Contoh Desain Slide Presentasi Ilmiah Kreatif dan Menarik #1

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Ketika saya mengampu mata kuliah permodelan sistem, di mana mata kuliah ini merupakan mata kuliah untuk mahasiswa tingkat 3, saya menugaskan mahasiswa untuk melakukan sebuah penelitian sederhana dengan menerapkan prinsip - prinsip ilmiah ke lapangan langsung. Saya juga menantang mereka untuk dapat mempresentasikan hasil penelitian mereka dengan tampilan slide yang tidak biasa dan menjemukan. Hingga akhirnya, inilah beberapa di antaranya. Bagaimana menurut Anda?

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Contoh Desain Slide Presentasi Ilmiah Kreatif dan Menarik #1

  1. 1. MOTORCYCLE PARKING SYSTEM P CENTRAL PARK MALL JAKARTA
  2. 2. 1 2 3 4 5 6 ASTARI WULANDARI DEA INDRIYANI DYASRENNY TIARA PUTRI THERESSA DEVINA ANGGITA LARASATI KENT SOLID THE PROJECT TEAM
  3. 3. OUTLINE 1 2 3 4 5 6 7 PROBLEM DEFINITION CONSEPTUALIZATION MODEL DATA GATHERING MODEL CONSTRUCTION VERIFICATION VALIDATION CONCLUSION P
  4. 4. PROBLEM DEFINITION
  5. 5. Biggest  Mall  in  West  Jakarta Including  shopping   mall,  office  tower,  and  hotel  developed  by  Podomoro   Group Biggest Mall West Jakarta Has reached visitors each month (source: marketing.co.id) 2.9 million Shopping Mall Office Apartments & Hotels PROBLEM DEFINITION Can be reached by Car Motorcycle Public transportation CAR PARKING MOTORCYCLE PARKING } }
  6. 6. CURRENT CONDITION PROBLEM DEFINITION MOTORCYCLE PARKING AREA 2 FLOOR: B1 & B2 GATE IN : 2 1 LINE 2 SERVER GATE OUT : 3 1 LINE 3 SERVER
  7. 7. PROBLEM DEFINITION WHAT PROBLEM DEFINITION WHERE WHEN WHO WHY Queuing System Central Park Mall Saturday Visitor of Central Park Mall Massive number of visitors PROBLEM STATEMENT Massive number of visitors in Central Park mall on weekend (especially on Saturday) led to queueing in the system. If queue happens more than 1 minute and time for motorcycle to search parking more than 2 minutes, it will decrease customer satisfaction so that it will cause opportunity loss to Central Park Mall.
  8. 8. MODEL CONCEPTUALIZATION
  9. 9. MODEL CONCEPTUALIZATION FLOW CHART
  10. 10. DATA GATHERING
  11. 11. SOURCE OF DATA Credible Expert Opinion Personal Observation COLLECTION OF DATA Queuing time DATA GATHERING Peak hour Capacity Searching time Arrival Time Service Time Counter Duration of parking P 1 2
  12. 12. RAW DATA & PROCESSING DATA GATHERING Peak hour 0 100 200 300 400 500 11.10-­‐12.0912.10-­‐13.0913.10-­‐14.0914.09-­‐15.0915.10-­‐16.0916.10-­‐17.0917.10-­‐18.0918.09-­‐19.1019.10-­‐20.1021.10-­‐22.10 Motorcycle  Arrival/Hour Peak hour • 13.10-14.10 • 14.10-15.10 • 15.10-16.10 • 16.10-17.10 • 17.20-18.20 • 18.20-19.20
  13. 13. RAW DATA & PROCESSING DATA GATHERING Capacity (492) in Basement 1 (603) in Basement 2
  14. 14. RAW DATA & PROCESSING DATA GATHERING Searching time Lantai 1 Mean 41.97 Std. 18.559
  15. 15. RAW DATA & PROCESSING DATA GATHERING Searching time Lantai 2 Mean 81.1 Std. 15.7
  16. 16. RAW DATA & PROCESSING DATA GATHERING Duration of parking 0 5 10 15 20 25 30 35 40 30 60 90 120 150 180 210 240 270 300 330 390 420 Frequency Minutes Duration  of  Parking  Time Mean Std.
  17. 17. RAW DATA & PROCESSING DATA GATHERING Queuing timeArrival Time Service Time Counter Observer 2 (observe the server) Observer 1 (observer arrival) Interarrival rate Arrival Time Service time Arrival time in server
  18. 18. RAW DATA & PROCESSING DATA GATHERING Queuing timeArrival Time Service Time Counter Kedatang an Ke- Inter Arrival Waktu kedatangan Server Waktu sampai depan loket Service Time Waktu keluar loket Waktu Antrian Antrian/Tidak Detik Jam Menit Detik Jam Menit Detik Detik Jam Menit Detik Detik 1 3 13 10 3 1 13 10 4 5 13 10 9 1 Tidak antri 2 9 13 10 12 1 13 10 13 4 13 10 17 1 Tidak antri 3 1 13 10 13 1 13 10 18 6 13 10 24 5 Antri 4 23 13 10 36 1 13 10 37 5 13 10 42 1 Tidak antri 5 34 13 11 10 1 13 11 12 8 13 11 20 2 Tidak antri 6 12 13 11 22 2 13 11 23 4 13 11 27 1 Tidak antri 7 20 13 11 42 1 13 11 43 6 13 11 49 1 Tidak antri 8 15 13 11 57 1 13 11 58 9 13 12 7 1 Tidak antri 9 21 13 12 18 1 13 12 19 10 13 12 29 1 Tidak antri 10 18 13 12 36 1 13 12 37 4 13 12 41 1 Tidak antri 11 13 13 12 49 1 13 12 50 5 13 12 55 1 Tidak antri 12 18 13 13 7 1 13 13 8 8 13 13 16 1 Tidak antri 13 6 13 13 13 1 13 13 15 4 13 13 19 2 Tidak antri 14 8 13 13 21 1 13 13 22 17 13 13 39 1 Tidak antri 15 9 13 13 30 1 13 13 41 9 13 13 50 11 Antri 16 5 13 13 35 2 13 13 50 4 13 13 54 15 Antri 17 15 13 13 50 1 13 13 52 5 13 13 57 2 Tidak antri 18 13 13 14 3 1 13 14 4 6 13 14 10 1 Tidak antri 19 3 13 14 6 2 13 14 8 5 13 14 13 2 Tidak antri 20 6 13 14 12 1 13 14 13 7 13 14 20 1 Tidak antri
  19. 19. RAW DATA & PROCESSING DATA GATHERING Arrival Rate
  20. 20. RAW DATA & PROCESSING DATA GATHERING Inter-Arrival Time
  21. 21. RAW DATA & PROCESSING DATA GATHERING Service Time Counter 1
  22. 22. RAW DATA & PROCESSING DATA GATHERING Queuing time 2.899 1.555 2.578 2.679 2.851 1.752 0 1 2 3 4 13.10-­‐14.09 14.10.15.09 15.10-­‐16.09 16.10-­‐17.09 17.10-­‐18.09 18.09-­‐19.09 Average  of  Queuing  Time
  23. 23. SYSTEM DOCUMENTATION DATA GATHERING 1 2 3 4 5 6
  24. 24. MODEL CONSTRUCTION
  25. 25. DATA GATHERING STEPS 1 2 3 4 BUILD   LOCATION ENTITIES ARRIVALS PROCESS MODEL CONSTRUCTION
  26. 26. DATA GATHERING LOCATION MODEL CONSTRUCTION
  27. 27. DATA GATHERING ENTITIES ARRIVALS MODEL CONSTRUCTION
  28. 28. DATA GATHERING PROCESS MODEL CONSTRUCTION
  29. 29. DATA GATHERING PROCESS MODEL CONSTRUCTION
  30. 30. MODEL CONSTRUCTION FINISHED MODEL
  31. 31. VALIDATION
  32. 32. 01 Watching Animation 02 Comparing with other models 03 Comparing with actual system 04 Conducting degeneracy and extreme condition 05 Performing sensitivity analysis VALIDATION
  33. 33. WATCHING ANIMATION VALIDATION CLICK
  34. 34. COMPARING WITH SPREADSHEET MODEL VALIDATION Spreadsheet Model Pro Model Average server utilization (ρ) 0.2875 0.24 Average number of customers in the queue (Lq) 0.0518 0.14 Average number of customers in the system (Ls) 0.6268 0.61 Average waiting time in the queue (Wq) 0.0002 0.018021 (minutes) 0.03 Average time in system (Ws) 0.0018 0.218021 (minutes) 0.22 Probability (% of time) system is empty (P0) 55% 85% Arrival rate during peak time 345 motorcycle/hour Average service time during peak time 6 seconds OBSERVATION Saturday, 26-09-2015 11.10 am to 9.20 pm 268 259 289 383 268268
  35. 35. COMPARING WITH ACTUAL SYSTEM VALIDATION Visitors will first fulfill parking area block which near the mall entrance Visitors will only go to P2 if only P1 capacity is full. P2 will be open when P1 capacity almost full Visitors tend to take Server 1 rather than Server 2 (First Available) If visitors didn’t find parking at P2, they will look again the available area at P1 Actual Model How? We create dummy process from P2 to P1 for motorcycle who didn’t get parking at P2
  36. 36. CONDUCTING DEGENERACY & EXTREME CONDITION VALIDATION EXTREME TEST Arrival Rate: 0
  37. 37. CONDUCTING DEGENERACY & EXTREME CONDITION VALIDATION EXTREME TEST Arrival Rate: 0
  38. 38. CONDUCTING DEGENERACY & EXTREME CONDITION VALIDATION EXTREME TEST Arrival Rate: Maximum
  39. 39. CONDUCTING DEGENERACY & EXTREME CONDITION VALIDATION EXTREME TEST Arrival Rate: Maximum
  40. 40. SENSITIVITY TEST VALIDATION
  41. 41. SENSITIVITY TEST VALIDATION
  42. 42. SENSITIVITY TEST VALIDATION
  43. 43. SENSITIVITY TEST VALIDATION
  44. 44. VERIFICATION
  45. 45. TRACE VERIFICATION
  46. 46. OUTPUT ANALYSIS
  47. 47. OUTPUT ANALYSIS OUTPUT ANALYSIS WHAT TO WATCH? Incoming/Outcoming Entities Average time in queue (Wq) and in system (Ws) Average number of entities in queue (Lq) and in system (Ls) Utilization of queueing system
  48. 48. VERIFICATION Total Input 1780 unit in 6 hour Single Line Multiserver Total Output 1202 unit Incoming/outcoming entities OUTPUT ANALYSIS
  49. 49. VERIFICATION LOCATION STATES MULTI OUTPUT ANALYSIS
  50. 50. VERIFICATION LOCATION STATES SINGLE OUTPUT ANALYSIS
  51. 51. VERIFICATION ENTITTY ACTIVITY AND STATES OUTPUT ANALYSIS
  52. 52. Wq = 0.03 min Ws for Server 1 = 0.12 min Ws for Server 2 = 0.13 min They are within limits required from this assignment (1 min) Therefor no additional server is needed for now VERIFICATIONOUTPUT ANALYSIS Average Time in Queue and Ticketing System Lq = 0.15 entities Ls for Server 1 & 2 = 0.62 entities These number are similar with our Spreadsheet model Average Number of Entities in Queue and System
  53. 53. VERIFICATIONOUTPUT ANALYSIS Utilization of Queueing System Server 1 utilization = 33% Server 2 utilization = 14% Their average are similar with our spreadsheet model The server is under utilized even at peak time Entity Activity Average Time in system = 92.86 min Average time in waiting = 0.03 min Average time blocked = 0.92 min Entity  Activity Operation Waiting Blocked
  54. 54. VERIFICATIONOUTPUT ANALYSIS Utilization of Parking Space Average time to search parking space 16 out of our parking space are utilized, 8 are continuously empty Average of empty parking space = 31.8% Average of full parking space = 28% Average # of entities in parking space system = 432 unit per hour There are overcapacity in Central Park parking system Average time = 1.69 min There are 6 locations where searching for parking space takes longer than 2 minutes (B1 area 2, 4, 5, and 6). We aim to reduce that to less than 2 minutes. There are several options: increasing parking space, better routing and capacity management
  55. 55. CONCLUSION
  56. 56. CONCLUSION CONCLUSION Peak time in Central Park happens on Saturday at 13.10-20.20 Average arrival rate in Central Park is 345 motorcycles/ hour Average service time on server 1 is 5,7 s and on server 2 is 5,8 s Queueing time in lockets is under 1 minute and searching time average is under 2 minutes, So, the parking system on Central Park is optimal. The problem that happens in Central Park is mostly because of breakdown in server. So, queue only happen when the server is breakdown.
  57. 57. RECOMENDATION
  58. 58. RECOMENDATION RECOMENDATION The problem that happens in Central Park is mostly because of breakdown in server. So, queue only happen when the server is breakdown. Better maintanance program for each server machine Increase parking space Better routing and capacity management
  59. 59. RECOMENDATION RECOMENDATION Increasing Parking Space Basement 1 location 2 = From 10 to 50 parking spaces Basement 1 location 4 = From 38 to 45 parking spaces Basement 1 location 6 = From 38 to 50 parking spaces Total Increase of parking space = 62 Average time to search parking space = 1.16 min No more spending over 2 minutes to search a parking space! Constraint : Limited Space to Expand
  60. 60. RECOMENDATION RECOMENDATION Better Routing and Capacity Management Since there are 8 parking location that is continuously empty, managementcan start routing entities there, when queue start to form Management can also partly closed several parking locations on B1 to route entities to search for parking space at B2
  61. 61. THANKYOU

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