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Designing UI/UX for Reading Games in Indonesian and English for Early Childhood Using the Human-Centered Design Method Azzam, Abdullah; Ratnasari, Chanifah Indah
INOVTEK Polbeng - Seri Informatika Vol. 9 No. 2 (2024): November
Publisher : P3M Politeknik Negeri Bengkalis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35314/dy9tf969

Abstract

This research aims to design an educational game "BacaKids" to help young children learn to read in Indonesian and English using the Human-Centered Design (HCD) method. The main issue addressed is the low reading ability of young children, caused by a lack of interactive learning methods and engaging media. This research seeks to create an intuitive, engaging user interface (UI) and user experience (UX) tailored to children's preferences. The research method consists of four stages in the HCD process: discover, define, design, and validate. In the discover stage, observations and interviews were conducted to understand user needs. These findings were analyzed in the define stage, forming the basis for wireframes and initial prototypes. During the design stage, the prototype was developed into an interactive game. Validation was conducted using the System Usability Scale (SUS), yielding a usability score of 91.75, well above average. The game’s Acceptability Ranges were rated as Acceptable, the Grade Scale as A, and the Adjective Ratings as Best Imaginable, indicating that the game is easy to use and well-received by users. This study demonstrates the effectiveness of HCD in creating enjoyable educational games that support reading development in early childhood.
Adoption of the CSD Matrix to Improve the Business Process Quality of Software Development Teams Nabila Putri Ocktavia; Beni Suranto; Chanifah Indah Ratnasari
bit-Tech Vol. 8 No. 2 (2025): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v8i2.2739

Abstract

This research aims to improve the quality of business processes in software development teams through the application of the CSD Matrix method. The CSD Matrix was reformulated in this research as a visual decision support tool to improve early sprint planning, by mapping project elements into three categories: certainties, suppositions, and doubts. The method was applied to the software engineering team at Mamikos through the completion of Capability Maturity Model Integration (CMMI) indicator-based questionnaires, both before (pre-test) and after (post-test) implementation. The results showed a significant improvement in the process maturity level, from an average score of 2.70 (Level 2: Developing) to 4.20 (Level 4: Managed), especially in the areas of retrospective, requirements management, and onboarding. This finding confirms that the CSD Matrix is able to encourage the structuring of the planning process, strengthen the team's collective awareness of risks and assumptions, and improve the effectiveness of cross-functional communication. With its lightweight, visual, and adaptive characteristics to Agile work environments, CSD Matrix proves to be a practical approach that can fill the gap between formal documentation and the daily coordination needs of software development teams.
Measuring e-Filing Adoption as an e-Government Service Using the Technology Acceptance Model Syifa Aliya Putri; Chanifah Indah Ratnasari
bit-Tech Vol. 8 No. 1 (2025): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v8i1.2804

Abstract

The digital transformation of public services in Indonesia, as mandated by Presidential Regulation No. 95 of 2018 on SPBE (Electronic-Based Government System), has led to the development of e-Filing—an electronic tax return reporting system that allows taxpayers to submit their Annual Tax Return (SPT) online. However, adoption among individual taxpayers remains uneven. This study investigates the factors influencing the acceptance and use of e-Filing among individual taxpayers registered at KPP Pratama Banjarmasin using the Technology Acceptance Model (TAM). Employing a quantitative explanatory approach, data were collected from 100 purposively selected respondents through structured questionnaires and analyzed using PLS-SEM. The findings reveal that perceived ease of use significantly influences users’ attitudes, and positive attitudes, in turn, strongly predict the intention to continue using e-Filing. However, perceived usefulness shows no significant effect on either user attitudes or usage intentions, highlighting a key divergence from core TAM assumptions. Moreover, intentions to use the system significantly influence actual usage, while ease of use and usefulness do not directly drive usage intentions. This study contributes uniquely by identifying a gap between perceived system benefits and actual behavioral intent, especially in the context of infrequent or assisted use among taxpayers. It recommends broader research that includes varied demographic groups and adopts extended models like UTAUT to explore external influences such as digital literacy, policy enforcement, and user support.
Personalized Skincare Recommendation System Based on Ontology and User Preferences Asista Ainun Jannatin; Chanifah Indah Ratnasari
bit-Tech Vol. 8 No. 1 (2025): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v8i1.2857

Abstract

Personalized skincare product selection remains a complex but critically important challenge, as tailoring recommendations to individual skin profiles directly enhances treatment efficacy and fosters consumer trust. Traditional systems, such as content-based and collaborative-filtering, often fail to capture semantic interactions among skin types, concerns, and ingredients. To address these limitations, we propose an innovative ontology-based skincare recommendation system that integrates structured dermatological knowledge with semantic reasoning. Leveraging the Methontology framework, we developed an ontology composed of twelve core classes such as Product, Ingredient, Skin Type, and Skin Concern and more than twenty-five object properties to model interrelated concepts. The knowledge base was populated via web scraping from three prominent platforms (Sociolla, Beautyhaul, Skinsort), yielding over 3,800 products and 28,000 ingredients. We augmented this dataset with dermatological literature to ensure clinical validity. The architecture employs Apache Jena Fuseki and SPARQL for inference, with a React-Node.js web interface. Users input skin type, concerns, and sensitivities, which are translated into RDF triples and processed through semantic rules to generate personalized recommendations. An evaluation based on the Technology Acceptance Model (TAM) assessed Perceived Usefulness and Ease of Use. Ten diverse respondents rated the system with an average score of 4.5 out of 5 (SD=0.3) and endorsed the relevance of recommendations with a score of 4.8. Our findings demonstrate that semantic technologies can significantly enhance personalization and transparency in skincare solutions. This work lays a robust foundation for future innovations in beauty technology, clinical decision support, and consumer health platforms.
Siaga Kids: An Educational Game for Enhancing Self-Safety Awareness Among Elementary School Students Husein Abimanyyu; Chanifah Indah Ratnasari; Septiana Widayanti
bit-Tech Vol. 8 No. 2 (2025): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v8i2.3296

Abstract

Safety education is a crucial component of early childhood learning, as elementary school students often have limited ability to identify potential dangers and respond appropriately. Although numerous studies have introduced educational games for safety learning, most focus on a single topic, such as disaster preparedness or traffic safety. There remains a lack of integrated, multi-threat learning media that simultaneously address different types of risks within one child-friendly platform. This study aims to address this gap by developing "Siaga Kids," an Android-based educational game designed to enhance children’s safety awareness through interactive and age-appropriate gameplay. The development process followed the ADDIE model, which consisted of Analysis, Design, Development, Implementation, and Evaluation. The game covers three key safety themes—earthquake preparedness, traffic sign recognition, and awareness of strangers—presented through visual storytelling and simple, engaging interactions suited for young learners. The study involved 20 students from grades 2 and 3 (ages 7–9) at SDII Nurul Musthofa, Klaten, Indonesia. Data collection included a pre-test, post-test, and a usability evaluation using the System Usability Scale (SUS). The findings show an improvement in students’ average scores from 8.10 to 9.75 after playing the game. The SUS score of 80.71 indicates “Acceptable” usability with an “Excellent” adjective rating. These results demonstrate that "Siaga Kids" is easy to use, engaging, and well-received by young users. Overall, the game effectively supports multi-threat safety education and offers a promising digital tool for strengthening personal safety awareness in elementary school children.
A Comparative Study of Naïve Bayes, SVM, and BiLSTM for Indonesian Tweet Gender Classification Purna Aji Wardhana; Chanifah Indah Ratnasari
bit-Tech Vol. 8 No. 2 (2025): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v8i2.3405

Abstract

Indonesian social media platforms, particularly X (formerly Twitter), generate short and highly informal texts that contain linguistic cues useful for demographic inference. Given the scarcity of controlled comparative studies in Indonesian gender prediction, especially with modest datasets, this research evaluates the performance of Multinomial Naïve Bayes, Linear Support Vector Machine (SVM), and Bidirectional Long Short-Term Memory (BiLSTM) using a balanced corpus of 478 manually labeled Indonesian-language tweets. These three models were selected to represent classical probabilistic learning, margin-based linear classification, and neural sequence modeling, thereby enabling a methodologically coherent comparison across distinct algorithmic paradigms. The study implemented a unified workflow consisting of manual labeling, structured preprocessing with Sastrawi stemming, RandomOverSampler for class balancing, TF-IDF features for classical models, and sequence-based tokenization for BiLSTM. All models were trained and evaluated using a stratified 80:20 split. Experimental results show that Linear SVM achieved the strongest performance, reaching 0.833 accuracy and 0.832 macro-F1, surpassing Naïve Bayes (0.771 accuracy) and BiLSTM (0.740 accuracy). SVM also demonstrated the most stable confusion-matrix distribution and superior AUC characteristics, while BiLSTM exhibited fluctuating validation curves, indicating sensitivity to the limited dataset size. These findings reinforce that classical models—particularly Linear SVM remain highly competitive for Indonesian short-text gender classification in low-resource environments and offer practical advantages where computational constraints and data scarcity are prominent. Although the dataset is topically narrow and limited in scale, the results highlight the need for larger corpora or transformer-based Indonesian models to further enhance generalizability and downstream demographic inference.
Business Process Modeling and Prototype Development for a Digital Custom Batik Ordering System Mahendi Putri Dinanti; Chanifah Indah Ratnasari
bit-Tech Vol. 8 No. 2 (2025): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v8i2.3439

Abstract

Manual ordering practices pose significant challenges for many craft-based small enterprises in Indonesia, including batik producers, where customer interactions, documentation, and production tracking remain largely informal. These fragmented processes result in inconsistencies, limited data access, and coordination difficulties, particularly in custom-order workflows involving multiple approval stages. This study seeks to redesign Batik Aryu’s ordering system, develop a user-centered prototype, and evaluate its user experience to assess the impact of digitalization on operational efficiency and service quality. The methodology combines Business Process Model and Notation (BPMN) for workflow analysis, evolutionary prototyping for iterative system design, and the User Experience Questionnaire (UEQ) to evaluate perceptions from both customers and administrators. BPMN analysis identified key bottlenecks in the existing manual process, leading to the development of a streamlined digital workflow that improves traceability and communication. The prototype underwent refinement through iterative feedback from the business owner, five administrative staff, and seventeen customers. UEQ results revealed varying perceptions: administrators rated most dimensions as Below Average, while Efficiency was rated as Above Average and Novelty as Good; customers rated Efficiency as Excellent, with Attractiveness and Novelty classified as Good. These findings highlight the effectiveness of the digital system in enhancing customer-facing processes, though administrative usability requires further refinement. This study contributes to the growing body of SME digitalization literature by providing an actionable framework that integrates BPMN, evolutionary prototyping, and UEQ for digital transformation, with recommendations for backend integration and real-world testing.
PERBANDINGAN ANTARMUKA TRAVELOKA DAN TIKET.COM MENGGUNAKAN EYE-TRACKING DAN UEQ Triyanto, Ahmad Gunawan; Ratnasari, Chanifah Indah
Technologia : Jurnal Ilmiah Vol 17, No 2 (2026): Technologia (April)
Publisher : Universitas Islam Kalimantan Muhammad Arsyad Al Banjari

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31602/tji.v17i2.22966

Abstract

Penelitian ini membandingkan efektivitas desain antarmuka pada dua platform Online Travel Agent, yaitu Traveloka dan Tiket.com, dengan mengombinasikan analisis perilaku visual dan evaluasi pengalaman pengguna. Metode yang digunakan adalah eksperimen komparatif dengan desain within-subject, di mana setiap partisipan menguji kedua platform menggunakan skenario tugas yang sama. Data dikumpulkan melalui teknologi eye-tracking untuk menganalisis distribusi perhatian visual serta User Experience Questionnaire (UEQ) untuk mengukur persepsi pengalaman pengguna. Hasil penelitian menunjukkan bahwa perhatian visual pengguna pada kedua platform terutama terfokus pada elemen antarmuka yang mendukung penyelesaian tugas. Meskipun tidak ditemukan perbedaan signifikan dalam pola perhatian visual, evaluasi UEQ menunjukkan perbedaan karakteristik pengalaman pengguna. Traveloka unggul pada aspek efisiensi penggunaan, sedangkan Tiket.com menunjukkan keunggulan pada aspek daya tarik visual dan pengalaman emosional. Temuan ini menunjukkan bahwa kombinasi evaluasi perilaku visual dan persepsi pengguna dapat memberikan pemahaman yang lebih komprehensif mengenai kualitas interaksi pada sistem layanan digital.
PERANCANGAN UI/UX APLIKASI KEAMANAN PEREMPUAN MENGGUNAKAN DESIGN THINKING UNTUK PENGGUNA PRIMER DAN SEKUNDER Muhammad Dendy Avendyca Ramadhan; Ratnasari, Chanifah Indah
Jurnal INSTEK (Informatika Sains dan Teknologi) Vol 11 No 1 (2026): APRIL
Publisher : Department of Informatics Engineering, Faculty of Science and Technology, Universitas Islam Negeri Alauddin, Makassar, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24252/instek.v11i1.66585

Abstract

Keamanan perempuan di ruang publik masih menjadi isu penting, sementara aplikasi keamanan yang tersedia belum selalu dirancang berdasarkan kebutuhan pengguna yang beragam, khususnya antara pengguna utama dan penerima notifikasi darurat. Penelitian ini bertujuan merancang UI/UX aplikasi keamanan perempuan berbasis mobile bernama SERENA dengan mempertimbangkan pengguna primer dan sekunder. Metode yang digunakan adalah design thinking melalui tahap empathize, define, ideate, prototype, dan test. Tahap empathize melibatkan 69 responden perempuan berusia 15–53 tahun untuk mengidentifikasi kebutuhan pengguna. Hasil menunjukkan bahwa fitur yang paling dibutuhkan adalah tombol SOS, pelacakan lokasi real-time, dan kontak darurat, dengan desain yang sederhana dan mudah digunakan. Prototipe kemudian dievaluasi menggunakan User Experience Questionnaire (UEQ) dan Technology Acceptance Model (TAM). Hasil UEQ menunjukkan seluruh aspek pada pengguna primer dan sekunder berada pada kategori Excellent. Hasil TAM menunjukkan bahwa pada pengguna primer, Perceived Usefulness berpengaruh signifikan terhadap Behavioral Intention (Sig. = 0,029), sedangkan Perceived Ease of Use tidak signifikan. Sebaliknya, pada pengguna sekunder, Perceived Ease of Use berpengaruh signifikan terhadap Behavioral Intention (Sig. = 0,044), sedangkan Perceived Usefulness tidak signifikan. Temuan ini menunjukkan bahwa SERENA berpotensi memenuhi kebutuhan pengguna dan meningkatkan efektivitas penggunaan aplikasi keamanan di situasi nyata.
ROBUSTNESS EVALUATION OF GRADIENT BOOSTING MODELS FOR GRADUATION PREDICTION UNDER COHORT-BASED DISTRIBUTION SHIFTS Rifandito Daniswara; Chanifah Indah Ratnasari
JIKO (Jurnal Informatika dan Komputer) Vol 9 No 1 (2026)
Publisher : Program Studi Teknik Informatika Universitas Khairun

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33387/jiko.v9i1.11546

Abstract

Student graduation rate is a critical performance indicator for higher education institutions, particularly in accreditation assessment. Early prediction of on-time graduation supports academic planning and quality assurance. Although prior studies report high predictive accuracy using conventional cross-validation, limited attention has been given to robustness under cohort-based distribution shifts. This study evaluates the robustness of three gradient boosting models—Histogram-Based Gradient Boosting (HGB), Extreme Gradient Boosting (XGBoost), and Light Gradient Boosting Machine (LightGBM)—for predicting on-time graduation using structured academic trajectory data from 370 labeled instances across three cohorts. Two validation strategies were employed: a stratified 80:20 split for aggregated evaluation and Leave-One-Group-Out (LOGO) validation to simulate cohort-based distribution shifts. Under stratified evaluation, all models achieved macro F1-scores above 0.74, with HGB obtaining the highest score (0.7568). However, LOGO evaluation revealed substantial performance degradation, with mean F1-scores below 0.51 and increased variability across cohorts. XGBoost demonstrated comparatively better stability under distribution shifts. These findings indicate that high predictive accuracy under random splits does not guarantee cross-cohort robustness, highlighting the importance of distribution-aware validation for reliable deployment in educational data mining.