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In this work, we prove that the sparse matrix resulting from a finite-element-based analysis of electrodynamic problems can be represented by an H matrix without any approximation, and the inverse of this sparse matrix has a data-sparse H-matrix approximation with error well controlled. Two proofs are developed. One is based on the general eigenvalue-based solution to the ordinary differential equations, and the other is based on the relationship between a partial differential operator and an integral operator. Both proofs have reached the same conclusion. Based on the proof, we develop an H-matrix-based direct finite-element solver of O (kN logN) memory complexity and O (k2Nlog2N) time complexity for solving electromagnetic problems, where k is a small parameter that is adaptively determined based on accuracy requirements, and N is the number of unknowns. Both inverse-based and LU-based direct solutions are developed. The LU-based solution is further accelerated by nested dissection. A comparison with the state-of-the-art direct finite element solver that employs the most advanced sparse matrix solution has shown clear advantages of the proposed direct solver. In addition, the proposed solver is applicable to arbitrarily-shaped three-dimensional structures and arbitrary inhomogeneity.