Rather than looking at LOOIC, you should look at the elpd (expected log predictive density), as LOOIC is just -2 * elpd as @andre.pfeuffer has already mentioned.
For elpd, the larger the better, but there is no intrinsic meaning in that number on its own (as that depends, among other things, on the number of observations you have). It starts to get a meaning only when compared to the elpd of a different model (on the same data), and then you can start interpreting the difference.
In your example, the interaction model is worse compared to the main effects model. The difference is large wrt to the standard error of the difference. I think @avehtari recommends at least 4-5 times, as the computed standard error is likely to be an underestimate. In your case you have elpd_diff > 6 * se_diff, so you can be confident that the simpler model is better.