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All Journal International Journal of Electrical and Computer Engineering IAES International Journal of Artificial Intelligence (IJ-AI) IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Dinamik Seminar Nasional Aplikasi Teknologi Informasi (SNATI) JURNAL SISTEM INFORMASI BISNIS Jurnal Sistem Komputer JSI: Jurnal Sistem Informasi (E-Journal) Prosiding SNATIF Jurnal Teknologi Informasi dan Ilmu Komputer Scientific Journal of Informatics Journal of Information Systems Engineering and Business Intelligence Khazanah Informatika: Jurnal Ilmu Komputer dan Informatika JOIV : International Journal on Informatics Visualization Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) International Journal of Artificial Intelligence Research INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi JURNAL MEDIA INFORMATIKA BUDIDARMA Desimal: Jurnal Matematika INOVTEK Polbeng - Seri Informatika BAREKENG: Jurnal Ilmu Matematika dan Terapan International Journal on Emerging Mathematics Education Jurnal ULTIMA InfoSys MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Jurnal Teknologi Sistem Informasi dan Aplikasi Journal of Information Technology and Computer Engineering J-SAKTI (Jurnal Sains Komputer dan Informatika) Aptisi Transactions on Management JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Aptisi Transactions on Technopreneurship (ATT) EDUKATIF : JURNAL ILMU PENDIDIKAN Building of Informatics, Technology and Science Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Progresif: Jurnal Ilmiah Komputer Journal of Information Systems and Informatics KAIBON ABHINAYA : JURNAL PENGABDIAN MASYARAKAT Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) ICIT (Innovative Creative and Information Technology) Journal Computer Science and Information Technologies Jurnal Bumigora Information Technology (BITe) Aiti: Jurnal Teknologi Informasi Jurnal Teknik Informatika (JUTIF) IAIC Transactions on Sustainable Digital Innovation (ITSDI) JOINTER : Journal of Informatics Engineering International Journal of Engineering, Science and Information Technology Advance Sustainable Science, Engineering and Technology (ASSET) Journal of Information Technology (JIfoTech) J-SAKTI (Jurnal Sains Komputer dan Informatika) Jurnal Nasional Teknik Elektro dan Teknologi Informasi Magistrorum et Scholarium: Jurnal Pengabdian Masyarakat JEECS (Journal of Electrical Engineering and Computer Sciences) Metris: Jurnal Sains dan Teknologi Scientific Journal of Informatics International Journal of Information Technology and Business INOVTEK Polbeng - Seri Informatika JuTISI (Jurnal Teknik Informatika dan Sistem Informasi) Jurnal DIMASTIK
Hindriyanto Dwi Purnomo
Universitas Kristen Satya Wacana
Agriculture, Biological Sciences & Forestry 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 Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Social Sciences Transportation Other

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Pengaruh E-Payment Trust terhadap Minat Transaksi pada E-Marketplace Menggunakan Framework Technology Acceptance Model (TAM) 3 Lestari, Merryana; Purnomo, Hindriyanto Dwi; Sembiring, Irwan
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 8 No 5: Oktober 2021
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2021855212

Abstract

Transaksi melalui e-Marketplace dilakukan menggunakan transaksi pembayaran secara digital yang disebut sebagai layanan e-Payment. Oleh karena itu, e-Payment memegang peranan penting dalam proses transaksi jual beli pada e-Marketplace khususnya dalam transaksi pembayaran. Seringkali pengguna memiliki kekhawatiran tersendiri dalam melakukan transaksi pembayaran menggunakan e-Payment, salah satu kekhawatiran paling mendasar adalah mengenai jaminan integritas keamanan data dan privasi data pelanggan. Kepercayaan pengguna dipandang menjadi suatu resiko besar yang dapat memberikan pengaruh terhadap minat pembelian pada e-Marketplace. Melalui penelitian ini, akan dianalisis bagaimana tingkat pengaruh kepercayaan pengguna pada e-Payment di Indonesia terhadap transaksi pada e-Marketplace memakai metode Technology Acceptance Model (TAM) versi 3. Hasil penelitian ini merupakan bahan evaluasi bagi vendor e-Marketplace guna melakukan analisis seberapa sering pengguna melakukan transaksi di dalam e-Marketplace sehingga semakin memberikan kepercayaan pengguna untuk melakukan transaksi menggunakan layanan e-Payment. AbstractTransactions through e-Marketplace are carried out using digital payment transactions or commonly referred to as e-Payments. Therefore, e-Payment plays an important role in the process of buying and selling transactions on the e-Marketplace, especially in payment transactions. Often users have their own concerns in making payment transactions using e-Payment, one of the most basic concerns is about guaranteeing data security integrity and customer data privacy. User trust is seen as a big risk that can have an influence on buying interest in the e-Marketplace. Through this research, it will be analyzed how the level of influence of user trust in e-Payment in Indonesia on the impact of purchases on e-Marketplace using the Technology Acceptance Model 3 (TAM 3) framework. The results of this study can be used as evaluation material for e-Marketplace vendors to analyze how often users make transactions in the e-Marketplace so that it gives more confidence to users to make transactions using e-Payment services.
IMPLEMENTATION OF THE FMADM ALGORITHM AND SAW METHOD IN BOARDING HOUSE SEARCH Baun, Sindy Cristine; Purnomo, Hindriyanto Dwi
Jurnal Teknik Informatika (Jutif) Vol. 5 No. 4 (2024): JUTIF Volume 5, Number 4, August 2024 - SENIKO
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2024.5.4.2056

Abstract

Current developments have made many developments, one of which is boarding houses. There are many immigrants from outside the region who want to study at Nusa Cendana University, Kupang City but have difficulty in finding a boarding house because of many considerations such as what facilities are provided by the boarding house owner. The lack of information on boarding house occupancy makes it difficult for prospective residents who are looking for boarding houses to obtain information about boarding houses with the criteria of each boarding house, to overcome this problem the Fuzzy Multi Attribute Decision Making (FMADM) Algorithm and Simple Additive Weighting (SAW) Method are needed with the aim of making it easier for female students to find boarding houses that suit their wishes and the best around Nusa Cendana University, Kupang, NTT. After analysis, the FMADM algorithm turned out to be able to help determine the weight of the value of each criterion in finding the best boarding house and also the SAW method can be implemented very well so that it can make it easier to add up the weight value of each criterion by doing alternative ranking. The results of the research that have been studied show that using the FMADM algorithm and the SAW method can produce the best alternative as the best solution from other alternatives, with Kost Putri Bilm@t being the best alternative out of 100 other alternatives studied with a ranking value of 4.106667. With the best alternative obtained, it shows that by using the FMADM algorithm and the SAW method, the number of samples used is large, the level of validity also often increases.
Exploring Data Analytics in Attendance Systems: Unveiling Machine Learning Techniques, Patterns, Practices, and Emerging Trends Santoso, Joseph Teguh; Manongga, Danny; Setyawan, Iwan; Purnomo, Hindriyanto Dwi; Hendry
Scientific Journal of Informatics Vol. 11 No. 2: May 2024
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v11i2.3438

Abstract

Purpose: The research aims to identify patterns and trends in attendance management through the application of reward and punishment systems as innovative solutions for improving employee attendance and well-being. Methods: This research utilizes a descriptive analysis approach with the application of Machine Learning (ML) techniques to enhance the accuracy of attendance pattern prediction and ML models for the classification of emerging trends and patterns. Research data were obtained through the company's attendance system and divided into two segments (80% for training and 20% for testing) while maintaining a balanced class proportion, then processed using SPSS and Python software with the Scikit-learn library. Result: The results of the study show that employee attendance is increased from 86.52% to 90.44% when the reward and punishment method is applied to the employee attendance system. Proper reward allocation can increase employee motivation to adhere to work schedules and consistently attend, while punishment tends to lead to lower attendance rates. Novelty: This research emphasizes the optimization of attendance management through data analytics approaches and the implementation of advanced technology in attendance systems with the application of ML techniques to analyze attendance data comprehensively and detect significant patterns.
Perancangan Sistem Pendukung Objek Deteksi untuk Permainan Kartu Cardfight!Vanguard Menggunakan Aplikasi Roboflow dan Flask Tungady, Cornelius Arvel Pratama; Purnomo, Hindriyanto Dwi
Jurnal Teknologi Sistem Informasi dan Aplikasi Vol. 6 No. 3 (2023): Jurnal Teknologi Sistem Informasi dan Aplikasi
Publisher : Program Studi Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The covid-19 pandemic that emerged in early 2020 has affected our activities with various limitations, for this reason the government has implemented several protocols starting from using masks, maintaining cleanliness, and social distancing. It is also undeniable that humans are social creatures, in this context boredom is the main enemy. There are some activities to be able relieve stress such as reading, listening to music, watching, or playing a game. TCG (Trading Card Game) is an artificial game that build in with such various interesting themes. Card games are generally played with other people, but what would happen if the card game was played in the covid-19 pandemic. Of course, the biggest obstacle we will be facing are distance and time. Konami as a card game manufacturer and developer has a brilliant idea by implementing Remote Duel where tournaments and other official matches can be held virtually. Cardfight!Vanguard is no exception, which has a gameplay that really depends on the interaction between players. Remote play requires players to use a camera that will take pictures of the card field while playing. This study uses the Waterfall Model which will be taken from dataset preparation, train the data, perform the Annotate process, and carry out a web-based implementation using the flask framework so that it can be used and tested for its functionality using one of tensorflow's product technologies, Roboflow, which is an application that specifically designed to be able to assist in the process of creating and recognizing objects. The results obtained by using flask as a web base can be seen to perform card object recognition properly so that it can display data from the detected cards.
Analisis Sentimen Komentar Konsumen Industri Jamu di Media Sosial menggunakan Artificial Neural Network dan K-Nearest Neighbor Kurniawan, Daniel; Purnomo, Hindriyanto Dwi; Iriani, Ade
Jurnal Sistem Informasi Bisnis Vol 14, No 3 (2024): Volume 14 Nomor 3 Tahun 2024
Publisher : Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21456/vol14iss3pp210-223

Abstract

Phytopharmaceutical plants have become one of the main commodities contributing significantly to the economy through their use in the pharmaceutical, cosmetic, and health industries. However, behind this economic potential, traditional herbal medicine businesses often face challenges, particularly in promotion and brand identity. Social media platforms like Instagram have now introduced unique features to support business and marketing, primarily by providing in-depth information about herbal products and offering opportunities for businesses to receive feedback from consumers. Comments on social media are valuable but often unstructured; hence, sentiment analysis is necessary to organize and categorize this data. By combining comment data with information from Google Trends, cause-and-effect relationships from comments during specific periods can be identified using path analysis. This research aims to analyze consumer comments on the Sidomuncul company's Instagram platform, with the hope of benefiting the company and advancing herbal medicine products. The methods used in this study include Artificial Neural Network (ANN) and K-nearest neighbor (KNN) to classify comments into positive, negative, and neutral categories. Both methods show satisfactory results in classification, with an average accuracy of 0.887 for ANN and 0.874 for KNN. However, the ROC curve for the KNN model indicates a relatively low AUC value in classifying negative comments, at 0.598.
Analysis Of Library Visitors' Interest Using Factor Analysis And Discriminant Analysis Hery Santono; Eko Sediyono; Hindriyanto Dwi Purnomo
INOVTEK Polbeng - Seri Informatika Vol. 10 No. 1 (2025): March
Publisher : P3M Politeknik Negeri Bengkalis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35314/g3vb2a79

Abstract

The relevance of libraries as learning centers, gathering places for the scientific community, and access points for resources not always available online underscores the importance of understanding the factors that influence library visitor interest. This study aims to analyze the factors impacting visitor interest using Factor Analysis and Discriminant Analysis. The key factors explored include service quality, comfort of facilities, quality of book collections, access to digital technology, and frequency of visits. Data was collected through surveys conducted with 500 library visitors across five different locations over a three-month period. Factor Analysis revealed that comfort factors and access to technology were the most significant variables influencing visitor interest, accounting for 65% of the variance in visitor behavior. Discriminant Analysis further classified visitors into high and low interest groups, showing that library facilities were the primary differentiator between these two groups. The study found that visitors with high interest were more likely to be influenced by the library's physical comfort and technology access, while those with low interest were less engaged with the library's services. This research provides valuable insights for library managers to enhance services, optimize library environments, and incorporate technological advancements to increase visitor engagement. It also contributes to the theoretical understanding of library management by identifying key factors that affect visitor interest, which can inform future strategies in the field. However, this study is limited by its cross-sectional nature, and the results may not be generalizable to other regions or visitor demographics. Future research could explore longitudinal data to assess how visitor preferences evolve over time.
The Strategic Role of Orange Technology in Cultivating Innovation and Well-Being Kristiyanto, Daniel Yeri; Purnomo, Hindriyanto Dwi; Cesna, Galih Putra; Ani, Nyree
IAIC Transactions on Sustainable Digital Innovation (ITSDI) Vol 7 No 1 (2025): October
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/itsdi.v7i1.707

Abstract

This paper examines the integration of Orange Technology a human-centred paradigm advancing health, happiness, and care (H2O triad) within strategic management frameworks. While strategic management provides the processes of environmental scanning, formulation, implementation, and evaluation, Orange Technology introduces models that emphasize well-being as a strategic asset. Employing an exploratory conceptual design, this study synthesizes interdisciplinary literature across information technology, biomedical engineering, psychology, and cognitive sciences, and maps them against the established stages of strategic management. The analysis highlights the potential for Orange Technology to enrich strategic processes by embedding health and happiness indicators into value propositions, governance systems, and performance evaluation tools. A phenomenon-level gap persists, however, as empirical evidence on governance systems, interdisciplinary adoption, and performance measurement remains scarce. To bridge this divide, two propositions are advanced for embedding an Orange Index into Balanced Scorecard frameworks, and developing a Three-Dimensional Transformational Balanced Scorecard to evaluate human centred innovation. Finally, emerging applications such as TRAIVIS demonstrate how Orange Technology principles extend beyond healthcare into education, combining AI, blockchain, and human centred learning to foster innovation and societal well-being.
Trends in sentiment of Twitter users towards Indonesian tourism: analysis with the k-nearest neighbor method Purnama Harahap, Eka; Dwi Purnomo, Hindriyanto; Iriani, Ade; Sembiring, Irwan; Nurtino, Tio
Computer Science and Information Technologies Vol 5, No 1: March 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/csit.v5i1.p19-28

Abstract

This research analyzes the sentiment of Twitter users regarding tourism in Indonesia using the keyword "wonderful Indonesia" as the tourism promotion identity. The aim of this study is to gain a deeper understanding of the public sentiment towards "wonderful Indonesia" through social media data analysis. The novelty obtained provides new insights into valuable information about Indonesian tourism for the government and relevant stakeholders in promoting Indonesian tourism and enhancing tourist experiences. The method used is tweet analysis and classification using the K-nearest neighbor (KNN) algorithm to determine the positive, neutral, or negative sentiment of the tweets. The classification results show that the majority of tweets (65.1% out of a total of 14,189 tweets) have a neutral sentiment, indicating that most tweets with the "wonderful Indonesia" tagline are related to advertising or promoting Indonesian tourism. However, the percentage of tweets with positive sentiment (33.8%) is higher than those with negative sentiment (1.1%). This study also achieved training results with an accuracy rate of 98.5%, precision of 97.6%, recall of 98.5%, and F1-score of 98.1%. However, reassessment is needed in the future as Twitter users' sentiment can change along with the development of Indonesian tourism itself.
Predicting students' success level in an examination using advanced linear regression and extreme gradient boosting Wahyuningsih, Tri; Iriani, Ade; Dwi Purnomo, Hindriyanto; Sembiring, Irwan
Computer Science and Information Technologies Vol 5, No 1: March 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/csit.v5i1.p29-37

Abstract

This research employs a hybrid approach, integrating advanced linear regression and extreme gradient boosting (XGBoost), to forecast student success rates in exams within the dynamic educational landscape. Utilizing Kaggle-sourced data, the study crafts a model amalgamating advanced linear regression and XGBoost, subsequently assessing its performance against the primary dataset. The findings showcase the model's efficacy, yielding an accuracy of 0.680 on the fifth test and underscoring its adeptness in predicting students' exam success. The discussion underscores XGBoost's prowess in managing data intricacies and non-linear features, complemented by advanced linear regression offering valuable coefficient interpretations for linear relationships. This research innovatively contributes by harmonizing two distinct methods to create a predictive model for students' exam success. The conclusion emphasizes the merits of an ensemble approach in refining prediction accuracy, recognizing, however, the study's limitations in terms of dataset constraints and external factors. In essence, this study enhances comprehension of predicting student success, offering educators insights to identify and support potentially struggling students. 
Consumer Behavior Analysis using Apriori Algorithm Safitri, Adila; Purnomo, Hindriyanto Dwi
International Journal of Information Technology and Business Vol. 1 No. 2 (2019): April: International Journal of Information Techonology and Business
Publisher : Universitas Kristen Satya Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Along with the development of the era, also followed by growth and also the birth of many companies in the field of goods and services, where each company always strives as much as possible to obtain and maintain market share. This can make competition tight, especially for business people, especially those that occur in digital printing companies owned by Abadi Digital Printing, Salatiga. Because this printing company is still a new company, it requires a lot of research on consumer purchasing patterns to increase sales and marketing strategies so as not to be rivaled by other printing that has been longer, the following analysis uses apriori algorithms with RapidMiner tools. By using a support value of 0,025 and confidence of 0,6, the results are that the items often purchased by consumers are standing banner with x banner. From these results it can be used as a promotional event, deal packages, etc to increase consumer attractiveness.
Co-Authors 12.5202.0161 Daniel Yeri Kristiyanto Ade Iriani Adimas Tristan Nagara Hartono Adriyanto Juliastomo Gundo Agung Wibowo Agus Priyadi Ahmad Bayu Yadila Andre Kurniawan Andrew Aquila Chrisanto Pabendon Andry Ananda Putra Tanggu Mara Andry Tanggu Mara Angela Atik Setiyanti Ani, Nyree Anton Hermawan Anwar, Muchamad Taufiq April Firman Daru April Lia Hananto Aris Puji Widodo Arseta, Gama Astawa, I Wayan Aswin Dew Atik Setyanti, Angela Aziz Jihadian Barid Azzahra Nurwanda Bandung Pernama Baun, Sindy Cristine Budhi Kristianto Budi Kristianto Budi Kristianto, Budi C. Leuwol, Sylvie Cahyaningtyas, Christyan Cahyo Dimas K Cesna, Galih Putra Chandra Halim Charitas Fibriani Christyan Cahyaningtyas Daniel Kurniawan Daniel Kurniawan Danny Manongga Danu Satria Wiratama Deden Rustiana Dedy Prasetya Kristiadi Didit Budi Nugroho Dody Agung Saputro Dwi Hosanna Bangkalang Edwin Zusrony Eko Sediyono Eliansion Ivan eremia Silvester Sutoyo Erwien Christianto Evang Mailoa Evangs Mailoa Fajar Rahmat Faudisyah, Alfendio Alif Fauzi Ahmad Muda Feibe Lawalata Florentina Tatrin Kurniati Giner Maslebu Gladis Tri Enggiel Griya Jitri Pabutungan Gudiato, Candra Hanita Yulia Hanna Arini Parhusip Hari Purwanto Hendra Kusumah Hendra Waskita Hendradito Dwi Aprillian Hendro Steven Tampake Hendry Heni Pujiastuti Hermanto Abraham, Rendy Hery Santono HR. Wibi Bagas N Hsin Rau Huda, Baenil Hui-Ming Wee Irdha Yunianto Irwan Sembiring Istiarsi Saptuti Sri Kawuryan Istiarsih Saputri Sri Kawuryan Iwan Setiawan Iwan Setyawan Janinda Puspita Anidya Jihot Lumban Gaol Joanito Agili Lopo Jonas, Dendy Kainama, Marchel Devid Karema Sarajar, Dewita Kho, Delvian Christoper Krismiyati Kristoko Dwi Hartomo Lea Klarisa Lumban Gaol, Jihot Markus Permadi Mau, Stevanus Dwi Istiavan Maya Sari Mellyuga Errol Wicaksono Merryana Lestari Mira Mira Mira Muhammad Aufal Muhammad Rizky Pribadi Nadya Octavianna Lompoliuw Nahak, Yosef Jeffri Silvanus Nahusona, Ferry Nanle, Zeze Nina Rahayu Nina Setiyawati Ninda Lutfiani Nurrokhman, Nurrokhman Nurtino, Tio Permadi, Markus Picauly, Irma Amy Pratyaksa Ocsa Nugraha Saian Priatna , Wowon Purbaratri, Winny Purnama Harahap, Eka Purwanto - Purwanto Putri, Violita Eka Radius Tanone Ramos Somya Raynaldo Raynaldo Raynaldo Raynaldo, Raynaldo Richard William Kho Riko Yudistira Robert William Ruhulessin Rufina Rahma Ajeng Setyaningsih Safitri, Adila Sakalessy, Afelia Jozalin Elisa Sampoerno Santoso, Fian Julio Santoso, Fian Yulio Santoso, Joseph Teguh Setiyaji, Akhfan Sri Kawuryan, Istiarsi Saptuti Sri Sri Yulianto Joko Prasetyo Sugiman, Marcelino Maxwell Sutarto Wijono Syamsul Arifin Tad Gonsalves Tad Gonsalves Teguh Indra Bayu Teguh Wahyono Theopillus J. H. Wellem Tirsa Ninia Lina Tri Wahyuningsih Trivena Andriani Tukino, Tukino Tumbade, Marcho Oknivan Tungady, Cornelius Arvel Pratama Untung Rahardja Utama, Deffa Ferdian Alif Valentino Kevin Sitanayah Que Walangara Nau, Novriest Umbu Wibowo, Mars Caroline Widyarini, Liza Wilujeng Ayu Nawang Sari Winny purbaratri Wisnu Wibisono, Indra Wiwien Hadikurniawati Yerik Afrianto Singgalen Yessica Nataliani Yos Richard Beeh Yos Richard Beeh Yos Richard Beeh Yudistira, Riko Yuli Agung Suprabowo, Gunawan Yusuf, Natasya Aprila Zakaria, Noor Azura