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All Journal Infotech Journal Sinkron : Jurnal dan Penelitian Teknik Informatika JURNAL MEDIA INFORMATIKA BUDIDARMA IKRA-ITH Informatika : Jurnal Komputer dan Informatika Journal Information System Development IJISTECH (International Journal Of Information System & Technology) Building of Informatics, Technology and Science Jurnal Mantik REMIK : Riset dan E-Jurnal Manajemen Informatika Komputer Journal of Computer Networks, Architecture and High Performance Computing IJISTECH DEVICE Jurnal Abdimas ADPI Sains dan Teknologi Jurnal Pengabdian Kepada Masyarakat Jurnal Inkofar Jurnal Sains dan Teknologi Jurnal Pengabdian Masyarakat Bidang Sains dan Teknologi SATIN - Sains dan Teknologi Informasi Journal of Data Mining and Information Systems Jurnal Bersama Pengabdian Kepada Masyarakat
Romindo
Universitas Pelita Harapan, Jakarta
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Sosialisasi Peran Virtual Reality terhadap Pembelajaran dan Edukasi Kevin Bastian Sirait; Jefri Junifer Pangaribuan; Okky Putra Barus; Triandes Sinaga; Romindo, Romindo
ABDIKAN: Jurnal Pengabdian Masyarakat Bidang Sains dan Teknologi Vol. 4 No. 2 (2025): Mei 2025
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55123/abdikan.v4i2.5022

Abstract

Education orients on the process of transferring and acquiring knowledge and skills from learning activities. With the use of Virtual Reality (VR) in education, it can help students to experiment with the learned concepts and assess their implications within the virtual environment. The idea and implementation of VR in education are crucial since they enhance the student’s learning experience and process to understand various concepts and implement them to solve problems. Therefore, this socialization aims to provide deeper insights to the students of SMA Chandra Kumala Medan on how VR can help them improve their learning experience and performance. At this event, the socialization is conducted by following three sessions: (1) material presentation, (2) questions and answers session, and (3) VR demonstration where the students can take part. The results show that the students are highly engaged in all three sessions. It is found in the questions asked by the students, from how to create a virtual environment to the roles and impact of VR in real life (e.g., business). These findings indicate that the students are interested in how VR can improve their learning experience by understanding and testing new ideas or concepts within the virtual environment.
Analisis Kualitas Wine Menggunakan Machine Learning dengan Pendekatan SMOTE dan Seleksi Fitur Triandes Sinaga; Kevin Bastian Sirait; Pangaribuan, Jefri Junifer; Barus, Okky Putra; Romindo, Romindo
INSOLOGI: Jurnal Sains dan Teknologi Vol. 4 No. 3 (2025): Juni 2025
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55123/insologi.v4i3.5436

Abstract

Conventional wine quality assessment remains reliant on subjective expert judgment, which introduces potential bias and inconsistency in quality control processes. This study aims to develop an objective and automated machine learning-based classification model to enhance the accuracy of wine quality prediction. To address the issue of class imbalance, the Synthetic Minority Over-sampling Technique (SMOTE) was applied, along with ANOVA F-test-based feature selection to optimize model performance. The White Wine Quality dataset from the UCI Machine Learning Repository (4,898 samples, 11 numerical features) was utilized to evaluate five classification algorithms: Naïve Bayes, Decision Tree, Random Forest, Support Vector Machine (SVM), and K-Nearest Neighbors (KNN). Before SMOTE application, the Random Forest model achieved an accuracy of only 67.55%. After implementing SMOTE and parameter tuning, the Random Forest (Tuned) model demonstrated the best performance with 90.29% accuracy, 89.99% precision, 90.29% recall, and 89,97%.  % F1-score. Additionally, Decision Tree and KNN algorithms also exhibited notable improvements. SMOTE effectively balanced extreme minority class representations (quality levels 3 and 9). The most influential features in quality classification were alcohol content, density, and chlorides. These findings indicate that the proposed framework offers a reliable, objective, and scalable solution for automated wine quality control in industrial production environments.
OPTIMALISASI ALGORITMA C4.5 TERHADAP METODE DECISION TREE DALAM MENENTUKAN PLAFON KREDIT NASABAH Romindo, Romindo; Barus, Okky Putra; Pangaribuan, Jefri Junifer
Device Vol 14 No 1 (2024): Mei
Publisher : Fakultas Teknik dan Ilmu Komputer (FASTIKOM) UNSIQ

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32699/device.v14i1.6877

Abstract

The most basic banking activity is collecting money and buying money from the whole society. Then sell the collected money by directing it to the community through credit or credit. However, it is often found that customers are unable to pay their receivables based on the amount of receivables which often exceeds the specified payment period. Therefore, banking companies must know the ability to pay customers by providing credit limits to avoid losses. The purpose of this study was to analyze the data using the Decision Tree method with the C4.5 Algorithm on the report data of BPR Pijer Podi Kekelengen receivables in order to determine the customer's credit ceiling. From the data obtained from the accounts receivable report, the company produces 5 attributes, namely Payments, Receivables, Transactions, Recommendations, and Ceiling where the decision label is Ceiling. After testing the report data at BPR Pijer Podi Kekelengen using the Decision Tree method with the C4.5 Algorithm, it is concluded that if the ceiling is large, the payment is not good.
Penyuluhan Mengenai Artificial Intelligence Untuk Siswa-Siswi SMP dan SMA Sekolah Lentera Harapan Medan Barus, Okky Putra; Pangaribuan, Jefri Junifer; Romindo, Romindo; Anggara, Alfin; William, William
ABDIKAN: Jurnal Pengabdian Masyarakat Bidang Sains dan Teknologi Vol. 2 No. 4 (2023): November 2023
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55123/abdikan.v2i4.2281

Abstract

Artificial Intelligence (Artificial Intelligence or AI) is a field that is growing rapidly and has great potential in influencing various aspects of human life. AI education is important for the younger generation in facing future challenges. This study aims to teach the basics of AI to junior high school (SMP) students at Sekolah Lentera Harapan (SLH). Learning sessions are carried out using interactive methods and actively involve students in discussions. The material includes an introduction to AI, the history and purpose of AI, how it works, the types of AI, and the advantages and disadvantages of AI. AI needs data to come up with appropriate answers, and with time, it will learn and improve. There are three types of AI, namely Artificial Narrow Intelligence (limited AI), Artificial General Intelligence (general AI), and Artificial Superintelligence (super AI). The advantages of AI include fast data processing, job efficiency and handling of dangerous tasks. However, there are also drawbacks such as reliance on big data, limitations to the specific capabilities of AI, and security concerns. This research provides insight into AI and promotes optimal use of AI in society.
Generative AI for Students: Inovasi Pembelajaran Digital untuk Peningkatan Pemahaman dan Manfaatnya bagi Mahasiswa Okky Putra Barus; Yugopuspito, Pujianto; Pangaribuan, Jefri Junifer; Romindo, Romindo
PaKMas: Jurnal Pengabdian Kepada Masyarakat Vol 5 No 2 (2025): November 2025
Publisher : Yayasan Pendidikan Penelitian Pengabdian Algero

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54259/pakmas.v5i2.3699

Abstract

The rapid development of artificial intelligence (AI) technology demands increased AI literacy among students. Generative AI, as a growing branch of AI, offers great potential to transform the learning process. Unfortunately, the level of AI literacy in Indonesia is still low. The study "The ASEAN Digital Generation Report 2023" by Kearney shows that Indonesia ranks 4th out of 6 Southeast Asian countries in readiness to face the AI era. In response, a team of lecturers from Universitas Pelita Harapan (UPH) developed a digital learning program called "Generative AI for Students." This program aims to improve students' understanding of the concepts, applications, and tools of Generative AI, especially in the academic context. This program's development uses the ADDIE method, which includes analysis, design, development, implementation, and evaluation. The "Generative AI for Students" program is implemented through the SPADA platform, utilizing features such as the Learning Management System (LMS), discussion forums, and quizzes. The evaluation results show that this program has succeeded in increasing students' understanding of Generative AI. This is indicated by an increase in post-test scores and a high level of participant satisfaction. The "Generative AI for Students" program positively increases AI literacy and equips students with skills relevant to technological developments.
Penguatan Kompetensi Pelaku UMKM dalam Penerapan Strategi Digital Marketing melalui Kegiatan Seminar Angelia Putriana; Romindo, Romindo
Jurnal Bersama Pengabdian Kepada Masyarakat (SAMAMAS) Vol. 1 No. 4 (2025): Desember 2025
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55123/samamas.v1i4.480

Abstract

Usaha Mikro, Kecil, dan Menengah (UMKM) play a strategic role in promoting economic growth and job creation. However, many UMKM actors still face limitations in optimally utilizing digital marketing strategies due to low digital literacy and limited understanding of technology-based marketing. This community service activity aims to strengthen the competencies of UMKM actors in implementing digital marketing strategies through an educational and practical seminar. The activity was conducted on Saturday, March 22, 2025, from 15:00 to 18:00 WIB, located at Jl. Pertahanan No. 32, Timbang Deli, Medan Amplas District, Medan City, North Sumatra (GBI Metro Building). The implementation methods included material presentations, interactive discussions, and question-and-answer sessions covering fundamental concepts of digital marketing, the use of social media as a promotional tool, digital content creation strategies, and the introduction of relevant digital marketing platforms for UMKM. The results of the activity indicate an increase in UMKM actors’ understanding, awareness, and motivation regarding the importance of digital marketing in enhancing business competitiveness. This seminar contributes to improving the digital literacy of UMKM actors and encourages the adoption of more adaptive and sustainable marketing strategies in the era of digital transformation.
Integrasi Filsafat Ilmu dan Etika dalam Pengembangan Model Analisis Sentimen Berbasis IndoBERT pada Wacana #IndonesiaEmas2045 Romindo, Romindo; Mahyuddin K. M. Nasution
INSOLOGI: Jurnal Sains dan Teknologi Vol. 5 No. 1 (2026): Februari 2026
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55123/insologi.v5i1.7231

Abstract

The philosophy of science positions scientific knowledge as the result of a systematic and logical thought process grounded in clear ontological, epistemological, and axiological foundations. In the context of computer science, the philosophical approach serves as an essential framework to ensure that the development of artificial intelligence-based models is not merely technical in nature but also founded on rational reasoning and ethical responsibility. This study integrates the paradigm of the philosophy of science with the development of an IndoBERT-based sentiment analysis model for social media comments under the hashtag #IndonesiaEmas2045. Through ontology, this research establishes digital social interactions as a legitimate object of scientific inquiry; through epistemology, it applies computational logic and machine learning–based scientific methods to interpret public opinion; and through axiology, it utilizes the analytical results to understand societal perceptions and support data-driven public policy. The model testing results demonstrate high performance with an accuracy of 96.5%, validating the coherence between a philosophical scientific approach and an empirical computational methodology. Therefore, this study not only contributes to the advancement of Indonesian-language sentiment analysis technology but also strengthens the scientific dimension of computer science within the framework of the philosophy of science.
Kuantifikasi Prioritas Pengembangan Fitur Aplikasi dengan Kerangka Outcome-Driven Innovation: Studi Kasus Aplikasi Pembelajaran Bahasa Asing Kevin Bastian Sirait; Dickson, Nicholas; Romindo, Romindo
INSOLOGI: Jurnal Sains dan Teknologi Vol. 4 No. 6 (2025): Desember 2025
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55123/insologi.v4i6.6762

Abstract

This study aims to identify user satisfaction, importance, and development priorities for the English Language Speech Assistant (ELSA) application by integrating Outcome-Driven Innovation (ODI) and sentiment analysis methods. Using reviews collected from the Google Play Store via ScrapeStorm, two sentiment models were applied. Namely, Valance Aware Dictionary and sEntiment Reasoner (VADER) for overall sentiment polarity and Aspect-Based Sentiment Analysis (ABSA) for feature-spesific sentiment extraction. The result show that 86.23% of user reviews express positive sentiments, reflecting high satisfaction with ELSA’s functionality and learning experience. Correlation testing confirms strong validity between VADER and ABSA models (r = 0.98), and moderate alignment with user rating (r  0.55), confirming both construct and external validity. The ODI analysis further identifies Pronunciation as the highest-priority aspect (opportunity = 12.1), followed by Learning (opportunity = 2.6), highlighting key areas for innovation. Other aspects, such as Support and Subscription, show balanced performance with low opportunity values. The integration of ODI and sentiment analysis provide a data-driven framework for product improvement, enabling developers to prioritize enhancements based on user-perceived value. The findings contribute to informed strategic decision-making in the development of digital language-learning applications.
Co-Authors Angelia Putriana Anggara, Alfin Asnawi, Muhamad Fuat Baihaqy, M Alif Muwafiq Barus, Okky Putra Chandra, Wenripin Dickson, Nicholas Ferawaty Ferawaty, Ferawaty Hidayat, Muslim Hondro, Ety Debora Ilhami, Mirza Jamaludin . Jefri Junifer Pangaribuan Kevin Bastian Sirait Mahyuddin K. M. Nasution Pangaribuan, Jefri Junifer Siti Hardianti Siti Hardianti, Siti Tjokro, Stanley Triandes Sinaga Ulfa, Ayu Wiliem, Evelyn William William Yudhistira Adhitya Pratama Yugopuspito, Pujianto