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All Journal International Journal of Advances in Applied Sciences Lontar Komputer: Jurnal Ilmiah Teknologi Informasi Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) RABIT: Jurnal Teknologi dan Sistem Informasi Univrab Widya Cipta : Jurnal Sekretari dan Manajemen Applied Information System and Management JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) International Journal of Advances in Data and Information Systems Journal of Applied Data Sciences Jurnal Altifani Penelitian dan Pengabdian kepada Masyarakat Jurnal Janitra Informatika dan Sistem Informasi LEBAH Journal of Information System and Education Development Edumaspul: Jurnal Pendidikan Lontar Komputer: Jurnal Ilmiah Teknologi Informasi
Rio Andika Malik
Universitas Perintis Indonesia
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Easily Determining Post-Study System Usability for Anime Community E-Commerce Analysis Malik, Rio Andika; Octafia, Sri Mona; Gunawan, Vicky Setia
Applied Information System and Management (AISM) Vol 7, No 2 (2024): Applied Information System and Management (AISM)
Publisher : Depart. of Information Systems, FST, UIN Syarif Hidayatullah Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/aism.v7i2.39352

Abstract

The rapid growth of e-commerce as a form of electronic commerce has transformed the global shopping landscape. To maintain user satisfaction and competitiveness, e-commerce sites must effectively understand and improve the usability of their systems after launch. The aims of the study are to improve e-commerce post-launch usability so that anime fans' enthusiasm can be capitalized upon for financial gain and market expansion. In this study, we adopted a combined approach that included user observations, interviews, surveys, and performance measurement for anime community e-commerce analysis Weeboo web commerce. Through this method, we analyze the behavior and views of users towards e-commerce systems. The results show that most users experience a positive experience in shopping online by appreciating the usability of the layout, search process, and fast checkout process. The results indicated that most users have a positive online shopping experience, appreciating the layout, search process, and fast checkout process. The SUS score of 75.375 (grade B) and the overall PSSUQ satisfaction score of 2.0296 indicate that the system is acceptably well-received. The proposed recommendations can help e-commerce companies quickly identify usability issues and implement relevant fixes.
Enhancing the Performance of Machine Learning Algorithm for Intent Sentiment Analysis on Village Fund Topic Anam, M. Khairul; Putra, Pandu Pratama; Malik, Rio Andika; Karfindo, Karfindo; Putra, Teri Ade; Elva, Yesri; Mahessya, Raja Ayu; Firdaus, Muhammad Bambang; Ikhsan, Ikhsan; Gunawan, Chichi Rizka
Journal of Applied Data Sciences Vol 6, No 2: MAY 2025
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v6i2.637

Abstract

This study explores the implementation of Intent Sentiment Analysis on Twitter data related to the Village Fund program, leveraging Multinomial Naïve Bayes (MNB) and enhancing it with Synthetic Minority Over-sampling Technique (SMOTE) and XGBoost (XGB). The analysis categorizes tweets into six labels: Optimistic, Pessimistic, Advice, Satire, Appreciation, and No Intent. Initially, the MNB model achieved an accuracy of 67% on a 90:10 data split. By applying SMOTE, accuracy improved by 12%, reaching 89%. However, adding Chi-Square feature selection did not increase accuracy further. Incorporating XGB into the MNB+SMOTE model led to a 6% improvement, achieving a final accuracy of 95%. Comprehensive model evaluation revealed that the MNB+SMOTE+XGB model achieved 96% accuracy, 96% precision, 96% recall, and a 96% F1-score, with an AUC of 99%, categorizing it as excellent. These findings demonstrate that the combination of SMOTE for addressing class imbalance and XGBoost for boosting performance significantly enhances the MNB model's classification capabilities. The novelty lies in the integration of these techniques to improve intent sentiment classification for public opinion analysis on the Village Fund program. The results indicate that the majority of tweets labeled as "No Intent" reflect a lack of specific sentiment or actionable intent, providing valuable insights into public perception of the program.
The emergence of a technology-based scheme for monitoring and managing remembrance in Al-Quran knowledge Malik, Rio Andika; Octafia, Sri Mona; Werifmayeni, Annisa; Muzaki, M.Nabil
Lebah Vol. 18 No. 2 (2025): Maret: Pengabdian
Publisher : IHSA Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/lebah.v18i2.285

Abstract

Quran memorization education plays an important role in shaping children's character and spiritual intelligence from an early age. To improve the effectiveness of tahfiz learning, a system is needed that is not only harmonious but also manages memorization progress in a structured manner. This community service activity aims to develop a memorization management and monitoring system based on information technology in Early Childhood Tahfiz (TAUD). The main problem faced is the absence of an integrated system that allows comprehensive recording, evaluation, and reporting of memorization progress. The solution offered is the development of a web-based worksheet application that allows students, teachers, and parents to communicate and manage memorization progress in real-time. The methods used include needs assessment, system development, teacher training, application implementation, and evaluation of program success. The results of the evaluation through pre-test and post-test showed an average increase in understanding of +35.33 points for parents and +35 points for teachers after training and use of the system. Mentoring is carried out periodically to ensure continued use of the system. These results indicate that the use of technology can increase the effectiveness of memorization management and parental involvement in supporting children's tahfiz learning
Digital Transformation of Women-Owned MSMEs: Marketing Strategies to Adapt to The Dynamics of Consumer Behavior in The Digital Era Octafia, Srimona; Malik, Rio Andika; Widia, Elsa
Widya Cipta: Jurnal Sekretari dan Manajemen Vol 9, No 2 (2025): September
Publisher : Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/widyacipta.v9i2.24504

Abstract

Women-owned MSMEs play a strategic role in the national economy. However, many women MSMEs do not yet have adequate digital capacity to respond to changes in consumer behavior that now rely on technology in making purchasing decisions. In addition, structural barriers such as limited access to technology and capital, as well as socio-cultural barriers such as gender stereotypes and double workloads, complicate the process of adopting digitalization. Although many studies discuss these challenges, there are still limited studies that specifically explore the digital marketing strategies implemented by women-owned MSMEs in response to the dynamics of consumer behavior, especially in the local context. This study aims to analyze the digital marketing strategies adopted by women-owned MSMEs in Padang City. The approach used is a mixed method with an explanatory sequential design, starting with a survey of 125 women MSMEs, followed by in-depth interviews. The findings of this study indicate a significant shift in consumer behavior in the digital era, emphasizing the importance of convenience and ease in purchasing decisions. Therefore, it is crucial for women-led MSMEs to understand these behavioral changes and master appropriate marketing strategies to thrive in this evolving market landscape.
Pengukuran Tingkat Kepuasan Mahasiswa Terhadap Bahan Ajar Mata Kuliah PTI Menggunakan Algorithma K-Means Clustering Malik, Rio Andika; Firmansyah, Wilis
Jurnal Janitra Informatika dan Sistem Informasi Vol. 3 No. 2 (2023): Oktober - Jurnal Janitra Informatika dan Sistem Informasi
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25008/janitra.v3i2.174

Abstract

Media pembelajaran memiliki kedudukan yang sangat penting dalam mencapai tujuan pembelajaran secara efektif. Berbagai penelitian yang dilakukan terhadap penggunaan media dalam pembelajaran sampai pada kesimpulan bahwa proses dan hasil belajar setiap siswa menunjukkan perbedaan yang signifikan antara pembelajaran tanpa media dan pembelajaran menggunakan media. Penelitian ini menggunakan ilmu komputasi dan metode numerik dengan pendekatan model formulatif dimana pengolahan algoritma clustering menggunakan pemodelan K-Means memetakan dataset yang paling tepat sehingga dapat membantu menganalisis atau mengukur tingkat kepuasan suatu media pembelajaran. Hasil yang diperoleh dari evaluasi akan memberikan petunjuk kepada dosen tentang bagian mana dari media pembelajaran yang baik dan bagian mana yang kurang baik sehingga belum dapat mencapai tujuan pengembangan media pembelajaran yang dalam hal ini. Dengan menggunakan k-means diperoleh hasil evaluasi media pembelajaran studi kasus mata kuliah Pengenalan Teknologi Informasi menjadi 2 cluster. Dapat disimpulkan bahwa clustering hasil cluster dengan pemodelan K-Means mampu untuk menghasilkan akurasi cluster yang presisi.
Enrichment of microscopic photographs by utilizing CNN regarding soil-transmitted helminths identification Malik, Rio Andika; Frimadani, Marta Riri; Putra, Dwipa Junika
International Journal of Advances in Applied Sciences Vol 13, No 1: March 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijaas.v13.i1.pp46-53

Abstract

Soil-transmitted helminth (STH) infection remains a significant global health challenge, affecting millions of people, particularly in developing countries. A convolutional neural network (CNN) approach to optimize the detection of STH infections in microscopic images. The study aims to assess the effectiveness of the CNN model in identifying and classifying STH worm eggs accurately. The research employs MATLAB as the primary tool for conducting experiments and validation tests. By implementing image preprocessing techniques to enhance image quality and applying precise segmentation methods, the CNN model is trained on a dataset of microscopic images to learn and classify STH infections effectively. The validation test results demonstrate that the CNN model achieved a high accuracy rate of 92.31% in classifying STH infections. This accuracy surpasses traditional methods, which are time-consuming and susceptible to human errors. This study underscores the importance of integrating artificial intelligence, particularly CNN, into the healthcare domain to support detecting and diagnosing diseases requiring specialized expertise, such as STH infections. The findings of this research can serve as a valuable reference for researchers, medical practitioners, and data scientists in leveraging artificial intelligence to enhance the quality of healthcare services, leading to positive impacts on society worldwide.
Easily Determining Post-Study System Usability for Anime Community E-Commerce Analysis Malik, Rio Andika; Octafia, Sri Mona; Gunawan, Vicky Setia
Applied Information System and Management (AISM) Vol. 7 No. 2 (2024): Applied Information System and Management (AISM)
Publisher : Depart. of Information Systems, FST, UIN Syarif Hidayatullah Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/aism.v7i2.39352

Abstract

The rapid growth of e-commerce as a form of electronic commerce has transformed the global shopping landscape. To maintain user satisfaction and competitiveness, e-commerce sites must effectively understand and improve the usability of their systems after launch. The aims of the study are to improve e-commerce post-launch usability so that anime fans' enthusiasm can be capitalized upon for financial gain and market expansion. In this study, we adopted a combined approach that included user observations, interviews, surveys, and performance measurement for anime community e-commerce analysis Weeboo web commerce. Through this method, we analyze the behavior and views of users towards e-commerce systems. The results show that most users experience a positive experience in shopping online by appreciating the usability of the layout, search process, and fast checkout process. The results indicated that most users have a positive online shopping experience, appreciating the layout, search process, and fast checkout process. The SUS score of 75.375 (grade B) and the overall PSSUQ satisfaction score of 2.0296 indicate that the system is acceptably well-received. The proposed recommendations can help e-commerce companies quickly identify usability issues and implement relevant fixes.
Beyond experience: how customer engagement transforms AI interactions into Generation Z loyalty Sri Mona Octafia; Dina Hadia; Annisa Weriframayeni; Rio Andika Malik; Vicky Setia Gunawan
Edumaspul: Jurnal Pendidikan Vol 9 No 2 (2025): Edumaspul: Jurnal Pendidikan
Publisher : Universitas Muhammadiyah Enrekang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33487/edumaspul.v9i2.9215

Abstract

The use of Artificial Intelligence (AI) in customer service, including chatbots, personalized recommendations, and virtual assistants, has significantly improved service efficiency and customer experience. However, how these AI-enabled experiences translate into long-term customer loyalty is still not fully understood, especially among Generation Z, who expect digital interactions to be efficient, authentic, and engaging. Previous studies indicate that customer engagement—reflecting cognitive, emotional, and behavioral involvement—may play an important mediating role, yet empirical evidence in emerging market contexts such as Indonesia remains limited. This study aims to examine the mediating role of customer engagement in the relationship between AI-enabled experience and sustainable loyalty among Generation Z consumers in Padang City, Indonesia. Using a quantitative cross-sectional survey design, data were collected from Generation Z respondents who had interacted with AI-based services in the last six months. The data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) to test both direct and indirect relationships among variables. The results indicate that AI-enabled experience has a positive and significant effect on sustainable loyalty, both directly and indirectly through customer engagement. AI-enabled experience significantly influences customer engagement, which in turn strongly affects sustainable loyalty, confirming the partial mediating role of engagement. These findings highlight that AI-driven services should be designed not only for efficiency but also to foster active interaction and engagement in order to build long-term loyalty among Generation Z consumers.
Quickly Assess the Acceptability Sentiment of White Paracetamol Intake Using KNN-SMOTE Based On Receptive Deciding Rio Andika Malik; Faizal Riza; Sarjon Defitb
Lontar Komputer : Jurnal Ilmiah Teknologi Informasi Vol. 15 No. 01 (2024): Vol. 15, No. 01 April 2024
Publisher : Institute for Research and Community Services, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/LKJITI.2024.v15.i01.p05

Abstract

This research aims to develop a fast and adaptive sentiment evaluation approach related to the use of white paracetamol using a combination of the K-Nearest Neighbors (KNN) algorithm, Synthetic Minority Over-Sampling Technique (SMOTE), and the Receptive Deciding concept. Imbalances in the dataset, where positive sentiment may predominate, are addressed using SMOTE to synthesize minority class samples. The KNN algorithm is applied to build a sentiment classification model, while Receptive Deciding is used to provide adaptive intelligence to changes in sentiment. The SMOTE oversampling process is carried out to achieve class balance, while KNN is used to classify sentiment. Receptive Deciding is applied to increase the model's adaptability to changes in sentiment. The research results show that integrating the SMOTE, KNN, and Receptive Deciding methods effectively assesses sentiment accurately and adaptively. The developed model can recognize changes in sentiment over time and provide balanced evaluation results. These findings are expected to contribute to understanding public sentiment towards using white paracetamol and be the basis for developing more effective health communication strategies.
Co-Authors Anam, M Khairul Carelsa, Hasnah Vithon Dina Hadia Dwipa Junika Putra Elsa Widia Elva, Yesri Faizal Riza Faizal Riza Firdaus, Muhammad Bambang Frimadani, Marta Riri Gunawan, Chichi Rizka Ikhsan Ikhsan Karfindo, Karfindo Mahessya, Raja Ayu Marta Riri Frimadani Marta Riri Frimadani Marta Riri Frimadani Muzaki, M.Nabil Natrio, Yeyep Pandu Pratama Putra, Pandu Pratama Putra, Dwipa Junika Rinawati Kasrin, Rinawati Sarjon Defit Sarjon Defit Sarjon Defitb Sri Mona Octafia Teri Ade Putra Vicky Setia Gunawan Vicky Setia Gunawan Werifmayeni, Annisa Weriframayeni, Annisa Wilis Firmansyah Wilis Firmansyah Yuhandri Yuhandri Yuhandri Yuhandri, Yuhandri