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Lina Irawati
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Education Mathematics Other

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PENERAPAN STRATEGI KOOPERATIF TEKNIK MURDER YANG DIKOLABORASIKAN DENGAN NUMBERED HEADS TERHADAP PEMAHAMAN KONSEP MATEMATIS SISWA KELAS XI SMK SEMEN PADANG TAHUN PELAJARAN 2013/2014 Irawati, Lina; Haryono, Yulia; Suryani, Mulia
Pendidikan Matematika Vol 1, No 1 (2014): Jurnal Wisuda Ke 48 Mahasiswa Prodi Pendidikan Matematika
Publisher : STKIP PGRI Sumbar

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ABSTRACTThis research was conducted based on the phenomena indicating that the students tended to be noisy during the learning process and they got low understanding on mathematics concept. This research aimed to reveal whether the use of MURDER technique of cooperative strategy collaborated with Number Heads could improve the students’ understanding on mathematics concept better than that of conventional technique. This was an experimental research. The data gotten then was analyzed by using t-test assisted with software MINITAB. Based on the result of data analysis, it was found that P-value was 0.019 which was smaller than α = 0.05. This result indicated that the mathematics conceptual understanding of the students taught by using MURDER technique of cooperative strategy collaborated with Number Heads was better than that of students taught by using conventional technique in which the level of the reliability was 95%. 
PERAMALAN INDEKS HARGA KONSUMEN 4 KOTA DI JAWA TENGAH MENGGUNAKAN MODEL GENERALIZED SPACE TIME AUTOREGRESSIVE (GSTAR) Lina Irawati; Tarno Tarno; Hasbi Yasin
Jurnal Gaussian Vol 4, No 3 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (666.462 KB) | DOI: 10.14710/j.gauss.v4i3.9479

Abstract

Generalized Space Time Autoregressive (GSTAR) models are generalization of the Space Time Autoregressive (STAR) models which has the data characteristics of time series and location linkages (space-time). GSTAR is more flexible when faced with the locations that have heterogeneous characteristics. The purposes of this research are to get the best GSTAR model and the forecasting results of Consumer Price Index (CPI) data in Purwokerto, Solo, Semarang and Tegal. The best model obtained is GSTAR (11) I(1) using cross correlation normalization weight because it generated white noise and multivariate normal residuals with average value of MAPE 3,93% and RMSE 10,02. The best GSTAR model explained that CPI of Purwokerto is only affected by times before, it does not affect to other cities but can be affecting to other cities. Otherwise, CPI of Surakarta, Semarang and Tegal are affecting each others. Keywords: GSTAR, Space Time, Consumer Price Index, MAPE, RMSE
Co-Authors Hasbi Yasin Mulia Suryani Tarno Tarno Yulia Haryono