Penyakit TORCH merupakan kelompok infeksi beberapa jenis virus yaitu Toxoplasma, Rubella, Cytomegalovirus dan Herpes. Penyebab utama dari virus dan parasit TORCH adalah hewan yang ada disekitar kita seperti ayam, kucing, burung, tikus, merpati, dan lainnya. Toxoplasma, Rubella, Cytomegalovirus dan Herpes dapat menyebabkan rusaknya vertilitas pada ibu hamil. Sel telur maupun inti sel pada ibu hamil dirusak oleh virus tersebut kemudian sel telurnya mengecil, menyebabkan terbentuknya mioma, penyumbatan atau perlengketan, sehingga sel telur tidak bisa dibuahi dan mengakibatkan sulit hamil. Oleh sebab itu, sangat penting dilakukan diagnosis dini agar dapat dilakukan pencegahan atau pengobatan lebih awal. Proses diagnosis dapat dilakukan langsung kepada dokter atau bidan, namun sering terjadi permasalahan seperti: keterbatasan waktu, keadaan fisik yang tidak memungkinkan untuk meninggalkan rumah, masalah keuangan, keterbatasan tenaga dokter atau bidan dan lain-lain. Untuk dapat mempermudah masyarakat dalam mengenali masalah TORCH pada pada ibu hamil, maka diperlukan suatu sistem yang dapat membantu pekerjaan dokter dalam diagnosa awal masalah TORCH pada ibu hamil. Pada penelitian ini digunakan metode certainty factor dan fuzzy logic dalam mendiagnosa masalah TORCH pada ibu hamil untuk menghitung tingkat akurasi jenis masalah yang dialami berdasarkan gejala-gejala yang dirasakan oleh user. Dari pengujian diperoleh hasil dalam menangani masalah TORCH pada ibu dengan tingkat akurasi sebesar 40,00%. Sistem pakar yang dihasilkan dapat membantu pasien dalam berkonsultasi untuk menangani masalah TORCH pada ibu hamil.
Lecturers are academic staff who are in charge of planning and implementing the learning process, guidance and training, and are able to bring students into activities held by the University, both official and non-official. Selection of favorite lecturers chosen by students can encourage lecturers to communicate more with students to be able to invite students to take part in groups or organizations involving students and lecturers. However, in reality, Universitas Putra Indonesia YPTK Padang is still not actively conducting this election. To overcome these problems, a Decision Support System was designed to determine the student's favorite lecturers by using the simple additive weighting method. The Decision Support System for Determining Favorite Lecturers of Student Choice is a system that is able to increase the ease of decision making in determining lecturers who have student attractiveness so that students are more active and more competent in the guidance of the selected lecturers. In this system the lecturer's assessment is based on 5 criteria. The criteria used are responsibility, discipline, attitude, initiative, and presence. To get the final conclusion as an alternative decision to determine the lecturer of this choice requires the calculation process stage on each variable that has been determined based on the criteria. The position of the decision support system in this study is as a decision supporter, not replacing the role of the decision maker, so that the decision maker has the right to fully refer to the decision support system or not. The research results from the calculated simple additive weighting method can be concluded that the favorite lecturer of the student's choice is lecturer 2 with a score of 1.00 which is the result of the highest ranking and can be used as an alternative for determining the favorite lecturer of the student's choice.
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