Unexpected behavior in train_test_split with shuffle=False

When using `train_test_split` with `shuffle=False` and a Dask dataframe, I notice 2 issues - 1) The index is actually shuffled and 2) the train/test size seems incorrect. The behavior doesn't match sklearn or when you pass a raw DataFrame.

**Minimal Complete Verifiable Example**:
Setup
```python
import pandas as pd
import numpy as np
import dask.dataframe as dd

from sklearn.model_selection import train_test_split as sk_train_test_split
from dask_ml.model_selection import train_test_split as dd_train_test_split

df = pd.DataFrame(np.random.rand(10, 3), columns=["y", "x1", "x2"])
ddf = dd.from_pandas(df, 5)
```

With `sklearn.model_selection`, order is maintained (i.e. no shuffle)
```python
y = df["y"]
X = df[["x1", "x2"]]

X_train, X_valid, y_train, y_test = sk_train_test_split(X, y, test_size=0.5, shuffle=False)
y_train, y_test
```
```text
Output:
(0 0.166713
1 0.961016
2 0.483907
3 0.979503
4 0.553724
Name: y, dtype: float64,
5 0.158432
6 0.078795
7 0.440427
8 0.673160
9 0.657797
Name: y, dtype: float64)
```

With `dask_ml.model_selection` using Pandas Dataframe, order is maintained (i.e. no shuffle)
```python
y = df["y"]
X = df[["x1", "x2"]]

X_train, X_valid, y_train, y_test = dd_train_test_split(X, y, test_size=0.5, shuffle=False)
y_train, y_test
```
```text
(0 0.166713
1 0.961016
2 0.483907
3 0.979503
4 0.553724
Name: y, dtype: float64,
5 0.158432
6 0.078795
7 0.440427
8 0.673160
9 0.657797
Name: y, dtype: float64)
```

With `dask_ml.model_selection` using Dask Dataframe, , order is *NOT* maintained and train/test size is incorrect.
```python
y = ddf["y"]
X = ddf[["x1", "x2"]]

X_train, X_valid, y_train, y_test = dd_train_test_split(X, y, test_size=0.5, shuffle=False)
y_train.compute(), y_test.compute()
```
```text
(0 0.166713
1 0.961016
2 0.483907
3 0.979503
8 0.673160
9 0.657797
Name: y, dtype: float64,
4 0.553724
5 0.158432
6 0.078795
7 0.440427
Name: y, dtype: float64)
```

**Environment**:

- Dask version: 2023.11.0
- Python version: 3.11.8
- Operating System: MacOS
- Install method (conda, pip, source): micromamba