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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
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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Analisis Potensi Bencana Tanah Longsor di Kabupaten Banjarnegara Menggunakan Interpolasi Inverse Distance Weigthed (IDW) Supit, Christanti Ekkelsia; Prasetyo, Sri Yulianto Joko
Building of Informatics, Technology and Science (BITS) Vol 6 No 1 (2024): June 2024
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v6i1.5187

Abstract

Landslides are a common disaster in Indonesia, especially in Banjarnegara Regency, caused by geomorphology and tropical climate. This is triggered by several factors, namely high rainfall and slope steepness, impacting communities and resulting in losses and even fatalities. According to data obtained from the BNPB website for the period of 2018-2023, there were 51 landslide disasters. Based on this background, the research problem formulates an analysis of landslide-prone areas using rainfall data, classification, and overlay techniques. The research objective is to produce mapping of areas potentially prone to landslides. The study discusses the analysis of rainfall data and slope classification, followed by overlay techniques to produce mapping. The research is supported by the Inverse Distance Weighted (IDW) method and overlay technique. The results obtained from the study include rainfall maps, slope maps, and landslide-prone maps from overlay results. Thus, based on the research findings, the conclusion is drawn that out of a total of 20 districts, there are 7 districts with a very high potential for experiencing landslides, namely Susukan, Mandarija, Madukara, Pagedongan, Sigalu, Pandanarum, and Pagetan
The Adoption of Blockchain Technology the Business Using Structural Equation Modelling Aini, Qurotul; Manongga, Danny; Sediyono, Eko; Joko Prasetyo, Sri Yulianto; Rahardja, Untung; Santoso, Nuke Puji Lestari
IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 18, No 1 (2024): January
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijccs.82107

Abstract

There are many aspects of readiness that must be considered when implementing technological breakthroughs, the business sector is still relatively slow in adopting blockchain technology. However, considering that blockchain technology is still in its early stages of development and has many potential applications, it is necessary to conduct empirical studies on the factors influencing its application in the industry. The problem of this study is to develop an appropriate framework based on how well its features match the needs of the business sector. This research method uses data collection using online questionnaires to obtain information from 86 respondents. The current study also utilizes the Smart PLS 4 model to produce a structural hypothetical model. The results of this study find a significant influence on Revolutionary Innovation by enriching the literature on the relationship between Blockchain, Big Data and the Business Sector, which is expanded by adding new variables. The novelty of this research identifies potential utilization, analyzes internal and external factors, and identifies how blockchain disrupts the business sector. The purpose of this study is to assess how blockchain technology is currently used in the business sector for data provision as a theoretical information technology innovation
Android-based Marketplace Application for Surakarta Local Products Baronio, Nodas Constantine; Prasetyo, Sri Yulianto Joko
Sinkron : jurnal dan penelitian teknik informatika Vol. 7 No. 3 (2023): Article Research Volume 7 Issue 3, July 2023
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i3.12812

Abstract

During the Covid-19 pandemic, many companies suffered losses, leading to a reduction in employees and adversely affecting the community's economy. A significant portion of the local economy depends on the sale of locally produced goods. Moreover, the rapid advancement of information technology has intensified business competition, further impacting the development of local products. Unfortunately, the potential of information technology, particularly Marketplace platforms, to boost the economy and facilitate transactions between customers and sellers has been overlooked. To address these issues, this research aims to develop a Marketplace application to assist the community in selling and promoting their locally made products. The research involves several stages, including analysis, design, simulation prototyping, implementation, monitoring, and management. The result of this study is an Android-based Marketplace application designed to support the sale of local products.
Computer model for detecting tsunami wave hazard on built-up land using machine learning and sentinel 2A satellite imagery Joko Prasetyo, Sri Yulianto; Sulistyo, Wiwin; Christanto, Erwien; Hasiholan Simanjuntak, Bistok
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 13, No 2: June 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v13.i2.pp1535-1546

Abstract

The aim of this research is to compile a tsunami wave hazard scale based on built-up land density extracted and classified by machine learning from Sentinel 2A satellite and digital elevation model (DEM) imageries. This research was carried out in 5 stages, namely: (i) pre-processing of Sentinel 2A and DEM images, (ii) Classification of VI data using the machine learning algorithms, (iii) Spatial prediction using the ordinary kriging method, (iv) Field testing using the confusion matrix method, (v) Preparation of decision matrix for tsunami wave hazard. The results of the study show that the most accurate classification algorithm for classifying built-up indices data is the k-nearest neighbor (k-NN) algorithm. The results of the statistical accuracy test show that the most accurate is normalized difference built-up index (NDBI) with a mean of square error (MSE) value of 0.073 and a mean of absolute error (MAE) of 0.003. DEM analysis shows that the research area is at an altitude of 0–15 meters above sea level so it is in the high vulnerability to medium vulnerability category. Field testing showed user accuracy of 91.11%, manufacturer accuracy of 92.16%, and overall average accuracy of 91%.
Membaca Sinyal Electroencephalogram (EEG) Dalam Menangkap Tingkat Emosi (Berdasarkan Ontologi) Devianto, Yudo; Sediyono, Eko; Prasetyo, Sri Yulianto Joko; Manongga, Danny
Faktor Exacta Vol 17, No 2 (2024)
Publisher : LPPM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/faktorexacta.v17i2.20878

Abstract

Philosophically based EEG (electroencephalography) signal data processing is an engaging interdisciplinary approach and opens up new perspectives in understanding brain function. In this context, it is necessary to examine data from a technical or biological point of view and consider its metaphysical, epistemological and even ontological aspects. Ontology is a branch of metaphysics that deals with objects and the types of objects that exist according to one's metaphysical (or even physical) theory, their properties, and their relationship. This article attempts to provide a philosophical view of science based on ontology for processing EEG signal data, the data source of which is taken from brain waves. With the results of trials using the Artificial Neural Network (ANN) classification, an accuracy value of 46.73 was obtained. The Convolutional Neural Network (CNN) algorithm can also be used to process EEG signal data to determine a person's emotional level; this is proven in research results; although the overall accuracy of emotion recognition has increased significantly, several problems cause low accuracy in the DEAP and DREAMER data sets. There are also results of other experiments carried out using CNN, and the experimental results show that the weight of channels related to emotions is greater than that of different channels. The Continuous Capsule Network (CCN) algorithm and Deep Neural Network (DNN) algorithm can also be used to process EEG signal data to determine the level of emotion.
Optimasi Penilaian Mutu Kerja Pegawai Dengan Metode Clustering Pada RRI Tual Bunga, Alex Frianco; Prasetyo, Sri Yulianto Joko
Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Vol 9, No 1 (2024): Edisi Februari
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/jurasik.v9i1.746

Abstract

This research aims to optimize the process of assessing employee work quality at Radio Republik Indonesia (RRI) Tual using the clustering method. This research method involves analyzing historical data on employee performance assessments as well as applying clustering techniques to group employees based on their performance characteristics. The data used includes employee performance evaluations over the past year, including employee performance, competency, productivity and projects. The clustering method used is K-means clustering to group employees into categories according to the level of quality of their work. The results of this research indicate that the use of the clustering method can optimize the process of assessing employee work quality by allowing the identification of groups based on their performance. In this way, management can provide more appropriate and fair recognition and rewards, as well as design skills development programs that suit each group. The case study at RRI Tual indicates that implementing the clustering method can increase efficiency and objectivity in assessing work quality, strengthen employee motivation, and support strategic decision making for human resource development. These findings can contribute to the improvement of performance appraisal systems in organizations as well as provide a basis for further research in this area.
A machine learning-based computer model for the assessment of tsunami impact on built-up indices using 2A Sentinel imageries Joko Prasetyo, Sri Yulianto; Simanjuntak, Bistok Hasiholan; Susatyo, Yeremia Alfa; Sulistyo, Wiwin
Bulletin of Electrical Engineering and Informatics Vol 13, No 2: April 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i2.5910

Abstract

This study aims to build a computer model to detect built-up land in the identified tsunami hazard zone based on Sentinel 2A imagery using the normalized built up area index (NBI), urban index (UI), normalize difference build-up index (NDBI), a modified built-up index (MBI), index-based builtup index (IBI) algorithms, optimized with machine learning Random Forest (RF) and extreme gradient boosting (XGboost) algorithms and the spatial patterns are predicted using the ordinary kriging (OK) method. Testing of the accuracy of the classification and optimization results was performed using the Kohen Kappa and overall accuracy functions. The results of the study show that a built-up land consisting of open land and water, settlements, industry areas, and agriculture and tourism areas can be identified using the parameters of built-up indices. The accuracy testings that were performed using overall accuracy and Kohen Kappa methods show that classification and prediction are highly accurate using XGboost machine learning, namely 91%. This study produces a novelty of finding, namely a computer model to detect and predict the spatial distribution of built-up land in 4 scales, i.e., very low, low, high, and very high based on NBI, UI, NDBI, MBI, IBI data extracted from Sentinel 2A imagery.
Systematic Literature Review: The Role of Artificial Intelligence in Digital Marketing Yusup, Muhamad; Wijono, Sutarto; Manongga, Danny; Sembiring, Irwan; Prasetyo, Sri Yulianto Joko; Wellem, Theophilus
Journal Sensi: Strategic of Education in Information System Vol 10 No 1 (2024): Journal Sensi
Publisher : UNIVERSITAS RAHARJA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/sensi.v10i1.3117

Abstract

Artificial Intelligence has given a competitive advantage and can increment competition and benefit or Return on Venture in Computerized Showcasing. This article points to recognize diary sources related to the part of Fake Insights, explanatory strategies, applicabilities, and execution measurements on the part of AI in Computerized Promoting from 2015 to 2022. Based on the incorporation and prohibition criteria outlined, it was established that 8 things related to the article were distributed in 2015 and 2022. This article is organized utilizing the SLR strategy which is characterized as a preparation for recognizing, evaluating and evaluating the all accessible investigation to supply answers to four Research Questions. With Suggestions, and add up to of eleven investigation strategies, seventeen usage and nine execution measurements have been distinguished that can be utilized by analysts for future inquire about the part of Manufactured Insights in Computerized Promoting.
Perancangan Website dan Sistem Informasi di Gereja Katolik Santo Paskalis Baylon Wangon Menggunakan Framework Laravel Nugroho, Ignatius Dion; Prasetyo, Sri Yulianto Joko
Jurnal Indonesia : Manajemen Informatika dan Komunikasi Vol. 5 No. 3 (2024): September
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Indonesia Banda Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jimik.v5i3.896

Abstract

The church is one that needs an information system to make it easier to convey information in the church every day. Therefore, the Catholic Church of St. Paskalis Baylon Wangon needs a website to convey all information to the people and the outside community. Judging from the development of Indonesian society today, the use of the internet as a means of information to the public is a new method that should be developed. The design of this website is expected to help the church in conveying information effectively. This developed information system has features such as worship schedules, church announcements, photo and video documentation, and contact information. With these features, the congregation is facilitated in obtaining information about activities in the church and worship schedules. This website can be accessed by congregants and church administrators as outside admins. This design uses the waterfall method, to design websites using the Laravel framework and using PHP and JavaScript programming languages.
Analisis Pengelompokan Jumlah Penumpang Bus Trans Jateng Menggunakan Metode Clustering K-Means Dan Agglomerative Hierarchical Clustering (AHC) Wicaksono, Muhammad Ryqo Jallu; Prasetyo, Sri Yulianto Joko
Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Vol 5, No 3 (2024): Edisi Juli
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/kesatria.v5i3.453

Abstract

This study aims to analyze the clustering of Trans Jateng bus passenger numbers using the K-means clustering method and Agglomerative Hierarchical Clustering (AHC). Data on the number of Trans Jateng bus passengers from the Central Java Transportation Department is used to group passengers based on bus routes and shelters. The K-means method produces 3 clusters with different data quantities for each cluster, while AHC also produces 3 clusters with different patterns. The analysis results show that the K-means method provides more measurable results compared to the AHC method in clustering the Trans Jateng bus passenger data. The information obtained from this analysis can be used to improve Trans Jateng bus transportation services and provide useful insights for decision-makers. Thus, this research contributes to the field of public transportation data analysis and clustering techniques
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