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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) JURNAL MEDIA INFORMATIKA BUDIDARMA Indonesian Journal of Artificial Intelligence and Data Mining Communication in Biomathematical Sciences JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Building of Informatics, Technology and Science JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Journal of Computer System and Informatics (JoSYC) Charity : Jurnal Pengabdian Masyarakat eProceedings of Engineering Jurnal INFOTEL Cahaya Pengabdian LOGIC: Jurnal Penelitian Informatika Proceeding of Community Service and Engagement Journal of Soft Computing Exploration
Aditya Firman Ihsan
Universitas Telkom
Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Social Sciences Other

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EDUKASI POLA ASUH ANAK DALAM KELUARGA MELALUI VIDEO UNTUK KADER PKK KELURAHAN CIPAMOKOLAN BANDUNG Deni Saepudin; Didit Adytia; Aditya Firman Ihsan
The Proceeding of Community Service and Engagement (COSECANT) Seminar Vol. 4 No. 1 (2024): The Proceeding of Community Service and Engagement (COSECANT) Seminar
Publisher : Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25124/cosecant.v6i1.7825

Abstract

Kegiatan abdimas ini merupakan kelanjutan dari abdimas sebelumnya dengan judul Edukasi Pencegahan Stunting dengan Media Interaktif. Mengingat pencegahan stunting perlu dilakukan secara komprehensif, materi edukasi yang disampaikan diperluas ke pola asuh anak, mulai edukasi untuk remaja calon ibu, fase kehamilan, merawat anak sejak janin dan paska melahirkan, terutama sampai anak berusia dua tahun. Materi edukasi tersedia dalam bentuk buku dan paparan narasumber yang disampaikan kepada para kader inti PKK Kelurahan. Namun untuk menyebarkan materi tersebut untuk masyarakat umum dengan bahasa yang mudah dan singkat merupakan tantangan tersendiri untuk para kader PKK. Dalam abdimas ini, materi edukasi disampaikan dalam bentuk paparan melalui video interaktif dan quiz. Media ini diharapkan dapat digunakan oleh para kader tim penggerak PKK untuk melakukan edukasi pada calon dan orang tua anak di bawah dua tahun (baduta). Hal ini dilakukan untuk memastikan bahwa ibu baduta yang merupakan tokoh kunci dapat memahami pola asuh yang benar sehingga anaknya sehat secara fisik dan mental, dan pastinya dapat terhindar dari stunting. Untuk mengukur efektivitas media edukasi ini akan dilakukan post-test melalui quiz untuk mengukur pemahaman masyarakat sasar.
MNetNCR: MobileNet model for efficient traditional Nusantara script character recognition Untari Novia Wisesty; Aditya Firman Ihsan; Mahmud Dwi Sulistiyo; Donni Richasdy; Prasti Eko Yunanto; Gamma Kosala; Arfive Gandhi; Febryanti Sthevanie
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 15, No 2: April 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v15.i2.pp1513-1528

Abstract

Preservation of traditional Nusantara scripts is very important because these traditional scripts are part of the cultural heritage that reflects the identity and history of the nation. This research proposed MobileNet for Nusantara character recognition (MNetNCR) model based on MobileNetV3 architecture to recognize traditional Nusantara scripts with lightweight, efficient architecture, and accurate recognition. The novel and comprehensive datasets for traditional Nusantara scripts have been curated in this research, that will later be stored digitally and can be used in further research. This novel dataset includes handwritten Balinese, Batak, Javanese, Lontara, and Sundanese scripts, each with unique visual characteristics. The proposed MNetNCR model is highly effective in recognizing characters, achieving F1-scores of 0.9934 for Balinese, 0.9450 for Batak, 0.9788 for Javanese, 0.9936 for Lontara, and 0.9961 for Sundanese scripts, according to the experimental results. The MNetNCR model built in this research has been proven to be effective and efficient in recognizing traditional scripts accurately. It also supports the preservation and promotion of the nation's cultural and historical heritage.
Investigating Shallow Learning Methods for Optical Character Recognition of Indonesia’s Nusantara Scripts Mahmud Dwi Sulistiyo; Aji Gautama Putrada; Aditya Firman Ihsan; Prasti Eko Yunanto; Donny Richasdy; Hassan Rizky Putra Sailellah; Sabrina Adinda Sari
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 9 No 6 (2025): December 2025
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v9i6.6648

Abstract

Indonesia has numerous regional scripts—or so-called Nusantara scripts—and recognizing them is important to preserve Indonesia's cultural heritage. The advances of AI and computer vision technologies make it possible for a machine to optically read the handwritten scripts through the Optical Character Recognition (OCR) technique. However, collecting some of the top OCR solutions and comprehensively investigating their performances on the Nusantara scripts is currently lacking. This study investigates and evaluates some shallow learning-based methods on our newly introduced datasets, consisting of more than 38,000-character images across 80 letter classes in total; here, we focus on three regional scripts: Javanese, Sundanese, and Balinese. The methods include Random Forest, SVM, Logistic Regression, and Gaussian Naïve Bayes, as well as boosting techniques such as XGBoost, Light GBM, and CatBoost. A 5-fold cross-validation approach assessed model performance based on accuracy, precision, recall, and F1-score. Based on the experimental results, the methods demonstrated their competitiveness in reaching the best models for scripts; in particular, XGBoost, Light GBM, and Random Forest-Gini were the winners for Javanese, Sundanese, and Balinese scripts, respectively. These findings demonstrate the effectiveness of ensemble learning methods for diverse handwritten scripts. Comparative analysis to prior deep learning studies is also discussed in this paper. In addition, this research also contributes to preserving Indonesian traditional scripts, as well as offers insights for future regional OCR in other countries.
ANALYZING TEMPEARTURE ANOMALIES IN MONITORING DATA USING CONVOLUTIONAL NEURAL NETWORK Nurhidayah Puteri; Widi Astuti; Aditya Firman Ihsan
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 10, No 1 (2025)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v10i1.5616

Abstract

Temperature is a tool that shows the degree or measure of how hot or cold an object is. Incorrect temperature measurement can be fatal and cause various problems. Abnormal temperatures can prevent the temperature detection system from running optimally. Therefore, it is necessary to classify temperatures into normal and anomalous. Machine learning can be used as an alternative for temperature classification. By utilizing machine learning methods, one of which is Convolutional Neural Network. 3688569 temperature data were tested, dividing the results into 80% training data and 20% testing data. Accuracy, Precision, Recall, and F1 Score get a score of 100% and the CNN model graph is very good.
Model bidirectional GRU with bayesian optimization for dry gas pressure forecasting in transmission pipeline networks Mohammad Alvinanda Kurniawan; Aditya Firman Ihsan; I Wayan Palton Anuwiksa
Journal of Soft Computing Exploration Vol. 7 No. 3 (2026): September 2026
Publisher : SHM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52465/joscex.v7i3.166

Abstract

Operational robustness and infrastructure safety require that stable dry gas pressure in transmission pipeline networks be maintained. Due to the highly nonlinear and time-varying behaviors of the dry gas pressure, conventional methods cannot predict its tendencies accurately. Deep learning models have recently gained good performance for time-series forecasting, however combination of Bidirectional Gated Recurrent Unit (BiGRU) and Bayesian Optimization based approach for dry gas pressure forecasting remains underexplored. Based on these, this study develops Bayesian optimization-enhanced forecasting framework for BiGRU to enhance the prediction performance. The framework is based on a Gaussian Process surrogate model and an acquisition function — in this case Expected Improvement, which guides the search for optimal hyperparameter configurations. We used operational SCADA time-series data consisting of hourly measurements (pressure, temperature, flowrate and gas composition) collected from a dry gas transmission pipeline across two annual periods. Pre-processing of data consists of dealing with missing data, Min–Max normalization and sliding window conversion. Here a multistep forecasting scenario for the next 20 hours was used, and thismultistep prediction was evaluated calculating the MAE, RMSE, and R². The optimized BiGRU performed the MAE of 11.7729 psi, RMSE of 14.7827 psi and R² of 0.9389, which enhanced the baseline model by 13.67%, 12.90%, and 1.60 percentage points respectively. These results indicate that Bayesian Optimization improves the forecasting performance of BiGRU and, at the same time, decreases the manual hyperparameter tuning efforts.
Co-Authors Aji Gautama Putrada Andi Fadil Adiyaksa Anugrah, M. Taufik Arfive Gandhi Conny Tria Shafira Deni Saepudin Didit Adytia Djatnika Widia Nugraha Donni Richasdy Donny Richasdy Donny Richasdy Faqih Ahmad Muzakky Febryanti Sthevanie Gamma Kosala Hery Widijanto I Wayan Palton Anuwiksa Indidharmanto, Ahmad Maulana M. Taufik Anugrah Made Mita Wikantari Mahadzir, Shuhaimi Mahmud Dwi Sulistiyo Mohammad Alvinanda Kurniawan Muhammad Daffa Regenta Sutrisno Muhammad Helmy Faishal Nurhidayah Puteri Prasti Eko Yunanto Pratama, Alif Adwitiya Putra, Rachmat Dwi Putu Harry Gunawan Raisa Benaya Rheza Ramadhan Putra Sabrina Adinda Sari Sailellah, Hassan Rizky Putra Sri Suryani Prasetyowati Sujadi, Cika Carissa Sulistyo, Mahmud Dwi Untari Novia Wisesty Uruqul Nadhif Dzakiy Widi Astuti Widi Astuti Yuliant Sibaroni Yusuf, Afrizal Syahruluddin