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TREND IN PRECIPITATION OVER SUMATERA UNDER THE WARMING EARTH Iskandar, Iskhaq; Irfan, Muhammad; Syamsuddin, Fadli; Johan, Akmal; Poerwono, Pradanto
International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 8, (2011)
Publisher : National Institute of Aeronautics and Space of Indonesia (LAPAN)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.ijreses.2011.v8.a1737

Abstract

A long-term climate variations in the western Indonesian region (e.g. Sumatera) were evaluated using precipitation data as a proxy. The result showed that there was a long-term climate variation over Sumatera region indicated by a decreasing trend in precipitation (drying trend). Moreover, the long-term precipitation trend has a strong seasonality. Remarkable decreasing trend at a rate of 3.9 cm/year (the largest trend) was observed during the northwest monsoon (DJF) season, while the smallest decreasing trend of 1.5 cm/year occurred during the southeast monsoon (JJA) season. This result suggested that the Sumatera Island experienced a drying trend during the northwest monsoon season, and a dryer condition will be more frequently observed during the southeast monsoon season. The long-term precipitation over the Sumatera Island was linked to coupled air-sea interactions in the Indian and Pacific oceans. The connection between the seasonal climate trends and sea surface temperature (SST) in the Indian and Pacific oceans was demonstrated by the simultaneous correlations between the climate indices (e.g. Dipole Mode Index (DMI) and the Niño3.4 index) and the precipitation over the Sumatera Island. The results suggested that both the Indian Ocean Dipole (IOD) and the El Niño-Southern Oscillation Index (ENSO) have significant correlation with precipitation. However, remarkable correlations were observed during the fall transition of the IOD event. Keywords: Climate variations, Dry season, Precipitation, Sumatera and Kalimantan, Wet season.
INDENTIFYING PATTERNS OF SATTELITE IMAGERY USING AN ARTIFICIAL NEURAL NETWORK Iskandar, Iskhaq; Affandi, Azhar; Setiabudidaya, Dedi; Irfan, Muhammad; Mardiansyah, Wijaya; Syamsuddin, Fadli
International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 9, No 1 (2012)
Publisher : National Institute of Aeronautics and Space of Indonesia (LAPAN)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.ijreses.2012.v9.a1824

Abstract

An artificial neural network analysis based on the self-organizing map (SOM)  was used  to  examine  patterns  of  satellite  imagery.  This  study  used  3  ×  4  SOM  array  to  extract patterns  of  satellite-observed  chlorophyll-a  (chl-a)  along  the  southern  coast  of  the  Lesser Sunda Islands from 1998 to 2006. The analyses indicated two characteristic spatial patterns, namely the northwest and the southeast monsoon patterns. The northwest monsoon pattern was characterized by a low  chl-a concentration. In contrast, the southeast monsoon pattern was  indicated  by  a  high  chl-a  distributed  along  the  southern  coast  of  the  Lesser  Sunda Islands.  Furthermore,  this  study  demonstrated  that  the  seasonal  variations  of  those  two patterns  were  related  to  the  variations  of  winds  and  sea  surface  temperature  (SST).  The winds  were  predominantly  southeasterly  (northwesterly)  during  southeast  (northwest) monsoon, drived  offshore (onshore) Ekman transport and  produced  upwelling (downwelling) along  the  southern  coasts  of  the  Lesser  Sunda  Islands.  Consequently,  upwelling  reduce dSST  and  helped  replenish  the  surface  water  nutrients,  thus  supporting  high  chl-a concentration. Finally, this study demonstrated that the SOM method was very useful for the identifications of patterns in various satellite imageries.
Spatial and Temporal Variability of Sea Surface Height in the Southeastern Tropical Indian Ocean Based on the Satellite Altimeter Data Iskandar, Iskhaq; Mardiansyah, Wijaya; Setiabudidaya, Dedi
Jurnal Matematika dan Sains Vol 19 No 2 (2014)
Publisher : Institut Teknologi Bandung

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Abstract

Sea surface height (SSH) data from merged-satellite observations (e.g. TOPEX/Poseidon, JASON and ERS) were used to evaluate the spatial and temporal variations of sea surface circulations in the southeastern tropical Indian Ocean (SETIO). A Complex Empirical Orthogonal Function (CEOF) was used to extract the dominant mode of variability in the SETIO region. The results show that the first mode accounts for 41.2% of the total variance dominates the variation. The second mode accounts for 18.2% of the total variance, while the third and the fourth modes explain 6.5% and 2.6% of the total variance, respectively. The spectrum analysis indicates that the 35-day variations is a prominent feature in all CEOF modes. Furthermore, semiannual variation at period of about 180-day was observed in the first third modes, while the annual variation of about 300-day was only observed in the first two modes. A relatively strong variation at period of around 500-day was observed in the first, second and fourth modes. It is suggested that the spatial and phase pattern of the first and third modes are related to the propagation of the Kelvin waves generated by wind stress over the equatorial Indian Ocean. On the other hand, the second was likely related to the local upwelling and downwelling generated by the seasonal changes in the alongshore winds. Furthermore, the fourth mode represents the oceanic eddy generated from the downstream straits of the Indonesian Throughflow.Variasi Spasial dan Temporal Tinggi Muka Laut di Wilayah Tropis Samudera India Bagian Tenggara Berdasarkan Data Satelit AltimetriAbstrak Data tinggi permukaan laut hasil observasi dari beberapa satelit (yaitu: TOPEX/Poseidon, JASON dan ERS) digunakan untuk evaluasi variasi spasial dan variasi temporal sirkulasi permukaan laut di wilayah tropis Samudera Hindia bagian tenggara. Analysis dilakukan menggunakan metode Complex Empirical Orthogonal Function (CEOF) untuk mendapatkan mode variasi yang dominan di wilayah ini. Hasil analisis menunjukkan bahwa mode CEOF pertama menjelaskan 41,2% dari variasi total dan merupakan mode yang paling dominan. Mode CEOF kedua mengandung 18,2% dari variasi total, sedangkan mode ketiga dan keempat menjelaskan masing-masing 6,5% dan 2,6% dari variasi total. Analisis spektrum terhadap deret waktu masing-masing mode CEOF menunjukkan bahwa variasi dalam skala 35 hari merupakan variasi yang signifikan untuk setiap mode. Selanjutnya, variasi setengah-tahunan dengan periode osilasi sekitar 180 hari terekam pada tiga mode pertama, sementara variasi tahunan dengan periode osilasi sekitar 300 hari hanya terekam pada mode pertama dan mode kedua. Variasi yang cukup kuat pada periode osilasi sekitar 500 hari terekam pada mode pertama, mode kedua dan mode keempat. Hasil analisis ini juga menunjukkan bahwa pola spasial dan fase gelombang pada mode pertama dan mode ketiga adalah terkait dengan penjalaran gelombang Kelvin yang dibangkitkan oleh stres angin di wilayah ekuator Samudera Hindia. Sementara itu, mode kedua terkait dengan proses upwelling dan downwelling yang dibangkitkan oleh angin muson di sepanjang pantai. Selanjutnya, mode keempat merepresentasikan oceanic eddy yang terbentuk dari selat-selat arus lintas Indonesia (ARLINDO).  Kata kunci: Complex empirical orthogonal function, Analisis Fourier, Samudera Hindia, Tinggi permukaan laut. 
ANTIBACTERIAL ACTIVITY AS INHIBITORS PATHOGEN BACTERIAL ON POND SHRIMP OF EXTRACT MARINE BIOTA COLLECTED FROM MASPARI ISLAND, SOUTH SUMATERA, INDONESIA Rozirwan, .; Iskandar, Iskhaq; Hendri, Muhammad; Apri, Rezi; Azhar, Nuril
Jurnal Ilmu dan Teknologi Kelautan Tropis Vol. 10 No. 3 (2018): Jurnal Ilmu dan Teknologi Kelautan Tropis
Publisher : Department of Marine Science and Technology, Faculty of Fisheries and Marine Science, IPB University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1977.663 KB) | DOI: 10.29244/jitkt.v10i3.22997

Abstract

Marine biota has variety of bioactive compound that is potential to be an antibacterial for shrimp ponds diseases. Some of marine biota has potential as antibacterial i.e. soft coral Sarcophyton sp., Sponge Aaptos sp., seaweeds Sargassum sp. and Halimeda sp. and mangroves Avicennia sp. and Rhizophora sp. species. This study is purposed to find the most potential marine biota as antibacterial. The research method was as follows; sampling, sample identification, extraction and antibacterial activity test. The results is soft coral and sponge extract Sarcophyton sp. has bioactivity against of shrimp bacteria pathogen such as Vibrio spp2. bacteria for around 6.3±0.1 mm, while Aaptos sp. has bioactivity against Vibrio spp1. bacteria for around 7.9+0.1 mm, Vibrio spp2. bacteria for around 7.2± 0.1 to 7.9±0.1 mm, Vibrio spp6. bacteria for around 7.5±0.2 mm, Escherichia coli for around 7.2±0.1 mm and Staphylococcus aureus for around 15.9±0.2 mm. Seaweed extract activity found only of Sargassum sp. which has antibacterial activity against for around 7.1±0.0 mm for Vibrio spp6. and mangrove species activity has Rhizophora sp. extract which has bioactivity against Vibrio spp4. were 7.3±0.1 mm and E. coli bacteria were 6.7±0.1 mm. The most potential marine biota as antibacterial is showed on sponge Aaptos sp.. with an inhibitory zone for around 15.9±0.2 mm (for S. aureus bacteria).
Penentuan Tanggapan Frekuensi Rangkaian Pengatur Nada Baxandall Pasif Berbantuan Komputer Iskandar, Iskhaq
Jurnal Penelitian Sains No 3 (1998)
Publisher : Faculty of Mathtmatics and Natural Sciences

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Abstract

Penentuan tanggapan frekuensi Rangkaian Pengatur Nada Baxandall Pasif bila dilakukan secara manual memerlukan pengkajian matematis yang relatif cukup rumit karena melalui perhitungan yang berulang-ulang sehingga ketelitian perhitungan akan berkurang. Dengan penelitian ini diperoleh datu software yang dapat menampilkan tanggapan frekuensi Rangkaian Pangatur Nada Baxandall Pasif yang berupa tampilan tanggapan amplitudo dan tanggapan fasa. Software yang dihasilkan dari penelitian ini akan membantu pemakai mempermudah memahami hal-hal yang berkaitan dengan masalah ini.
DYNAMICAL LINK OF PEAT FIRES IN SOUTH SUMATRA AND THE CLIMATE MODES IN THE INDO-PACIFIC REGION Putra, Raden; Lestari, Deni Okta; Sutriyono, Edy; Sabaruddin, Sabaruddin; Iskandar, Iskhaq
Indonesian Journal of Geography Vol 51, No 1 (2019): Indonesian Journal of Geography
Publisher : Faculty of Geography, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (6736.806 KB) | DOI: 10.22146/ijg.35667

Abstract

Peat fire is one of the environmental disasters occurring widespread during the dry season in South Sumatra. The region has long been recognized to have extensive peatland, hence it is considered as the vulnerable areas to fire. This study employs spatial analysis to evaluate the likely linked factors causing peat fire in the study area. Two interannual climate modes such as the El Niño ? Southern Oscillation and Indian Ocean Dipole were considered to have affected the area with respect to climate anomaly at the 1995-2016 periods. This phenomenon was followed by the peat fire in many areas. There appears a close linkage between the occurrence of peat fires and climate anomaly. A number of hotspots tend to occur annually during the drought season. A significant number of hotspots took place during the 2006 pIOD and 2015 El Niño events due to a significant decrease in rainfall intensities.
The Rapid Changes of the Landscape Structure of the Meranti-Dangku Tropical Lowland Forest in the South Sumatra Province, Indonesia Zulfikhar, Zulfikhar; Zulkifli, Hilda; Kadir, Sabaruddin; Iskandar, Iskhaq
Sriwijaya Journal of Environment Vol 2, No 1 (2017): Green Environment For Human Welfare
Publisher : Program Pascasarjana Universitas Sriwijaya

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Abstract

The fragmentation of forest vegetation cover can be measured quantitatively, using tools that can characterize the geometry and spatial properties of the patch or patches of mosaic, which depicts the forest loss and the changes in the temporal pattern.   The aims of this paper are to observe the process of the forest fragmentation, to find out the changes of spatial patterns of habitat continuum by applying the spatial dynamics change analysis of the forest fragmentation phases, and to provide the comprehensive approach in determining the rapid change of the forest landscape structure in the spatial transformation process, based on the decision tree models.  We find three phases of the forest fragmentation were identified, namely dissection, dissipation, and attrition.  This study shows that the production forest area and a wildlife conservation area that contiguous or borders, has the same phases in the process of fragmentation of the forest, but both have a difference of the magnitude of forest loss.  We find there are at least five effects of forest fragmentation to the landscape structure, those are  increasing in a number of habitat patches, decreasing in a size of habitat patches, reduction in a habitat amount, increasing in a dispersion and interspersion of patch types, and reduction in a size of spatial connectedness between patches.Keywords: fragmentation, landscape metrics, spatial transformation.
Monthly rainfall prediction based on artificial neural networks with backpropagation and radial basis function Sofian, Ian Mochamad; Affandi, Azhar Kholiq; Iskandar, Iskhaq; Apriani, Yosi
International Journal of Advances in Intelligent Informatics Vol 4, No 2 (2018): July 2018
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/ijain.v4i2.208

Abstract

Two models of Artificial Neural Network (ANN) algorithm have been developed for monthly rainfall prediction, namely the Backpropagation Neural Network (BPNN) and Radial Basis Function Neural Network (RBFNN). A total data of 238 months (1994-2013) was used as the input data, in which 190 data were used as training data and 48 data used as testing data. Rainfall data has been tested using architecture BPNN with various learning rates. In addition, the rainfall data has been tested using the RBFNN architecture with maximum number of neurons K = 200, and various error goals. Statistical analysis has been conducted to calculate R, MSE, MBE, and MAE to verify the result. The study showed that RBFNN architecture with error goal of 0.001 gives the best result with a value of MSE = 0.00072 and R = 0.98 for the learning process, and MSE = 0.00092 and R = 0.86 for the testing process. Thus, the RBFNN can be set as the best model for monthly rainfall prediction.
Aplikasi Bidirectional Assosiatif Memori (BAM) Network pada Pengenalan Model Iskandar, Iskhaq
Jurnal Penelitian Sains No 10 (2001)
Publisher : Faculty of Mathtmatics and Natural Sciences

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Abstract

Penelitian ini bertujuan untuk menyusun suatu simulasi komputer yang dapat dipergunakan untuk menguji kemampuan memori komputer dalam mengenali suatu model tertentu berdasarkan algoritma Bidirectional Assosiatif Memori Neural Network. Model yang digunakan dalam penelitian dalam penelitian ini adalah huruf-huruf abjad yang dinyatakan dalam kode polar –1 dan +1 dalam bentuk matrik [5x3]. Hasil yang didapat dalam penelitian ini menunjukkan bahwa rancangan network yang disusun mampu mengenali model input yang diberikan walaupun model tersebut mengandung noise. Network masih tetap memberikan respon yang cukup baik untuk model input yang mengandung maksimum 4 (empat) buah noise untuk model input yang dinyatakan dalam vektor X, dan 1 (satu) buah noise untuk model input yang dinyatakan dalam vektor Y.
ANOMALOUS OCEANIC CONDITIONS IN THE TROPICAL INDIAN OCEAN DURING 2006 AS REVEALED BY MULTI-SATELLITE SENSORS Iskandar, Iskhaq
Marine Research in Indonesia Vol 34, No 2 (2009)
Publisher : Research Center for Oceanography - Indonesian Institute of Sciences (LIPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (9542.161 KB) | DOI: 10.14203/mri.v34i2.461

Abstract

A positive Indian Ocean Dipole (IOD) took place in the tropical Indian Ocean during 2006. The evolution of this event started in July 2006 and intensified during August 2006. It was indicated by negative sea surface temperature anomalies, lower than normal sea level and supressed convection in the southeastern equatorial Indian Ocean in contrast to western counterpart. Peak negative SST anomalies exceeding 1°C were observed in the eastern basin during September-November coinciding with anomaous easterly winds along the equator and strong southeasterly winds along the coast of Sumatra and Java. The expression of this positive IOD was also seen in other physical variables: negative sea surface height anomalies about 30 cm and negative rainfall anomalies exceeding 8 mm/day were observed in the eastern basin. The events was terminated in December 2006 mainly due to warming of the eastern pole. The magnitude of this event determined by the east-west temperature gradient across the tropical Indian Ocean was the third largest in the last 30 years, after 1997 and 1994 events.