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All Journal Semantik Pro Bisnis Telematika JUITA : Jurnal Informatika JOIV : International Journal on Informatics Visualization RABIT: Jurnal Teknologi dan Sistem Informasi Univrab JITK (Jurnal Ilmu Pengetahuan dan Komputer) Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Journal of Information Systems and Informatics Jambura Journal of Electrical and Electronics Engineering Community Engagement and Emergence Journal (CEEJ) TIN: TERAPAN INFORMATIKA NUSANTARA Journal of Soft Computing Exploration Jurnal Pendidikan dan Teknologi Indonesia Jurnal Pendidikan Sains dan Komputer Jurnal Pengabdian Masyarakat : Pemberdayaan, Inovasi dan Perubahan Journal of Artificial Intelligence and Engineering Applications (JAIEA) International Journal of Health, Engineering and Technology Jurnal Penelitian Sistem Informasi Jurnal Ilmiah Multidisiplin Indonesia Journal of Information Technology and Cyber Security Jurnal Siber Multi Disiplin Jejak digital: Jurnal Ilmiah Multidisiplin Jurnal Teknik Informatika dan Teknologi Informasi International Journal of Machine Learning (IJOML)
Purwadi Purwadi
Magister Ilmu Komputer, Fakultas Ilmu Komputer, Universitas Amikom Purwokerto
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Analysis of the Effect of Price on Students Purchase Interest Using Linear Regression Yulia Risma Yanti; Novitasani Putri; Purwadi Purwadi
Jurnal Ilmiah Multidisiplin Indonesia (JIM-ID) Vol. 5 No. 05 (2026): Jurnal Ilmiah Multidisplin Indonesia (JIM-ID), May 2026
Publisher : Sean Institute

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

Abstract

This study aims to analyze the effect of price on students’ purchase intention using a simple linear regression method. This research adopts a quantitative approach with data collected through questionnaires distributed to 94 student respondents. The independent variable is price, while the dependent variable is purchase intention. The results show that price has a positive and significant effect on students’ purchase intention, with a regression coefficient value of 0.58. This indicates that an increase in perceived price value will be followed by an increase in purchase intention. In addition, the coefficient of determination (R²) of 0.36 indicates that price explains 36% of the variation in purchase intention, while the remaining 64% is influenced by other factors outside this study. The significance test also shows that the effect of price on purchase intention is statistically significant. Therefore, it can be concluded that price is an important factor influencing students’ purchase intention, although other factors also play a role in the purchasing decision process.
A Hybrid Feature-Enriched IndoBERT Framework for Sentiment Analysis of Ride-Hailing Service Reviews in Indonesia Puas Triawan; Imam Tahyudin; Purwadi
Journal of Information System and Informatics Vol 8 No 2 (2026): April
Publisher : Asosiasi Doktor Sistem Informasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63158/journalisi.v8i2.1587

Abstract

This study examines sentiment classification for Indonesian ride-hailing user reviews, which often contain informal expressions, ambiguity, and strong contextual dependency. Existing studies commonly rely on either traditional machine learning or transformer-based models, while limited attention has been given to integrating heterogeneous feature representations. To address this gap, this study proposes a feature-level hybrid integration strategy combining TF-IDF and IndoBERT embeddings. This approach enables the model to capture statistical term importance and contextual semantic meaning within a unified representation. A quantitative experimental design was applied to approximately 20,000 reviews collected from Gojek, Grab, and Maxim. Sentiment labels were generated through rating-based mapping and manually validated for consistency. The dataset, which was relatively balanced across positive, neutral, and negative classes, was divided into training and testing sets using an 80:20 split. Model performance was evaluated on the test set using accuracy, precision, recall, and F1-score. The proposed hybrid model achieved the highest accuracy of 93.5%, outperforming IndoBERT (91.8%) and traditional machine learning models (78.4%–87.6%). The results show that feature-level integration improves sentiment classification performance, although neutral sentiment remains challenging due to contextual ambiguity.
Analisis Hubungan Durasi Penggunaan Smartphone dan Produktivitas Belajar Mahasiswa: Studi Eksploratif Monte Carlo Panca Ragil Prasetyo; Purwadi Purwadi
TIN: Terapan Informatika Nusantara Vol 7 No 1 (2026): June 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v7i1.9911

Abstract

The rapid development of digital technology has made smartphones an essential part of students' academic activities. However, the high intensity of smartphone usage raises questions regarding its relationship with learning productivity. This study aims to analyze the relationship between smartphone usage duration and learning productivity among Informatics students and to explore the data using a Monte Carlo simulation approach. The study was conducted on 80 second- and fourth-semester Informatics students at Amikom University Purwokerto. Data analysis included descriptive statistics, validity testing, reliability testing, normality testing, Pearson correlation analysis, simple linear regression, and Monte Carlo simulation with 1,000 iterations using Python. The results revealed a Pearson correlation coefficient of with a significance value of indicating a negative but statistically insignificant relationship between smartphone usage duration and learning productivity. Simple linear regression analysis produced the regression equation with a coefficient of determination of , indicating that smartphone usage duration explains only a small proportion of the variance in students' learning productivity. Monte Carlo simulation was employed as an exploratory approach to illustrate the potential variation in learning productivity based on the characteristics of the observed data. The simulation results demonstrated variability in learning productivity scores across different smartphone usage scenarios; however, these findings cannot be interpreted as evidence of a significant effect between the two variables. This study concludes that the relationship between smartphone usage duration and learning productivity among Informatics students tends to be weak and is influenced by various factors beyond the scope of the proposed model. Therefore, further research with a larger sample size and additional explanatory variables is recommended to achieve a more comprehensive understanding of student learning productivity in the digital era. The contribution of this research lies in providing empirical evidence regarding the weak relationship between the two variables among informatics students, as well as demonstrating that the Monte Carlo simulation can be utilized as an exploratory approach to illustrate variations in possible outcomes based on empirical data characteristics, rather than as a conclusive predictive tool.
Integrasi Coding dalam Pembelajaran Statistika dan Probabilitas di SMK: Dampak terhadap Kompetensi Siswa: Coding Integration in Statistics and Probability Learning in Vocational High Schools: Impact on Student Competence Fairus Aufa Baharita; Ilham Suryo Saputra; Rehandika Priambudi; Hamzah Tsabit Akdama; Ilham Robbani; Purwadi Purwadi
Jurnal Pendidikan Sains dan Komputer Vol. 6 No. 02 (2026): Call for Papers Juni 2026
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/jpsk.v6i02.8777

Abstract

The development of digital technology has driven the need for learning innovations that not only improve understanding of mathematical concepts but also develop students' digital skills. One possible approach is to integrate a coding platform into the learning of probability and statistics in Vocational High Schools (SMK). This study aims to analyze the implications of using a coding platform on students' understanding of probability and statistics concepts, data analysis skills, and the development of digital skills. The research method is a descriptive approach that employs coding-based learning simulations in Python. Implementation is carried out through probability simulation activities, statistical data processing, data visualization, and project-based learning. Data processing uses 500 student grades to calculate measures of central tendency, analyze data distribution, and automatically generate statistical visualizations. The results show that using a coding platform can facilitate understanding of probability through interactive simulations, improve students' ability to efficiently process and analyze large amounts of data, and help create more accurate and understandable data visualizations. The integration of coding into learning fosters logical thinking, problem-solving, computational thinking, and digital literacy relevant to the needs of the workforce in the digital industrial era. The integration of coding platforms into probability and statistics learning has the potential to be an effective strategy for improving the quality of mathematics learning while preparing vocational school students to face the challenges of future technological developments.
Utilization of SPSS Application as A Data Analysis Tool For Various Research Needs Azkyatul Mardiyah; De Ajeng Vien Saputri; Novaneza Rasendriya; Syahdan Jamjami; Purwadi Purwadi
Jejak digital: Jurnal Ilmiah Multidisiplin Vol. 2 No. 4 (2026): JUNI-JULI
Publisher : INDO PUBLISHING

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63822/2hzfh132

Abstract

The development of information technology has significantly changed the way research data is processed and analyzed. One of the software that is often used is IBM SPSS, which functions to perform statistical analysis quickly and organized. This study aims to study the use of SPSS applications as a tool to analyze data for various research needs and evaluate the extent to which the application is effective in assisting the data processing process. The method used is a literature study that involves collecting and analyzing various journals, scientific articles, as well as previous research that discusses the use of SPSS in various academic and research activities. The research stages include determining the problem, reading existing material, collecting information, analyzing data using SPSS, evaluating the results, and concluding the research.
Penerapan Simulasi Monte Carlo untuk Memprediksi Kinerja dan Keandalan Sistem Komputer Berbasis Artificial Intelligence Augusta Dwi Putra; Bangkit Ririatini; Dzaki Dwi Abdullah; Rifqi Aziz; Purwadi Purwadi
Jejak digital: Jurnal Ilmiah Multidisiplin Vol. 2 No. 4 (2026): JUNI-JULI
Publisher : INDO PUBLISHING

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63822/4dv3rv27

Abstract

The development of Artificial Intelligence (AI)-based computer systems in large-scale data processing environments introduces significant uncertainty regarding operational success rates. AI systems handling thousands to millions of processing requests daily are vulnerable to failures caused by workload variations, limited computational capacity, and model complexity. This study applies a quantitative approach using Monte Carlo Simulation to predict the performance and reliability of AI-based computer systems in data processing by utilizing probability concepts, discrete probability distributions, cumulative probabilities, expected value analysis, and Mean Absolute Percentage Error (MAPE). The research data consist of 250 historical processing observations classified into four categories: optimal success (58%), delayed success (24%), temporary failure with retry (12%), and total failure (6%). The expected processing time was calculated as E(X) = 3.816 seconds. A Monte Carlo Simulation with 10,000 iterations produced an average MAPE of 0.58%, indicating excellent predictive accuracy since it is well below the 5% tolerance threshold. Furthermore, under a workload of 50,000 requests per day, approximately 8,950 requests (17.9%) were estimated to potentially affect service reliability. The findings demonstrate that Monte Carlo Simulation is an effective quantitative tool for capacity planning and operational risk mitigation in AI-based computer systems.
Analysis Of Social Media Use Among Students Using Approaches Statistics And Probability Ecca Andini Naretawati; Arvita Tivanny Ellen; Nandia Triyusvita; Dias Puspita Anggareni; Purwadi Purwadi
Jurnal Ilmiah Multidisiplin Indonesia (JIM-ID) Vol. 5 No. 06 (2026): Jurnal Ilmiah Multidisplin Indonesia (JIM-ID), June 2026
Publisher : Sean Institute

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

Abstract

Social media has become an important part of students' lives as a medium for communication, entertainment, and information seeking. This study aims to analyze social media usage patterns among university students using descriptive statistics and probability approaches. Data were collected through a survey of 30 students using Google Forms. The observed variables included gender, semester level, residence status, duration of social media usage, purpose of use, and Grade Point Average (GPA). The results showed that 76.67% of respondents were female and 50% were second-semester students. Furthermore, 63.33% of students used social media for more than eight hours per day, while entertainment was the primary purpose of use (50%). Probability analysis indicated that the likelihood of a student using social media for more than eight hours daily was 0.633. The findings suggest that social media has become a major necessity for students, requiring proper time management to avoid negative impacts on academic activities.
Pemodelan Statistik Sentimen Pengguna terhadap Artificial Intelligence pada Media Sosial X Menggunakan Analisis Sentimen Berbasis Natural Language Processing Faras Alfito Dwi; Purwadi
Jurnal Siber Multi Disiplin Vol. 4 No. 2 (2026): Jurnal Siber Multi Disiplin (Juli - September 2026)
Publisher : Siber Nusantara Research & Yayasan Sinergi Inovasi Bersama (SIBER)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38035/jsmd.v4i2.866

Abstract

Penelitian ini mengkaji sentimen publik terhadap kecerdasan buatan generatif pada media sosial X dengan menggabungkan analisis sentimen berbasis leksikon, pemodelan topik, dan klasifikasi teks prediktif. Objek penelitian berupa unggahan pengguna berbahasa Indonesia yang membahas ChatGPT, Gemini, Copilot, Grok, dan layanan AI generatif lain selama Januari-Desember 2024. Setelah melalui penyaringan, deduplikasi, dan normalisasi teks, sebanyak 3.842 unggahan dianalisis menggunakan leksikon InSet, representasi TF-IDF, Multinomial Naive Bayes, Support Vector Machine, dan Logistic Regression. Hasil penelitian menunjukkan sentimen positif mendominasi sebesar 52,3%, diikuti sentimen negatif 28,1% dan netral 19,6%. Topik yang paling banyak muncul ialah produktivitas, kekhawatiran pekerjaan, kualitas luaran, privasi, dan penggunaan pendidikan. Model Multinomial Naive Bayes memperoleh akurasi 84,7% dan F1-score 0,83, sedangkan SVM mencapai akurasi komparatif tertinggi 86,2%. Temuan ini menunjukkan bahwa pengguna Indonesia cenderung menerima AI generatif sebagai alat praktis, tetapi tetap menaruh kekhawatiran terhadap disrupsi pekerjaan, misinformasi, privasi, dan integritas akademik
Mapping UI/UX Evaluation Methods, Evaluation Objects, and Measured Aspects in Comparative Studies: A Systematic Literature Review Bachtiar Mujaddidi; Berlilana Berlilana; Purwadi Purwadi
Jambura Journal of Electrical and Electronics Engineering Vol 8, No 2 (2026): Juli - Desember 2026
Publisher : Electrical Engineering Department Faculty of Engineering State University of Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/jjeee.v8i2.39319

Abstract

— UI/UX evaluation is a crucial aspect in ensuring the quality of interaction between users and systems, particularly in the context of increasingly complex digital applications. However, the wide variety of available evaluation methods often leads to differences in results and interpretations when assessing system performance and user satisfaction. This study aims to review and compare UI/UX evaluation approaches used in comparative studies. Unlike previous review studies that mainly focused on specific application domains, user perceptions, or technological trends, this study specifically maps the relationship between UI/UX evaluation methods, evaluated objects, and user experience dimensions measured in comparative studies. The method employed is a systematic literature review (SLR) following the PRISMA guidelines. Literature was retrieved from the Scopus database, and through the selection process, 13 articles met the inclusion criteria. The analysis revealed that UI/UX evaluation approaches in comparative studies are predominantly focused on comparing interaction techniques or interaction approaches, accounting for 61.5% (8 articles) of the selected studies. This is followed by comparisons of software performance, which represent 23.1% (3 articles), and comparisons of evaluation methods, which account for 15.4% (2 articles). Evaluations generally employ a combination of performance metrics, user perception measures, and additional experiential indicators such as cognitive workload and physiological responses. The findings show that each method or system demonstrates strengths in specific evaluation dimensions, highlighting the need for a multidimensional and multi-method evaluation approach to obtain a more comprehensive understanding of UI/UX. The main contribution of this study is the development of a systematic synthesis that links evaluation methods, evaluation objects, and UI/UX indicators employed in comparative studies. The findings provide a broader understanding of current evaluation practices and may serve as a reference for researchers and practitioners in designing more appropriate and consistent UI/UX evaluation strategies.
Motion Graphics Branding Video for Increasing Audience Engagement at Zahira Media Publisher Using R&D Method Putri Oktavianingsih; Purwadi Purwadi
Jambura Journal of Electrical and Electronics Engineering Vol 8, No 2 (2026): Juli - Desember 2026
Publisher : Electrical Engineering Department Faculty of Engineering State University of Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/jjeee.v8i2.39190

Abstract

The development of social media encourages companies to utilize more engaging and interactive digital communication media to increase audience engagement. Zahira Media Publisher has used video-based promotional media, but has not yet utilized motion graphics optimally, resulting in relatively low audience interaction. This study aims to develop a motion graphics-based branding video and analyze its effectiveness in increasing audience engagement on Instagram. The method used is Research and Development (RD) with a Waterfall model that includes needs analysis, design, implementation, validation, testing, and evaluation. The branding video was developed using Canva and CapCut by applying the AIDA (Attention, Interest, Desire, Action) concept, then validated by media experts and subject matter experts before being published via Instagram Reels. Testing was conducted for seven days using indicators likes, comments, shares, views, and reach. The results showed an increase in all engagement indicators: likes from 13 to 173, comments from 0 to 109, shares from 4 to 31, views from 635 to 1,384, and reach from 398 to 676. Engagement rates also increased from 4.27% to 46.30%. These results indicate that motion graphics-based branding videos effectively increase audience engagement, encourage user interaction, and expand the reach of information through Instagram Reels.
Co-Authors Abdul Jahir Adam Prayogo Kuncoro Ade Toti Febrian Adhisa Nanda Kurnia Akbar Priyanto Akto Hariawan Alya Zhafira Amelia Nur Azizah Ammar Fauzan, Ammar Andi Dwi Riyanto Andina, Anisa Nur ANNISA HANDAYANI Arief Kurnia Ramadhani Arvita Tivanny Ellen Atiqah Noor Zhaafirah Augusta Dwi Putra Aulia Suryaning Tyas Azkyatul Mardiyah Bachtiar Mujaddidi Bagus Adhi Kusuma Bagus Adhi Kusuma Bangkit Ririatini Berlilana Berlilana De Ajeng Vien Saputri Denaya Fadilah Dendi Putra Prakoso Desi Riyanti Dhanar Intan Surya Saputra Dias Puspita Anggareni Dzaki Dwi Abdullah Ecca Andini Naretawati Fadila Nur Syifa Fairus Aufa Baharita Faras Alfito Dwi Fendi Elyon Ramadhan Ferix Aziz Susandi Fini Ikhfiani Fadilah Giat Karyono Giat Karyono Hamzah Tsabit Akdama Hendra Marcos Hidayah, Debby Ummul Ibrahim, Farrel Ilham Robbani Ilham Suryo Saputra Imam Tahyudin Imam Tahyudin Intan Surya Saputra, Dhanar Iskoko, Angga Jaka Wijaya Kusuma jordy, Roy Jordy Juwita Septiani Kuat Indartono Lina Nur Afifah M. Syaiful Amin Mardiyanto Mardiyanto Ma`dan Shomsomi Mohammad imron Muliasari Pinilih, Muliasari Nandia Triyusvita Nor Azman Abu Nor Azman Bin Abu Novaneza Rasendriya Novitasani Putri Othman Bin Mohd Othman Bin Mohd Panca Ragil Prasetyo Pandu W, Muhammad Arfianto Puas Triawan Pungkas Subarkah Putri Oktavianingsih Putri Vidia Lestari Rahayu, Dania Gusmi Rahman Rosyidi Ratih Anggraeni Refida Putri Rehandika Priambudi Rifqi Aziz Rohmah, Umdah Aulia Rujianto Eko Saputro Sitaresmi Wahyu Handani Solihatun Havidah Sri Rahayu Stella Putriseptiyani Septeragil Syahdan Jamjami Vevinciya Dila Dita Widhaksa Triawan Yulia Risma Yanti Yusmedi Nurfaizal