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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 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 Teknologi Informasi dan Ilmu Komputer Jurnal Transformatika Jurnal Edukasi dan Penelitian Informatika (JEPIN) Khazanah Informatika: Jurnal Ilmu Komputer dan Informatika Sinkron : Jurnal dan Penelitian Teknik Informatika INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi JURNAL MEDIA INFORMATIKA BUDIDARMA Faktor Exacta Jurnal Ilmiah Matrik JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Jurnal Sisfokom (Sistem Informasi dan Komputer) MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Indonesian Journal of Computing and Modeling 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 Pendidikan Teknologi Informasi (JUKANTI) Jurnal Indonesia : Manajemen Informatika dan Komunikasi Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) JuTISI (Jurnal Teknik Informatika dan Sistem Informasi) Lontar Komputer: Jurnal Ilmiah Teknologi 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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Implementation Of Clara Clustering Algorithm On Modis Data For Detection Of Forest Fire Potential In Indonesia Petty, Holbed Joshua; Prasetyo, Sri Yulianto Joko
Jurnal Info Sains : Informatika dan Sains Vol. 14 No. 02 (2024): Informatika dan Sains , Edition, June 2024
Publisher : SEAN Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54209/infosains.v14i02.4122

Abstract

Forest fires are a recurring issue every year in various countries, especially in those with extensive forests like Indonesia. An initial step in fire prevention is detecting the potential occurrence of fires, which can be achieved by utilizing satellite data, such as MODIS data. In this study, clustering or grouping of MODIS data in Indonesia for the years 2021 and 2022 was conducted using the CLARA algorithm due to its robustness against outliers and efficiency in handling large datasets. The application of clustering with the CLARA algorithm on both datasets resulted in two clusters, and the evaluation using the Silhouette Coefficient yielded values of 0.89 and 0.88 for both years. The analysis revealed that both clusters in both datasets exhibited similar characteristics. In the data for the years 2021 and 2022, the first cluster displayed a moderate to high potential for fire, while the second cluster indicated a low potential for fire. The results of this study can be used as a reference for authorities to identify the level of forest/land fire potential from observed hotspots in Indonesia, thus enabling early prevention measures such as early extinguishment to prevent further spread of the fire.
Pemanfaatan K-Means Clustering Untuk Pengelompokan Dan Pemetaan Bencana Alam Di Indonesia Otniel, Marcelinus Vito; Prasetyo, Sri Yulianto Joko
Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Vol 5, No 4 (2024): Edisi Oktober
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/kesatria.v5i4.489

Abstract

Indonesia's geographical and geological conditions, which are prone to natural disasters, necessitate the country to mitigate their impact by identifying causes and studying previous disaster events through existing disaster data analysis. This study aims to map cities or regencies in Indonesia based on the clustering results using the K-Means clustering algorithm in the R programming language. Disaster data management, from collection to dissemination, plays a crucial role in disaster management. The research findings reveal that natural disaster data from 2019-2021 divided cities or regencies in Indonesia into five clusters, with Java Island identified as the most vulnerable region to natural disasters compared to other regions. Cluster visualization is presented in the form of a map to facilitate quick reading and understanding of information
Pembuatan Aplikasi Validasi Document Tagihan Pembelian Barang Secara Digital Menggunakan OCR dengan tool tesseract pada System Portal Perusahaan Septio, Pius Aldi; Prasetyo, Sri Yulianto Joko
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 7, No 2 (2023): EDISI SEPTEMBER
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v7i2.674

Abstract

This journal reviews the Making of a Digital Invoices Document Validation Application Using OCR with the tesseract tool on the Company Portal System. This study aims to implement Optical Character Recognition (OCR) using the tesseract tool in the company portal to make it easier to validate invoices. The method used is a prototype with the aim of building a system model where the system is based on user needs where the user does not provide input and output details. The results of the application that was made were tested using Black Box testing with the results that all application functions can be used properly.
Pemanfaatan WebGIS untuk Pemetaan Wilayah Rawan Longsor Kabupaten Boyolali dengan Metode Skoring dan Pembobotan Muhammad Sholikhan; Sri Yulianto Joko Prasetyo; Kristoko Dwi Hartomo
Jurnal Teknik Informatika dan Sistem Informasi Vol 5 No 1 (2019): JuTISI
Publisher : Maranatha University Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28932/jutisi.v5i1.1588

Abstract

WebGIS is an online-based application of Geographic Information System, this application is a combination of web design and web mapping. WebGIS is mainly used for publishing map-based spatial information. Therefore, the author utilized webGIS, in order to mapping area that prone to landslides by using scoring and weighting methods. Parameters that used in this paper referring to the estimation model by Puslittanak in 2004, the parameters were rainfall, rock type, slope, land use, and type of soil maps. The determination of area prone to landslides was carried out by multiplying score by weight for each parameter, subsequently, the result was added up according to the reference of Puslittanak. The result of this study indicates that there are 4 sub-districts with high disaster-prone level, the sub-districts are Ampel, Cepogo, Musuk, and Selo. The final result of the map processed into a webGIS by applying Google maps service and framework bootstrap; the webGIS can be accessed by internet browser.
Klasifikasi Wilayah Potensi Risiko Kerusakan Lahan Akibat Bencana Tsunami Menggunakan Machine Learning Arvira Yuniar Isnaeni; Sri Yulianto Joko Prasetyo
Jurnal Teknik Informatika dan Sistem Informasi Vol 8 No 1 (2022): JuTISI
Publisher : Maranatha University Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28932/jutisi.v8i1.4056

Abstract

Indonesia is an archipelagic country with a long coastline where some areas are prone to tsunami waves which can result in land damage. Tsunamis occur due to earthquakes or volcanic eruptions under the sea that cause movement of the seabed and then create strong waves. The Special Region of Yogyakarta, precisely in Bantul Regency, is one of the areas that have a high risk of a tsunami disaster because the area is located in the expanse of the Indian Ocean which has quite impulsive plate movements. This study aims to find out information about the level of risk of land damage due to the tsunami using vegetation index data from OLI 8 Landsat imagery. Classification or prediction using the Artificial Neural Network (ANN) method. The vegetation index used is NDVI, NDWI, NDBI, SAVI, and MNDWI. The relationship between SAVI and NDVI has a positive correlation coefficient with the highest value of 0.962 where the potential risk of low damage is 0.933 and the potential risk of high damage is 0.856. Classification of potential areas of high risk of damage to tsunami land (High Risk) using the ANN method resulted in 7 villages with high risk. The ANN algorithm is the most accurate method for classification predictions between the Random Forest and SVM methods which get an accuracy of 95.45% and get a Kappa value of 86.08%. Spatial prediction using IDW produces a map of the distribution of the potential risk area for land damage caused by the tsunami.
Analisis sentimen terhadap dampak banjir rob dengan menggunakan metode Support Vector Machine Sarassati, Dwi Sinta; Joko Prasetyo , Sri Yulianto
IT Explore: Jurnal Penerapan Teknologi Informasi dan Komunikasi Vol 4 No 2 (2025): IT-Explore Juni 2025
Publisher : Fakultas Teknologi Informasi, Universitas Kristen Satya Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24246/itexplore.v4i2.2025.pp233-244

Abstract

Tidal flooding is an event of a natural phenomenon when sea water rises to land due to the influence of changes in sea tides, which causes waterlogging around the coastal area. This tidal flood hit the Demak-Semarang area, especially in the Sayung District area, which hampers and impacts community life. The purpose of this analysis is to analyze public sentiment regarding the impact of tidal flooding in Demak Regency using data obtained from social media, and the results of the analysis can be used as an evaluation for the government and related parties to formulate more responsive and effective policies to overcome the problem of tidal flooding. The SVM (Support Vector Machine) method is used to classify sentiment from each data into positive, negative, or neutral categories. The results of the analysis using SVM showed 3580 initial data, after preprocessing, 3147 data were obtained, with sentiment results of 1581 neutral opinions, 1257 negative, and 309 positive. Most opinions are neutral, indicating that people consider tidal flooding as a natural phenomenon and are used to dealing with it. However, significant negative opinions indicate dissatisfaction with the government's handling, while positive opinions are very minimal. SVM showed 84.44 percent accuracy, 86.7 percent precision, and 97.8 percent recall. The study recommends improvements in flood mitigation, assistance for affected communities, and infrastructure improvements.
Analisis Faktor Risiko Stunting pada Balita di Desa Kesetnana Menggunakan Metode Random Forest Kase, Celomitha Putri Welhelmina; Prasetyo, Sri Yulianto Joko
Jurnal Indonesia : Manajemen Informatika dan Komunikasi Vol. 6 No. 3 (2025): September
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Indonesia Banda Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63447/jimik.v6i3.1449

Abstract

Stunting is a growth disorder triggered by chronic malnutrition, impacting the physical and cognitive development of young children. Kesetnana Village in South Central Timor Regency records a high prevalence of stunting. This study aims to classify stunting status using the Random Forest Classifier algorithm and assess its performance. The quantitative analysis was conducted on secondary data from 1,451 toddlers obtained through total sampling from the Health Center and Kesetnana Village Office in 2023. The variables analyzed include birth weight and height, measurement age, as well as Z-scores for Height/Age, Weight/Age, and Weight/Height. Data were processed using Python on the Google Colaboratory platform, with 75% allocated for training and 25% for testing. The findings indicate that birth weight, measurement age, and height are the primary factors in stunting classification. The model achieved 97% accuracy, with high precision and recall values, demonstrating its effectiveness in classifying stunting. This model can be utilized by health professionals and policymakers to identify stunting risk at an early stage and design targeted nutritional interventions in high-prevalence areas.
Deteksi Anomali dalam Penipuan E-commerce Menggunakan Hybrid Autoencoder-Transformer Frameworks Priatna, Wowon; Prasetyo, Sri Yulianto Joko; Wijono, Sutarto; Maria, Evi; Manongga, Danny
JEPIN (Jurnal Edukasi dan Penelitian Informatika) Vol 11, No 1 (2025): Volume 11 No 1
Publisher : Program Studi Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/jp.v11i1.82330

Abstract

Peningkatan e-commerce telah menyebabkan peningkatan aktivitas penipuan, seperti pencurian identitas dan transaksi palsu, yang menimbulkan risiko signifikan terhadap keamanan transaksi online. Penelitian ini mengusulkan kerangka kerja hybrid yang menggabungkan Autoencoder (AE) untuk reduksi dimensi dan representasi laten data, serta Transformer untuk menangkap ketergantungan global dan lokal melalui mekanisme self-attention. Pendekatan ini dirancang untuk mengatasi keterbatasan metode tradisional dalam mendeteksi pola data kompleks dan meningkatkan kinerja deteksi anomali. Evaluasi menggunakan dataset transaksi e-commerce menunjukkan bahwa Hybrid AE-Transformer mencapai akurasi sebesar 95,2%, precision sebesar 89,0%, recall sebesar 74,0%, F1 score sebesar 80,0%, dan AUC sebesar 82,0%. Model ini menunjukkan peningkatan precision sebesar 12,0%, recall sebesar 7,0%, F1 score sebesar 8,0%, dan AUC sebesar 1,0% dibandingkan model terbaik lainnya seperti Ensemble. Validasi statistik melalui Uji Friedman dan Uji T-Test mengonfirmasi bahwa Hybrid AE-Transformer secara signifikan mengungguli model konvensional seperti DNN, LSTM, dan RNN dalam mendeteksi anomali pada transaksi e-commerce.
CLASSIFICATION OF REGIONAL LANGUAGES USING METHODS GRADIENT BOOTS AND RANDOM FOREST Patasik, Eva Sapan; Yulianto, Sri
Jurnal Teknik Informatika (Jutif) Vol. 4 No. 5 (2023): JUTIF Volume 4, Number 5, October 2023
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2023.4.5.1459

Abstract

Indonesia is one of the countries that has the most regional languages ​​in the world, ranking second most. The large number of regional languages ​​that are owned makes it difficult for people between regions to recognize the origins of the regional language, so the author aims to conduct research by identifying a regional language. Identifying a language using data mining, one of the data mining techniques is classification. Classification is a technique used to find the value of data. Classification will build a model from samples of data into groups of the same type. There are two classification methods used in this research, namely gradient boots and random forest, where the two methods will be compared using regional language data from Java, Nias and Toraja. The results of calculating the accuracy values ​​for the two methods used are quite good in classifying languages ​​with results of an accuracy level of 0.8 or 80%, where the results of the gradient boots research have an accuracy value of 0.8850 or 88.5%, while the random forest method has an accuracy value. random forest is lower, namely 0.8794 or 87.94%, so in this study the gradient boots method is the best method.
Developing Fishpond Control System for School Natural Laboratory Automation Sebastian, Danny; Chandra, Dian Widiyanto; Wijono, Sutarto; Prasetyo, Sri Yulianto Joko; Trihandaru, Suryasatriya; Saputra, Laurentius Kuncoro Probo
Jurnal Informatika: Jurnal Pengembangan IT Vol 9, No 1 (2024)
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v9i1.5640

Abstract

Pandemi Covid-19 memaksa kegiatan belajar dilakukan secara daring. Sekolah berusaha melakukan kegiatan secara luring dengan membatasi jumlah siswa atau dengan melaksanakan kegiatan di laboratorium alam. Mengelola laboratorium alam membutuhkan banyak biaya terutama pada kondisi pasca covid-19. Internet of Things adalah teknologi yang memungkinkan kendali jarak jauh dan otomatisasi. Hal ini memungkinkan pengelolaan laboratorium alam dilakukan dari jarak jauh atau secara otomatis. Penelitian ini bertujuan untuk membuat desain dan sistem IoT yang meliputi penentuan modul dasar dan fungsinya, penentuan perangkat sensor dan aktuator yang dibutuhkan. Sistem dibangun menggunakan arsitektur MQTT. Aplikasi Android dibuat untuk mengontrol periferal IoT. Sistem yang telah berhasil dibangun diuji dengan metode blackbox testing. Berdasarkan hasil blackbox testing, aplikasi Android dan periferal IoT dapat berkomunikasi dan berfungsi dengan baik. Penelitian ini masih memiliki keterbatasan yaitu perlu dilakukannya kalibrasi perangkat IoT dan pengujian perangkat keras IoT dalam jangka waktu yang lama.
Co-Authors Adenia Kusuma Dayanthi Adi Setiawan Anna Simatauw Antar Maramba Jawa Antonius Budi Istiadi Antonius Mbay Ndapamury Ardian Ariadi Ardito Laksono Suryoputro Arit Imanuel Meha Arvira Yuniar Isnaeni Aurilia Dinda Permatasari Baali, Gabriel Megfaden Kenisa Bandhu Nusantara Baronio, Nodas Constantine Bintang Lazuardi Bistok Hasiholan Simanjuntak Brian Laurensz Brilliananta Radix Dewana Budhi Kristianto Bunga, Alex Frianco Cahyaningtyas, Christian Charitas Fibriani Christanto, Erwien Christiana Ari Setyaningrum Daniel HF Manongga Danny Manongga 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 Fajar Ayuningtyas 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 Indrastanti Ratna Widiasari Irdha Yunianto Irwan Sembiring Isnaeni, Arvira Yuniar Johan Jimmy Carter Tambotoh Joko Siswanto Josua Josen Alexander Limbong Kase, Celomitha Putri Welhelmina Kristoko Dwi Hartomo Kurnia Latifatul Nazila Laurentius Kuncoro Probo Saputra, Laurentius Kuncoro Probo Lerry Godwin Nanariain Lobo, Murry Albert Agustin Lyonly Evany Tomasoa Maipauw, Musa Marsel 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 Nurul Fadilah, Nurul Oliver Elvino Putra Pratama Otniel, Marcelinus Vito Patasik, Eva Sapan Patrick Simbolon Petty, Holbed Joshua Praditya, Al-Farrel Raka Prayitno, Gunawan Priatna , Wowon Prihanto Ngesti Basuki Priyadi Priyadi Purwoko, Agus Puteri Justia Kardia Momuat Wahani Puteri Justia Kardia Momuat Wahani 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 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 Wasis Pancoro Wicaksono, Muhammad Ryqo Jallu Winarko, Edi Wiwin Sulistyo Yansen Bagas Christianto Yerik Afrianto Singgalen Yesi Arumsari Yohanes Aji Priambodo Yudo Devianto Yuliawan, Kristia