This study intends to develop a new duplicate detection algorithm to improve database quality. The new algorithm is developed to analyze by variables of language and bibliographic type, and it checks elements in bibliographic data not just MARC fields. The algorithm computes the degree of similarity and the weight values to avoid possible elimination of records by simple input error. The study was peformed on the 7,649 newly uploaded records during the last one year against the 210,000 sample master database. The findings show that the new algorithm has improved the duplicates recall rate by 36.2%.