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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Jurnal Ilmu dan Teknologi Kelautan Tropis IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Jurnal Informatika Lontar Komputer: Jurnal Ilmiah Teknologi Informasi Jurnal Simetris Elkom: Jurnal Elektronika dan Komputer Bulletin of Electrical Engineering and Informatics Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) JTSL (Jurnal Tanah dan Sumberdaya Lahan) Jurnal Transformatika Jurnal Edukasi dan Penelitian Informatika (JEPIN) Khazanah Informatika: Jurnal Ilmu Komputer dan Informatika Sinkron : Jurnal dan Penelitian Teknik Informatika JURNAL MEDIA INFORMATIKA BUDIDARMA Faktor Exacta Jurnal Ilmiah Matrik JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Indonesian Journal of Computing and Modeling J-SAKTI (Jurnal Sains Komputer dan Informatika) JURIKOM (Jurnal Riset Komputer) JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Building of Informatics, Technology and Science Journal Sensi: Strategic of Education in Information System JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) TIN: TERAPAN INFORMATIKA NUSANTARA Aiti: Jurnal Teknologi Informasi Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Jurnal Teknik Informatika (JUTIF) Journal of Information Technology (JIfoTech) J-SAKTI (Jurnal Sains Komputer dan Informatika) Jurnal Info Sains : Informatika dan Sains Jurnal Nasional Teknik Elektro dan Teknologi Informasi IT-Explore: Jurnal Penerapan Teknologi Informasi dan Komunikasi Jurnal Informatika: Jurnal Pengembangan IT Jurnal Indonesia : Manajemen Informatika dan Komunikasi Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) JuTISI (Jurnal Teknik Informatika dan Sistem Informasi)
Sri Yulianto Joko Prasetyo
Universitas Kristen Satya Wacana
Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Social Sciences Veterinary Other

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SISTEM PERINGATAN DINI SERANGAN HAMA PENYAKIT PADI DI JAWA TENGAH MENGGUNAKAN GI DAN GI* STATISTIC Prasetyo, Sri Yulianto Joko
JURNAL ILMIAH MATRIK MATRIK Vol.17 No.3 Desember 2015
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (774.298 KB)

Abstract

Abstract: The research aims to develop the early warnung system application of the endemic areas of pest using Gi and Gi * statistic methods. The research focused on developing early warning system based Geograpical Information System (GIS) technology. The research was conducted through two stages: (1) data preprocessing based on the local characteristics of the studied areas, processing and modeling the data including the digitalization process of cumulative pest area attack using database and (2) architectural design and develop of GIS application. Developing of GIS application using PHP Programming and MapServer. The result of the research showed it can be used to provide information of endemic areas in the future based on the indicator of attack pest. The result of the research could be developed as decission support tool to determine of the endemic pest areas which has been done by observation center for Pest Plant Diseases Laboratory Observations Region V Surakarta, Central Java, Indonesia, Ministry of Agriculture, Republic of Indonesia for many times. Keywords: Getis Ord, GIS, Pest Outbreak, Early Waning System
ANALISIS DATA STATUS DI FACEBOOK UNTUK MEREKOMENDASIKAN PRODUK MAKANAN RINGAN MENGGUNAKAN TF-IDF DAN DOCUMENT WEIGHTING Abidin, Rohmad; Sediyono, Eko; Prasetyo, Sri Yulianto joko
Simetris: Jurnal Teknik Mesin, Elektro dan Ilmu Komputer Vol 9, No 2 (2018): JURNAL SIMETRIS VOLUME 9 NO 2 TAHUN 2018
Publisher : Universitas Muria Kudus

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (285.42 KB) | DOI: 10.24176/simet.v9i2.2518

Abstract

Penelitian ini bertujuan untuk mengembangkan menganalisa tingkat analisis status pada akun media sosial untuk mendukung kegiatan promosi Usaha Mikro Kecil khususnya produk makanan ringan. Penelitian menggunakan teknik yang terdapat pada text mining, analisis Term Frequency- Invers Document Frequency dan Document Weighting untuk merekomendasikan produk. Objek penelitian akun media sosial facebook dengan sample random yang tergabung dalam grup Warga Demak serta produk hasil UMK yang terdaftar pada Dinas Perdagangan dan Koperasi Kabupaten Demak. Hasil akhir penelitian ini adalah prototype sistem analisis status media sosial untuk mengklasifikasikan pelanggan produk UMK yang sesuai dengan hasil analisa status facebook. Dari hasil analisa didapatkan rata-rata tingkat akurasi prediksi sebesar 73.27% untuk keberhasilan merekomendasikan produk. Hasil penelitian ini menunjukkan bahwa analisis TF-IDF dan Document Weighting dapat dimanfaatkan untuk pengembangan sistem baru guna mendukung kegiatan promosi pengelola kelompok UMK agar lebih tepat sasaran.
ANALISIS PEMANFAATAN KAWASAN WILAYAH PESISIR MENGGUNAKAN LOCAL INDICATORS OF SPATIAL ASSOCIATION (LISA) (STUDI KASUS : KABUPATEN KULON PROGO) Lina, Tirsa Ninia; Sediyono, Eko; Prasetyo, Sri Yulianto Joko
Simetris: Jurnal Teknik Mesin, Elektro dan Ilmu Komputer Vol 8, No 2 (2017): JURNAL SIMETRIS VOLUME 8 NO 2 TAHUN 2017
Publisher : Universitas Muria Kudus

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (334.247 KB) | DOI: 10.24176/simet.v8i2.1608

Abstract

Kawasan pesisir Kabupaten Kulon Progo terdiri dari empat kecamatan, yaitu kecamatan Galur, Panjatan, Wates, dan Temon. Kawasan pesisir ini rentan terhadap dampak negatif aktifitas manusia seperti penggunaan tanah atau pemanfaatannya yang sering tumpang tindih. Tujuan penelitian ini untuk menganalisis autokorelasi spasial terhadap pemanfaatan kawasan wilayah pesisir di Kabupaten Kulon Progo. Penelitian ini menggunakan salah satu pengujian autokorelasi spasial yaitu Local Indicators of Spatial Association (LISA) dengan indikator Local Moran's I, yang menghasilkan signifikansi secara statistik tinggi (hotspots), signifikansi secara statistik rendah (coldspots), dan pencilan (outlier). Hasil dari penelitian ini menunjukkan bahwa kecamatan yang termasuk kategori hotspots (H-H) diantaranya Temon dengan lima hotspots pada kawasan permukiman perdesaan, pertanian lahan kering, industri, sempadan pantai, dan suaka alam, Panjatan dengan tiga hotspots pada kawasan permukiman perkotaan, perdagangan, dan sempadan sungai, Galur dengan dua hotspots pada kawasan pertanian lahan basah dan perdagangan, dan Wates dengan satu hotspots pada kawasan industri.Kata kunci: kawasan pesisir, Kabupaten Kulon Progo, Local Indicators of Spatial Association, LISA, Local Moran's I.
PEMETAAN DINAMIKA WILAYAH ENDEMIK PENYAKIT DEMAM BERDARAH DENGUE KOTA SALATIGA MENGGUNAKAN PENDEKATAN MULTIVARIAT LOCAL INDICATOR SPATIAL ASSOCIATION Yulianto J.P., Sri; Hartati, Sri
Jurnal Informatika Vol 11, No 1 (2012): MAY 2012
Publisher : Institute of Research and Community Outreach - Petra Christian University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (250.948 KB) | DOI: 10.9744/informatika.11.1.63-69

Abstract

The objective of this study is to map the change dynamic of dengue endemic area in Salatiga, Central Java in 2001-2008. This study is carried out in three stages. The first one is the descriptive survey to find the secondary sociodemographic and epidemiologic data. The second stage is data analysis using spatial association, in this case is Global Moran’s dan Local Moran’s (LISA). The last stage is the interpretation of the result of analysis in form of Moran Scatterplot and LISA map. The result of the study shows that spatial pattern based on the dynamic distribution of Dengue occurrence could be identified using Global Moran’s method. From 2001 to 2008, it could be found that there are hotspots and outlier. The area with high frequency of hotspot is Sidorejo Lor, Mangunsari and Kutowinangun. Using Local Moran’s I method, the spatial pattern of the distribution of dengue could be visualized in form of LISA (Local Indicator Spatial Association) map. The map is categorized into HH, HL, LH dan LL. The ABJ value is not significant with the dengue happenings in each village. The area with high ABJ is not followed by the high value of dengue happening. Based on the choropleth, it could be described that the dengue happening is caused by the dense of the population. The result of this study could be used as a tool to control and identify the cause of dengue.
DROUGHT ANALYSIS AND FORECAST USING LANDSAT-8 SATTELITE IMAGERY, STANDARDIZED PRECIPITATION INDEX AND TIME SERIES Maipauw, Musa Marsel; Sediyono, Eko; Prasetyo, Sri Yulianto Joko
Khazanah Informatika Vol. 6 No. 1 April 2020
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/khif.v6i1.8863

Abstract

A drought is a phenomenon of shortages in water supply in an area for a long time. Drought usually occurs in areas that have little rain for a long time or in areas with low precipitation. Drought have negative impacts on many sectors such as agriculture, plantations, water resources and environment. This paper describes the results of a research that aims to analyze data to get the level of drought during four yearly periods, and predict the likelihood of drought to occur in the future. The level of drought was analyzed using the Inverse Distance Weighted (IDW) method and the Standardized Precipitation Index (SPI). Least square time series was utilized to forecast the level of drought in the near future. Data consists of drought data collected from electronic news, rainfall data from BMKG, and anual Landsat-8 satellite imagery. All data are for Western Southeast Mallucas in the range of 2015-2018. Analysis using IDW and SPI methods produce similar interpretation for year 2015, i.e. mild dryness, and fro year 2018, i.e. no drought. However, the two methods show discrepancy in analysis of data for 2016 and 2017. The use of least square time series to forecast drought in 2019 gives SPI value of 0.03 which intepretes as normal weather (no drought) that is consistent with the result of field observation.
Game Theory Dalam Penentuan Strategi Pemasaran Optimal Dalam (Studi Kasus Persaingan E-Commerce Shopee dan TokoPedia) Praditya, Al-Farrel Raka; Prasetyo, Sri Yulianto Joko
TIN: Terapan Informatika Nusantara Vol 2 No 2 (2021): Juli 2021
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

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

Abstract

The development of information technology in the field of online business continues to increase. This causes the internet to become a coincidence that cannot be separated from society. Developments that cause people to use it for business activities. Businesses in the digital industry continue to compete to meet people's needs instantly. Meeting the needs of e-commerce businesses to customers with many users is an important thing for companies to pay attention to the quality of their services. This is what creates competition between Shopee and Tokopedia e-commerce. So, this research was made using the Game Theory method and assisted using IBM's SPSS to determine customer satisfaction in terms of interface design, completeness of goods and prices offered by both Shopee and Tokopedia e-commerce. There are several factors that support the rapid growth of the e-commerce sector in Indonesia. First, the increasing number of smartphones and the internet. Second, the size of the population. Third, Indonesia has a lot of young people who are technology literate, which means they are quick to adapt to new things, in this case, new technology.
Satellite imagery and machine learning for aridity disaster classification using vegetation indices Sri Yulianto Joko Prasetyo; Kristoko Dwi Hartomo; Mila Chrismawati Paseleng; Dian Widiyanto Chandra; Edi Winarko
Bulletin of Electrical Engineering and Informatics Vol 9, No 3: June 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1593.071 KB) | DOI: 10.11591/eei.v9i3.1916

Abstract

Central Java Province is one of provinces in Indonesia that has a high aridity risk index. Aridity disaster risk monitoring and detection can be done more accurately in larger areas and with lower costs if the vegetation index is extracted from the remote sensing imagery. This study aims to provide accurate aridity risk index information using spectral vegetation index data obtained from LANDSAT 8 OLI satellite. The classification of drought risk areas was carried out using k-nn with the Spatial Autocorrelation method. The spectral vegetation indices used in the study are NDVI, SAVI, VHI, TCI and VCI. The results show a positive correlation and trend between the spectral vegetation index influenced by seasonal dynamics and the characteristics of the High R.A. and Middle R.A. drought risk areas. The highest correlation coefficient is SAVI with a High R.A. amounted to 0.967 and Middle R.A. amounted to 0.951. The results of the Kappa accuracy test comparison show that SVM and k-nn have the same accuracy of 88.30. The result of spatial prediction using the IDW method shows that spectral vegetation index data that initially as an outlier, using the k-nn method, the spectral vegetation index data can be identified as data in the aridity classification. The spatial connectivity test among sub-districts that experience drought was done using Moran’s I Analysis.
Computer model for tsunami vulnerability using sentinel 2A and SRTM images optimized by machine learning Sri Yulianto Joko Prasetyo; Bistok Hasiholan Simanjuntak; Kristoko Dwi Hartomo; Wiwin Sulistyo
Bulletin of Electrical Engineering and Informatics Vol 10, No 5: October 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v10i5.3100

Abstract

This study aims to develop a software framework for modeling of tsunami vulnerability using DEM and Sentinel 2 images. The stages of study, are: 1) extraction Sentinel 2 images using algorithms NDVI, NDBI, NDWI, MSAVI, and MNDWI; 2) prediction vegetation indices using machine learning algorithms. 3) accuracy testing using the MSE, ME, RMSE, MAE, MPE, and MAPE; 4) spatial prediction using Kriging function and 5) modeling tsunami vulnerability indicators. The results show that in 2021 the area was dominated by vegetation density between (-0.1-0.3) with moderate to high vulnerability and risk of land use tsunami as a result of the decreasing of vegetation. The prediction results for 2021 show a low canopy density of vegetation and a high degree of land surface slope. Based on the prediction results in 2021, the study area mostly shows the existence of built-up lands with a high tsunami vulnerability risk (more than 0.1). Vegetation population had decreased to 67% from the original areas in 2017 with an area of 135 km2. Forest vegetation had decreased by 45% from 116 km2 in 2017. Land use for fisheries had increased to the area of 86 km2 from 2017 with an area of 24 km2.
ANALISIS PEMANFAATAN KAWASAN WILAYAH PESISIR MENGGUNAKAN LOCAL INDICATORS OF SPATIAL ASSOCIATION (LISA) (STUDI KASUS : KABUPATEN KULON PROGO) Tirsa Ninia Lina; Eko Sediyono; Sri Yulianto Joko Prasetyo
Simetris: Jurnal Teknik Mesin, Elektro dan Ilmu Komputer Vol 8, No 2 (2017): JURNAL SIMETRIS VOLUME 8 NO 2 TAHUN 2017
Publisher : Universitas Muria Kudus

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (334.247 KB) | DOI: 10.24176/simet.v8i2.1608

Abstract

Kawasan pesisir Kabupaten Kulon Progo terdiri dari empat kecamatan, yaitu kecamatan Galur, Panjatan, Wates, dan Temon. Kawasan pesisir ini rentan terhadap dampak negatif aktifitas manusia seperti penggunaan tanah atau pemanfaatannya yang sering tumpang tindih. Tujuan penelitian ini untuk menganalisis autokorelasi spasial terhadap pemanfaatan kawasan wilayah pesisir di Kabupaten Kulon Progo. Penelitian ini menggunakan salah satu pengujian autokorelasi spasial yaitu Local Indicators of Spatial Association (LISA) dengan indikator Local Moran's I, yang menghasilkan signifikansi secara statistik tinggi (hotspots), signifikansi secara statistik rendah (coldspots), dan pencilan (outlier). Hasil dari penelitian ini menunjukkan bahwa kecamatan yang termasuk kategori hotspots (H-H) diantaranya Temon dengan lima hotspots pada kawasan permukiman perdesaan, pertanian lahan kering, industri, sempadan pantai, dan suaka alam, Panjatan dengan tiga hotspots pada kawasan permukiman perkotaan, perdagangan, dan sempadan sungai, Galur dengan dua hotspots pada kawasan pertanian lahan basah dan perdagangan, dan Wates dengan satu hotspots pada kawasan industri.Kata kunci: kawasan pesisir, Kabupaten Kulon Progo, Local Indicators of Spatial Association, LISA, Local Moran's I.
Analisis Daerah Rawan Longsor Di Kabupaten Brebes Memanfaatkan Citra Landsat 8 Dengan Metode Inverse Distance Weighted (IDW) Maya Sari; Christian Cahyaningtyas; Sri Yulianto Joko Prasetyo
Journal of Information Technology Vol 1 No 2 (2021): Journal of Information Technology
Publisher : Institut Shanti Bhuana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46229/jifotech.v1i2.276

Abstract

Brebes adalah salah satu Kabupaten di Provinsi Jawa Tengah. Sebagian besar wilayahnya berupa dataran rendah yang diapit sungai pemali dan sungai serayu. Maka dari itu, Kabupaten Brebes merupakan salah satu daerah yang rawan terjadi tanah longsor maupun bencana lainnya. Maka dari itu akan dilakukan penelitian untuk menganalisis daerah rawan longsor di Kabupaten Brebes dengan citra landsat 8 yang dipadukan dengan metode Inverse Distance Weighted (IDW) sehingga dapat diketahui daerah mana saja yang berpotensi longsor. Parameter yang digunakan untuk melakukan analisis adalah jenis tanah, curah hujan, dan kemiringan lereng. Ketiga parameter tersebut akan dilakukan overlay sehingga mendapatkan peta daerah rawan tanah longsor. Hasil penelitian ini diharapkan dapat digunakan oleh pemerintah setempat untuk melakukan upaya preventif sehingga dapat mengurangi kerugian dari masyarakat setempat.
Co-Authors Adenia Kusuma Dayanthi Anna Simatauw Antar Maramba Jawa Antonius Mbay Ndapamury Ardian Ariadi Ardito Laksono Suryoputro Arit Imanuel Meha Arvira Yuniar Isnaeni Ayuningtyas, Fajar Baali, Gabriel Megfaden Kenisa Baronio, Nodas Constantine Bintang Lazuardi Bistok Hasiholan Simanjuntak Brian Laurensz Brilliananta Radix Dewana Bunga, Alex Frianco Cahyaningtyas, Christian Charitas Fibriani Christanto, Erwien Christiana Ari Setyaningrum Daniel HF Manongga Danny Manongga Devianto, Yudo Dian Widiyanto Chandra Dwi Hayati Edwin Zusrony Eko Sediyono Elvira Umar Engles Marabangkit Yoesmarlan Erik Wahyu Abdi Nugroho Evan Bagus Kristianto Evan Geraldy Suryoto Evi Maria Evi Maria Fabian Valerian Feibe Lawalata Florentina Tatrin Kurniati Gallen cakra adhi wibowo Gideon Bartolomeus Kaligis Gilbert Yesaya Likumahua Gudiato, Candra Haikal Nur Rachmanrachim Achaqie Haikal Nur Rachmanrachim Achaqie Hindriyanto Dwi Purnomo Ida Ayu Putu Sri Widnyani Indra Yunanto Irdha Yunianto Irwan Sembiring Isnaeni, Arvira Yuniar Joko Siswanto Josua Josen Alexander Limbong Kase, Celomitha Putri Welhelmina Kristoko Dwi Hartomo Kurnia Latifatul Nazila Laurentius Kuncoro Probo Saputra, Laurentius Kuncoro Probo Lobo, Murry Albert Agustin Lyonly Evany Tomasoa Maipauw, Musa Marsel Manongga, Daniel HF Maya Sari Merryana Lestari Mikhael Dio Eclesi Mila Chrismawati Paseleng Mira Mira Muhamad Yusup Muhammad Rizky Pribadi Muhammad Sholikhan Nadia Renatha Yuwono Nadya Inarossy Novem Berlian Uly Nugroho, Ignatius Dion Nusantara, Bandhu Otniel, Marcelinus Vito Patasik, Eva Sapan Patrick Simbolon Permatasari, Aurilia Dinda Petty, Holbed Joshua Praditya, Al-Farrel Raka Prayitno, Gunawan Priatna , Wowon Priyadi Priyadi Purwoko, Agus Qurotul Aini Ratu, Herman Huki Ravensca Matatula Raymond Elias Mauboy Riko Yudistira Rina Pratiwi Pudja I. A Rohmad Abidin, Rohmad Rony, Zahara Tussoleha Roy Rudolf Huizen Santoso, Nuke Puji Lestari Sarassati, Dwi Sinta Sebastian, Danny Septian Silvianugroho Septio, Pius Aldi Solly Aryza Sri Hartati Stanny Dewanty Rehatta Stevanus Dwi Istiavan Mau Supit, Christanti Ekkelsia Suryasatria Trihadaru Suryasatriya Trihandaru Susatyo, Yeremia Alfa Sutarto Wijono Theopillus J. H. Wellem Tirsa Ninia Lina Triloka Mahesti Triloka Mahesti Untung Rahardja Untung Rahardja Valentino Kevin Sitanayah Que Vinsensius Aprila Kore Dima Wahani, Puteri Justia Kardia Momuat Wasis Pancoro Wicaksono, Muhammad Ryqo Jallu Winarko, Edi Wiwin Sulistyo Yansen Bagas Christianto Yerik Afrianto Singgalen Yesi Arumsari Yohanes Aji Priambodo Yuliawan, Kristia