‘I do not understand what should be the inputs for my problem.’
There are several different filter types. The Chebyshev design is a good choice, although the elliptical design (that I use here) is more efficient with equally narrow transition regions, so I would use an elliptical filter.
For a lowpass filter, you need to sampling frequency, and the sampling interval (1/sampling frequency) must be constant. If it is not, you will need to use the Signal Processing Toolbox resample function to interpolate your data to constant sampling intervals.
A prototype filter assuming a sampling interval of 1 sample/day is:
Ts = 1/365.25;
Fs = 1/Ts;
Fn = Fs/2;
Wp = (1/13)/Fn;
Ws = Wp*1.1;
Rp = 1;
Rs = 50;
[n,Wp] = ellipord(Wp,Ws,Rp,Rs);
[z,p,k] = ellip(n,Rp,Rs,Wp);
[sos, g] = zp2sos(z,p,k);
freqz(sos, 2^14, Fs)
set(subplot(2,1,1), 'XLim',[0 1])
set(subplot(2,1,2), 'XLim',[0 1])
Then use the filtfilt function to filter your signal. Note that the frequency uints for this filter are cycles/year, not Hz.
The passband and stopband ripple values are arbitrary. The values I use here are essentially standard, and give good filter performance.
This will get you started, as will the MATLAB documentation. If you are going to be doing signal processing, you likely need to take a course in it, since you will need to understand the assumptions and design decisions that enter into it.