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Peningkatan Akurasi Penentuan Base Transceiver Station Menggunakan Kombinasi Metode Weighted Product Dan Analisa Regresi Linier Berganda Wibowo, Gracia Sonia Lestari; Sulistyo, Wiwin
TEKNIK Vol 39, No 1 (2018): (July 2018)
Publisher : Diponegoro University

Kebutuhan akan tersedianya internet semakin meningkat sekarang ini. Untuk menunjang kebutuhan tersebut, Internet Service Provider (ISP) membangun menara Base Transceiver Station (BTS). Permasalahan timbul ketika terdapat banyak pilihan BTS yang dapat digunakan client untuk terhubung ke jaringan ISP. Metode Weighted Product dapat digunakan untuk menentukan pilihan BTS yang tepat dalam waktu singkat. Metode ini dikombinasikan dengan analisa regresi linear berganda untuk menentukan bobot awal bagi masing-masing kriteria penentuan pilihan. Pada pengujiannya, model yang dihasilkan memberikan akurasi mencapai 73% yang dilakukan terhadap 30 titik client pada PT. Grahamedia Informasi.

Development of a Spatial Path-Analysis Method for Spatial Data Analysis Wiwin Sulistyo; Subanar Subanar; Reza Pulungan
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 4: August 2018
Publisher : Institute of Advanced Engineering and Science

Path analysis is a method used to analyze the relationship between independent and dependent variables to identify direct and indirect relationship between them. This method is developed by Sewal Wright and initially only uses correlation analysis results in identifying the variables' relationship. Path analysis method currently is mostly used to deal with variables with non-spatial data type. When analyzing variables that have elements of spatial dependency, path analysis could result in a less precise model. Therefore, it is necessary to build a path analysis model that is able to identify and take into account the effects of spatial dependencies. Spatial autocorrelation and spatial regression methods can be used to develop path analysis method so as to identify the effects of spatial dependencies. This paper proposes a method in the form of path analysis method development to process data that have spatial elements. This study also discusses our effort on establishing a method that could be used to identify and analyze the spatial effect on data in the framework of path analysis; we call this method spatial path analysis.

Computer model of Tsunami vulnerability using machine learning and multispectral satellite imagery Sri Yulianto Joko Prasetyo; Wiwin Sulistyo; Prihanto Ngesti Basuki; Kristoko Dwi Hartomo; Bistok Hasiholan
Bulletin of Electrical Engineering and Informatics Vol 11, No 2: April 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i2.3372

This research aims to develop a tsunami vulnerability assessment model on land use and land cover using information on NDVI, NDWI, MDWI, MSAVI, and NDBI extracted from sentinel 2 A and ASTER satellite images. The optimization model using algorithms LASSO and linear regression. The validation test is MSE, ME, RMSE and MAE which show that the linear regression has a higher accuracy than the LASSO. The NDWI interpolation values are 0.00 - (-0.35) and MNDWI interpolation values are 0.00 - (-0.40) which are interpreted as the presence of water surfaces along a coast. MSAVI are values (-0.20) - (-0.35) which are interpreted as the presence of no vegetation. The NDBI interpolation values are values 0.15-0.20 which are interpreted as the presence of built-up lands with social and economic activities. While the NDVI interpolation values are 0.20-0.30 which are interpreted as the presence of vegetation densities, biomass growths from the photosynthesis process, and moderate to low levels of vegetation health. The digital elevation model ASTER analysis shows that all areas with high socioeconomic activities, low NDVI, high NDWI/MDWI, high MSAVI and high NDBI are in areas with low elevation (less than 10 meters) so they have a high vulnerability to tsunami waves.

Computer model of Tsunami vulnerability using machine learning and multispectral satellite imagery Sri Yulianto Joko Prasetyo; Wiwin Sulistyo; Prihanto Ngesti Basuki; Kristoko Dwi Hartomo; Bistok Hasiholan
Bulletin of Electrical Engineering and Informatics Vol 11, No 2: April 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i2.3372

This research aims to develop a tsunami vulnerability assessment model on land use and land cover using information on NDVI, NDWI, MDWI, MSAVI, and NDBI extracted from sentinel 2 A and ASTER satellite images. The optimization model using algorithms LASSO and linear regression. The validation test is MSE, ME, RMSE and MAE which show that the linear regression has a higher accuracy than the LASSO. The NDWI interpolation values are 0.00 - (-0.35) and MNDWI interpolation values are 0.00 - (-0.40) which are interpreted as the presence of water surfaces along a coast. MSAVI are values (-0.20) - (-0.35) which are interpreted as the presence of no vegetation. The NDBI interpolation values are values 0.15-0.20 which are interpreted as the presence of built-up lands with social and economic activities. While the NDVI interpolation values are 0.20-0.30 which are interpreted as the presence of vegetation densities, biomass growths from the photosynthesis process, and moderate to low levels of vegetation health. The digital elevation model ASTER analysis shows that all areas with high socioeconomic activities, low NDVI, high NDWI/MDWI, high MSAVI and high NDBI are in areas with low elevation (less than 10 meters) so they have a high vulnerability to tsunami waves.

Computer model of Tsunami vulnerability using machine learning and multispectral satellite imagery Sri Yulianto Joko Prasetyo; Wiwin Sulistyo; Prihanto Ngesti Basuki; Kristoko Dwi Hartomo; Bistok Hasiholan
Bulletin of Electrical Engineering and Informatics Vol 11, No 2: April 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i2.3372

This research aims to develop a tsunami vulnerability assessment model on land use and land cover using information on NDVI, NDWI, MDWI, MSAVI, and NDBI extracted from sentinel 2 A and ASTER satellite images. The optimization model using algorithms LASSO and linear regression. The validation test is MSE, ME, RMSE and MAE which show that the linear regression has a higher accuracy than the LASSO. The NDWI interpolation values are 0.00 - (-0.35) and MNDWI interpolation values are 0.00 - (-0.40) which are interpreted as the presence of water surfaces along a coast. MSAVI are values (-0.20) - (-0.35) which are interpreted as the presence of no vegetation. The NDBI interpolation values are values 0.15-0.20 which are interpreted as the presence of built-up lands with social and economic activities. While the NDVI interpolation values are 0.20-0.30 which are interpreted as the presence of vegetation densities, biomass growths from the photosynthesis process, and moderate to low levels of vegetation health. The digital elevation model ASTER analysis shows that all areas with high socioeconomic activities, low NDVI, high NDWI/MDWI, high MSAVI and high NDBI are in areas with low elevation (less than 10 meters) so they have a high vulnerability to tsunami waves.

Computer model of Tsunami vulnerability using machine learning and multispectral satellite imagery Sri Yulianto Joko Prasetyo; Wiwin Sulistyo; Prihanto Ngesti Basuki; Kristoko Dwi Hartomo; Bistok Hasiholan
Bulletin of Electrical Engineering and Informatics Vol 11, No 2: April 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i2.3372

This research aims to develop a tsunami vulnerability assessment model on land use and land cover using information on NDVI, NDWI, MDWI, MSAVI, and NDBI extracted from sentinel 2 A and ASTER satellite images. The optimization model using algorithms LASSO and linear regression. The validation test is MSE, ME, RMSE and MAE which show that the linear regression has a higher accuracy than the LASSO. The NDWI interpolation values are 0.00 - (-0.35) and MNDWI interpolation values are 0.00 - (-0.40) which are interpreted as the presence of water surfaces along a coast. MSAVI are values (-0.20) - (-0.35) which are interpreted as the presence of no vegetation. The NDBI interpolation values are values 0.15-0.20 which are interpreted as the presence of built-up lands with social and economic activities. While the NDVI interpolation values are 0.20-0.30 which are interpreted as the presence of vegetation densities, biomass growths from the photosynthesis process, and moderate to low levels of vegetation health. The digital elevation model ASTER analysis shows that all areas with high socioeconomic activities, low NDVI, high NDWI/MDWI, high MSAVI and high NDBI are in areas with low elevation (less than 10 meters) so they have a high vulnerability to tsunami waves.

Computer model of Tsunami vulnerability using machine learning and multispectral satellite imagery Sri Yulianto Joko Prasetyo; Wiwin Sulistyo; Prihanto Ngesti Basuki; Kristoko Dwi Hartomo; Bistok Hasiholan
Bulletin of Electrical Engineering and Informatics Vol 11, No 2: April 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i2.3372

This research aims to develop a tsunami vulnerability assessment model on land use and land cover using information on NDVI, NDWI, MDWI, MSAVI, and NDBI extracted from sentinel 2 A and ASTER satellite images. The optimization model using algorithms LASSO and linear regression. The validation test is MSE, ME, RMSE and MAE which show that the linear regression has a higher accuracy than the LASSO. The NDWI interpolation values are 0.00 - (-0.35) and MNDWI interpolation values are 0.00 - (-0.40) which are interpreted as the presence of water surfaces along a coast. MSAVI are values (-0.20) - (-0.35) which are interpreted as the presence of no vegetation. The NDBI interpolation values are values 0.15-0.20 which are interpreted as the presence of built-up lands with social and economic activities. While the NDVI interpolation values are 0.20-0.30 which are interpreted as the presence of vegetation densities, biomass growths from the photosynthesis process, and moderate to low levels of vegetation health. The digital elevation model ASTER analysis shows that all areas with high socioeconomic activities, low NDVI, high NDWI/MDWI, high MSAVI and high NDBI are in areas with low elevation (less than 10 meters) so they have a high vulnerability to tsunami waves.

IMPLEMENTASI DAN ANALISIS PENGGUNAAN DD-WRT FIRMWARE UNTUK MEMBANGUN JARINGAN WIRELESS DISTRIBUTION SYSTEM PADA JARINGAN HOTSPOT (STUDI KASUS: FTI UKSW) Wiwin Sulistyo; Teguh Indra Bayu; Achmad Sathibi
Seminar Nasional Aplikasi Teknologi Informasi (SNATI) 2012
Publisher : Jurusan Teknik Informatika, Fakultas Teknologi Industri, Universitas Islam Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar

Wireless Distribution System allows for creating a wireless network without using a wired network backbone. Wireless network using WDS technology associated by create a link on some wireless access point that is called WDS links. The advantage by using WDS technology is to integrate all access points in a single wireless network. Wireless distribution system can handle the complexity of the cable instalation, where physically impossible to pull the cable as a backbone network. Wireless network using WDS technology has the mobility and high reliability. However, not all access points support WDS technology. Access points that use indoor access point that is WRT54GL which does not have WDS feature, because the standard firmware of access points it is still very less features. This problem can be solved by installing DD-WRT firmware into access point. after performing a firmware upgrade, the capability of the access points increase and has full features such as WDS feature.

Analisis QoS Differentiated Service pada Jaringan MPLS Menggunakan Algoritma Threshold Laufi Dian Deodo Saputra; Wiwin Sulistyo
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 4 No 4: Desember 2017
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

AbstrakSeiring perkembangan layanan komunikasi data seperti voice (VoIP) dan video streaming pada jaringan yang memiliki buffer space dan bandwidth terbatas menyebabkan terjadinya beban traffic. Hal tersebut membuat pengguna VoIP dan video streaming membutuhkan suatu jaringan yang dapat memberikan Quality of Service (QoS) dalam memenuhi kebutuhan pengguna. IETF (Internet Engineering Task Force) mempunyai standar mekanisme layanan untuk memenuhi permintaan QoS diantaranya adalah penggabungan teknologi MPLS Diffserv yang mampu mengklasifikasi paket sesuai kebutuhan, tetapi ketika penumpukan terjadi akibat proses QoS ini, paket yang menumpuk tersebut akan di-drop, maka solusi untuk mengantisipasi dropping digunakanlah algortima threshold pada WRED. Penambahan WRED sebagai algoritma threshold pada jaringan MPLS Diffserv memberikan pengaruh yang signifikan, dari hasil parameter QoS untuk layanan VoIP mampu mengurangi packet loss 43,1%, delay 0,005%, memaksimalkan throughput 1,26% dan mengurangi jitter 48,56%, untuk layanan video streaming mengurangi packet loss 15,93% dan memaksimalkan throughput 1,6% dibandingkan sebelum menerapkan algoritma threshold.Kata kunci: QoS, Diffserv, MPLS, threshold, VoIP, video streamingAbstractThe development of data communication services like voice (VoIP) and video streaming, causing traffic load on networks which has limited buffer space and bandwidth. This condition makes VoIP and video streaming users need a network which can provide Quality of Service (QoS) to fill user needs. The IETF (Internet Engineering Task Force) has a standard service mechanism to fill QoS requests such as Incorporation of MPLS Diffserv technology which able to classify the package as needed but when the buildup occurs due to this QoS process, the packet will be dropped, Then the solution to anticipate dropping is used threshold algorithm on WRED. Added WRED as threshold algorithm on the MPLS-Diffserv network give a significant effect, from the results of QoS parameters for VoIP service is able to reduce packet loss 43.1%, delay 0.005%, maximize of throughput 1.26% and reduce jitter 48.56%, for streaming video services reduce packet loss 15.93% and maximize the troughput 1,6% than before applying the threshold algorithm.Keywords: QoS, Diffserv, MPLS, threshold, VoIP, video streaming

PERANCANGAN RELIABILITAS SISTEM TRANSMISI DATA PADA PROTOKOL UDP (USER DATAGRAM PROTOCOL) Wiwin Sulistyo
Seminar Nasional Informatika (SEMNASIF) Vol 1, No 3 (2009): Network And Security
Publisher : Jurusan Teknik Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar

Jaminan pengiriman data melalui jaringan komputer menjadi sesuatu yang sangat penting .Salah satu jaminan yang dibutuhkan olrh user (pemakai) ádalah bahwa data yang dikirimkan ke komputer tujuan sampai dengan baik. Selain itu, terdapat fasilitas yang memberikan keterangan terhadap status pengiriman data kepada user terutama bila pengiriman gagal dilakukan. Sehingga dibutuhkan mekanisme yang berfungsi untuk melakukan kontrol pada saat proses pengiriman data. Protokol UDP merupakan protokol yang bersifat connectionless dan unreliable dalam proses pengiriman data.Dengan menggunakan metode command/request dapat dilakukan perancangan sistem reliabilitas transmisi data pada protokol udp (user datagram protocol).

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