KERJASAMA INDONESIA DAN KEPOLISIAN NEGARA ANGGOTA ASEANAPOL (ASEAN NATIONS POLICE) DALAM PENANGANAN KASUS PERDAGANGAN MANUSIA TAHUN 2020-2023

The increase in cases of human trafficking among Indonesian citizens has encouraged cooperation between the police of ASEAN member countries, especially the Indonesian National Police in dealing with this problem. This research aims to determine the efforts of the INP and the police who are members of the ASEANAPOL (ASEAN Nations Police) organization in carrying out cooperation to reduce and minimize cases of human trafficking in Southeast Asia. The method used in this research is a descriptive method supported by various reference sources through literature studies and interviews with related parties. The results of this research indicate that coordination/communication is the main key to the cooperation carried out by the ASEAN police, whether through international meetings, deployment of INP personnel abroad, or joint training of personnel. Apart from that, this research also shows that there has been a reduction in the number of cases through the coordination system (directly and indirectly). From this coordination, a cooperation model was formed, namely the Joint Coordination System (JCS) to analyze the cooperation between the INP and the police in Southeast Asia in repatriating Indonesian citizens who were victims of human trafficking so they could return to Indonesia. Therefore, having coordination between the parties involved really helps the success and effectiveness of the collaboration carried out

Neural nets - their use and abuse for small data sets

Neural nets can be used for non-linear classification and regression models. They have a big advantage over conventional statistical tools in that it is not necessary to assume any mathematical form for the functional relationship between the variables. However, they also have a few associated problems chief of which are probably the risk of over-parametrization in the absence of P-values, the lack of appropriate diagnostic tools and the difficulties associated with model interpretation. The first of these problems is particularly important in the case of small data sets. These problems are investigated in the context of real market research data involving non-linear regression and discriminant analysis. In all cases we compare the results of the non-linear neural net models with those of conventional linear statistical methods. Our conclusion is that the theory and software for neural networks has some way to go before the above problems will be solved

Purely non-atomic weak L^p spaces

Let \msp be a purely non-atomic measure space, and let $1 < p < \infty$. If \weakLp\msp is isomorphic, as a Banach space, to \weakLp\mspp for some purely atomic measure space \mspp, then there is a measurable partition $\Omega = \Omega_1\cup\Omega_2$ such that $(\Omega_1,\Sigma\cap\Omega_1,\mu_{|\Sigma\cap\Omega_1})$ is countably generated and $\sigma$-finite, and that $\mu(\sigma) = 0$ or $\infty$ for every measurable $\sigma \subseteq \Omega_2$. In particular, \weakLp\msp is isomorphic to $\ell^{p,\infty}$