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All Journal Jurnal Administrasi Publik (JAP) Desimal: Jurnal Matematika
Pandri Ferdias
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Education Mathematics Social Sciences

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Sequence modeling of batik dyeing with RNN–LSTM: An AI approach to automated color design Muhammad Muhajir; Rahmadi Yotenka; Prihanto Edy Sanjaya; Ismail B Mustapha; Pandri Ferdias
Desimal: Jurnal Matematika Vol. 8 No. 3 (2025): Desimal: Jurnal Matematika
Publisher : Universitas Islam Negeri Raden Intan Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/djm.v8i3.202529320

Abstract

Traditional Batik production relies on skilled artisans to plan multistage dyeing sequences that yield culturally meaningful and visually harmonious color combinations. This manual practice is time-consuming, difficult to document, and hard to scale to novice designers, and prior work on Batik color design has rarely treated the dyeing process explicitly as a learnable temporal sequence. This study addresses that gap by modeling Batik dyeing as a sequence learning problem and applying a Recurrent Neural Network with Long Short-Term Memory (RNN–LSTM) to support automated color design. We construct a dataset of 72 fabric samples obtained from single- and two-color dyeing procedures that follow traditional Batik wax–dye–dewax workflows. For each sample, RGB values are extracted at each dyeing stage and encoded as time-ordered inputs, while the final fabric colors are used as target outputs. The proposed RNN–LSTM learns to predict harmonious color sequences that are consistent with examples in the dataset. It achieves a prediction accuracy of 0.869 on held-out data, outperforming several feedforward and recurrent neural network baselines under the same training protocol. An interactive simulation interface then integrates the trained model, allowing users to explore and visualize predicted color outcomes step-by-step. The results show how AI-based sequence modeling can help preserve Batik color traditions while making expert color design strategies more accessible.
ANALYSIS OF SERANG REGENCY INFRASTUCTURE SERVICE SATISFACTION INDEX Agus Lukman Hakim; Pandri Ferdias; Agus Sjafari; Muhammad Haekal Saniarjuna; Hanifah Hanifah; Siti Yuniar
Jurnal Administrasi Publik Vol 16, No 1 (2025): JURNAL ADMINISTRASI PUBLIK
Publisher : Universitas Sultan Ageng Tirtayasa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62870/jap.v16i1.30862

Abstract

This research aims to determine the level of public satisfaction with the implementation of public services in the infrastructure sector provided by the Regional Government of Serang Regency, as well as the efforts of the local government to improve infrastructure services in Serang Regency. This study was conducted on the local government of Serang Regency. The research period lasted for two months, from July to September 2024. The variables to be examined are related to Physical Availability, Physical Quality, Appropriateness, Utility, and Contribution. The data used is primary data in the form of questionnaires distributed to the residents of Serang Regency aged over 17 years, spread across 29 districts, with a sample size of 205. The sampling technique used is multistage random sampling. The analysis technique employed is quantitative descriptive with the Infrastructure Service Satisfaction Index (IKLI) model. The results of the study indicate that the Infrastructure Service Satisfaction Index value for Serang Regency in 2024 is 2.62, equivalent to 65.62, which falls under the criteria of being fairly satisfied. This result shows that the residents of Serang Regency feel that the performance of the Serang Regency local government in priority infrastructure services is quite good and satisfactory. However, there is still a need for improvements in priority infrastructure services, particularly in bridge services, clean water, housing/settlements, and land transportation.
Co-Authors Agus Lukman Hakim Agus Sjafari Hanifah Hanifah Ismail B Mustapha Muhammad Haekal Saniarjuna Muhammad Muhajir Prihanto Edy Sanjaya Rahmadi Yotenka Siti Yuniar