Kurniawan, Isma Dwi
Department of Biology, Faculty of Mathematics and Sciences, Semarang State University . Ro

Published : 2 Documents

Found 2 Documents

The Impact of Lampenflora on Cave-dwelling Arthropods in Gunungsewu Karst, Java, Indonesia Kurniawan, Isma Dwi; Rahmadi, Cahyo; Ardi, Tiara Esti; Nasrullah, Ridwan; Willyanto, Muhammad Iqbal; Setiabudi, Andy
Biosaintifika: Journal of Biology & Biology Education Vol 10, No 2 (2018): August 2018
Publisher : Department of Biology, Faculty of Mathematics and Sciences, Semarang State University . Ro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/biosaintifika.v10i2.13991


The development of wild caves into show caves is required an installation of electric lights along the cave passages for illumination and decoration purposes for tourist attraction. The presence of artificial lights can stimulate the growth of photosynthetic organisms such as lampenflora and alter the typical cave ecosystem. The study was aimed to detect the effect of lampenflora on cave-dwelling arthropods community. Four caves were sampled during the study, 2 caves are show caves with the existence of lampenflora and 2 others are wild caves without lampenflora. Arthropods sampling were conducted by hand collecting, pitfall trap, bait trap and berlese extractor. Lampenflora comprises of algae (Phycophyta), moss (Bryophyta) and fern (Pteridophyta) grow mostly around white light lamps. Richness, diversity, and evenness indices of Arthropods are higher in caves with the existence of lampenflora compared to caves without lampeflora. This study clearly shows that the presence of lampenflora can increase Arthropods diversity and suppress dominancy of common Arthropods species in caves, also increasing the relative abundance of predators. This condition will shift the ecosystem equilibrium and lead to cave ecosystem destruction. The results of this study should be a scientific consideration for show cave development and management. Lampenfloras have to be removed from all caves and preventive efforts should be taken to minimize their growth.
Neurocomputing fundamental climate analysis Caraka, Rezzy Eko; Bakar, Sakhinah Abu; Tahmid, Muhammad; Yasin, Hasbi; Kurniawan, Isma Dwi
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 17, No 4: August 2019
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (884.937 KB) | DOI: 10.12928/telkomnika.v17i4.11788


Rainfall is a natural phenomenon that needs to be studied more deeply and interesting to be analyzed. It involves numbers of human activities such as aviation, agriculture, fisheries, and also disaster risk reduction. Moreover, the characteristics of rainfall data follows seasonality, fluctuation, not normally distributed and it makes traditional time series challenging to use. Therefore, neurocomputing model can be used as an alternative to extraction information from rainfall data and give high performance also accuracy. In this paper, we give short preview about SST Anomalies in Manado, Northern Sulawesi and at the same time comparing the performance of rainfall forecasting by using three types of neurocomputing methods such as Generalized Regression Neural Network (GRNN), Feed forward Neural Network (FFNN), and Localized Multi Kernel Support Vector Regression (LMKSVR). In a nutshell, all of neurocomputing methods give highly accurate forecasting as well as reach low MAPE FFNN 1.65%, GRNN 2.65% and LMKSVR 0.28%, respectively.