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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Jurnal Ilmu Komputer dan Informasi Jurnal Teknik Elektro Tadris: Jurnal keguruan dan Ilmu Tarbiyah Sinergi Jurnal Penelitian dan Pembelajaran IPA Economic Education Analysis Journal IJIE (Indonesian Journal of Informatics Education) Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Diglosia: Jurnal Kajian Bahasa, Sastra, dan Pengajarannya Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) Indonesian Journal of Electrical Engineering and Computer Science Jurnal Teknik Informatika (JUTIF) Community Empowerment Journal of Soft Computing Exploration TIERS Information Technology Journal MATRIX : JURNAL MANAJEMEN TEKNOLOGI DAN INFORMATIKA Jurnal Pendidikan Indonesia (Japendi) Information Technology Education Journal Journal of Mandalika Literature Jurnal Bina Desa Jurnal Abdi Negeri
Yahya Nur Ifriza
Information System Study Program, Universitas Negeri Semarang, Indonesia
Arts Humanities 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 Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Public Health Social Sciences Other

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Strengthening Javanese literature material through the Novaja.id application as a form of Javanese cultural preservation Fateah, Nur; Subhan, Subhan; Ifriza, Yahya Nur; Ninsiana, Widhiya
Diglosia: Jurnal Kajian Bahasa, Sastra, dan Pengajarannya Vol 8 No 4 (2025)
Publisher : Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30872/diglosia.v8i4.1319

Abstract

The preservation of regional languages, including Javanese, increasingly requires digital innovations that can support literacy development and sustain readers’ engagement. However, existing digital platforms for Javanese literary access often lack systematic development frameworks and user-centered design features, limiting their effectiveness and long-term usability. Responding to this gap, this study develops the Novaja.id Javanese Novel Library application through the integration of the System Development Life Cycle (SDLC) and User-Centered Design (UCD) methodologies. The research began with a user needs analysis conducted through surveys and in-depth interviews, which informed the design of an intuitive interface and optimized user experience. A prototype was subsequently tested through usability evaluations, and user feedback was incorporated into iterative refinements. The findings show that the final application meets user needs effectively, demonstrating high navigation ease, satisfactory feature performance, and stable and secure functionality. These outcomes indicate that combining SDLC and UCD enhances application quality and usability. Overall, Novaja.id has strong potential to expand access to Javanese literary works and contribute to Javanese language literacy and cultural preservation.
Optimization CatBoost using GridSearchCV for Sentiment Analysis Customer Reviews in Digital Transportation Industry Ifriza, Yahya Nur; Sanusi, Ratna Nur Mustika; Febriyanto, Hendra; Kamaruddin, Azlina
TIERS Information Technology Journal Vol. 6 No. 2 (2025)
Publisher : Universitas Pendidikan Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38043/tiers.v6i2.7201

Abstract

The rapid expansion of ride-hailing services has generated a massive volume of user feedback, making automated sentiment analysis essential for understanding customer satisfaction. This study aims to classify public sentiment towards the Uber application into positive, neutral, and negative categories using the CatBoost algorithm, a gradient boosting method prioritized for its Ordered Boosting mechanism, which effectively prevents overfitting and enhances the model's generalization capabilities. Despite the use of TF-IDF for numerical text representation, CatBoost is selected for its superior performance on heterogeneous datasets compared to other boosting frameworks like XGBoost and LightGBM. The dataset comprises customer reviews collected 12.000 from the Google Play Store between January and March 2024 using web scraping techniques upload in Kaggle. The data underwent rigorous preprocessing, including lemmatization and TF-IDF vectorization, to structure the textual features, to maximize model performance, hyperparameter optimization was conducted using GridSearchCV. The experimental results demonstrate that the optimization process successfully improved the model's generalization capabilities, raising the Accuracy from 0.907 to 0.910 and the F1-Score from 0.893 to 0.897. Most significantly, the AUC score increased from 0.949 to 0.957, indicating a superior ability to distinguish between sentiment classes. However, while the model exhibited high precision in identifying positive and negative polarities, analysis of the confusion matrix revealed limitations in correctly predicting the neutral class, suggesting challenges related to class imbalance. These findings confirm that an optimized CatBoost model is a robust tool for sentiment classification, though future work is recommended to address minority class detection.
Optimizing Javanese script recognition using fine-tuned ResNet-18 and transfer learning Fateah, Nur; Subhan, Subhan; Ifriza, Yahya Nur
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 15, No 1: February 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v15.i1.pp443-453

Abstract

Javanese script, known as Aksara Jawa, is an ancient script used in historical and cultural texts. However, its complex character structure poses challenges for accurate recognition in modern digital applications. This study proposes an optimized classification approach for Aksara Jawa using a fine-tuned ResNet-18 model combined with the Adam optimization algorithm and transfer learning on the Hanacaraka image dataset. By leveraging the residual learning framework of ResNet-18, the model effectively captures deep spatial features of the script while reducing vanishing gradient issues. Fine-tuning is applied to enhance model adaptability, ensuring robust feature extraction specific to Javanese characters. Experimental results demonstrate that the fine-tuned ResNet-18 outperforms conventional deep learning architectures in recognizing Aksara Jawa characters, achieving 93% precision, 91% recall, 91% F1-score, and 91% accuracy. The study further explores the impact of hyperparameter tuning, data augmentation, and dropout regularization on model performance. The findings highlight the effectiveness of transfer learning in resource-limited scenarios, making it a feasible solution for optical character recognition (OCR) applications in Javanese script digitization. This research contributes to the preservation of cultural heritage through advancements in deep learning-based script recognition.
Enhanced Wind Turbine Power Forecasting via Hyperparameter-Optimized XGBoost Dimas Ramadhani; Yahya Nur Ifriza
Information Technology Education Journal Vol. 5, No. 2, May (2026)
Publisher : Jurusan Teknik Informatika dan Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/intec.v5i2.278

Abstract

Purpose – This study aims to evaluate the accuracy and computational efficiency of XGBoost in forecasting wind turbine output using a dataset aligned at hourly timestamps. This topic is important because wind turbine output exhibits fluctuating and non-linear patterns, requiring a model capable of capturing the relationship between meteorological conditions, historical turbine patterns, and the generated Energy values. Design – This study uses the 2016 Sotavento Galicia data, which consist of hourly Numerical Weather Prediction (NWP) data and historical turbine operational data originally recorded every 10 minutes. Temporal alignment was performed by retaining only turbine operational records located exactly at hourly timestamps and then merging them with the NWP data at the same timestamps. The final dataset was modeled as an hourly aligned time series dataset. The Energy variable was used as the prediction target. Since the dataset does not explicitly state the unit of Energy, RMSE and MAE were reported in the original scale of the Energy variable and cautiously interpreted as kWh per retained 10-minute record based on the variable label, recording resolution, and value range. Three model scenarios were compared, namely the XGBoost baseline, XGBoost with GridSearchCV, and XGBoost with RandomizedSearchCV. Internal validation was performed using TimeSeriesSplit, while final testing was conducted using monthly holdout on months 10, 11, and 12. Findings – The results show that XGBoost with RandomizedSearchCV produced the lowest average prediction error, with an RMSE of 135.591, MAE of 87.710, and R² of 0.907. This model reduced RMSE by 5.86% compared to the XGBoost baseline and reduced computation time by 69.51% compared to GridSearchCV. Research implications – These findings are limited to a single wind farm dataset, one observation period, and a constrained hyperparameter search space. Originality – This study demonstrates that RandomizedSearchCV can serve as an efficient tuning strategy for XGBoost-based wind power forecasting.
Analysis of Relationship Between Self Efficacy and Resilience on Kip-Kuliah Students Learning Outcomes Yahya Nur Ifriza; Istijabah Ifti Mufsiroh; Amalina Shabrina; Nurul Faizah; Sri Murti Retnoningrum
Jurnal Pendidikan Indonesia Vol. 6 No. 5 (2025): Jurnal Pendidikan Indonesia
Publisher : Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59141/japendi.v6i5.7796

Abstract

The KIP-Kuliah scholarship program aims to support underprivileged Indonesian students in higher education, yet the psychological factors influencing their success remain underexplored. This study investigates the interplay between self-efficacy and resilience in shaping academic and non-academic outcomes among KIP-Kuliah recipients. The research aims to (1) analyze the relationship between self-efficacy and resilience, and (2) assess their combined impact on learning achievements. A mixed-methods approach was employed, combining quantitative surveys (n=100) and qualitative interviews (n=10) with KIP-Kuliah students at Universitas Negeri Semarang. Statistical analyses (correlation, regression) and thematic interviews were conducted. Results revealed a strong positive correlation (r=0.678, p<0.01) between self-efficacy and resilience. Qualitative data underscored the role of financial aid, social support, and organizational involvement in enhancing these traits. The study highlights the need for integrated support programs that address both financial and psychological barriers. Recommendations include tailored mentoring and policy enhancements to maximize the KIP-Kuliah program’s impact.
Modelling of Laboratory Information Systems in Higher Education Based on Enterprise Architecture Planning for Optimizing Monitoring and Equipment Maintenance Ifriza, Yahya Nur; Veronika, Trisni Wulandari; Suryarini, Trisni; Supriyadi, Antonius
IJIE (Indonesian Journal of Informatics Education) Vol 6, No 2 (2022): IJIE (Indonesian Journal of Informatics Education)
Publisher : Universitas Sebelas Maret

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

Abstract

Retracted on author's request 
Co-Authors Abdul Jabbar Agung Kuswantoro Alamsyah - Amalina Shabrina Antonius Supriyadi Azkiya, M. Akiyasul Budi Prasetiyo, Budi Budiman, Kholiq Damayanti, Dela Rista Decky Avrilianda Dhela Septian Anggaretta Dimas Ramadhani Djuniadi Djuniadi Efrilianda, Devi Ajeng Erna Noor Savitri, Erna Noor Fateah, Nur Febriyanto, Hendra Hakim, M Faris Al Hakim, M. Faris Al Istijabah Ifti Mufsiroh Jumanto Jumanto Jumanto, Jumanto Kamaruddin, Azlina Masfufati Azizah Mu'arifuddin, Mu'arifuddin Muarifuddin Muarifuddin, Muarifuddin Much Aziz Muslim Muhammad Sam&#039;an Muhammad Sam’an Niam Wahzudik Nina Oktarina Nur Fateah Nurul Faizah Parmin - Parmin Parmin Parmin, Parmin Prabowo Yudo Jayanto Purasani, Hana Netti Raditya Ahmad Rifandi Rahayu, Endah Fitriani Rakainsa, Senda Kartika Riza Arifudin Sam'an, Muhammad Sam’an, Muhammad Sanusi, Ratna Nur Mustika Satrio Ardiansyah, Adi Siminto Siminto Siminto Siminto, Siminto Sri Murti Retnoningrum Subhan Subhan Subhan Sudarno Sudarno Supriyadi, Antonius Syarif, Deny Lukman Trisni Suryarini Trisni Wulandari Veronika Veronika, Trisni Wulandari Wicaksono, Suntoro Widhihastuti, Endah Widhiya Ninsiana, Widhiya Wisudani Rahmaningtyas Yosza Dasril Yusuf Wisnu Mandaya