Judul: Pendugaan Curah Hujan Musim Kemarau Menggunakan Data Southern Oscillation Index dan Suhu Permukaan Laut NINO3.4 dengan Metode Support Vector Regression
Abstrak: Various climate disasters in Indonesia are mostly related to the El Nino Southern Oscillation (ENSO) phenomenon. The variability of climate especially rainfall is strongly related to this phenomenon. Southern Oscillation Index (SOI) and sea surface temperature anomaly (SSTA) at Nino3.4 region are two common indicators used to monitor phenomenon of El Nino and La Nina. Furthermore, SOI and NINO SSTA can be the indicator to find the rainfall probability in a particular season, related to the existing condition of climate irregularities. This research was conducted to estimate the rainfall during dry season at Indramayu district. The basic method used in this study was Support Vector Regression (SVR). Predictors used were SOI and NINO3.4 sea surface temperature (SST) data. The experiments were conducted by comparing the model performance and prediction results. The training set was clustered in advance and then SVR model was generated using RBF kernel based on their clustering result. This research obtained an SVR model with correlation coefficient of 0.76 and NRMSE error value of 1.73
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Judul: The Modeling of Downscaling GCM output and SST Anomaly Nino 3.4 Using Support Vector Regression (A Case Study of The monthly Rainfall In Indramayu).
Abstrak: The objective of this research is to develop a downscaling model GCM output and SST anomaly Nino 3.4 as input in the training to predict a rainfall monthly in Indramayu. The techniques of a downscaling is used for a phenomenon indicators of El Nino and Southern Oscillation (ENSO) climate anomaly such as a Global Circulation Model (GCM) and Sea Surface Temperature (SST) nino 3.4 are commonly used as a primary study learn and understand the climate system. This research propose a method for developing a downscaling model GCM output and SST anomaly Nino 3.4 by using Support Vector Regression (SVR). The research showed that GCM output and SST anomaly Nino 3.4 can be approach the average value of monthly rainfall. The best result of prediction is Bondan station which has average correlation that is 0.700.
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Judul: Akupuntur pada Kasus Konstipasi Kucing Persia.
Abstrak: Seekor kucing betina ras persia bernama Lucy telah mengalami konstipasi yang berulang kali sehingga terjadi kronis. Terapi akupuntur digunakan sebagai pengobatan alternatif dalam studi kasus ini dengan tujuan meningkatkan motilitas gastrointestinal. Studi kasus ini bertujuan untuk mengetahui efek akupuntur pada kasus konstipasi di kucing Lucy. Terapi akupuntur dilakukan dengan menggunakan dry neddle pada titik BL-21, BL-25, CV-4, CV-6, CV-12, GV-1, ST-25, dan ST-36. Terapi dilaksanakan selama 15 menit setiap terapi dan dilakukan seminggu 3 kali sampai terjadi perkembangan persembuhan. Berdasarkan hasil pemeriksaan fisik dan pemeriksaan penunjang radiografi, terdapat penumpukan feses yang banyak dari kolon hingga rektum. Kucing dapat defekasi dengan lancar setelah terapi ke-3 dan kondisi kucing yang awalnya buruk semakin membaik.
Keyword: akupuntur, dry needle akupuntur, konstipasi, motilitas gastrointestinal