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All Journal International Journal of Electrical and Computer Engineering IAES International Journal of Artificial Intelligence (IJ-AI) BERKALA FISIKA Media Statistika MATEMATIKA JURNAL SISTEM INFORMASI BISNIS Semantik Jurnal Ilmiah Kursor Jurnal Inovasi Teknologi Pendidikan Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Edukasi dan Penelitian Informatika (JEPIN) Register: Jurnal Ilmiah Teknologi Sistem Informasi Proceeding of the Electrical Engineering Computer Science and Informatics AKSIOMA Jurnal Teknologi dan Sistem Komputer Informatika Mulawarman: Jurnal Ilmiah Ilmu Komputer Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal Matematika: MANTIK Jurnal Penelitian Pendidikan IPA (JPPIPA) Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control BAREKENG: Jurnal Ilmu Matematika dan Terapan Unisda Journal of Mathematics and Computer Science (UJMC) JTAM (Jurnal Teori dan Aplikasi Matematika) Jurnal Segara Jurnal Teknik Informatika (JUTIF) Journal of Applied Data Sciences Journal of Soft Computing Exploration Interdisciplinary Social Studies Journal of Fundamental Mathematics and Applications (JFMA) Buletin Abdi Masyarakat (BAM) Prosiding Konferensi Nasional Penelitian Matematika dan Pembelajarannya Jurnal Ekonomi, Teknologi dan Bisnis Scientific Journal of Informatics
Bayu Surarso
Department Of Mathematics & Graduate School Of Information System
Agriculture, Biological Sciences & Forestry Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Public Health Social Sciences Transportation Other

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ANALYSIS OF FACTORS AFFECTING THE SELLING PRICE OF FROZEN BIG EYE TUNA (TUNNUS OBESUS) AT CILACAP FISHING PORT Shalichaty, Shiffa Febyarandika; Saputra, Suradi Wijaya; Wijayanto, Dian; Surarso, Bayu
Jurnal Segara Vol 20, No 2 (2025): December
Publisher : Politeknik Kelautan dan Perikanan Dumai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15578/segara.v20i2.19438

Abstract

Bigeye tuna is one of Indonesia's leading fishery commodities. One of the main locations for the routine landing and handling of this species is the Cilacap Fishing Port. The selling price of bigeye tuna plays a crucial role in the sustainability of fisheries businesses. However, unstable and unpredictable tuna prices make it difficult for some businesses to assess their long-term sustainability. Various factors influence tuna prices, both internal to fishing operations and external economic conditions. This study aims to identify factors that influence the selling price of bigeye tuna at the Cilacap Fishing Port. This study used direct observation, interviews, and a literature review, with data ranging from 2022 to 2024. The analytical approach used was multiple linear regression analysis. The research findings indicate that the selling price of frozen bigeye tuna is influenced by production volume, production value, fishing month, and operational costs. The F-test results indicate that the dollar exchange rate, export volume and value, production volume, production value, fishing month, and operational costs simultaneously influence the selling price of bigeye tuna. These variables influence 80.6% of the selling price of bigeye tuna, while 19.4% is influenced by other factors outside the research.                   
Customer Segmentation Based on Recency, Frequency, Monetary Analysis Using K-Means Algorithms in Apple Ecosystem Edwin Setiawan; Bayu Surarso; Dinar Mutiara Kusumo Nugraheni
Jurnal Penelitian Pendidikan IPA Vol 11 No 2 (2025): February
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v11i2.10011

Abstract

One of the companies in Semarang engaged in gadget sales services has an Apple Ecosystem information system for selling products from an exclusive brand, Apple. Inside there are sales transactions and also service devices iPad, Macbook Air, Macbook Pro, AirPods, Mac, and Apple Accsessories. This research uses purchase transaction data from Apple Ecosystem customers for the period 2023. The use of RFM (Recency, Frequency, Monetary) analysis helps in determining the attributes used for customer segmentation. To determine the optimal number of clusters from the RFM dataset, the Elbow method is applied. The dataset generated from RFM is grouped using the K-Means algorithm, the quality of the algorithm will be compared in cluster formation using the Silhouette Coefficient method. All procedures will be loaded into the Customer Segmentation App (RFM Clustering) web application. Customer segmentation from RFM datasets that have been clustered produces 3 optimal clusters, namely Cluster 2 is High Spenders with 326 customers, Cluster 0 is VIP Customers, Cluster 1 is Frequent Buyers. Cluster validation of k-means using the silhouette coefficient produces a value of 0.3524.
Integration of BERTopic and IndoBERTweet for Aspect-Based Sentiment Analysis (ABSA) on Short Text Data: A Case Study of Responses to Government Policies in 2025 Nabiel Putra Adam; Rahmat Gernowo; Bayu Surarso
Jurnal Ekonomi, Teknologi dan Bisnis Vol. 5 No. 1 (2026): Jurnal Ekonomi, Teknologi dan Bisnis
Publisher : Al-Makki Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57185/k9s34530

Abstract

The implementation of various government policies in 2025 has triggered massive public opinion on social media platform X; however, traditional sentiment analysis often fails to provide details on specific topics, necessitating an Aspect-Based Sentiment Analysis (ABSA) approach. This research integrates the BERTopic model for aspect extraction and IndoBERTweet for sentiment classification to address the challenges associated with the characteristics of short and unstructured text. By preserving the data without a stemming process to maintain semantic context integrity, the BERTopic model demonstrates optimal performance with a Coherence score (C_v) of 0.7539 and a Topic Diversity of 0.9285. The synergy between BERTopic and IndoBERTweet proves effective in generating coherent topic representations and accurate sentiment classification for informal language on social media. Consequently, this integration provides a more profound and superior solution for mapping public responses to the dynamics of government policy.
Analysis of Naïve Bayes and K-Nearest Neighbors Algorithms for Classifying Fishermen Aid Eligibility Muhammad Nasrullah; Bayu Surarso; Oky Dwi Nurhayati
Jurnal Penelitian Pendidikan IPA Vol 10 No 10 (2024): October
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v10i10.8818

Abstract

This article analyzes the use of data mining with Naïve Bayes and K-Nearest Neighbor (KNN) algorithms to build classification models and evaluate their performance in identifying fishermen eligible for aid. The study aims to compare the effectiveness of these algorithms in handling imbalanced datasets using the Synthetic Minority Over-sampling Technique (SMOTE). The research applies SMOTE to improve the balance of the dataset before classification. Without SMOTE, Naïve Bayes achieved an accuracy of 97.01%, precision of 94.16%, recall of 96.67%, and F1-score of 95.39%. KNN, on the other hand, reached an accuracy of 94.04%, precision of 94.53%, recall of 86.00%, and F1-score of 90.06%. After applying SMOTE, both algorithms improved: Naïve Bayes attained an accuracy of 98.33%, precision of 96.86%, recall of 100.00%, and F1-score of 98.49%, while KNN reached an accuracy of 96.90%, precision of 97.72%, recall of 96.19%, and F1-score of 96.94%. The results show that Naïve Bayes, with SMOTE, outperforms KNN in managing data imbalance and accurately classifying eligible fishermen for aid.
Image Cryptography Process Using Arnold’s Cat Map And Henon Map Algorithms Al Ghifari, Moch Azhar; Surarso, Bayu; Sugiharto, Aris
Jurnal Teknik Informatika (Jutif) Vol. 7 No. 3 (2026): JUTIF Volume 7, Number 3, June 2026
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2026.7.3.5354

Abstract

The security of digital image data is a crucial aspect in various fields, such as communications, medicine, and the military. The inherent characteristics of digital images—namely high pixel correlation and large data size—render conventional encryption methods less optimal. This study aims to evaluate the encryption quality of images using the Arnold’s Cat Map (ACM) and Henon Map algorithms, both individually and in combination (ACM-Henon and Henon-ACM). ACM is utilized to rearrange pixel positions to create a confusion effect, while the Henon Map is employed to randomly alter pixel values (diffusion). The implementation is carried out using the Python programming language within the Visual Studio Code development environment. Encryption quality is assessed using parameters such as Avalanche Effect (AE), Unified Average Changing Intensity (UACI), Number of Pixels Change Rate (NPCR), and correlation coefficient. Experimental results show that the combined chaos-based methods significantly enhance security compared to the individual algorithms, particularly by analyzing the impact of algorithm order on encryption quality. The best performance was achieved by the Henon→ACM combination, producing NPCR ≈ 99.44%, UACI ≈ 19.93%, entropy ≈ 7.9874, and AE ≈ 50.12%, indicating strong randomness and resistance to differential attacks. This research demonstrates that combining confusion and diffusion mechanisms yields more secure cipher images than using either method alone. The main contribution of this study lies in providing a systematic comparative evaluation of single and combined chaos-based encryption schemes, including order-sensitive analysis across different image characteristics, rather than proposing a new encryption algorithm. However, the encryption performance is influenced by image size, parameter selection, and iteration count, which may limit consistency across different image characteristics. Future work may explore adaptive parameter optimization and improved diffusion mechanisms for higher UACI values.
BERT Model Fine-tuned for Scientific Document Classification and Recommendation Muhammad Deagama Surya Antariksa; Aris Sugiharto; Bayu Surarso
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 9 No 4 (2025): August 2025
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v9i4.6789

Abstract

The increasing number of academic documents requires efficient and accurate classification and recommendation systems to assist in retrieving relevant information. This system is built using the "bert-base-uncased” model from Hugging Face, which has been fine-tuned to improve the classification accuracy and relevance of document recommendations. The dataset used consists of 2.000 academic documents in the field of computer science, with features including titles, abstracts, and keywords, which were combined into a single input for the model. Document similarity is measured using cosine similarity, resulting in recommendations based on semantic proximity. Unlike traditional approaches, which rely primarily on word frequency or surface-level matching, the proposed method leverages BERT’s contextual embeddings to capture deeper semantic meanings and relationships between documents. This allows for more accurate classification and more context-aware recommendations. Evaluation results show that the best model configuration (learning rate 3e-5, batch size 32, optimizer AdamW) achieved 89.5% training accuracy and an F1-score of 0.8947, while testing yielded 91% accuracy and 90% F1-score. The recommendation system consistently produced Precision@k values above 92% for k between 5 and 30, with Recall@k reaching 1.0 as k increased. These results indicate that the system not only performs reliably in classifying complex academic texts but also effectively recommends contextually relevant documents. This integrated approach shows strong potential for enhancing academic document retrieval and supports the development of semantically aware information management systems.
Co-Authors A. Nafis Haikal Adi Wibowo Adi Wibowo Agus Subagio Ahmad Abdul Chamid Ahmad Aviv Mahmudi Aina Latifa Riyana Putri Al Ghifari, Moch Azhar Alfajri, Willy Bima Ali Bardadi Anak Agung Gede Sugianthara Arief Hidayat Aris Puji Widodo Aris Sugiharto Aris Sugiharto Aslam Fatkhudin Aulia, Lathifatul Badieah Assegaf Bambang Irawanto Beta Noranita Budi Warsito Budi Warsito Budi Warsito Che Pee, Ahmad Naim Dedy Kurniadi Dian Wijayanto Dinar Mutiara Kusumo Nugraheni Dwi Putri Handayani Dwiyanasari, Desty Edwin Setiawan Eko Adi Sarwoko Eko Sediyono Etna Vianita Fajar Nugraha Fra Siskus Dian Arianto Ghufron Ghufron Harjito - Henny Indriyawati Imam Tahyudin Indah Jumawanti Irfan Santiko I’tishom Al Khoiry Jumawanti, Indah Jumawanti, Indah Juwanda, Farikhin Khoerunnisa, Selvi Fitria Khusnah, Miftakhul Laily Rahmania, Laily Lili Rusdiana, Lili LM Fajar Israwan, LM Fajar Lucia Ratnasari Masruroh, Fitriana Maunah, Uun Migunani Migunani Muhammad Deagama Surya Antariksa Muhammad Haris Qamaruzzaman Muhammad Nasrullah Muhammad Sam'an Mustafid Mustafid Mustaqim Mustaqim Mustaqim Mustaqim, Mustaqim Nabiel Putra Adam Nugraheni, Dinar Oky Dwi Nurhayati Pukky Tetralian Bantining Ngastiti Putri, Nitami Lestari Putut Sriwasito Rachmat Gernowo Ragil Saputra Ragil Saputra Rahmat Gernowo Rahmawati, Nurhita Ratri Wulandari Rezki Kurniati, Rezki Rineka Brylian Akbar Satriani Robertus Heri Sulistyo Utomo Saputra, Ragil Satriani, Rineka Brylian Akbar Shiffa Febyarandika Shalichaty St. Budi Waluya Sulastri Daruni Sulistiyo, Budi Suradi Wijaya Saputra Suryono Suryono Suryono Suryono Suryono, Suryono Susi Hendartie Susilo Hariyanto sutimin sutimin Sutrisno, Sutrisno Sutrisno, Sutrisno T Indriastuti . Titi Udjiani SRRM Tri Retnaningsih Soeprobowati Uswatun Khasanah Vianita, Etna Wahyul Amien Syafei Wicaksono, Mahad Zainal Arifin Hasibuan