Studi Komparasi Hasil Belajar Kimia Pada Materi Koloid Menggunakan Model Pembelajaran Berbasis Proyek Dan Model Pembelajaran Berbasis Masalah Siswa Kelas XI IPA Man 2 Mataram Tahun Ajaran 2013/2014

: The aims of this quasi experimental research is to compare the chemistry study result by using the project based learning model and problem based learning model at class XI science of MAN 2 Mataram in academic year 2013/2014. Sample of this research were class XI science U1 as experiment I class and class XI science U2 as experiment II class which taken by using purposive sampling technique.Data cognitive of the result study obtained through a written test (post-test) were analyzed using a different test (t test). The results showed that the experimental class I obtained an average value of 67 with classical completeness of 7.69% while the experimental class II obtained an average value of 70 with classical completeness 28.57%. T-test results of the unequal sample at the significant level of 5% was obtained tcalculation =-0,4709 andttable= 2,060, with the result that tcalculationin the range from to -2,060 and +2,060which means that the Ho in this research is approved. In conclusion, there is no significant difference in result study between students who are taught chemistry using project-based learning model and the problem based learning model students of class XI IPA 2 Mataram MAN in Academic Year 2013/2014

Analisis Tingkat Akurasi Metode Neuro Fuzzy dalam Prediksi Data IPM di NTB

Penelitian ini dilakukan untuk menganalisis proses forecasting dalam menentukan tipe terbaik yang digunakan pada sistem peramalan (forecast). Pada penelitian ini data yang digunakan yaitu data IPM Provinsi Nusa Tengara Barat (NTB) tahun 2008-2018 untuk memprediksi data Indeks Pembangunan Manusia (IPM) tahun 2019. Penelitian ini menggunakan metode Artificial Intelligence Neuro Fuzzy yaitu Fuzzy Mamdani dan ANFIS Sugeno yang diterapkan pada Matlab. Adapun tipe yang diuji adalah Trimf, Trapmf, Gbellmf, Gaussmf, Gauss2mf, Sigmf, Dsigmf, Psigmf, dan Primf. Tipe tersebut bertujuan untuk melihat tingkat akurasi berdasarkan hasil error. Hasil peramalan terbaik didapatkan pada tipe Gauss2mf karena menghasilkan prediksi sebesar 69.5 dengan error sebesar 0.95947 dan MAD sebesar 0.530.354, MSE sebesar 1.570035, MAPE sebesar 0.049273