scholarly journals Estimasi Periode Ulang Gempa Bumi Di Wilayah Sulawesi Dengan Menggunakan Distribusi Gumbel

Jurnal MIPA ◽  
2013 ◽  
Vol 2 (2) ◽  
pp. 151
Author(s):  
Yustiani Frastika ◽  
Guntur Pasau ◽  
Jantje D. Prang
Keyword(s):  
Data Processing ◽  
Return Period ◽  
Data Distribution ◽  
Gumbel Distribution ◽  
Distribution Patterns ◽  
North Sulawesi ◽  
South Sulawesi ◽  
Using Data ◽  
Two Stages ◽  
Central Sulawesi

Estimasi periode ulang gempa bumi yang bersifat ekstrim dengan menggunakan Distribusi Gumbel dilakukan untuk menganalisis kejadian gempa bumi yang telah terjadi sebelumnya menggunakan data sejak Januari 1905-Juni 2013. Pengolahan dan analisis data dilakukan dengan dua tahap. Pertama,Pengujian dan pemeriksaan pola sebaran data. Kedua, menentukan periode ulang gempa bumi untuk mengetahui keberulangan gempa ekstrim yang akan terjadi selanjutnya. Hasil analisis yang diperoleh adalah Wilayah Sulawesi sangat rawan terhadap kejadian gempa bumi yang bersifat ekstrim. Tingkat pengulangan kejadian gempa bumi untuk Wilayah  Provinsi Sulawesi Utara dalam kurun waktu 62-100  tahun adalah 7 Mw, Wilayah Provinsi Gorontalodalam kurun waktu 75-100 tahun adalah 6,8 Mw, Wilayah Provinsi Sulawesi Tengah dalam kurun waktu 82-100 tahun adalah 6,9 Mw, Wilayah Provinsi Sulawesi Selatan dalam kurun waktu 319-686 bulan adalah 6,2 Mw, Wilayah Provinsi Sulawesi Barat dalam kurun waktu 113-217 bulan adalah  6,2 Mw dan Wilayah Provinsi Sulawesi Tenggara dalam kurun waktu 45-97 tahun adalah 6,0 Mw.The estimation of extreme earthquake return period by using the Gumbel distribution is made to analyze the occurrence of earthquakes that have occurred previously using data from January 1905 to June 2013. Data processing and analysis has been in two stages. First, testing and examination of data distribution patterns to see whether the data follow the theoretical distribution, in this case the Gumbel distribution. Second, determining the return period of the earthquake to see a recurrence of extreme earthquake is going to happen in the future. Results of the analysis showed that Sulawesi Region is highly vulnerable to earthquakes which are extreme. Return period of earthquake on the region of North Sulawesi province in the period of 62-100 years is 7.0 Mw, the region of Gorontalo Province in the period of 75-100 years is 6.8 Mw, the region of Central Sulawesi Province in the period of 82-100 years is 6.9 Mw, the region of South Sulawesi Province in the period of 319-686 months is 6,.2 Mw, the region of West Sulawesi province in the period of 113-217 months is 6.2 Mw and the region of Southeast Sulawesi province in the period of 45-97 years is 6.0 Mw.

scholarly journals Stabilitas Hasil Jagung Varietas Hibrida Harapan Umur Genjah

2016 ◽  
Vol 35 (2) ◽  
pp. 125
Author(s):  
Slamet Bambang Priyanto ◽  
R. Nenny Iriani ◽  
Andi Takdir M.
Keyword(s):  
Performance Test ◽  
Block Design ◽  
Small Variation ◽  
Maize Yield ◽  
High Yield ◽  
Yield Data ◽  
North Sulawesi ◽  
South Sulawesi ◽  
Early Maturing ◽  
Central Sulawesi

Maize yield represents the interaction between genotype and environment. An excellent genotype should have high mean yield and small variation across common locations.This information could be obtained through yield performance test and stability analysis of yield data obtained from multilocation trials. This research was aimed to find out yield stability of eight early maturing maize promising lines at five sites using the AMMI method. There were total 12 genotypes of maize hybrids used in this research, consisted of eight hybrids (CH-1, CH-2, CH-3, CH-4, CH-5, CH-6, CH-7, and CH-8) and four check varieties (Gumarang, Bima 3, AS-1, and Bisi 2). This research was conducted at five locations ie. Gowa (South Sulawesi), Donggala (Central Sulawesi), Manado (North Sulawesi), Probolinggo (East Java) and Lombok Barat (West Nusa Tenggara) from April to September 2013. The treatments were arranged in a randomized complete block design (RCBD) with 3 replications. Variable measured was grain yield at all trial locations. Analysis of variance was performed for each site data to determine the performance of each genotype at each location. Results showed that genotype CH-2, CH-4 and CH-6 were considered as stable genotypes. Genotype CH-2 and CH-4 have a potensial to be released as new early maturing variety, due to its high yield of 8.71 and 7.52 t/ha averaged over 5 locations. Genotype CH-6 yielded below the mean yield of all genotypes, while genotype CH-8 was adaptive to a specific location, such as in Donggala, with yield of 8.38 t/ha.

scholarly journals PELATIHAN METODE PENELITIAN UNTUK MENINGKATAN KINERJA GURU-GURU SMKN 1 KOTA BATU

2019 ◽  
Vol 2 (3) ◽  
pp. 157
Author(s):  
Farida Rahmawati ◽  
Sri Handayani ◽  
Hari Wahyono ◽  
Imam Mukhlis ◽  
Hadi Sumarsono
Keyword(s):  
Data Processing ◽  
Community Service ◽  
Learning Process ◽  
Research Method ◽  
Teacher Professionalism ◽  
Teacher Skills ◽  
Service Activity ◽  
Conducting Research ◽  
Using Data ◽  
Two Stages

Salah satu upaya meningkatkan profesionalisme guru adalah dengan meningkatkan intensitas guru dalam melalukan penelitian. Tujuan dilakukan kegiatan pengabdian masyarakat ini adalah untuk meningkatkan kemampuan guru-guru ekonomi dalam bidang penelitian yang berkaitan dengan proses pembelajaran di SMKN 1 Kota Batu. Pelaksanaan kegiatan pengabdian dilakukan melalui dua tahapan kegiatan, yakni tahap penyampaian materi prinsip riset dan tahapanya termasuk aplikasi SPSS, Stata, dan Eviews dan tahap pendampingan penyusunan proposal. Kegiatan pengabdian ini diikuti 25 orang guru. Metode yang digunakan adalah ceramah, diskusi, penugasan, pendampingan dan evaluasi. Hasil kegiatan adalah terdapat peningkatan wawasan dan semangat guru dalam melakukan penelitian bagi kepentingan pembelajaran, keterampilan guru dalam penggunaan aplikasi pengolahan data serta terdapat proposal yang telah layak untuk ditindaklanjuti dalam bentuk penelitian.Kata kunci—Profesionalisme Guru, Pendampingan Pelatihan Metode Penelitian, SMKN 1 Kota BatuAbstractOne effort to improve teacher professionalism is to increase the intensity of teachers in conducting research. The purpose of this community service activity is to improve the ability of economic teachers in the field of research related to the learning process at SMK 1 Batu. The implementation of community service activities is carried out through two stages of activities, namely the stage of delivering the material of research principles and the stages including the application of SPSS, Stata, and Eviews and the assistance stage of preparing the proposal. This community service activity was attended by 25 teachers. The methods used are lectures, discussions, assignments, assistance and evaluation. The result of the activity is that there is an increase in teachers' insights and enthusiasm in conducting research for the sake of learning, teacher skills in using data processing applications and there are proposals that have been feasible to be followed up in the form of research.Keywords—Teacher Professionalism, Research Method Training Assistance, SMK 1 Batu

scholarly journals DAMPAK KETERKAITAN EKONOMI PULAU SULAWESI, JAWA TIMUR DAN KALIMANTAN TIMUR TERHADAP EKONOMI WILAYAH

2016 ◽  
Vol 7 (1) ◽  
pp. 97 ◽  
Author(s):  
. Arman ◽  
Setia Hadi ◽  
Noer Azam Achsani ◽  
Akhmad Fauzi
Keyword(s):  
Spillover Effect ◽  
East Kalimantan ◽  
North Sulawesi ◽  
South Sulawesi ◽  
Small Influence ◽  
The Impact ◽  
Central Sulawesi ◽  
Better Than ◽  
Economic Linkages

This study analyzed the effects of the economic linkages between regions Other Sulawesi, South Sulawesi, East Java and East Kalimantan. North Sulawesi, Central Sulawesi, Southeast Sulawesi and Gorontalo aggregated into one unit area of Sulawesi Other. South Sulawesi and West Sulawesi aggregated into a single unit into a region of South Sulawesi. Combined with consideration of South Sulawesi, West Sulawesi because in 2005 both areas are still joined in a single administration. Basic Data 2005 in upgrade to the Year 2011 by using the technique of RAS. The estimated number of sectors as many as 35 sectors. The study analysis showed patterns of economic linkages Other Sulawesi region is relatively lower than other regions. The pattern of economic linkages in South Sulawesi region is relatively better than Other Sulawesi. Role of East Java's economy is very large compared to other regions. The pattern of East Kalimantan's economy is relatively good, but more influenced by oil mining sector. The impact of economic linkages between regions showed Sulawesi region Another economic impact to the region of East Java and East Kalimantan but very little significance to the region of South Sulawesi. Other Sulawesi region provide spillover effect to East Java and East Kalimantan but very little influence to South Sulawesi. The impact of economic linkages East Java provides a very small influence other regions. The impact of economic linkage East Kalimantan region give greater influence to the East Java region than to Other Sulawesi and South Sulawesi region

scholarly journals Efek Investasi Terhadap Pertumbuhan Ekonomi di Pulau Jawa dan Pulau Sulawesi

2020 ◽  
Vol 3 (2) ◽  
pp. 29
Author(s):  
Muh Jamil
Keyword(s):  
Economic Growth ◽  
Structural Equation ◽  
Secondary Data ◽  
Growth Index ◽  
Equation Model ◽  
Central Java ◽  
North Sulawesi ◽  
South Sulawesi ◽  
Central Sulawesi ◽  
Very High

This research aimed to analyze Efect Of Investment to economic growth in Java island and Sulawesi island in 2006-2013. The research used the secondary data, time series and cross section of the eight provinces, namely Jakarta, West Java, Central Java, East Java, North Sulawesi, Central Sulawesi, South Sulawesi and Southeast Sulawesi. The data used comprised the investment index and economic growth index. The data were then Analyzed using Structural Equation Model (SEM) processed using Amos and SPSS econometric software. The results showed that the effect of investment on positive economic growth was significant on Java and positively insignificant on Sulawesi Island. That means that each increase in investment by one percent increases economic growth by 0.479 percent on Java and on Sulawesi Island investment has no effect on economic growth. The investment spread in Java is more stable from year to year and from region to region. Different things on the island of Sulawesi, investment is not stable, sometimes very high and sometimes also very low in other years

scholarly journals ANALISIS KELAYAKAN FINANSIAL INDUSTRIALISASI RUMPUT LAUT ATC Chips DI TUJUH PROPINSI INDONESIA TIMUR

2017 ◽  
Vol 5 (1) ◽  
Author(s):  
Bambang Susanto ◽  
Sukadwilinda Sukadwilinda
Keyword(s):  
Financial Analysis ◽  
Economic Value ◽  
Field Surveys ◽  
Medium Scale ◽  
North Sulawesi ◽  
South Sulawesi ◽  
The World ◽  
Seaweed Production ◽  
Central Sulawesi ◽  
Seaweed Industry

Indonesia has one of the largest wet seaweed producer in the World. It will impact the  economic value if the seaweed processing industry small and medium-scale can be established disentra seaweed production centers such as in Eastern Indonesia. The establishment of the seaweed industry small and medium-scale can be realized through several approaches, both economic and financial approach. The research method using descriptive analytic  with field surveys as reinforcement data analysis . The object of  this study is the financial analysis of the seaweed industry in Indonesia, especially in eastern regions such as South Sulawesi, Central Sulawesi, North Sulawesi, West Nusa Tenggara, East Nusa Tenggara, Maluku and North Maluku. The results of the financial analysis of the overall approach to demonstrate the positive zone seen from the feasibility, both NPV, IRR, and Payback Ratio ratio BC

Design Inflow Intensity and Design Inflow Profiles for Storm Sewers

1984 ◽  
Vol 16 (8-9) ◽  
pp. 207-218 ◽  
Author(s):  
Frans H M van de Ven
Keyword(s):  
Return Period ◽  
Gumbel Distribution ◽  
Extreme Value Distribution ◽  
Data Series ◽  
Design Discharge ◽  
Common Location ◽  
Housing Area ◽  
Parking Lot ◽  
Box Cox Transformation ◽  
Frequency Curves

Twelve year records of rainfall and of sewer inflow data in a housing area and in a parking lot in Lelystad were available. These data series contained 5-minute depths of rainfall and sewer inflow. Depth-duration-frequency curves were calculated from the monthly extremes, using Box-Cox transformation and a Gumbel distribution. The differences between the curves for rainfall and for inflow are explained by inertia and rainfall losses. These differences are the reason to use inflow as a sewer design parameter. Forthe choice of the design discharge (or inflow) intensity the curves are not well suited. Storage-design,discharge-frequency curves proved to be better interprétable. The selected design discharge is 4 or 5 m3/s/km2. For non-steady flow calculations in sewer systems an inflow profile has to be provided. The prof ileshould be peaked. The most common location of the peak lies between 20 and 50% of the event duration. The return period of the profile has to be known. A bivariate extreme value distribution is used to estimate this return period. From these distributions synthetic inflow profiles could be calculated.

Neural networks trained with high-dimensional functions approximation data in high-dimensional space

2021 ◽  
pp. 1-12
Author(s):  
Jian Zheng ◽  
Jianfeng Wang ◽  
Yanping Chen ◽  
Shuping Chen ◽  
Jingjin Chen ◽  
...  
Keyword(s):  
Neural Networks ◽  
Dimensional Space ◽  
Data Distribution ◽  
High Dimensional ◽  
Sufficient Information ◽  
Sufficient Data ◽  
High Dimensional Space ◽  
Positive Effects ◽  
The Neural Networks ◽  
Using Data

Neural networks can approximate data because of owning many compact non-linear layers. In high-dimensional space, due to the curse of dimensionality, data distribution becomes sparse, causing that it is difficulty to provide sufficient information. Hence, the task becomes even harder if neural networks approximate data in high-dimensional space. To address this issue, according to the Lipschitz condition, the two deviations, i.e., the deviation of the neural networks trained using high-dimensional functions, and the deviation of high-dimensional functions approximation data, are derived. This purpose of doing this is to improve the ability of approximation high-dimensional space using neural networks. Experimental results show that the neural networks trained using high-dimensional functions outperforms that of using data in the capability of approximation data in high-dimensional space. We find that the neural networks trained using high-dimensional functions more suitable for high-dimensional space than that of using data, so that there is no need to retain sufficient data for neural networks training. Our findings suggests that in high-dimensional space, by tuning hidden layers of neural networks, this is hard to have substantial positive effects on improving precision of approximation data.

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