Article Per Year (5 Year)
p-Index From 2021 - 2026
8.063
P-Index
This Author published in this journals
All Journal Jurnal Paradigma Ekonomika TEKMAPRO Journal of Industrial Engineering and Management SITEKIN: Jurnal Sains, Teknologi dan Industri Sistemasi: Jurnal Sistem Informasi Policy & Governance Review Educatio INTECOMS: Journal of Information Technology and Computer Science Journal of Entrepreneurship, Management and Industry (JEMI) JURNAL TEKNOLOGI DAN OPEN SOURCE Almana : Jurnal Manajemen dan Bisnis JUSIM (Jurnal Sistem Informasi Musirawas) JURNAL TEKNOLOGI INFORMASI Jurnal Ilmiah Akuntansi Manajemen Jurnal Teknologi Informasi dan Multimedia Journal of Information Systems and Informatics Jurnal Ilmiah Betrik : Besemah Teknologi Informasi dan Komputer International Journal of Economics Development Research (IJEDR) Prosiding National Conference for Community Service Project Jurnal Industri Kreatif dan Kewirausahaan Jurnal E-Komtek JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Jurnal Manajemen Bisnis Eka Prasetya Economics and Digital Business Review Teknika Jurnal Akuntansi, Manajemen dan Ilmu Ekonomi (JASMIEN) Journal La Bisecoman International Journal of Global Accounting, Management, Education, and Entrepreneurship (IJGAME2) JEBDEKER: Jurnal Ekonomi, Manajemen, Akuntansi, Bisnis Digital, Ekonomi Kreatif, Entrepreneur Journal of Information System and Technology (JOINT) Jurnal Info Sains : Informatika dan Sains Priviet Social Sciences Journal Conference on Management, Business, Innovation, Education and Social Sciences (CoMBInES) Conference on Business, Social Sciences and Technology (CoNeScINTech) Social Engagement: Jurnal Pengabdian Kepada Masyarakat Madani: Jurnal Pengabdian Masyarakat dan Kewirausahaan Jurnal Ilmiah Betrik : Besemah Teknologi Informasi dan Komputer
Aripradono, Heru Wijayanto
Universitas Internasional Batam
Aerospace Engineering Arts Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Social Sciences Other

Published : 59 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 59 Documents
Search

 2   3   4   5   6 
Impulsive Buying of Fashion Goods on Digital Marketplace among Z-Generation in Batam City: a Multi Method Analysis Approach Aripradono, Heru Wijayanto; Silvina, Silvina
SITEKIN: Jurnal Sains, Teknologi dan Industri Vol 20, No 2 (2023): June 2023
Publisher : Fakultas Sains dan Teknologi Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/sitekin.v20i2.21859

Abstract

This study aims to determine factors such as ideal self-congruence, fashion consciousness, positive emotion, materialism, product attributes, online platform quality, and online sales promotion that affect impulsive buying behavior among Z-Generation in Batam. This study uses quantitative and qualitative method. Sampling method used is convenience sampling for quantitative and disproportionate stratified sampling for qualitative data. A total of 400 questionnaire respondents and 20 interviews which target specifically had an experience of buying fashion products through online platforms, generation Z, and live in Batam. Data analysis using regression analysis by SPSS Statistics 26. The result shows that fashion consciousness, materialism, product attributes, and online sales promotion have a significant effect on impulsive buying. This study provides a different demography compared to previous research, as people from different ages, places, and culture may behave in a different way considering their lifestyle. These can provide insight into what should attract impulsive buying behavior towards Z-Generation consumers in Batam.
Pengembangan Metode Permainan Teka Teki Untuk Meningkatkan Minat Siswa Dalam Belajar Bahasa Mandarin Dengan Menggunakan Pendekatan Design Thinking Sofyanti, Sofyanti; Aripradono, Heru Wijayanto
Educatio Vol 18 No 2 (2023): Educatio: Jurnal Ilmu Kependidikan
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/edc.v18i2.24091

Abstract

The introduction of Mandarin as a foreign language is increasingly important in the era of globalization and increasingly close international relations between countries. In many countries, including Indonesia, the ability to speak Mandarin is considered a competitive advantage in various fields. Despite its importance, interest in learning Mandarin is still low. The purpose of this study is to identify and analyze the effect of the puzzle game method in increasing students' interest in learning Chinese. This study used qualitative research methods. Data collection techniques were carried out by observation and literature study. The data that has been collected is then analyzed thematically. The results showed that efforts to increase students' interest in learning Chinese, namely by playing charades implemented through power point media at Zoom meetings, proved to be able to increase students' interest in learning Chinese because it was considered interesting and fun by students. In addition, in this game there are also prizes for students who have the highest points. Points are obtained by answering questions correctly, this makes students eager to collect points and indirectly increases students' interest in learning.
Pengembangan Proses Bisnis Inovatif Batam Animal Lovers Community dengan Metode Design Thingking Aripradono, Heru Wijayanto; Lau, Vionny
Tekmapro Vol. 19 No. 1 (2024): TEKMAPRO
Publisher : Program Studi Teknik Industri Universitas Pembangunan Nasional Veteran Jawa Timur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33005/tekmapro.v19i1.380

Abstract

Artikel ini membahas penggunaan metodologi Design Thinking dalam pengembangan proses bisnis inovatif Batam Animal Lovers Community (BALC), sebuah organisasi nirlaba, untuk mengatasi masalah kesejahteraan hewan terlantar di Kota Batam. Organisasi ini menggunakan strategi komprehensif yang mencakup inisiatif pemberian makanan kepada hewan jalanan dan kampanye edukasi terkait kegiatan pemberian makanan kepada hewan jalanan serta kesejahteraan hewan. Saat ini, BALC beroperasi secara independen tanpa kolaborasi dengan lembaga pemerintah atau organisasi kesejahteraan hewan lainnya. Penelitian ini menguraikan tujuan dari inisiatif BALC, metodologi yang digunakan, dan temuan-temuan umum dari pelaksanaan program pemberian makan di jalanan dan kampanye kesadaran kesejahteraan hewan. Meskipun BALC beroperasi secara independen, temuan penelitian ini menunjukkan efektivitas inisiatif yang digerakkan oleh masyarakat dalam meningkatkan kesejahteraan hewan terlantar di Batam.
Implementasi Red Hat Web Console dalam Proses Pemantauan Sumber Daya Sistem Leonardo, Kevin; Haeruddin, Haeruddin; Aripradono, Heru Wijayanto
Madani: Jurnal Pengabdian Masyarakat dan Kewirausahaan Vol. 4 No. 1 (2025): Oktober 2025
Publisher : LPPM Universitas Internasional Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37253/madani.v4i1.11364

Abstract

Program pengabdian ini mengimplementasikan Red Hat Web Console (Cockpit) dalam memantau dan mengelola sistem berbasis Linux di PT Kinema Systrans Multimedia. Tujuan utama dari proyek ini adalah menciptakan solusi pemantauan yang efisien dan mudah diakses melalui antarmuka web. Metodologi yang digunakan meliputi instalasi RHEL, aktivasi Cockpit, serta pengujian fitur-fitur seperti pemantauan sistem, log, firewall, dan jaringan. Hasil implementasi menunjukkan kemudahan penggunaan, kemampuan pemantauan secara real-time, dan fleksibilitas akses jarak jauh yang dapat digunakan oleh mitra. Sehingga, Red Hat Web Console dapat menjadi solusi modern yang efektif untuk meningkatkan efisiensi administrasi server dalam lingkungan teknologi informasi.
Perbandingan Support Vector Machine, Random Forest Classifier, dan K-Nearest Neighbour dalam Pendeteksian Anomali pada Jaringan DDos Haeruddin Haeruddin; Erick Erick; Heru Wijayanto Aripradono
Jurnal Teknologi Informasi dan Multimedia Vol. 7 No. 1 (2025): February
Publisher : Sekawan Institut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/jtim.v7i1.628

Abstract

A Distributed Denial of Service (DDoS) attack poses a serious threat to network security and can disrupt online services by overwhelming the target server with excessive traffic. Effective detection of DDoS attacks requires a system capable of identifying anomalies in network traffic. In this context, Machine Learning (ML) offers an effective approach for classification and anomaly detection. However, different ML algorithms have varying strengths and weaknesses when processing large and complex network data. Therefore, this study aims to evaluate the performance of three ML algorithms: Support Vector Machine (SVM), Random Forest Classifier (RFC), and K-Nearest Neighbors (KNN) in detecting DDoS anomalies. The dataset used consists of 225,745 data points with 85 attributes that describe various characteristics of network traffic, such as destination port, flow duration, packet count, and packet size. This dataset is classified into two classes, BENIGN and DDoS, representing normal traffic and DDoS attacks, respectively. Evaluation is performed using several performance metrics, including accuracy, precision, recall, MCC (Matthews Correlation Coefficient), F-Measure, ROC Area, PRC Area, True Positive Rate (TPR), and False Positive Rate (FPR). The results show that the Random Forest Classifier (RFC) delivers the best performance with an accuracy of 99.99%, precision of 99.98%, recall of 100%, and a very low FPR of 0.02%. This is followed by the Support Vector Machine (SVM) with an accuracy of 99.91%, and the K-Nearest Neighbor (KNN) with an accuracy of 99.98%. All three algorithms demonstrate strong performance in detecting DDoS anomalies, with RFC slightly outperforming others in terms of consistency and higher classification capability. The findings of this study provide valuable insights for selecting the best algorithm to detect DDoS attacks in networks.
Student Satisfaction and Continuance Intention of E-learning System: University Student Perspective Heru Wijayanto Aripradono; Surya Tjahyadi; Winson Kennedy
JURNAL TEKNOLOGI DAN OPEN SOURCE Vol. 8 No. 1 (2025): Jurnal Teknologi dan Open Source, June 2025
Publisher : Universitas Islam Kuantan Singingi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36378/jtos.v8i1.3954

Abstract

The development of technology has also had an impact on changes in the digitalization of the world of education, which we know as online learning. Therefore, this study aims to examine the factors that influence student satisfaction and continuance intention in using the LMS-type e-learning system. This research uses ECM as model and quantitative approach by collecting questionnaires from 443 students in Batam City who come from different universities. After the questionnaire was collected, the research hypothesis variables were tested using SEM-PLS. The results of this study found that various indicators of interactivity, course content, and design quality positively significantly affect perceived usefulness, confirmation, and satisfaction, which then affects students continuance intention to continue to use the e-learning system to support the learning process. This research shows that students in Batam are satisfied and want to continue using the e-learning system as their learning support with interactivity and adequate course content and design quality. Even so, the development of e-learning systems must still be carried out in line with technological developments, and students need to maximize the results, satisfaction, and continuance of their intention towards the use of e-learning systems.
Analysis of Consumer Perceptions of Healthy Snacks Vivian, Vivian; Aripradono, Heru Wijayanto
Almana : Jurnal Manajemen dan Bisnis Vol. 9 No. 3 (2025): December
Publisher : Bandung: Prodi Manajemen FE Universitas Langlangbuana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36555/almana.v9i3.2948

Abstract

Healthy snacks are often one of the forgotten options for some people, with the mindset “Healthy snacks are not tasty, healthy snacks are tasteless.” However, not all healthy snacks are bland, it's more about the food we eat with the original or natural flavour of the food itself and no MSG added to the food. As awareness about the importance of healthy eating increases, there is a need to change consumer perceptions that healthy snacks are also delicious. Besides, there are some consumers who are confused to find healthy yet tasty snacks. In this case, an analysis of consumer perception for healthy snacks in Batam city will be conducted. This research will use qualitative methods in the form of interview, observation and the design thinking approach. The design thinking approach includes the stages of empathize, define, ideate, prototype and test to understand consumer needs and formulate problems. With this method, it is expected to create solutions to consumer perception for healthy snacks and provide one example of a healthy snack product idea.
Integrasi Feature Engineering dan SMOTE pada Algoritma Random Forest untuk Prediksi Kerusakan Chip RFID di Industri Sel Surya Haeruddin, Haeruddin; Winata, Franklin; Tresnawan, Muhammad Ilham Ashiddiq; Wijaya, Gautama; Wijayanto Aripradono, Heru
Journal of Information System Research (JOSH) Vol 7 No 2 (2026): January 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v7i2.9038

Abstract

The electronics industry, particularly solar cell manufacturing, demands production processes that are fast, precise, and supported by high data integrity. One critical component in the production flow is the chip embedded in the flower basket, which functions to store and transmit data through an RFID system. Damage to the chip can lead to information loss, tag reading failures, and disruptions in production efficiency and continuity. This study aims to predict chip status, classified as either normal or damaged, based on various process parameters, including immersion temperature, ambient humidity, process pressure, machine vibration, drying speed, heating and cooling duration, firing temperature, usage frequency, and RFID reading conditions. A feature engineering approach is applied to construct more representative derived features, while SMOTE is utilized to address class imbalance in the dataset. This study focuses on developing a predictive model using the Random Forest method to identify the most influential process variables related to chip damage risk. The data used in this study are obtained from historical production process records of a solar cell manufacturing plant. The results indicate that combinations of multiple process parameters significantly contribute to the potential risk of chip damage, and the Random Forest model demonstrates good predictive performance in classifying chip conditions. These findings suggest that the proposed model can serve as an early warning system to detect chip damage risks before they impact production processes. With proper implementation, the predictive model is expected to support preventive actions, enhance data integrity, and minimize disruptions in the solar cell manufacturing workflow.
Integrating artificial intelligence as a catalyst for entrepreneurship education in higher education: a conceptual framework for Indonesian higher education Aripradono, Heru Wijayanto
Priviet Social Sciences Journal Vol. 6 No. 4 (2026): April 2026
Publisher : Privietlab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55942/pssj.v6i4.1445

Abstract

This article proposes a conceptual framework for integrating Entrepreneurship Education, Artificial Intelligence Technology, and Educational Technology as a transformative catalyst for Higher Education in Indonesia. Higher education in Indonesia currently faces difficult challenges, where universities are required to produce graduates who are not only competent but also creative, innovative, and adaptive so that they can overcome the high unemployment rate among young people. A systematic literature review, which refers to entrepreneurship theories and the latest trends in Artificial Intelligence and education technology (over the past five years), reveals the synergistic potential of technology in shaping entrepreneurial mindsets and skills that are relevant to the needs of the times. Although Indonesia's digital ecosystem can be said to have developed rapidly and there are national policies from Indonesia Government related to AI, the implementation process faces significant challenges, such as infrastructure gaps and human resource readiness. The framework proposed in this study describes a holistic approach that includes AI-enriched curricula, Educational Technology-driven pedagogy, a robust digital support ecosystem, and AI-based assessment and analysis, all tailored to the Indonesian context. This article recommends strategic investment in digital infrastructure, capacity building for teaching staff, cross-sector and multi-stakeholder partnerships, and a robust AI ethics framework to realize the vision of higher education that produces socially responsible, ethical, and impactful entrepreneurs.
Co-Authors Abdul Wahab Alzi Alzi Andik Yulianto Ariadi, Cindy Arron Arron Avista Mindy Benhans, Devina Boby Candra Candra, Boby Christina Christina Christy Christy David David David Febrian Defryn Fratelry Willim Elisna Levia Elisna Levia Elvin, Elvin Erick Erick Ervin Setyawan Al Wen Jun Evander, Owen Febrianto Febrianto, Febrianto Felix Felix Felix Jethro Holly Galang, Yehezkiel Putra Gautama Wijaya Gracia, Nicole Haeruddin Haeruddin Haeruddin Haeruddin, . Hengki Hengki Hirawan, Jason Idayanti Nursyamsi Ikhlas, Junior Jemmy Jemmy Jerry Jardian Jery Tango Jong, Ricky Jucelyn, Devica Kelvianto Kelvin Kelvin Kevin Anderson Kevin Anderson Kisusyenni Kisusyenni Venessa Kisusyenni Venessa Kurnia Cantra Kurniawan, Jasen Lau, Vionny Leonardo, Kevin Lim, Daniel Melvin, Melvin Mettatama Gandha Puspita Michael Owen Mieko Huang Vincent Muhammad Ardiansyah Muhammad Ardiansyah Muhammad Dzaky Akbar Muhammad Rivaldy Hisham Natalia , Sherly Celia Ningsih, Vivian Febri Nursudiono Nursudiono Nursudiono, Nursudiono Peiwen , Sally Tan Prasetyo, Stefanus Eko Putra, Rezki Sari Raudlatul Khairiah Ricardo Ricardo Ricardo Rio Putra, Rio Ruben Pangeran Pangestu Silvina Silvina Silvina, Silvina Sofyanti, Sofyanti SULTAN, ZULKIFLI Te, Celine Tiffany, Evellyn Try Tina Tina Tjahyadi, Surya Tresnawan, Muhammad Ilham Ashiddiq Vanessa Felicia Leedora Vincent Vanessa Ting Vincent Vincent Vivian Vivian Vivian Vivian Viviany Viviany Wandi Wandi William Wilsen Lau Winata, Franklin Winson Kennedy Winson Ng Yap Rui Qi, Katherine Oktaviani