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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
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Evaluasi Keberhasilan F-Learn Menggunakan Human Organization Technology (HOT) Fit Model pada Universitas Kristen Satya Wacana Kezia Sharent Kodoati; Kristoko Dwi Hartomo
JATISI (Jurnal Teknik Informatika dan Sistem Informasi) Vol 9 No 3 (2022): JATISI (Jurnal Teknik Informatika dan Sistem Informasi)
Publisher : Lembaga Penelitian dan Pengabdian pada Masyarakat (LPPM) STMIK Global Informatika MDP

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/jatisi.v9i3.2201

Abstract

Flexible Learning (F-Learn) is an online learning media support facility that is used to support the lecture process at SWCU. The purpose of this study is to evaluate the success rate of F-Learn implementation using the HOT Fit model and see which factors have a significant influence between Human, Organization, Technologicaland Net Benefit. This type of research was carried out with a quantitative approach, and data analysis using SEM PLS with the tools used, namely SmartPLS 3.0 in testing validity, reliability and hypothesis testing. The data was obtained through the results of distributing questionnaires and interviews with several lecturers, so that it is known that user satisfaction on human factors greatly influences the benefits of F-Learn. The results obtained from hypothesis testing there are 12 hypotheses, 8 accepted hypotheses and 4 rejected hypotheses. The success of the implementation of the system is declared a success, where the value of the usefulness of the system at the level of 70.8% is included in the strong category.
Analisis dan Pengujian Sistem Informasi Penjualan Produk UMKM Menggunakan Metode Scrum Gladiola Lavinia Ambayu; Kristoko Dwi Hartomo
JATISI (Jurnal Teknik Informatika dan Sistem Informasi) Vol 9 No 3 (2022): JATISI (Jurnal Teknik Informatika dan Sistem Informasi)
Publisher : Lembaga Penelitian dan Pengabdian pada Masyarakat (LPPM) STMIK Global Informatika MDP

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/jatisi.v9i3.2229

Abstract

In Indonesia, developments in the large-scale to small-scale business sectors are beginning to emerge. One of them is MSMEs that utilize patchwork waste. Sometimes in running their business, business owners have difficulty finding patchwork. Based on the issues, e-commerce is an alternative solution to accommodate the sale of patchwork. The benefits of e-commerce for MSMEs are provide flexibility in production, send and receive offers quickly and efficiently, and conduct marketing with the aim of global markets. The method used in this study is the scrum method. Scrum was chosen because of its flexibility, so that it can produce quality software that suits the user, can be used in large and small projects, and easy to adopt changes. The scrum method consists of 5 stages, starting with the product backlog, sprint planning, daily scrum, sprint review, and sprint retrospective. The results of this study are to provide convenience in system design, such as anticipating changes in requirements during the system development process. The purpose of this study is to make it easier for users to find patchwork and help patchwork sellers in expanding the market.
Analisa Rekomendasi Fitur Persetujuan Pinjaman Perusahaan Financial Technology Menggunakan Metode Random Forest Kevin Benedictus Simarmata; Kristoko Dwi Hartomo
JATISI (Jurnal Teknik Informatika dan Sistem Informasi) Vol 9 No 3 (2022): JATISI (Jurnal Teknik Informatika dan Sistem Informasi)
Publisher : Lembaga Penelitian dan Pengabdian pada Masyarakat (LPPM) STMIK Global Informatika MDP

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/jatisi.v9i3.2258

Abstract

Financial technology is an industry that utilizes technology to support the financial system and the delivery of financial services more effectively and efficiently.One type of financial technology is peer-to-peer lending. To get a peer-to-peer loan, the company should collect data such as annual income, credit history, work history, and others, the companies perform screening on applications made by borrowers. The results of screening are applications that are accepted and rejected with should be done rapidly and accurately. The machine learning approach is suitable to overcome this problem and can predict the factors that influence loan approval using the feature importance. This study wants to predict the factors that influence loan approval using the Lending Club dataset. The stages of the research method used include data understanding, feature extraction, data pre-processing, exploratory data analysis (EDA), modeling, and insight. The modeling process uses the random forest algorithm because it runs efficiently on large amounts of data. The evaluation model used in the modeling process is recall with quite high result, namely 0.97. Insight obtained from all stages, there are five major determining factors, namely annual income, monthly payments of the borrower, interest rates, investor funds, and the length of work.
Analisis Sentimen Kebutuhan Fast Track Pada Originals Vidio Menggunakan Support Vector Machine Mozad Timothy Waluyan; Kristoko Dwi Hartomo
JATISI (Jurnal Teknik Informatika dan Sistem Informasi) Vol 9 No 3 (2022): JATISI (Jurnal Teknik Informatika dan Sistem Informasi)
Publisher : Lembaga Penelitian dan Pengabdian pada Masyarakat (LPPM) STMIK Global Informatika MDP

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/jatisi.v9i3.2348

Abstract

Sentiment analysis is an analysis of textual data that provides a detailed analysis of expressed emotions, opinions, and can predict opportunities related to the results of the analysis. This study was conducted to see how Vidio.Com users responded to the original series, which did not yet have fast track capabilities. This helps Vidio.Com grow and improve its business compared to some other OTT companies that already have this feature. This survey uses Vidio.Com's original series of comments, which consists of 1403 comments. Since the dataset has no data labels, perform sentiment analysis to determine positive, neutral, and negative emotions. Sentiment analysis revealed 663 neutral emotions, 517 positive emotions, and 224 negative emotions. Based on these results, we can conclude that most Vidio.Com users need the fast-track features of the original series. This study also used the support vector machine method to test the distribution of training data and test data with 25%, 50%, 75%, and 100% characteristics. In addition, TfIdf weighting was performed and tests were run using the KFoldCrossValidationSystem. The 25er offers the highest accuracy at 86.04%. In tests using the kfold cross-validation system, a second kfold gives the highest accuracy with an accuracy score of 87.74%.
Analisis Kesuksesan Aplikasi Shopee Dari Perspektif Penggemar K-Pop Menggunakan Model Delone dan McLean Estie Grace Melisa Sinulingga; Kristoko D. Hartomo
Jurnal Sisfokom (Sistem Informasi dan Komputer) Vol 11, No 2 (2022): JULI
Publisher : ISB Atma Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32736/sisfokom.v11i2.1411

Abstract

Aplikasi Shopee dirancang sebagai sebuah aplikasi e-commerce yang dapat membantu penggunanya untuk berbelanja secara efisien dan menghemat waktu. Tujuan dari penelitian ini adalah untuk mengetahui seberapa sukses dari aplikasi Shopee dan variabel apa yang mempengaruhi kepuasan pengguna dari perspektif penggemar K-Pop selaku salah satu pengguna pada aplikasi tersebut. Penelitian ini akan menguji menggunakan lima variabel dari metode DeLone and McLean yaitu: kualitas sistem, kualitas informasi, kualitas layanan, kegunaan dan kepuasan pengguna. Penelitian yang digunakan adalah menggunakan metode kuantitatif berupa survey dengan kuesioner, kemudian analisis data menggunakan Structural Equation Model (SEM) dengan Smartpls V3. Data yang dihasilkan berupa hasil analisa dengan menampilkan data dari uji validitas dan uji reliabilitas. Kuesioner yang akan dibagikan kepada responden melalui jejaring sosial, dimana yang menjadi target untuk mengisi data pada kuesioner ini adalah para penggemar K-Pop yang sering atau sudah pernah menggunakan aplikasi Shopee. Hasil dari penelitian ini menunjukan bahwa terdapat 1 (satu) hipotesis dari 6 (enam) hipotesis yang ditolak. Hipotesis yang ditolak merupakan sebuah hipotesis yang memprediksi Kualitas Informasi mempengaruhi Kegunaan menunjukkan koefisien 1.674 (t-statistik 1.96) tidak diterima. Hasil dari penelitian ini memberikan pandangan bahwa Kualitas Informasi dan Kegunaan memiliki pengaruh yang sangat tidak baik, oleh karena itu perlunya peningkatan untuk memperbaiki aplikasi menjadi lebih baik.
Evaluasi Keamanan Fitur Tarik Tunai Cardless pada Aplikasi BRImo Menggunakan PIECES Dearmelliani Tarigan; Kristoko Dwi Hartomo
AITI Vol 19 No 2 (2022)
Publisher : Fakultas Teknologi Informasi Universitas Kristen Satya Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24246/aiti.v19i2.153-166

Abstract

Financial technology (fintech) is a technological development that makes it easier for us in the current digital era. One of the fintech applications in mobile banking services is the BRI Mobile (BRImo) application. BRImo application users still do not fully trust the security of the BRImo feature when withdrawing cash without an Automatic Teller Machine (ATM) card due to cybercrime, such as cases of online fraud. So in this study, we will analyze security and user satisfaction with the cardless cash withdrawal feature in the BRImo application. This study uses the PIECES framework method with six aspects: Performance, Information and Data, Control and Security, Efficiency, and Service. Data was collected by distributing questionnaires and processing data with the help of software version 3.0, namely Smart Partial Least Squares (Smart-PLS). The results from the study indicate that the quality of service and data information on the BRImo cardless cash withdrawal feature significantly influence Control and Security and BRImo user satisfaction.
A new approach of scalable traffic capture model with Pi cluster Kristoko Dwi Hartomo; April Firman Daru; Hindriyanto Dwi Purnomo
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 2: April 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i2.pp2186-2196

Abstract

The development of the internet of things (IoT), which functions as servers, device monitors, and controllers of several peripherals inside the smart home, eased workload in many sectors. Most devices are accessible through the internet because they communicate with wired or wireless interfaces. However, this feature makes them prone to the risk of being exposed to the public. The exposed devices are an easy target for the third party to launch a flooding attack through the network. This attack overloads the system due to the low processing capability, thereby interrupting any running process and harming the device. Therefore, this study proposed a scalable network capturing model that utilized multiple Raspberry Pi boards in parallel to monitor the network traffics simultaneously. An isolated experiment was used for evaluation by running simultaneous flooding attacks on each device. The result showed that the model consumed 30.44% more memory with 14.66% lower central processing unit (CPU) usage and 3.63% faster execution time. This means that this model is better in terms of performance and effectiveness than the single capture model.
Pemetaan Karakteristik Sekolah Sasaran Promosi pada UNKRISWINA SUMBA menggunakan K-Means Murry Albert Agustin Lobo; Sri Yulianto J Prasetyo; Kristoko D Hartomo
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 6, No 4 (2022): Oktober 2022
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v6i4.4464

Abstract

The rapid development of technology has an impact on how data is collected. A high level of data productivity will be in vain if it is not followed by the ability to process data that can produce information that helps the development of the organization. This study aims to help the Promotion Section of UNKRISWINA SUMBA in mapping the characteristics of the target schools and then provide alternative promotion strategies as input in formulating forms of institutional promotion. The data used is in the form of student data who have registered at UNKRISWINA SUMBA since 2016 – 2020. Data processing uses the concept of data mining by applying the K-Means algorithm. K-Means algorithm is used for clustering promotion target schools as many as 4 clusters. Cluster determination is carried out using the elbow method to determine the optimal value of k to perform calculations. Based on the results of processing based on the K-Means algorithm, it is known that as many as 8 schools in cluster 0 are the schools with the most students enrolling in UNKRISWINA SUMBA, 76 schools in cluster 1 are schools with the fewest students enrolling in UNKRISWINA SUMBA, 21 schools those in cluster 2 are schools with quite a lot of students enrolling in UNKRISWINA SUMBA, and 1 school in cluster 3 is a school with quite a number of students enrolling in UNKRISWINA SUMBA but focusing on the Economic Development and Management study program.
Penerapan Algoritma Random Forest dalam Menganalisa Perubahan Suhu Permukaan Wilayah Kota Salatiga Triloka Mahesti; Kristoko Dwi Hartomo; Sri Yulianto Joko Prasetyo
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 6, No 4 (2022): Oktober 2022
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v6i4.4603

Abstract

The population increase in Salatiga city is growing rapidly from 2010 to 2020. This change affects the area with vegetation cover, increasing building density and increasing land surface temperatures. The rising of land surface temperature can affect climate change, air quality, human health quality and energy usage. The purpose of this research is to find out the effect of the area with built-up land and area with vegetation cover to land surface temperature by exploring the values of NDVI, NDBI, LST and Albedo. This research shows that the NDVI value has decreased while the NDBI, LST and Albedo values have increased from 2014 to 2021. The values of NDVI, NDBI and Albedo are the components used as validation of the value of the land surface temperature (LST) change in the study area. The results of the correlation between indices show that the highest correlation occurs between NDVI and NDBI with a value of -0.979 which has a negative correlation because vegetation density is always inversely proportional to the density of built up land. The classification results show that there are 7 villages in Salatiga City with high temperature increases, the villages name are Cebongan, Mangunsari, Ledok, Kutowinangun Kidul, Gendongan, Salatiga and Kalicacing. The results of the accuracy and kappa values in the Random Forest algorithm are quite accurate with an accuracy value of 90% and a kappa value of 73%. The usability test in this study was carried out by distributing questionnaires to city planning department in Salatiga City who had a recapitulation result of 3.62 with the criteria "quite useful". From these results, this research is in accordance with its objectives, the result can be used as one of the city government's recommendations for policy making, especially in Salatiga city planning department.
Analisis Faktor E-Learning Readiness dengan Menggunakan Principal Component Analysis Nuzhah Al Waaidhoh; Eko Sediyono; Kristoko Dwi Hartomo
JSINBIS (Jurnal Sistem Informasi Bisnis) Vol 10, No 1 (2020): Volume 10 Nomor 1 Tahun 2020
Publisher : Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (228.201 KB) | DOI: 10.21456/vol10iss1pp73-83

Abstract

Technological innovation in the industrial revolution era of 4.0 has changed the concept of learning. For example, the e-learning enables students to learn any where and any time without the limitations of distance, space and time. E-learning brings transformation in the world of education by enabling students to access information, data and learning material in more effective and efficient ways. With some of the benefit soffered by e-learning, many organizations want to apply e-learning system. Implementation of e-learning started with assessing thee-learning readiness. There are many factors found by researchers in the process of assessing e-learning readiness. This study aims to reduce the number of e-learning readiness variabels and to identify the factors that most affect the level of e-learning readiness by using the PCA (Principal Component Analysis) method, so it can help organizations that will implement e-learning to prepare important things in the process of implementation e-learning system. The results obtained show that the three factors that most affect there a diness of implementation e-learning are organization, technology and human resources.
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