Information and Communication Technology Seminar, Vol. 1 No. 1, August 2005
ISSN 1858-1633 2005 ICTS 74
− 0: Emergency. − 1: Very Important.
− 2: Important. − 3: Less important
d. Data of previous week schedule. This data was required because there was a
hospital’s rule that every nurse must work in night shift on two successive days every two weeks.
Delphi and SQL server were used to make the scheduling program and database of the nurse. Figure
2 shows the proposed schedule for period of 1-7 August 2004 for team A After running one cycle of
modified Bayesian optimization algorithm, program will display message dialog that show lowest fitness
function value in that cycle and let user to decide continue the program or not. If user does not satisfy
with current fitness function, program will ignore the lowest one-day weekly vacation request by nurse to
create new schedule. This will be repeated until the last priority and program will display the value of
fitness function, nurse’s preference, and penalty of current requirement.
.Figure 2 Proposed Schedule of Team A for period 1-7 August 2004
2.3. Comparison Proposed Schedule with Real Schedule
Using the program, the authors made a proposed schedule for period of 1st August-13th November
2004 to be compared to the real schedule. Mean comparative test between fitness function of
the real schedule and proposed schedule used one way paired samples t test [5]. The hypothesis was :
0H = mean of fitness function of real the real schedule and proposed schedule is equal.
1H = mean of fitness function of the proposed schedule is less than real schedule.
SPSS 10.0 software was used to perform the test. The mean of the fitness function of the real schedule was
3.268,67 and proposed schedule was 1.903,73. Based on the test result with
α = 0,05 and d.f.= 14, t table value was 1,761 and calculated t was 8,117 greater
than value of t table therefore 0 H was rejected. Mean comparative test of preference of the nurse
from the real schedule and proposed schedule also used one way paired samples t test. The hypothesis
was : 0H = mean of nurse preference of real the real
schedule and proposed schedule is equal. 1H = mean of nurse preference of the proposed
schedule is less than real schedule Mean of nurse preference using real schedule was
268,67 and using proposed one was 250,40. The result of one way paired samples t test with
α = 0,05 and d.f. = 14 value of t table was 1,761. Value of calculated t
was 10,407 greater than value of t table therefore 0H was rejected.
Mean comparative test between penalty of uncovered shifts of real schedule and proposed one
used paired samples t test. The hypothesis was : 0H = mean of penalty of uncovered shifts of real
schedule and proposed one was equal. 1H = mean of penalty of uncovered shifts of
proposed schedule was less than real one. Mean of penalty of uncovered shifts real schedule
was 3.000,00 and proposed schedule was 1.653,33. The result of the test with
α = 0,05 and d.f. = 14 value of t table was 1,761. Value of calculated t was 7,995
greater than value of t table therefore 0H was rejected.
From coverage aspect, both real and proposed schedule did not completely fulfill the requirement.
But for the requirement on number of nurse for every grade, proposed schedule was better than real
schedule. It can be seen from the result of paired samples t test of penalty of uncovered shifts between
real and proposed schedule. Mean of penalty of uncovered shifts proposed schedule 1.653,33 was
significantly less than the real one 3.000,00.
For total requirement covered per day without considering grade, both of the schedules did not
completely cover the requirement. Because of mean total uncovered shifts real schedule is less than the
proposed one, real schedule was better than the proposed one. This is because initial random
population making more difficult to get suitable shift pattern. Also cover rule, which was used in the
proposed schedule algorithm, did not concern how many nurse still needed in the particular shift. Cover
rule just counted total uncovered shifts and will be covered if a nurse work at hat shift pattern. Although
particular shift needed more nurse but had less cover value, will be denied. If this would happen for the next
nurse therefore that shift still uncovered.
Most uncovered shifts found in these schedules for nurse with senior grade. In real schedule, mean of
uncovered shifts of senior nurses was 7 nurses, and in proposed one was 4 nurses. In real schedule mean of
uncovered shifts of medior grade nurse was 6 and in proposed one was 4. For yunior grade nurse, mean of
uncovered shifts in real schedule was 3 nurses and 2 nurses in proposed one.
From quality aspect, proposed schedule was better than real one because it can fulfill the nurse’s
Modified Bayesian Optimization Algorithm for Nurse Scheduling – I N Sutapa, I H Sahputra, V M Kuswanto
ISSN 1858-1633 2005 ICTS 75
preferences. It can be seen from the result of paired samples t test for nurse’s preference that show mean
of nurse’s preference 250,40 was significantly less than real one 268,67. In the proposed schedule, the
nurse’s one-day weekly vacation request and preference were considered. In the real schedule, only
nurse’s one-day weekly request was considered.
From stability aspect, the proposed schedule was better because it could create schedule according to
the rotation shift and vacation rule. Rotation of the nurse from team A to team B can be done by change
the location of the nurse. The nurse’s request for one- day weekly vacation was given priority based on the
important level.
From flexibility aspect, both schedules have a good flexibility because both of them consider the
nurse’s request for specific shift pattern. From the fairness aspect, proposed schedule was better than the
real one because it’s process was not influenced by personal interest but randomly.
3. CONCLUSION
