PELAKSANAAN SISTEM INFORMASI MANAJEMEN KESEHATAN IBU DAN ANAK (SIM KIA) DENGAN PENDEKATAN TASK TECHNOLOGY FIT (TTF) DI PUSKESMAS ROWOSARI KOTA SEMARANG - Aminah Muslamet; Antono Suryoputro; Atik Mawarni (Jurnal Kesehatan Masyarakat (Undip), 2019)
The application of information technology is very important to support the accuracy of information and facilitate decision making, especially in the health sector. Health Management Information System (HMIS) for Maternal and Child Health (MCH) named SIM KIA is here to support inputting up to data reporting, which will then be used as material for decision making. Since 2016 SIM KIA has been implemented in Rowosari Puskesmas, but in its implementation manual recording is still done in addition to using SIM KIA. The purpose of this study is to look at the suitability of SIM KIA related to the work of MCH officers in collecting and reporting MCH programs data using the TTF approach. This type of research is qualitative with a descriptive approach. The method of data collection was carried out by in-depth interviews with MCH officers which is totaling 6 respondents, the Head of the Puskesmas, the Puskesmas Information Technology Officer, and the MCH programs holder in the Semarang DKK. Based on the results of the SIM KIA research it is considered not in accordance with the work of MCH officers, in terms of collection and recording of SIM KIA data has not been able to cover Puskesmas external data, in terms of manage of SIM KIA it has not been able to manage data such as coverage, and in terms of SIM KIA reporting only able to report medical records of puskesmas internal patient. It is recommended that Semarang DKK need to develop SIM KIA so that they are integrated with other health facilities, improve SIM KIA capabilities in managing data, fulfill MCH information needs that are not yet available, and remember the benefits of SIM KIA that are still lacking in supporting MCH programs. As for the puskesmas it is recommended to reorganize the job description for the management of MCH data to be more optimal.