching the computer
model that has conducted
Testing the model using
2 extreme conditions
Stage of processes
are traced using the
processing logic model
to be compared with
the actual model

43. VALIDATION
• ProModel validation
44
Comparing with Queuing Theory
VALIDATION OF BPJS BARU PROMODEL WITH QUEUING THEORY CALCULATION
Arival Rate 4.545455
Service Rate 14.66667
Average Utilization Rate 0.3099174
The Probability System in Empty Situation 73.342039%
Average Number of Patient in Queuing 44.43555
Average Number of Patient in System 44.745468
Average Patient’s Waiting Time in Queuing 9.7758211
Average Patient’s Waiting Time in System 9.8440029

44. VALIDATION
• ProModel validation
45
Watching the Animation

45. VALIDATION
• ProModel validation
46
• Total entities: 22200
Extreme Condition Test
• Total entities: 0

46. VALIDATION
• ProModel validation
47
Running Traces

47. VERIFICATION

48. VERIFICATION
• Model verification
49
Watching the
Animation
Using Trace and
Debugging Facilities
Reviewing the
Model Code
Visual verification
whether the model
running has been right
Checking for code
errors or inconsistency
in the statistics results
• Trace : chronologically describe
what’s happening during the
simulation
• Debugger : showing the stages of
the processes in the simulation
• Trace & Debugger enable us to
look deeper what’s happening in
the simulation

49. VERIFICATION
• Model verification
50
Watching the Animation

50. VERIFICATION
• Model verification
51
Reviewing the Model Code

51. VERIFICATION
• Model verification
52
Reviewing the Model Code (cont’d)

52. VERIFICATION
• Model verification
53
Reviewing the Model Code (cont’d)

53. VERIFICATION
• Model verification
54
Reviewing the Model Code (cont’d)
(1) (2)

54. VERIFICATION
• Model verification
55
• There are no bugs,
so the model can run
perfectly
Running Trace and Debugging Facilities

55. 06
• Showing the statistics results of ProModel
OUTPUT ANALYSIS

56. OUTPUT ANALYSIS
Showing the statistics results of ProModel
57

57. OUTPUT ANALYSIS
Showing the statistics results of ProModel
58

58. OUTPUT ANALYSIS
Showing the statistics results of ProModel
59

59. 07
• Answering the questions that have given by
Mr. Arry Rahmawan
QUESTIONS & ANSWERS

60. ANSWER TO THE 1ST QUESTION
61
• What is the best line formation?
• Single Line -> Multi Server
SquadBPJ

61. 62
• Where are the worst bottlenecks of system?
SquadBPJANSWER TO THE 2ND QUESTION
BPJS Baru Registration
• A lot of the new patients do not know about the documents they must bring in order to
register so that sometimes they have to go back home or go to photocopy station if
there’s missing documents. This affect the registration time since sometimes they have
been called but they’re still somewhere else.
BPJS Lama Registration
• Lack of server & ineffective queuing position
Poli Penyakit
• Every server has different opening time where a lot of patients have been waiting
Pharmacy
• There is no specific job for each employees & sometimes there is downtime sin the
Doctors send the medicine receipt by server online

62. 63
• How many staff should be assigned to reach the objective
with the lowest possible cost?
SquadBPJANSWER TO THE 3RD QUESTION
BPJS Baru
• 4 staff
BPJS Lama
• 7 staff
Poli Penyakit
• Penyakit Dalam 8 staff, Syaraf 4 staff & jantung 4 staff
Pharmacy
• 2 staff

63. 64
• What are the new and most effective business process ideas
for the hospital to reach the objective?
SquadBPJANSWER TO THE 4TH QUESTION
BPJS Lama
• Add servers & services, & give clear way-finding instruction for patients
Poli Penyakit Dalam
• Open room that used to be unused, open every checking room at the same time
(7.30 a.m.) & make the first line as priority seat
Poli Jantung
• Open every checking room at the same time (7.30 a.m.) & make 8 priority seat
Poli Syaraf
• Open every checking room at the same time (7.30 a.m.)

64. 32
• Other solutions that should be considered
SquadBPJANSWER TO THE 5TH QUESTION
Make a clear way-
finding & signage
system
Make information
board detailing the
procedures of BPJS
registration
Utilizing the website
for real-time waiting
line information at
the hospital
Making a clear job
description for
resources to avoid
idle human resources

65. 08
MODEL IMPROVEMENT

66. ANALYSIS MODEL IMPROVEMENT
32

67. ANALYSIS MODEL IMPROVEMENT
68
The Data After Improvement
(Waiting Time)
BPJS LAMA =79.23 min
BPJS BARU = 40.34 min
POLI PD = 68.71 min
POLI SYARAF = 60.86 min
POLI JANTUNG = 77.21 min
FARMASI = 50.31 min
The Data Before Improvement
(Waiting Time)
BPJS LAMA =112.4 min
BPJS BARU = 47.71 min
POLI PD = 98.67 min
POLI SYARAF = 71.48 min
POLI JANTUNG = 155.59 min
FARMASI = 196.42min

68. 69
ANALYSIS MODEL IMPROVEMENT

69. 09
• Concluding our project research
CONCLUSION

70. CONCLUSION
Concluding our project research
71
• The process of finding solutions through making models involves
making a conceptual model based on the real world and then a
computer model based on the conceptual model.
• The BPJS system in RSUD Pasar Minggu consists of BPJS Lama
registration, BPJS Baru registration, polyclinic, and pharmacy.
• The bottleneck of the system relative to the number of entries is Poli
Jantung.
• We improved the system by adding servers and introducing a
punctuality policy for doctors and employees.

71. THANK YOU
- Aisha Adilla (1406606152)
- Givanny Permata Sari (1406606070)
- Hanny Riana (1406606341)
- Latifa Ayu Lestari (1406606354)
- Salma Nabila Hadi (1406553133)
- Sarah Marsha Davinna (1406553285)
SquadBPJ