R help - Aug 2017 - Directional Forecast

I've some demand data, for which I wish to judge what will be the direction
in the forecast period (Up/Down). What will be a best ML method to do this?
Currently I'm using the data given below -

9/4/2016 241
9/11/2016 233
9/18/2016 226
9/25/2016 282
10/2/2016 291
10/9/2016 282
10/16/2016 308
10/23/2016 291
10/30/2016 268
11/6/2016 262
11/13/2016 273
11/20/2016 262
11/27/2016 309
12/4/2016 317
12/11/2016 331
12/18/2016 382
12/25/2016 358
1/1/2017 359
1/8/2017 342
1/15/2017 332
1/22/2017 324
1/29/2017 298
2/5/2017 283
2/12/2017 274
2/19/2017 278
2/26/2017 245
3/5/2017 214
3/12/2017 217
3/19/2017 234
4/16/2017 204
4/23/2017 197
4/30/2017 203
5/7/2017 198
5/14/2017 211
5/21/2017 186
5/28/2017 176
6/4/2017 183
6/11/2017 180
6/18/2017 177
6/25/2017 157
7/2/2017 179
7/9/2017 191

I'm using 'forecastHybrid' package in R with the following code, but
unfortunately the forecasts I'm getting based on last observation only
(i.e. 191), which doesn't seem to be correct.

Will any other model be relevant here, i.e. SVM, RF etc. Any specific
guidance/code in R will be much appreciated.

mod1 <- hybridModel(t) fc1 <- forecast(mod1) fc1

	[[alternative HTML version deleted]]

I suggest, you read:
Forecasting: principles and practice from Hyndman-Athana?sopou?los
https://www.otexts.org/fpp

> On Aug 11, 2017, at 4:47 AM, Suzen, Mehmet <msuzen at gmail.com>
wrote:
> 
> I suggest, you read:
> Forecasting: principles and practice from Hyndman-Athana?sopou?los
> https://www.otexts.org/fpp
I also suggest reading the Posting Guide and reposting the question in palin
text. The HTML format has mangled what is there.

Further:
It's not clear whether the initial post has a complete example because those
dates are not appreaing in a manner that suggests correct data entry.
> 
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> and provide commented, minimal, self-contained, reproducible code.
David Winsemius
Alameda, CA, USA

'Any technology distinguishable from magic is insufficiently advanced.' 
-Gehm's Corollary to Clarke's Third Law