Telah dilakukan penelitian tentang pencahayaan di gedung olahraga A dan gedung olahraga B di daerah Jakarta Selatan dengan metode pengukuran langsung dan menggunakan simulasi DIALux 4.13 berdasarkan SNI 03-3647-1994, SNI 03-6575-2001, dan Facilities Design Guidance Sports Lighting for Non-Televised Hockey 2018. Penelitian ini bertujuan untuk mendapatkan informasi nilai iluminasi dan melakukan optimalisasi pada gedung olahraga yang digunakan untuk olahraga hoki ruangan. Metode yang digunakan dalam penelitian ini adalah membandingkan hasil nilai pengukuran dengan standard pencahayaan. Pengukuran dilakukan pada malam hari saat gedung olahraga menggunakan lampu sebagai penerangan. Gedung olahraga A diperoleh nilai iluminasi sebesar 25.4 Lux, reflektansi lantai 28.6%, reflektansi dinding 31.6%. Gedung olahraga B diperoleh nilai iluminasi sebesar 46,2 Lux, reflektansi lantai 26.9%, reflektansi dinding 52.1%. Hasil penelitian menunjukkan bahwa tingkat iluminasi di gedung olahraga A maupun B belum memenuhi kondisi ideal sebesar 200 Lux, sehingga diperlukan optimalisasi pada kedua gedung olahraga tersebut. Setelah dilakukan optimalisasi peningkatan angka reflektansi lantai dan dinding, penggantian jenis lampu pada gedung olahraga A diperoleh 202 Lux dan 215 Lux sedangkan pada gedung olahraga B diperoleh 208 Lux dan 217 Lux. Untuk 6 buah lampu jenis fluoresent pada gedung Olahraga A menghasilkan 232 Lux, dan 9 buah lampu jenis fluoresent pada gedung olahraga B menghasilkan 218 Lux.

The development of information from time to time continues to increase` this is supported by the development of more advanced and adequate technology so that information can be accessed quickly and precisely. Based on the 2014-2018 Pasar Baru Kelurahan Vision that has been established and efforts to support the achievement of the Tangerang City mission by optimizing the authority of information technology-based public services through improving the quality of population administration and civil registration services. In fact in the process of storing data from the results of each work unit is still storing files in the ordner so it takes a long time to find the file that will be needed. To overcome the problems that occur, the authors make the design of a new village market administration information system The system will be built using the PHP programming language and Microsoft Access database. This application can simplify and speed up section heads and employees in accessing their documents independently so that administrative services become more effective and efficient and provide convenience in the processing of urban operational data in data storage services.

The generated energy capacity at a solar power plant depends on the availability of solar radiation. In some regions, solar radiation is not always available throughout the day, or even week, depending on the weather and climate in the area. To be able to produce energy optimally throughout the year, the availability of solar radiation needs to be predicted based on the weather and climate behavior data. Many methods have been so far used to predict the availability of solar radiation, either by mathematical approach, statistical probability, or even artificial intelligence-based methods. This paper describes a method of predicting the availability of solar radiation using the Extreme Learning Machine (ELM) method. It is based on the artificial intelligence methods and known to have a good prediction accuracy. To measure the performance of the ELM method, a conventional forecasting method using the Multiple Linear Regression (MLR) method has been used as a comparison. The implementation of both the ELM and MLR methods has been tested using the solar radiation data of the Basel City, Switzerland, which are available to public. Five years of data have been divided into training data and testing data for 6 case-studies considered. Root Mean Square Error (RMSE) and Mean Absolute Error (MAE) have been used as the parameters to measure the prediction results based on the actual data analysis. The results show that the obtained average values of RMSE and MAE by using the ELM method respectively are 122.45 W/m² and 84.04 W/m², while using the MLR method they are 141.18 W/m² and 104.87 W/m² respectively. It means that the ELM method proved to perform better than the MLR method, giving 15.29% better value of RMSE parameter and 24.79% better value of MAE parameter.

Telah dibuat sistem monitoring meter untuk aplikasi meter orifice dengan menggunakan perangkat lunak Plant Information ProcessBook. Meter orifice bekerja dengan mengukur beda tekanan antara tekanan tinggi dan tekanan rendah yang di akibatkan penyempitan aliran di orifice plate dan kemudian di konversi menjadi laju alir. Laju alir dan parameter proses ditampilkan di sistem monitoring meter dengan menggunakan perangkat lunak Plant Information ProcessBook. Performa meter orifice di ukur dengan menganalisa ketidakpastian sistem meter dan di kalibrasi dengan druck pressure calibrator.

No abstract