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SYSTEM MODELLING PROJECT
- Aisha Adilla
- Givanny Permata Sari
- Hanny Riana
- Latifa Ayu Lestari
- Salma Nabila Hadi
- Sa...
• BPJSquad consists of 6 female students from the Department of Industrial Engineering, Universitas Indonesia. This
team w...
DETERMINE	THE	PROBLEM
MODEL	CONCEPTUALIZATION
DATA	GATHERING	AND	ANALYSISIS
MODEL	CONSTRUCTION
VALIDATION	AND	VERIFICATION...
01
• Defining	the	problem,	objectives,	actual	
condition,	and	scope	of	our	research	project
DEFINE THE PROBLEM
What?
Service	and	
queue	system
PROBLEM DEFINITION
Who?
BPJS	Patients	
(Both	new	and	
old	members)
When?
During	peak	time	...
6
PROBLEM DEFINITION
• Defining	the	hypothesis	of	the	problem
And how it will affects?
If the management of RSUD Pasar
Min...
7
RESEARCH OBJECTIVES
• Defining	the	objectives	of	our	research	project
• Reducing	the	queuing	time	
of	BPJS	at	RSUD	Pasar...
02
• Representing	the	real	BPJS	system	at	RSUD	
Pasar Minggu as	a	flowchart
MODEL
CONCEPTUALIZATION
MODEL CONCEPTUALIZATION
• Using	a	flowchart	as	a	representation	of	the	real	system
9
03
• Explaining	the	method	used	for	data	
collection,	the	types	of	data,	and	analysis	of	
the	data	using	StatFit
DATA GATH...
DATA
COLLECTION
DATA COLLECTION
• Explaining	the	data	collection	method	and	the	data	types
12
Direct	
observation
Interview Direct	
Measur...
Inter-arrival	Time
13
DATA COLLECTION
• Explaining	about	the	data	that	we	collected
Arrival	Rate
Service Time	and	
Service...
DATA COLLECTION
• Explaining	how	we	know	the	peak	days	of	the	system	and	the	sampling	method	
14
We used direct observatio...
• Based on direct observation (service time and arrival rate), 80% of the service
time and arrival rate comes from 20% of ...
DATA COLLECTION
• Summing	up	all	data	to	find	mean	and	standard	deviation
16
REG	BPJS	LAMA
Mean Standar	Dev
Detik Menit De...
DATA COLLECTION
• Summing	up	all	data	to	find	mean	and	standard	deviation
17
POLI	JANTUNG
Mean Standar	Dev
Detik Menit Det...
DATA
ANALYSIS
DATA ANALYSIS
• Identifying	the	type	of	distribution	of	each	data
19
Normal
Normal
BPJS Lama
Inter-arrival
TimeServiceTime
DATA ANALYSIS
• Identifying	the	type	of	distribution	of	each	data
20
Normal
WaitingTime
DATA ANALYSIS
21
Exponen
tial
Exponen
tial
BPJS Baru
• Identifying	the	type	of	distribution	of	each	data
Inter-arrival
Tim...
DATA ANALYSIS
• Identifying	the	type	of	distribution	of	each	data
22
Normal
WaitingTime
DATA ANALYSIS
23
Normal
Normal
Poli Penyakit Dalam
• Identifying	the	type	of	distribution	of	each	data
WaitingTimeServiceT...
DATA ANALYSIS
• Identifying	the	type	of	distribution	of	each	data
24
Normal
Normal
Poli Jantung
WaitingTimeServiceTime
DATA ANALYSIS
25
Normal
Normal
• Identifying	the	type	of	distribution	of	each	data
WaitingTimeServiceTime
Poli Syaraf
DATA ANALYSIS
26
Normal
Normal
Farmasi
• Identifying	the	type	of	distribution	of	each	data
WaitingTime
ServiceTime
ofScann...
DATA ANALYSIS
27
Normal
• Identifying	the	type	of	distribution	of	each	data
ServiceTime
ofGiving
Medicine
04
• Illustrating	about	how	a	ProModel model	is	
built	to	represent	the	real	system
MODEL CONSTRUCTION
MODEL CONSTRUCTION
Illustrating	how	a	ProModel model	is	built		represent	the	real	system
29
ENTITIES
MODEL CONSTRUCTION
30
Illustrating	how	a	ProModel model	is	built		represent	the	real	system
LOCATIONS
MODEL CONSTRUCTION
31
Illustrating	how	a	ProModel model	is	built		represent	the	real	system
ARRIVALS
MODEL CONSTRUCTION
32
Illustrating	how	a	ProModel model	is	built		represent	the	real	system
PROCESSING
MODEL CONSTRUCTION
33
Illustrating	how	a	ProModel model	is	built		represent	the	real	system
ARRIVAL
CYCLES
MODEL CONSTRUCTION
34
Illustrating	how	a	ProModel model	is	built		represent	the	real	system
ATTRIBUTES
MODEL CONSTRUCTION
35
Illustrating	how	a	ProModel model	is	built		represent	the	real	system
USER
DISTRIBUTION
MODEL CONSTRUCTION
36
Illustrating	how	a	ProModel model	is	built		represent	the	real	system
• Final ProModel for the BPJS ...
05
• The	validation	and	verification	of	model	
conceptualization	and	computer	model
VALIDATION AND
VERIFICATION
VALIDATION
VALIDATION
• Model	conceptualization	validation
39
Trace Validity Face Validity
Trace in Promodel
Using a feature in ProMo...
VALIDATION
• Model	conceptualization	validation
40
Trace Validity
VALIDATION
• Model	conceptualization	validation
41
We	interviewed	people	from	
information	centre	and	also	security	
who	i...
VALIDATION
• ProModel validation
42
Comparing with
Queuing Theory
Watching the
Animation
Extreme
Condition Test
Running
Tr...
VALIDATION
• ProModel validation
44
Comparing with Queuing Theory
VALIDATION	OF BPJS	BARU	PROMODEL	WITH	QUEUING	THEORY	CAL...
VALIDATION
• ProModel validation
45
Watching the Animation
VALIDATION
• ProModel validation
46
• Total entities: 22200
Extreme Condition Test
• Total entities: 0
VALIDATION
• ProModel validation
47
Running Traces
VERIFICATION
VERIFICATION
• Model	verification
49
Watching the
Animation
Using Trace and
Debugging Facilities
Reviewing the
Model Code
...
VERIFICATION
• Model	verification
50
Watching the Animation
VERIFICATION
• Model	verification
51
Reviewing the Model Code
VERIFICATION
• Model	verification
52
Reviewing the Model Code (cont’d)
VERIFICATION
• Model	verification
53
Reviewing the Model Code (cont’d)
VERIFICATION
• Model	verification
54
Reviewing the Model Code (cont’d)
(1) (2)
VERIFICATION
• Model	verification
55
• There are no bugs,
so the model can run
perfectly
Running Trace and Debugging Facil...
06
• Showing	the	statistics	results	of	ProModel
OUTPUT ANALYSIS
OUTPUT ANALYSIS
Showing	the	statistics	results	of	ProModel
57
OUTPUT ANALYSIS
Showing	the	statistics	results	of	ProModel
58
OUTPUT ANALYSIS
Showing	the	statistics	results	of	ProModel
59
07
• Answering	the	questions	that	have	given	by	
Mr.	Arry Rahmawan
QUESTIONS & ANSWERS
ANSWER TO THE 1ST QUESTION
61
• What	is	the	best	line	formation?
• Single	Line	->	Multi	Server
SquadBPJ
62
• Where	are	the	worst	bottlenecks	of	system?	
SquadBPJANSWER TO THE 2ND QUESTION
BPJS	Baru Registration
• A	lot	of	the	...
63
• How	many	staff	should	be	assigned	to	reach	the	objective	
with	the	lowest	possible	cost?
SquadBPJANSWER TO THE 3RD QU...
64
• What	are	the	new	and	most	effective	business	process	ideas	
for	the	hospital	to	reach	the	objective?
SquadBPJANSWER T...
32
• Other	solutions	that	should	be	considered
SquadBPJANSWER TO THE 5TH QUESTION
Make	a	clear	way-
finding	&	signage	
sys...
08
MODEL IMPROVEMENT
ANALYSIS MODEL IMPROVEMENT
32
ANALYSIS MODEL IMPROVEMENT
68
The	Data	After	Improvement	
(Waiting	Time)
BPJS	LAMA =79.23	min
BPJS	BARU =	40.34	min
POLI	P...
69
ANALYSIS MODEL IMPROVEMENT
09
• Concluding	our	project	research
CONCLUSION
CONCLUSION
Concluding	our	project	research
71
• The	process	of	finding	solutions	through	making	models	involves	
making	a	...
THANK YOU
- Aisha Adilla (1406606152)
- Givanny Permata Sari (1406606070)
- Hanny Riana (1406606341)
- Latifa Ayu Lestari ...
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Contoh Presentasi Pembelajaran Berbasis Riset (PBR) Mata Kuliah Pemodelan Sistem

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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.

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Contoh Presentasi Pembelajaran Berbasis Riset (PBR) Mata Kuliah Pemodelan Sistem

  1. 1. SYSTEM MODELLING PROJECT - Aisha Adilla - Givanny Permata Sari - Hanny Riana - Latifa Ayu Lestari - Salma Nabila Hadi - Sarah Marsha Davinna SquadBPJ
  2. 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. 3. DETERMINE THE PROBLEM MODEL CONCEPTUALIZATION DATA GATHERING AND ANALYSISIS MODEL CONSTRUCTION VALIDATION AND VERIFICATION QUESTIONS ANSWERS CONCLUSION AND SUGGESTION OUTPUT ANALYSIS OUTLINE
  4. 4. 01 • Defining the problem, objectives, actual condition, and scope of our research project DEFINE THE PROBLEM
  5. 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. 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. 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. 8. 02 • Representing the real BPJS system at RSUD Pasar Minggu as a flowchart MODEL CONCEPTUALIZATION
  9. 9. MODEL CONCEPTUALIZATION • Using a flowchart as a representation of the real system 9
  10. 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. 11. DATA COLLECTION
  12. 12. DATA COLLECTION • Explaining the data collection method and the data types 12 Direct observation Interview Direct Measurement Books / Journals
  13. 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. 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. 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. 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. 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. 18. DATA ANALYSIS
  19. 19. DATA ANALYSIS • Identifying the type of distribution of each data 19 Normal Normal BPJS Lama Inter-arrival TimeServiceTime
  20. 20. DATA ANALYSIS • Identifying the type of distribution of each data 20 Normal WaitingTime
  21. 21. DATA ANALYSIS 21 Exponen tial Exponen tial BPJS Baru • Identifying the type of distribution of each data Inter-arrival TimeServiceTime
  22. 22. DATA ANALYSIS • Identifying the type of distribution of each data 22 Normal WaitingTime
  23. 23. DATA ANALYSIS 23 Normal Normal Poli Penyakit Dalam • Identifying the type of distribution of each data WaitingTimeServiceTime
  24. 24. DATA ANALYSIS • Identifying the type of distribution of each data 24 Normal Normal Poli Jantung WaitingTimeServiceTime
  25. 25. DATA ANALYSIS 25 Normal Normal • Identifying the type of distribution of each data WaitingTimeServiceTime Poli Syaraf
  26. 26. DATA ANALYSIS 26 Normal Normal Farmasi • Identifying the type of distribution of each data WaitingTime ServiceTime ofScanning Barcode
  27. 27. DATA ANALYSIS 27 Normal • Identifying the type of distribution of each data ServiceTime ofGiving Medicine
  28. 28. 04 • Illustrating about how a ProModel model is built to represent the real system MODEL CONSTRUCTION
  29. 29. MODEL CONSTRUCTION Illustrating how a ProModel model is built represent the real system 29 ENTITIES
  30. 30. MODEL CONSTRUCTION 30 Illustrating how a ProModel model is built represent the real system LOCATIONS
  31. 31. MODEL CONSTRUCTION 31 Illustrating how a ProModel model is built represent the real system ARRIVALS
  32. 32. MODEL CONSTRUCTION 32 Illustrating how a ProModel model is built represent the real system PROCESSING
  33. 33. MODEL CONSTRUCTION 33 Illustrating how a ProModel model is built represent the real system ARRIVAL CYCLES
  34. 34. MODEL CONSTRUCTION 34 Illustrating how a ProModel model is built represent the real system ATTRIBUTES
  35. 35. MODEL CONSTRUCTION 35 Illustrating how a ProModel model is built represent the real system USER DISTRIBUTION
  36. 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. 37. 05 • The validation and verification of model conceptualization and computer model VALIDATION AND VERIFICATION
  38. 38. VALIDATION
  39. 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. 40. VALIDATION • Model conceptualization validation 40 Trace Validity
  41. 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. 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. 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. 44. VALIDATION • ProModel validation 45 Watching the Animation
  45. 45. VALIDATION • ProModel validation 46 • Total entities: 22200 Extreme Condition Test • Total entities: 0
  46. 46. VALIDATION • ProModel validation 47 Running Traces
  47. 47. VERIFICATION
  48. 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. 49. VERIFICATION • Model verification 50 Watching the Animation
  50. 50. VERIFICATION • Model verification 51 Reviewing the Model Code
  51. 51. VERIFICATION • Model verification 52 Reviewing the Model Code (cont’d)
  52. 52. VERIFICATION • Model verification 53 Reviewing the Model Code (cont’d)
  53. 53. VERIFICATION • Model verification 54 Reviewing the Model Code (cont’d) (1) (2)
  54. 54. VERIFICATION • Model verification 55 • There are no bugs, so the model can run perfectly Running Trace and Debugging Facilities
  55. 55. 06 • Showing the statistics results of ProModel OUTPUT ANALYSIS
  56. 56. OUTPUT ANALYSIS Showing the statistics results of ProModel 57
  57. 57. OUTPUT ANALYSIS Showing the statistics results of ProModel 58
  58. 58. OUTPUT ANALYSIS Showing the statistics results of ProModel 59
  59. 59. 07 • Answering the questions that have given by Mr. Arry Rahmawan QUESTIONS & ANSWERS
  60. 60. ANSWER TO THE 1ST QUESTION 61 • What is the best line formation? • Single Line -> Multi Server SquadBPJ
  61. 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. 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. 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. 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. 65. 08 MODEL IMPROVEMENT
  66. 66. ANALYSIS MODEL IMPROVEMENT 32
  67. 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. 68. 69 ANALYSIS MODEL IMPROVEMENT
  69. 69. 09 • Concluding our project research CONCLUSION
  70. 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. 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

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