Article Per Year (5 Year)
p-Index From 2020 - 2025
14.979
P-Index
This Author published in this journals
All Journal International Journal of Electrical and Computer Engineering Jurnal Teknoin JURNAL SISTEM INFORMASI BISNIS Jurnal Buana Informatika Bulletin of Electrical Engineering and Informatics Journal of Education and Learning (EduLearn) Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) JUTI: Jurnal Ilmiah Teknologi Informasi Jurnal Algoritma Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Transformatika Journal of Information Systems Engineering and Business Intelligence Khazanah Informatika: Jurnal Ilmu Komputer dan Informatika Register: Jurnal Ilmiah Teknologi Sistem Informasi InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan Sistemasi: Jurnal Sistem Informasi Journal of Applied Geospatial Information JOIV : International Journal on Informatics Visualization Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) JURNAL MEDIA INFORMATIKA BUDIDARMA Information System for Educators and Professionals : Journal of Information System SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Jurnal Sisfokom (Sistem Informasi dan Komputer) GUIDENA: Jurnal Ilmu Pendidikan, Psikologi, Bimbingan dan Konseling Indonesian Journal of Computing and Modeling JURIKOM (Jurnal Riset Komputer) Jurnal Informatika JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Journal of Information Systems and Informatics Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Jurnal Abdi Insani Abdimasku : Jurnal Pengabdian Masyarakat Aiti: Jurnal Teknologi Informasi Budapest International Research and Critics Institute-Journal (BIRCI-Journal): Humanities and Social Sciences Jurnal Teknik Informatika (JUTIF) Journal of Applied Data Sciences JOINTER : Journal of Informatics Engineering IJECS: Indonesian Journal of Empowerment and Community Services International Journal of Engineering, Science and Information Technology International Journal of Community Service Jurnal Impresi Indonesia Jurnal Nasional Teknik Elektro dan Teknologi Informasi Jurnal Algoritma Magistrorum et Scholarium: Jurnal Pengabdian Masyarakat Jurnal Rekayasa elektrika Jurnal INFOTEL Scientific Journal of Informatics JuTISI (Jurnal Teknik Informatika dan Sistem Informasi)
Kristoko Dwi Hartomo
Universitas Kristen Satya Wacana
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry 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 Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Physics Public Health Social Sciences Transportation Other

Published : 108 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 108 Documents
Search

 5   6   7   8   9 
Analisis Sentimen Terhadap Pengaruh Minat Belanja Berdasarkan Komentar di Marketplace Menggunakan Metode Recurrent Neural Network (RNN) Gerry Santos Lasatira; Kristoko Dwi Hartomo; Irwan Sembiring
Jurnal Sistem Informasi Bisnis Vol 13, No 2 (2023): Volume 13 Nomor 2 Tahun 2023
Publisher : Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21456/vol13iss2pp112-119

Abstract

Product reviews on the marketplace can provide useful information if they are properly processed. Product review analysis can be performed by merchants to obtain information that can be used to evaluate products and services. It is not enough to look at the number of stars in product review analysis activities; it is also necessary to look at the entire contents of the review comments to determine the intent of the review. This can be done manually in small quantities, but in large quantities, the system is more efficient. In order to understand the intent of the reviews, a system that can effectively analyze many reviews is required. Using the Recurrent Neural Network (RNN) method, this study aims to analyze sentiment on the influence of shopping interest based on comments in the marketplace. The RNN model is trained to recognize positive and negative sentiments using data from the marketplace. The sentiment analysis results will be used to assess the impact on user shopping interest in the marketplace. Sentiment analysis was performed in this study using the RNN method in the GRU/LSTM training model with epochs. The researcher determined the epoch to achieve high accuracy. The data used for model training and testing is separated into training and testing data before it is used. A comparison of 80% of training data and 20% of test data is used to split data. This study uses a training model with 77 epochs and a batch size of 128 to create a system that automatically calculates comment sentiment in the marketplace with a 100% accuracy value and determines positive and negative sentiments.
Enhancing Multi-Output Time Series Forecasting with Encoder-Decoder Networks Kristoko Dwi Hartomo; Joanito Agili Lopo; Hindriyanto Dwi Purnomo
Journal of Information Systems Engineering and Business Intelligence Vol. 9 No. 2 (2023): October
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/jisebi.9.2.195-213

Abstract

Background: Multi-output Time series forecasting is a complex problem that requires handling interdependencies and interactions between variables. Traditional statistical approaches and machine learning techniques often struggle to predict such scenarios accurately. Advanced techniques and model reconstruction are necessary to improve forecasting accuracy in complex scenarios. Objective: This study proposed an Encoder-Decoder network to address multi-output time series forecasting challenges by simultaneously predicting each output. This objective is to investigate the capabilities of the Encoder-Decoder architecture in handling multi-output time series forecasting tasks. Methods: This proposed model utilizes a 1-Dimensional Convolution Neural Network with Bidirectional Long Short-Term Memory, specifically in the encoder part. The encoder extracts time series features, incorporating a residual connection to produce a context representation used by the decoder. The decoder employs multiple unidirectional LSTM modules and Linear transformation layers to generate the outputs each time step. Each module is responsible for specific output and shares information and context along the outputs and steps. Results: The result demonstrates that the proposed model achieves lower error rates, as measured by MSE, RMSE, and MAE loss metrics, for all outputs and forecasting horizons. Notably, the 6-hour horizon achieves the highest accuracy across all outputs. Furthermore, the proposed model exhibits robustness in single-output forecast and transfer learning, showing adaptability to different tasks and datasets.   Conclusion: The experiment findings highlight the successful multi-output forecasting capabilities of the proposed model in time series data, with consistently low error rates (MSE, RMSE, MAE). Surprisingly, the model also performs well in single-output forecasts, demonstrating its versatility. Therefore, the proposed model effectively various time series forecasting tasks, showing promise for practical applications. Keywords: Bidirectional Long Short-Term Memory, Convolutional Neural Network, Encoder-Decoder Networks, Multi-output forecasting, Multi-step forecasting, Time-series forecasting
Klasifikasi Wilayah Rawan Banjir di Tomohon Menggunakan Citra Satelit Landsat 8 OLI Gabriel Kenisa Meqfaden Baali; Kristoko Dwi Hartomo; Sri Yulianto Joko Prasetyo
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 12 No 4: November 2023
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/jnteti.v12i4.7396

Abstract

Natural disasters often occur unexpectedly, resulting in both material and nonmaterial losses. Floods are among natural disasters that often occurs in several regions in Indonesia, one of which is Tomohon. Tomohon is a city located in the highlands, so it is expected to have a low flood risk level. Nevertheless, in reality, flood still occurs in Tomohon, which then causes material and nonmaterial losses. The data used in this research were the satellite imagery of the Landsat 8 onboard operational land imager (OLI) accessed through the United States Geographical Survey (USGS). The land covers in Tomohon were classified using the supervised classification method with the minimum distance classification (MDC) algorithm. This method provided the advantage of classifying land covers by utilizing training data in Tomohon, achieving an accuracy rate of 99.56%. In addition, the calculations of normalized difference vegetation index (NDVI), normalized difference water index (NDWI), and soil adjusted vegetation index (SAVI) were also utilized to determine the level of vegetation and surface soil moisture in Tomohon using the Quantum GIS (QGIS) application. Upon examining the land covers and calculating the index, weighting was once more performed in accordance with criteria. It was done to facilitate the classification of the area into three flood risk classifications: high, medium, and low. The results showed that green spaces in Tomohon are still greater than residential areas. However, NDVI, NDWI, and SAVI calculations indicated that some densely populated areas are susceptible to flood. These areas include Tomohon Selatan and Tomohon Tengah Subdistricts, which have a high level of flood risk and the Tomohon Timur Subdistrict, which has a medium level of flood risk.
Toddler Stunting Consulting Chatbot using Rasa Framework Wiwien Hadikurniawati; Sutarto Wijono; Danny Manongga; Irwan Sembiring; Kristoko Dwi Hartomo
Jurnal Rekayasa Elektrika Vol 19, No 4 (2023)
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17529/jre.v19i4.33014

Abstract

Chatbots are artificial intelligence software that can communicate with users to assist them in certain tasks or provide information. They can reduce the need for human interaction and make processes more efficient. However, when it comes to more specific tasks related to handling the problem of stunting in toddlers these services are usually unable to provide an appropriate response. Chatbots were created with the help of the Rasa framework, which was designed to adapt the various components of natural language understanding (NLU). This adjustment allows him to understand more complex questions from respondents such as those related to healthy feeding of toddlers. This research explained the use of the Rasa framework to enhance their capabilities, describe the testing and evaluation process, and present the performance results of the chatbot model in addressing the issue of stunting in toddlers. The model is then tested using a confusion matrix, precision, accuracy, and F1 score, which measures how accurate the chatbot's responses are to the user's input. The model had a precision, accuracy, and F1 score of 0.928, 0.932 and 0.930, respectively.
REQUIREMENT ENGINEERING SISTEM MANAJEMEN ASET GEREJA BERBASIS SOFTWARE AS A SERVICE DAN PROGRESSIVE WEB APPLICATION Setiyawati, Nina; Bangkalang, Dwi Hosanna; Hartomo, Kristoko Dwi
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 9, No 3 (2024)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v9i3.5354

Abstract

One of the supports for carrying out church service functions is adequate assets. Some of the problems that often arise in handling church assets are: 1) there is no detailed asset data collection; 2) there is no monitoring or notification of regular asset maintenance schedules; 3) there is no monitoring of asset lending. These problems result in changes in asset status, additional assets, and asset movements not being properly documented. Therefore, an asset management system is needed that can manage, control and track assets effectively. In the system development process, the requirements engineering stage is a crucial stage that has a significant influence on the quality of the resulting system. This research focuses on the requirements engineering stages of the church asset management system using the Iterative Requirements Engineering model proposed by Loucopoulos and Karakostas which consists of three stages, namely elicitation, specification, and validation. In the process of exploring solutions based on problem identification, it was discovered that the system needed to be built by implementing software as a service and progressive web application architecture. The validation stage which is carried out using a high fidelity prototype helps potential users understand the real interactions between features in the system.
Deteksi Cacat pada Isolasi Trafo Secara Visual menggunakan Algoritma Convolutional Neural Network (CNN) Faudisyah, Alfendio Alif; Hartomo, Kristoko Dwi; Purnomo, Hindriyanto Dwi
Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 7 No 4 (2023): OCTOBER-DECEMBER 2023
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jtik.v7i4.1067

Abstract

Transformer insulation is a dielectric material that has the function of selling two or more voltage electrical conductors. Damage to the transformer insulation will cause interference with the performance of the transformer so that it can cause the transformer to experience operational failure or even damage. This research builds a system that can classify defective and normal transformer insulation images. The Convolutional Neural Network method is implemented in model building. The research method begins with conducting research planning, dataset collection, data preprocessing, classification of development models, training models, as well as testing and evaluation. Based on the test results with standardized data size 180 x 180 x 3 pixels, it produces an accuracy of 0.9913 for training, 0.9884 for testing, and 1.00 for evaluation. Test results with standardized data size 240 x 240 x 3 pixels produce an accuracy of 0.9798 for training, 0.9651 for testing, and 0.94 for evaluation. Based on the research that has been done, shows that differences in data standardization can affect the results of the model performance
Management of Traditional Business into Modern: from Microsoft Excel to Deep Learning for prototyping classification Swiftlet’s nests Arini Parhusip, Hanna; Trihandaru, Suryasatriya; Hartomo, Kristoko Dwi; Bianca Lewerissa, Karina; Ariany Mahastanti, Linda; Hartanto, Djoko
International Journal Of Community Service Vol. 4 No. 2 (2024): May 2024 (Indonesia - Ethiopia )
Publisher : CV. Inara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51601/ijcs.v4i2.268

Abstract

In this article, the transformation of traditional management of Swiftlet’s nests into modern business is proposed. Traditional business means that data management of Swiftlet’s nests is done manually, sorted by recording in Microsoft Excel. This is done by PT Waleta Asia Jaya, a company engaged in processing Swiftlet’s nests. This sorting is done because the number of feathers in the Swiftlet’s nests determines the price and cost of workers in processing feather cleaning. In addition, the shape of the Swiftlet’s nests needs attention. However, because it is complex, sorting is done simpler. Originally, Swiftlet’s nests were sorted into 50 categories. To facilitate sorting, deep learning is used with the SSD Mobile Net V2 algorithm as an algorithm to classify into 7 categories based on feather intensity. The device is still a prototype that shows an 85% accuracy rate but has been quite helpful in the process of purchasing Swiftlet’s nests before processing.
Pengembangan Kapasitas Tim Multimedia GKI Tegalrejo Salatiga Melalui Pelatihan Digital Content Creation Wahyono, Teguh; Tumimomor, Anthony Y.M.; Tambotoh, Johan J.C; Hartomo, Kristoko Dwi
Magistrorum et Scholarium: Jurnal Pengabdian Masyarakat Vol. 4 No. 3 (2024)
Publisher : Universitas Kristen Satya Wacana Salatiga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24246/jms.v4i32024p329-338

Abstract

Kegiatan pengabdian masyarakat ini dilatarbelakangi adanya peran penting multimedia dalam menunjang pelayanan gereja. Multimedia memungkinkan gereja untuk menyajikan pesan-pesan rohani, khotbah, ibadah, dan informasi lainnya dalam bentuk visual yang lebih menarik dan menggugah perhatian. Dengan demikian, Gereja perlu memiliki Tim Multimedia yang berkompeten dalam mengerjakan konten-konten video multimedia sesuai dengan kebutuhan. Tim multimedia harus dibekali dengan kemampuan Digital Conten Creation (DCC) yang memadai. Untuk itulah kegiatan pelatihan dan pendampingan ini dilakukan dengan tujuan agar dapat meningkatkan kapasitas Tim Multimedia Gereja dalam mengembangkan konten-konten video digital yang menarik. Metode pelaksanaan meliputi tahap (1) identifikasi kebutuhan, (2) perencanaan kegiatan, (3) pelaksanaan pelatihan, (4) pendampingan, dan (5) evaluasi kegiatan. Hasil evaluasi kegiatan menunjukkan sebagian besar peserta menyatakan bahwa kegiatan pelatihan sudah sesuai dengan kebutuhan. Hasil lainnya menunjukkan bahwa terjadi peningkatan yang siginifikan dari sisi jumlah konten video kreatif yang masuk ke sosial media Gereja pasca pelatihan, khususnya di channel Youtube Gereja.
Analysis of the USM Lecturer PPKM application portal using COBIT 2019 Framework nuranto, bogo; Hartomo, Kristoko Dwi; wahyono, Teguh
Jurnal Sisfokom (Sistem Informasi dan Komputer) Vol 13, No 2 (2024): JULY
Publisher : ISB Atma Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32736/sisfokom.v13i2.2108

Abstract

The USM lecturer PPKM application portal information system provides services and information regarding the research and community service activities of USM lecturers. The services available in this application include PPKM proposals, PPKM assessments, PPKM evaluations, progress reports, contracts, assignment letters and presentation schedules. To improve the system services that have been used so far, analysis and evaluation are needed so that system performance can provide accurate information and according to needs. The purpose of this research is to analyze the performance of applications using the COBIT 2019 framework. The method used is a mix method, which combines data from interviews and observations and data from questionnaires. The research subjects consisted of 7 (seven) IT admins and 30 USM permanent lecturers. The COBIT 2019 framework used as the basis for analysis consists of 11 factors, namely:  Enterprise strategy; Enterprise goals; Risk Profile; IT Related Issue; IT Threat Landscape; Compliance Requirement; Role Of IT; IT Sourcing Model; IT Implementation Method; Technology Adaptation Strategy; and Enterprise Strategy. The results showed that there are 2 (two) objectives that need to go to the core model evaluation stage, namely BAI03 and BAI07. The results of the maturity analysis on BAI03 are at level 2, which is 67.1%. While the results of the maturity analysis on BAI07 show results of 72.7%.
Perancangan Sistem Informasi Evaluasi Kinerja Guru Berbasis Website Menggunakan Soft System Methodology (SSM) (Studi Kasus di SMK Taruna Tama Getasan) Sinulingga, Yedija Sada Ukurta; Hartomo, Kristoko Dwi
Jurnal Transformatika Vol. 19 No. 1 (2021): July 2021
Publisher : Jurusan Teknologi Informasi Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/transformatika.v19i1.2921

Abstract

Performance assessment system is a reference of school to determine the performance quality of a teacher that also a reference to determine their career development and career promotion. The teacher has to improve their skills and ability to apply the competence to improve the quality of the learning process. The expansion of performance assessment information system in SMK Taruna Tama Getasan Salatiga will help the assessor  to make performance assessment report because the previous method they used conventional system that hinder the process of   the rating like a difficult calculation and take so much time. This system use Soft System Methodology (SSM) by using structured approach to understand some issues, build conceptual mode, get eligibility and the implementation. System testing use Webqual 4.0 and using 3 (three) instruments are Usability Quality, Information Quality and Service Interaction Quality. By using 122 that processed by SPSS software   which testing the validity test, reliability and linear regression correlation. From the test result that the website of performance assessment system are having a good quality based on Usability Quality, Information Quality and Service Interaction Quality.    
Co-Authors Ade Iriani Agata, Kristien Yuni Agus Bambang Nugraha Ahmad Ashifuddin Aqham Alexandra, Andrea Cellista Allu, Roy Armus Andeka Rocky Tanaamah Andriana, Myra Angelia Destriana Anggara Cahya Putra Anthony Y.M. Tumimomor April Firman Daru Ariany Mahastanti, Linda Ariel Kristianto Arthur, Christian Aruperes, Viveca Grivenda Aryanata Andipradana Baali, Gabriel Megfaden Kenisa Bagaskara, Adyatma Andhika Bambang Ismanto Brilliananta Radix Dewana Chandra Husada Danny Manongga Danny Sebastian Dearmelliani Tarigan Desyandri Desyandri Dewi, Stefani Fransisca Dian Widiyanto Chandra Diky Candra Muria Pratama Djoko Hartanto Dwi Anggono Winarso Suparjo Putra Dwi Hosanna Bangkalang Eko Sediyono Enik Muryanti Estie Grace Melisa Sinulingga Evangs Evi Maria Ezra Julang Prasetyo Faudisyah, Alfendio Alif Gerry Santos Lasatira Gladiola Lavinia Ambayu Gogo Krisatyo Hanna Arini Parhusip Hanna Prillysca Chernovita Hindriyanto Dwi Purnomo Hong, Hendry Indrajaya, Denny Irwan Sembiring Joanito Agili Lopo Joanito Agili Lopo Johan Jimmy Carter Tambotoh Joshua Rondonuwu Kamil, Muhammad Farhan Karina Bianca Lewerissa Kevin Benedictus Simarmata Kevin Hendra William Kevin Stevian Hermawan Kezia Sharent Kodoati Kho, Ardi Kuncoro, Wreda Agung Kurniawan, Timothy Arif Limbong, Josua Josen Alexander Linda Ariany Mahastanti Lobo, Murry Albert Agustin Magdalena Ariance Ineke Pakereng Martin Setyawan Martin Teddy Sihite Matheus Supriyanto Rumetna Mila Chrismawati Paseleng Mozad Timothy Waluyan Muflihanto, Ezar Juan Muhammad Rizky Ramadhan Muhammad Sholikhan Neilin Nikhlis Nicolas Evander Suhandi Nina Setiyawati Nining Fitriani nuranto, bogo Nurrokhman Nurrokhman Nuzhah Al Waaidhoh Penidas Fodinggo Tanaem Prakoso, Hendri Suryo Pramudhita Tunjung Seta Prasetyo, Sri Yulianto Prasianto, Kornelius Reinand Purnomo, Andreas Wisnu Adi Purwanto Purwanto Raditya Ditto Aryaputra Radius Tanone Radjawane, Samy Rahmawati, Lutfi Raymond Elias Mauboy Rizaldi, Alexander Sandy Pratama Saputro, Andreas Arga Rinjani Septian Silvianugroho Sinulingga, Yedija Sada Ukurta Sri Yulianto Sri Yulianto Joko Prasetyo Stevan Hamonangan Hardi Suhandi, Nicolas Evander Suharjo, Rahmat Abadi Sulistiawati, Anita Suryasatriya Trihandaru Sutarto Wijono Sutedja, Indrajani T. Arie Setiawan P Takakobi, Michael Richard Teguh Wahyono Theopillus J. H. Wellem Tri Harjani Tri Wahyuningsih Tridinatha, Zenitha Eunike Triloka Mahesti Tumbade, Marcho Oknivan Untung Rahardja Wahab, Nur Haliza Abdul Waliyuddin Rabbani, Imam Wattimena, Nalbraint Wibowo, Mars Caroline Winarko, Edi Wiwien Hadikurniawati Yessica Nataliani Yohan Maurits Indey