Tujuan dari penelitian ini adalah membangun sistem informasi MUI Pamekasan dengan menggunakan metode RAD (Rapid Application Development) dengan tahapan perencanaan, desain sistem, pengembangan dan implementasi. Modul yang dikembangkan dalam website MUI Pamekasan antara lain: (1) data masjid, (2) berita, (3) data fatwa, (4) laporan, (5) konsultasi, (6) pengguna (7) data pengurus, (8) data ulama, (9) kegiatan. Pada tahap implementasi terdapat pengujian sistem untuk mеndеtеkѕі kesalahan уаng аdа pada sistem yang dіkеmbаngkа menggunakan metode blасkbоx dengan functional testing. Jenis реnggujіаn іnі dilakukan untuk mengetahui setiap fungsi dari арlіkаѕі bеrjаlаn ѕеѕuаі dengan yang diharapkan, pengujian ini menghasilkan rata-rata 92% dari sembilan modul yang di uji dengan menemukan satu modul yang error atau belum terselesaikan. Kontribusi penelitian ini mampu memberikan informasi yang terpercaya dan valid kepada masyarakat, memberikan kontribusi nyata peran dan fungsi dari MUI khususny di kabupaten Pamekasan.
For concrete planners and salt farmers know the distribution of sulfate in sea water becomes very important as a basis for the manufacture of concrete and as a planning analysis of salt-making. Based on this need to be done mapping the distribution of sulfate concentrations in surface sea water. In addition to the way the analysis in the laboratory, suspected sulfate can be done using an estimation algorithm as a remote sensing technique that results are presented in the form of geographic information systems. With remote sensing techniques will be obtained regional information sulfate at the sea surface since using Landsat 8 satellite recording results.The mapping of sulfate in the straits of Madura Island with Landsat 8 OLI imagery on July 26, 2018, obtained the minimal value was 2078.89 and the maximal value 2429.89.The highest sulfate concentration is in the Ujung-Kamal port area.When using SNI 2847: 2013 / ACI 318M-11 sulfate exposure in the Madura Strait includes a class of S2 with severe severity.
Remote sensing technique to estimate the sea surface salinity has been widely implemented in the seas of various regions. The interface between them was developed using a regression equation like the algorithm in previous research. However, the use of this algorithm for waters in Indonesia, especially in Madura Strait, still requires some adjustment since it is related to the characteristics of different areas in which the algorithm was developed. The development of an applicable local algorithm was performed by finding the best coefficient value in estimating sea surface salinity by considering the value of its lowest NMAE (Normalized Mean Absolute Error). By using salinity and in-situ Rrs(l) (Reflectance of remote sensing) data, we found that the coefficient for the slope was -0.0092, and the intercept was 1.4903. The developed algorithm produces higher accuracy than the existing algorithm, with an NMAE of 0.51%. This NMAE value is smaller than previous research, so this new model can be used to estimate sea surface salinity, particularly in Indonesian sea waters.
The split attribute in the decision tree algorithm, especially C4.5, has an important influence in producing a decision tree performance that has high predictive performance. This study aims to perform an attribute split in the C4.5 algorithm using the value of the termination coefficient (R2/R Square) which is combined with the aim of increasing the performance of the model performance produced by the C4.5 algorithm itself. The data used in this research are public datasets and private datasets. This study combines the C4.5 algorithm developed by Quinlan. The results in this study indicate that the use of the R2 value in the C4.5 algorithm has good performance in terms of accuracy and recall because three of the four datasets used have a higher value than the C4.5 algorithm without R2. Whereas in the aspect of precision, it has quite good performance because only two datasets have a higher value than the performance results of the algorithm without R2.
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