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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 INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi 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) Lontar Komputer: Jurnal Ilmiah Teknologi Informasi
Sri Yulianto Joko Prasetyo
Universitas Kristen Satya Wacana
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Evaluasi Kinerja Pembelajaran Learning Management System Menggunakan COBIT 4.1 pada Universitas STEKOM Semarang Haikal Nur Rachmanrachim Achaqie; Eko Sediyono; Sri Yulianto Joko Prasetyo
Elkom : Jurnal Elektronika dan Komputer Vol 15 No 1 (2022): Juli : Jurnal Elektronika dan Komputer
Publisher : STEKOM PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/elkom.v15i1.788

Abstract

Universitas Ilmu Komputer dan Teknologi (STEKOM University) telah menggunakan Learning Management System (LMS) sejak tahun 2018, namun hingga saat ini pengukuran kinerja Learning Management System (LMS) belum dilakukan. Penelitian ini bertujuan untuk mengukur tingkat kematangan Learning Management System (LMS) dengan menggunakan Framework COBIT 4.1 pada domain Delivery and Support (DS) dan Monitoring and Evaluation (ME). Nilai tingkat kematangan pada kondisi eksisting berada pada level rata-rata 2, sedangkan kondisi yang ingin dicapai berada pada level rata-rata 3. Untuk mencapai level yang diharapkan, saran perbaikan mengacu pada Kerangka COBIT 4.1 perlu yang akan diberikan antara lain: pembuatan SOP (Standar Operasional dan Prosedur) LMS, kelengkapan isi LMS, tertib administrasi dokumentasi arsip penting, realisasi pelatihan LMS bagi dosen, alokasi biaya pemeliharaan dan pengujian sistem, penerapan reward and punishment, pembuatan dan penggunaan framework dan E governance - Pembelajaran dan semuanya dilakukan secara rutin minimal setiap 6 bulan sekali.
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.
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 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.
IMPLEMENTASI FRAMEWORK LARAVEL 7.1 PADA SISTEM INFORMASI PENJUALAN CONVENIENCE STORE EMMI SHOP Nusantara, Bandhu; Prasetyo, Sri Yulianto Joko
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 10, No 1 (2025)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v10i1.5584

Abstract

Studi kasus ini meneliti Emmi Shop untuk menerapkan framework Laravel pada sistem informasi penjualan berbasis web menggunakan metode waterfall. Dalam perkembangan teknologi, sistem informasi penjualan mampu untuk meningkatkan efisiensi dan kenyamanan bagi penjual maupun pelanggan. Analisis kebutuhan, desain, pengkodean, dan pengujian adalah metode yang digunakan dalam penelitian ini. Analisis kebutuhan mengumpulkan persyaratan pengguna dan spesifikasi perangkat lunak yang diperlukan. Setelah tahap desain, struktur data, arsitektur perangkat lunak, dan antarmuka pengguna dibuat. Selanjutnya, tahap pengkodean menyelesaikan desain dan menghasilkan kode program yang berfungsi dengan baik. Sistem diuji untuk mengurangi kesalahan dan memastikan kualitas sistem informasi. Dengan menggunakan implementasi framework Laravel, Emmi Shop dapat memanfaatkan sistem informasi penjualan yang dapat meningkatkan efisiensi proses transaksi dan pengolahan data. Sistem informasi ini memberikan manfaat bagi pemilik usaha dan pelanggan. Hasil penelitian ini diharapkan dapat membantu dalam proses pengembangan sistem informasi penjualan berbasis web yang menggunakan metode waterfall.
Predicting the Number of Passengers in Public Transportation Areas Using the Deep Learning Model LSTM Joko Siswanto; Sri Yulianto Joko Prasetyo; Sutarto Wijono; Evi Maria; Untung Rahardja
Lontar Komputer : Jurnal Ilmiah Teknologi Informasi Vol 15 No 03 (2024): Vol.15, No. 3 December 2024
Publisher : Institute for Research and Community Services, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/LKJITI.2024.v15.i03.p03

Abstract

Accurate predictions of the number of public transport passengers on buses in each region are crucial for operations. They are required by the planning and management authority for bus public transport. A deep learning-based LSTM prediction model is proposed to predict the number of passengers in 4 bus public transportation areas (central, north, south, and west), evaluated by MSLE, MAPE, and SMAPE with dropout, neuron, and train-test variations. The CSV dataset obtained from Auckland Transport(AT) New Zealand metro patronage report on bus performance(1/01/2019-31/07/2023) is used for evaluation. The best prediction model was obtained from the lowest evaluation value and relatively fast time with a dropout of 0.2, 32 neurons, and train-test 80-20. The prediction model on training and testing data improves with the suitability of tuning for four predictions for the next 12 months with mutual fluctuations. The strong negative correlation is central-south, while the strong positive correlation is north-west. Predictions are less closely interconnected and dependent, namely central-south. With its potential to significantly impact policy-making, this prediction model can increase public transport mobility in each region, leading to a more efficient and accessible public transport system and ultimately enhancing the public's daily lives. This research has practical implications for public transport authorities, as it can guide them in making informed decisions about service planning and resource allocation.
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.
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 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 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