Clearly, like Hey Lyla has pointed out, you have some seasonality in there. I would suggest you try to include $11$ monthly dummy variables for the first $11$ months. (Do not include $12$, since you will run into the dummy variable trap else.) I Then you can seasonally adjust the data by substracting the fitted model's monthly dummies from the actual data. This might do the job.
Alternatively, you could consider applying a Fourier Transformation (essentially fitting sine/cosine curves) and substracting the corresponding coefficients instead. The number of expansion terms (i.e., sine/cosine functions) can be determined with information criteria like AIC or BIC.
Edit: As pointed out by Richard Hardy in the comments, if you suspect any kind of deterministic time trend to be present in the data, you should also include an appropriate regressor (in your case potentially one for a linear trend). Note that you will still only have to substract the monthly dummies.