The purpose of the map here will really decide which CRS you will use. You basically have 2 options, a geographic coordinate system or a projected coordinate system and depending on what you want to accomplish will help you choose which system you want to make a map in.
The web page above will help you decide what projection to pick depending upon the map you want to produce. Remember that projections all try to be as accurate as possible, but to do so they must distort either Area, Direction, Size, Distance (http://geokov.com/education/map-projection.aspx)
So if you are making a map of land cover in Kenya, here are some papers that specifically deal with which projection you should choose:
According to the results found from the twelve one-by-one degree polygons, the Robinson
projection, a non-equal-area projection, showed the poorest estimation in terms of the percentage
of areas represented after rasterization, an expected result. Three equal-area projection methods,
the interrupted Goode homolosine, Mollweide, and equal-area cylindrical projections, showed
little difference in area representation in spatial resolutions of one kilometer or less. However, at
the spatial resolutions from one kilometer to eight kilometers, the Mollweide projection showed
the best result. At the spatial resolution ranges from 16 km to 25 km, the Goode homolosine and
equal-area cylindrical projections showed slightly better results than the Mollweide projection
(the Mollweide projection tends to under-represent the original area at this spatial resolution
range). The Robinson projection significantly over-represented the original area at the spatial
resolution ranges of 16 kilometers or less and the over-representation reached about 10 percent. At the spatial resolution of eight km, all the global projections used in this study tend to overrepresent
the original area at latitudes of 60 degrees or higher. The representation is most
accurate in the Mollweide projection with Goode homolosine, equal-area cylindrical, and
Robinson following in order of accuracy.
On a side note, Kenya is a good example here of a country that falls within multiple UTM zones (zones 36N, 37N, 36M, 37M) which makes things a little more difficult, if your data was coming from different UTM zones.
The lab below specifically deals with Kenya and different projections:
The appropriate scale is something that you will really have to figure out yourself, there is no way I could say 1:100000 is what you want or not, you will have to see which scale best allows for the presentation of your data. Also the type of deliverable will also decide your scale. Is it a wall map, page map, digital map? etc...