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All Journal Media Statistika JURNAL SISTEM INFORMASI BISNIS Telematika : Jurnal Informatika dan Teknologi Informasi Seminar Nasional Informatika (SEMNASIF) JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) bit-Tech G-Tech : Jurnal Teknologi Terapan International Journal of Advances in Data and Information Systems ESTIMASI: Journal of Statistics and Its Application Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Nusantara Science and Technology Proceedings Jurnal Teknik Informatika (JUTIF) Journal of Technology and Informatics (JoTI) International Journal of Data Science, Engineering, and Analytics (IJDASEA) International Journal Of Computer, Network Security and Information System (IJCONSIST) Journal of International Conference Proceedings Journal of Data Mining and Information Systems Parameter: Jurnal Matematika, Statistika dan Terapannya Jurnal PETISI (Pendidikan Teknologi Informasi) Joong-Ki
Kartika Maulida Hindrayani
Faculty Of Computer Science, Universitas Pembangunan Nasional “Veteran” Jawa Timur, Surabaya 60294, Indonesia
Religion Agriculture, Biological Sciences & Forestry Humanities Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology

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Optimisation of Hyperparameter Tuning and Optimiser on MobileNetV2 for Batik Parang Classification Rafli, Muhammad; Prasetya, Dwi Arman; Hindrayani, Kartika Maulida
bit-Tech Vol. 8 No. 3 (2026): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v8i3.3576

Abstract

Batik Parang is a prominent traditional motif in Indonesia, characterised by repetitive diagonal patterns and subtle visual variations across regional styles, such as Solo Parang and Yogyakarta Parang, which pose challenges for automated image classification. This study addresses this challenge by introducing an optimisation-focused framework that integrates hyperparameter tuning strategies with a lightweight convolutional neural network, extending the practical use of MobileNetV2 for fine-grained cultural motif classification. A balanced dataset of 160 batik images collected from Kaggle was employed and partitioned using an 80:20 stratified split to ensure class consistency. The model was evaluated on a limited yet representative dataset reflecting realistic small-scale cultural heritage scenarios. Two hyperparameter tuning methods, Bayesian Optimisation and Particle Swarm Optimisation, were applied to optimise learning rate, batch size, and dropout rate, while two optimisers, Adam and Adagrad, were compared to analyse their effects on convergence stability and generalisation. The training process followed a two-phase strategy consisting of transfer learning and selective fine-tuning of upper MobileNetV2 layers. Experimental results indicate that Adagrad-based configurations consistently outperform Adam-based models, which exhibited class collapse and poor generalisation. The optimal configuration, combining Adagrad with Bayesian Optimisation, achieved a validation accuracy of 91% with balanced precision, recall, and F1-score across both Parang classes. These findings demonstrate that careful optimisation enhances the reliability of lightweight CNNs and support extending the proposed framework to other cultural heritage classification tasks and resource-constrained real-time applications.
Analisis Sentimen Ulasan Aplikasi Maxim Merchant dengan Support Vector Machine (SVM) dan Random Forest Selly Rizkiyah; Indira Zein Rizqin; Milla Akbarany Baktiar Putri; Shindi Shella May Wara; Kartika Maulida Hindrayani
JDMIS: Journal of Data Mining and Information Systems Vol. 4 No. 1 (2026): February 2026
Publisher : Yayasan Pendidikan Penelitian Pengabdian Algero

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54259/jdmis.v4i1.4765

Abstract

The development of digital technology, especially mobile devices, has led to an increase in application-based services. One important aspect in app development is to deeply understand user perception and satisfaction. This study aims to analyze user sentiment towards the Maxim Merchant application based on reviews obtained from the Google Play Store platform. A total of more than 2800 Indonesian-language reviews were collected using web scraping techniques. The review data was processed through pre-processing stages such as text cleaning, normalization, tokenization, removal of unimportant words, and stemming. Sentiments are categorized into positive and negative based on the review score, where scores of 1 to 3 are considered negative, and scores of 4 and 5 are considered positive. Word cloud visualization is used to show the dominant words of each sentiment category. The data is then converted into numerical form using TF-IDF and selected using the Chi-Square method. Classification was performed using Support Vector Machine and Random Forest algorithms. The evaluation results show that the Support Vector Machine algorithm performs better in classifying sentiment, especially in handling high-dimensional text data.
Co-Authors Achmad Dzulfiqar Alfiansyah Adhigiadany, Chelsea Ayu Afandy, Selena Nurmanina Afidria, Zulfa Febi Ahmad, Davin Anezta Aisyah Kirana Putri Isyanto Altetiko, Faizal Johan Alzam, Muhammad Arsyad Amelia, Meisya Vira Amri Muhaimin Aviolla Terza Damaliana Azizah, Alisa Jihan Bhalqis, Anissa Andiar Brescia Ayundina Yuniarossy Budi, Aditya Septa Burhan Syarif Acarya Christina Halim Christina, Enzelica Vica Damaliana, Aviolla Terza Diyasa, I Gede Susrama Mas Dwi Arman Prasetya Elmaliyasari, Shifa Eristya Maya Safitri Fahrudin, Tresna Maulana Fajar Ramadhani Fernando, Moch. Firman I Gede Susrama Mas Diayasa idhom, Mohammad Imelda Widya Ningrum Indira Zein Rizqin Isyanto, Aisyah Kirana Putri Jauharis Saputra, Wahyu Syaifullah Made Hanindia Prami Swari Maulana F, Tresna Milla Akbarany Baktiar Putri Mohammad Idhom Ningrum, Imelda Widya Ningrum, Lisya Septyo Nur Aini Rakhmawati Pakpahan, Vera Febrianti Pratiwi, Nanda Aulia Prismahardi Aji Riyantoko Purwadwika, Reza Sadiya Putro, R. Kokoh H. rachmanto, Nugroho Fajar Rafli, Muhammad Riskiyah, Ameliyah Risnaldy Novendra Irawan Riyantoko, Prismahardi Aji Safira, Alya Mirza Saputra, Wahyu S. J. Saputra, Wahyu Syaifullah Jauharis Selly Rizkiyah Shindi Shella May Wara Shindi Shella May Wara Tresna Maulana F Tresna Maulana Fahruddin Tresna Maulana Fahrudin Tresna Maulana Fahrudin Trimono Trimono, Trimono Wahyu Syaifullah JS Wardati, Nanda Kurnia Wibowo, Muhammad Bagas Satrio