First a disclaimer. I'm not a statistician and I don't know a great deal about either of these methods. However, my understanding is the following:
A one in your data indicates the condition is present in the observation and a zero indicates it's not present (binary data).
The coefficients are calculated in pairs of observations. In other words, you will have to calculate coefficients for observations 1-2, 1-3, 1-4 up to 4-5 which is 10 sets of coefficients.
Assuming the following notation represents the number of matching attributes (the sum where each of these conditions exist)
N(1,1) means a one is in both observations for a given condition
N(0,0) means a zero is in both observations
N(1,0) means a one is in first observation and a zero is in the second observation
N(0,1) means a zero is in first observation and a one is in the second observation
Jaccard coefficient = N(1,1) / (N(0,1) + N(1,0) + N(1,1))
Matching coefficient = (N(0,0) + N(1,1)) / (N(0,0) + N(0,1) + N(1,0) + N(1,1))
For example, for observations 1 and 2:
N(1,1) = 4
N(0,0) = 1
N(1,0) = 1
Jaccard = 4/6 =.67%
Matching = 5/7 = .71%
I have a spreadsheet with this worked out, I just need to figure out how to post it.