Article Per Year (5 Year)
p-Index From 2021 - 2026
9.751
P-Index
This Author published in this journals
All Journal International Journal of Electrical and Computer Engineering JURNAL MEDIA INFORMATIKA BUDIDARMA JTAM (Jurnal Teori dan Aplikasi Matematika) SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan INTECOMS: Journal of Information Technology and Computer Science Journal of Education and Instruction (JOEAI) JSiI (Jurnal Sistem Informasi) JURNAL PENDIDIKAN TAMBUSAI JOURNAL OF SCIENCE AND SOCIAL RESEARCH JURNAL TEKNOLOGI DAN ILMU KOMPUTER PRIMA (JUTIKOMP) JISICOM (Journal of Information System, Infomatics and Computing) Journal of Information System, Applied, Management, Accounting and Research JURNAL TEKNOLOGI INFORMASI Jurnal Ekonomi Manajemen Jurnal Pendidikan dan Konseling Jurnal Informatika dan Rekayasa Perangkat Lunak Jurnal Sains dan Teknologi Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) SENADA : Semangat Nasional Dalam MengabdI Jurnal Indonesia : Manajemen Informatika dan Komunikasi Jurnal Sosial dan Teknologi International Journal Software Engineering and Computer Science (IJSECS) KERNEL: Jurnal Riset Inovasi Bidang Informatika dan Pendidikan Informatika Jurnal Tren Bisnis Global Malcom: Indonesian Journal of Machine Learning and Computer Science Publikasi Pengabdian Masyarakat Komputer dan Teknologi (PUNDIMASKOT) Journal of Artificial Intelligence and Digital Business CKI On Spot Kohesi: Jurnal Sains dan Teknologi SENADA : Semangat Nasional Dalam Mengabdi Jurnal Indonesia : Manajemen Informatika dan Komunikasi Repeater: Publikasi Teknik Informatika dan Jaringan International Journal of Information Engineering and Science International Journal of Mechanical, Electrical and Civil Engineering Journal of Engineering, Electrical and Informatics
Arinal, Veri
STIKOM Cipta Karya Informatika Jakarta, Indonesia
Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management 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 Other

Published : 78 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 78 Documents
Search

 4   5   6   7   8 
Efektivitas Penggunaan Ruang Warna HSV untuk Klasifikasi Daging Sapi Segar dan Busuk dalam Industri Pangan Dadang Iskandar Mulyana; Veri Arinal; Feri Akbarulloh
Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 9 No 1 (2025): JANUARI-MARET 2025
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.v9i1.3129

Abstract

Beef is a source of animal protein which is very important in the human diet. The quality of beef determines the nutritional value and taste of the processed meat product. However, the quality of beef can decrease over time, especially if it is not stored properly. Therefore, identifying the condition of beef is crucial to ensure that consumers get safe and quality products. The use of the HSV (Hue, Saturation, Value) color space for beef classification is an interesting method to research. The HSV color space is closer to human perception of color compared to the RGB color space, making it more effective for image analysis in the context of visual quality assessment of meat. In this study, researchers used HSV space extraction to classify fresh beef and bad beef. This research aims to develop a method for classifying fresh, medium and rotten beef using the HSV color space. This research produces accurate extraction results with appropriate classification of fresh and bad beef.
Expert System for Diagnosing Brain Tumors Using the Certainty Factor (CF) Method Veri Arinal; Nuary Inaldi Simarmata
Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 9 No 3 (2025): JULI-SEPTEMBER 2025
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.v9i3.3825

Abstract

The development of computer technology helps many aspects of life. One aspect of life that takes advantage of technological developments is the health sector, in order to solve problems including brain tumors. Brain Tumor Disease is the growth of abnormal cells in or around the brain in an unnatural and uncontrolled manner. Patients with brain tumors continue to increase every year, because the initial symptoms are often underestimated. Therefore created a software that can help diagnose brain tumors using the certainty factor method.
Integrating Sustainable Development Goals into educational information systems: toward a theoretical model for sustainable school management Arinal, Veri; Miswanto, Miswanto; Setiawan, Kiki; Rahayu, Agus Tanti
International Journal of Electrical and Computer Engineering (IJECE) Vol 16, No 3: June 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v16i3.pp1350-1359

Abstract

This research addresses the critical challenge of implementing Sustainable Development Goal (SDG) 4, "Quality education," in Indonesian secondary schools. While national policies exist, schools lack a systematic digital tool to plan, monitor, and evaluate sustainability-based activities against concrete SDG indicators. To bridge this gap, this study employs a six-cycle design science research (DSR) methodology to develop a theoretical model for a sustainable education information system. The model is designed to integrate SDG principles into school management, enabling systematic data handling, adaptive curriculum functions, and real-time monitoring. A web-based prototype was developed using a React.js frontend and Node.js backend and evaluated through a mixed-methods approach. Data from interviews with 15 administrators and surveys of 97 teachers (yielding a usability satisfaction score of 4.34/5) validated the model’s effectiveness in making educational administration more efficient, transparent, and quality-oriented. The resulting artifact serves as a foundational technical and managerial reference for schools, education offices, and policymakers to leverage information technology in fostering a sustainable, participatory learning culture aligned with the SDGs.
Inovasi Pembelajaran Menggunakan Teknologi AI di SDN Jatirahayu 4 Raudhan, Muhammad Nurur; Arinal, Veri; Nugroho, Adityo Purwo; Wardana, Shabrina Sukma
JOEAI (Journal of Education and Instruction) Vol. 8 No. 3 (2025): JOEAI (Journal of Education and Instruction)
Publisher : Institut Penelitian Matematika, Komputer, Keperawatan, Pendidikan dan Ekonomi (IPM2KPE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31539/joeai.v8i3.14525

Abstract

Penelitian ini bertujuan untuk mengevaluasi efektivitas penerapan teknologi Artificial Intelligence (AI) dalam proses pembelajaran di SDN Jatirahayu 4. Metode yang digunakan meliputi sosialisasi, pelatihan guru, serta penggunaan ChatGPT, Canva for Education, dan Kahoot dalam kegiatan belajar-mengajar. Data dikumpulkan melalui observasi, wawancara, dan kuesioner kepada guru dan siswa kelas 5. Hasil penelitian menunjukkan bahwa penggunaan AI mampu meningkatkan interaktivitas dan motivasi belajar siswa, meskipun masih ditemukan tantangan seperti keterbatasan infrastruktur teknologi dan pemahaman awal yang rendah tentang AI. Sosialisasi dan pelatihan yang intensif terbukti efektif meningkatkan literasi digital di lingkungan sekolah. Kata Kunci: Artificial Intelligence, Pembelajaran Berbasis AI, Keterlibatan Siswa, Efektivitas Pengajaran, Inovasi Pendidikan.
Satisfaction Level Analysis QRIS Users Based on Experience and Perception Twitter Users/X Using Naive Baiyes Veri Arinal; Satria Wira Yudha; Muhammad Joko Umbaran Kharis Bahrudin; Dessyanti Ryantina
International Journal of Information Engineering and Science Vol. 2 No. 4 (2025): November : International Journal of Information Engineering and Science
Publisher : Asosiasi Riset Teknik Elektro dan Infomatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijies.v2i4.53

Abstract

QRIS (Quick Response Code Indonesian Standard) has become a widely used national digital payment standard. User satisfaction with this service needs to be monitored continuously to ensure its sustainability. This study aims to predict the level of QRIS user satisfaction based on their experiences and perceptions expressed organically on the Twitter social media platform. The method used is sentiment analysis with the Naive Bayes classification algorithm implemented using RapidMiner software. The research data was obtained from Twitter user comments collected through web scraping techniques. The text data then went through a preprocessing stage that included cleansing, stopword filtering, stemming, and tokenizing to be prepared as features ready to be processed by the model. The data was divided into training (80%) and testing (20%) subsets for model training and validation. The results showed that the Naive Bayes model was able to predict user satisfaction sentiment with an accuracy of 80.99%. These findings indicate that the model is highly accurate in identifying satisfied comments and sufficiently sensitive in detecting dissatisfaction. This study concludes that sentiment analysis of Twitter UGC data using Naive Bayes is an effective and efficient approach for predicting QRIS user satisfaction in real time. The practical implication of this study is to provide an automatic feedback system for service providers to monitor public sentiment and take targeted corrective actions.
Implementation of Naive Bayes Algorithm and Support Vector Machine for Public Sentiment Analysis towards Imported Clothing Ban Veri Arinal; Frencis Matheos Sarimole; Kiki Setiawan; Ahmad Ramdani
Journal of Engineering, Electrical and Informatics Vol. 2 No. 3 (2022): Oktober: Journal of Engineering, Electrical and Informatics:
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jeei.v2i3.313

Abstract

This research was conducted to find out the public's opinion on the Issue of Imported Clothing on Twitter social media. One of the algorithms that can be used to carry out sentiment analysis is Naïve Bayes and Support VectorMachine. In this research the author aims to use the Naïve Bayes Algorithm and Support Vector Machine in analyzing positive and negative sentiment labels. The final result of the comparison with these two test methods, namely the prediction of public sentiment on the issue of imported clothing based on data obtained from Twitter and implemented using the SVM (Support Vector Machine) method, shows an accuracy value of 87.89%. Of the 603 test data, it is predicted that 194 data are Positive Sentiment and 409 data are Negative Sentiment. For prediction results from Negative Sentiment, there are 603 data predicted Negative and 2 data predicted Positive. and the Naive Bayes method shows an accuracy value of 97.01%. Of the 603 test data, it is predicted that 409 data are Negative Sentiment and 194 data are Positive Sentiment.
Implementation of Android-Based Futsal Court Booking Application Using Flutter (Case Study: Futsal Hayani Kopti, West Cengkareng) Veri Arinal; Mesra Betty Yel; I Komang Dewa Ananda Putra; Fauzan Azima; Mohammad Farhan; Muhammad Ikhsan Hakim; Dadang Mulyana Iskandar; Sutisna Sutisna
International Journal Software Engineering and Computer Science (IJSECS) Vol. 6 No. 1 (2026): APRIL 2026
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET) - Lembaga KITA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v6i1.6496

Abstract

The rapid development of information technology has encouraged service providers to improve efficiency and service quality, including in futsal court rental services. At Futsal Hayani Kopti Cengkareng Barat, the court booking process is still conducted manually through phone calls or direct visits, which often results in scheduling conflicts, limited access to information, and unstructured data management. These conditions reduce the effectiveness and efficiency of the booking process. This practical work aims to design and implement an Android-based futsal court booking application using the Flutter framework. The developed application provides real-time information on court availability, rental prices, facilities, and online booking features. In addition, the system assists administrators in managing booking schedules and transaction data in a centralized manner. The research method applied is qualitative, employing observation, interviews, documentation, and literature study. System development follows the System Development Life Cycle (SDLC) approach with an internet-based client–server architecture. The implementation results indicate that the application improves booking efficiency, reduces scheduling conflicts, and enhances service quality as well as user satisfaction.
Chili Pepper Variety Detection System Using the Principal Component Analysis Method Veri Arinal; Frencis Matheos Sarimole; Sugeng Sugeng; Rindy Julianda
International Journal of Mechanical, Electrical and Civil Engineering Vol. 1 No. 1 (2024): January : International Journal of Mechanical, Electrical and Civil Engineering
Publisher : Asosiasi Riset Ilmu Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/ijmecie.v1i1.273

Abstract

In the agricultural sector, the automatic identification of chili pepper varieties is crucial for improving production efficiency and quality. This study developed a chili pepper variety detection system based on characteristics using the Principal Component Analysis (PCA) method. The PCA method was used to reduce the dimensionality of chili pepper image data, thereby facilitating the classification process while retaining the key features necessary for chili pepper variety identification. The recognition system for chili pepper identification involves inputting chili pepper image data into a computer. The computer then interprets and identifies the chili pepper variety, and the test data utilizes a dataset of chili pepper images from various varieties. The research results indicate that the proposed system achieves a high level of accuracy in detecting and classifying chili pepper varieties. Consequently, this system can assist farmers and agricultural industry stakeholders in the chili pepper sorting and selection process, thereby improving operational efficiency and the quality of the harvest.
Co-Authors Adella Fitriany Cahyana Agus Tanti Rahayu Ahluna, Faza Ahmad Ramdani Ahmad Tarwanto Akbar, Yuma Akbarulloh, Feri Ali Akbar Ali Akbar Andriyana Fajar Angel, Gadies Anggi Ramadhan Anisa Puji Ikawati Anita Rosiana Arribatullah, Arribatullah Artha Patricia Atik Budi Paryanti Azizi, Doni Betty Yel, Mesra Bobby Arvian James Buulolo, Rupawan Calvin Bill Christian Gunawan Citra Pricylia Ananda Mulya Dadang Iskandar Mulyana` Dava Septya Arroufu Dede Sarikah Dessyanti Ryantina Dhita Aidilla Dicky Saputra Dirgantoro, Bagus Dita Safira Dita Yuliana Dita Yuliana Doni Azizi Edi Nurhadi Edwin Sentosa Fajar, Andriyana Fauzan Azima Fa’aso Lase Febri Yoga Harjanto Feri Akbarulloh Fikryadi, Fikryadi Fiktor Kurnia Fiky Alan Nuari Fileni Zalukhu I Komang Dewa Ananda Putra Ilham Wahyudi Indah Rosmalina Josua Pangaribuan Kiki Setiawan Kurniawan Irfan Nauval M. Rohyan Zidan M.Rafli Fadillah M.Taufik Maulida, Aulia Melani, Melani Afsari Melli Puspita S Miftahul Ulum Miftahul Ulum Miswanto, Miswanto Mohammad Farhan Muhammad Ikhsan Hakim Muhammad Joko Umbaran Kharis Bahrudin Mulya, Citra Pricylia Ananda Nauval, Kurniawan Irfan Nayoan, Vallen Ezra Piter Niarti Agustiani Nova Esterina Silitonga Novi Septiani Nuary Inaldi Simarmata Nuary Inaldi Simarmata Nugroho, Adityo Purwo Nur Arif Khairudin Nurul Khoiriyah Nurwijayanti Paryanti, Atik Budi Patricia, Artha Prabowo, Renno Sandi Prabowo, Reno Sandi Prakoso Angga I Purnomo, Bening Sari Puspita, Melli Putra, Adaffi Aditya Putra, Adhy Hantar Putri Nugraheni Utami Putri, Seftiana Eka Radikto Rahayu, Agus Tanti Ramadhan, M. Anggi Raudhan, Muhammad Nurur Refi Nabillah Royadi Reza Setiawan Reza Setiawan Reza Wanandi Riko Afriandika Rindy Julianda Rizky Adawiyah Rodhiyah Rodhiyah Romadan, Diva Putra Ronny Budi Santoso Rusmarhadi, Irma Ryantina, Dessyanti Safira, Dita Saidah, Andi Sarimole, Francis Matheus Sarimole, Frencis Matheos Satria Wira Yudha Septiyana Bila Setiawan, Kiki Setya Putra Adenugraha Shakila Shila Wati Shindy Apriyani Siti Nurhaliza Siti Raysyah Stepanus Stepanus Sugeng Sugeng Sugiyono Sugiyono Sugiyono Sugiyono Sutisna Sutisna Sutisna Sutisna Sutisna Sutisna Tundo, Tundo Wandi Sanip Wardana, Shabrina Sukma Yaqien, Akmal Yuliya Putri P Yunita T Lubis