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All Journal JPTK: Jurnal Pendidikan Teknologi dan Kejuruan Scan : Jurnal Teknologi Informasi dan Komunikasi Knowledge Engineering and Data Science JMKSP (Jurnal Manajemen, Kepemimpinan, dan Supervisi Pendidikan) MIND (Multimedia Artificial Intelligent Networking Database) Journal Warta Penelitian Perhubungan Jurnal Praksis dan Dedikasi Sosial Journal of Vocational Education Studies Dinamika Bahari: Journal of Maritime Dynamic TEKIBA : Jurnal Teknologi dan Pengabdian Masyarakat Journal of Dinda : Data Science, Information Technology, and Data Analytics Journal of Practical Computer Science (JPCS) Maritime Park: Journal Of Maritime Technology and Socienty Knowbase : International Journal of Knowledge in Database Journal Research of Social Science, Economics, and Management Innovative: Journal Of Social Science Research Bulletin of Social Informatics Theory and Application ITIJ Jurnal Riset & Teknologi Terapan Kemaritiman Warta Penelitian Perhubungan
Setiawan, Ariyono
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Humanities Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Mechanical Engineering Public Health Social Sciences Transportation Other

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Optimalisasi Penentuan Rute Terbaik Pelayaran Berbasis Analisis Big Data untuk Efisiensi Bahan Bakar Kapal Laut Setiawan, Ariyono; Bin Abdul Hadi, Abdul Razak; Widyaningsih, Upik; Pamungkas, Anjar
Jurnal Riset & Teknologi Terapan Kemaritiman Vol. 3 No. 1 (2024)
Publisher : Departemen Teknik Sistem Perkapalan, Universitas Hasanuddin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25042/jrt2k.062024.05

Abstract

Penelitian ini bertujuan untuk mengoptimalkan rute pelayaran dengan menerapkan big data analytics guna meningkatkan efisiensi bahan bakar. Dengan memanfaatkan data real-time dan historis, studi ini mengidentifikasi rute paling efisien untuk meminimalkan konsumsi bahan bakar tanpa mengorbankan efektivitas operasional. Berbasis pada teori logistik maritim, analitik big data, dan efisiensi bahan bakar, penelitian ini menggabungkan model optimasi rute, prakiraan cuaca, serta analisis kinerja kapal untuk mendukung pengambilan keputusan navigasi. Selain itu, dampak regulasi IMO MARPOL Annex VI, khususnya EEDI dan SEEMP, turut dipertimbangkan dalam upaya optimalisasi efisiensi energi. Metode yang digunakan adalah pendekatan campuran, yang mengombinasikan analisis kuantitatif dari data AIS, laporan cuaca, serta catatan konsumsi bahan bakar dengan algoritma pembelajaran mesin untuk optimasi rute. Analisis korelasi Pearson mengevaluasi hubungan antara kecepatan, jarak, waktu tempuh, dan konsumsi bahan bakar. Studi kasus digunakan untuk memvalidasi model yang dikembangkan. Hasil penelitian menunjukkan bahwa konsumsi bahan bakar sangat dipengaruhi oleh kecepatan kapal, dengan kecepatan lebih tinggi meningkatkan konsumsi bahan bakar. Korelasi negatif ditemukan antara waktu tempuh dan konsumsi bahan bakar harian, menunjukkan bahwa pelayaran lebih lambat dapat meningkatkan efisiensi. Studi ini menekankan pentingnya pemrosesan data real-time dalam penyesuaian rute berdasarkan cuaca, kemacetan, dan efisiensi energi. Penelitian ini menawarkan pendekatan inovatif berbasis data dalam perencanaan rute, berbeda dari metode tradisional yang mengandalkan bagan statis dan pengalaman. Integrasi big data dalam logistik maritim dapat mengurangi emisi, menekan biaya, serta meningkatkan keberlanjutan operasional.
Optimalisasi Proses Produksi Kerajinan Batik Kampoeng Batara Banyuwangi Patrisia Mintje, Quirina Ariantji; Rumani, Daniel Dewantoro; Setiawan, Ariyono; Qiram, Ikhwanul
TEKIBA : Jurnal Teknologi dan Pengabdian Masyarakat Vol. 2 No. 1 (2022): TEKIBA : Jurnal Teknologi dan Pengabdian Masyarakat
Publisher : Fakultas Teknik, Universitas PGRI Banyuwangi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36526/tekiba.v2i1.2117

Abstract

Abstract – Batik is one of the arts and crafts products that are full of customs and culture of the people in Indonesia. The batik art of Kampoeng Batara UKM has existed and developed in the last two years. The limitations of technical facilities are an obstacle to batik production on a mass scale. Through this community service activity, technical support is provided in the form of production facilities for dyeing, boiling and washing media for batik cloth in the form of 10 drums with a capacity of 200 liters. Some of the drums are modified according to production needs with the capacity required by partners. The results of the activity show that the provision of technical support has given partners confidence to increase the capacity of batik products on a larger scale. Keyword: BBatik; Kampoeng Batara, Production, Technical Facilities.
Unveiling Risk Patterns of Disability Progression A Clustering Based Transition Matrix Analysis Using Indonesian National Data Setiawan, Ariyono; Bin Abdul Hadi, Abdul Razak; Faller, Erwin; Wibawa, Aji Prasetya
Indonesian Journal of Data Science, IoT, Machine Learning and Informatics Vol 5 No 2 (2025): August
Publisher : Research Group of Data Engineering, Faculty of Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/dinda.v5i2.1868

Abstract

This study investigates the progression of disability severity from "some difficulty" to "a lot of difficulty" using a transition matrix framework. It aims to identify risk patterns and classify severity clusters based on national survey data from Indonesia between 2010 and 2023. The study draws on the theory of functional limitation progression, which assumes that individuals with mild disabilities face varying probabilities of developing severe limitations depending on contextual and demographic factors. It also incorporates clustering theory to group similar progression behaviors. We utilize 20,604 data points from multiple disability types (cognitive, hearing, mobility, etc.). The transition rate is computed as the ratio of individuals with "a lot" difficulty to the total with "some" and "a lot" difficulty. Statistical analyses include descriptive summaries, Pearson correlation, and K-Means clustering via the FASTCLUS procedure. Heatmaps are generated to observe annual and typological patterns. The average transition rate is 66.77%, with a maximum of 99.6% in some subgroups. Three distinct severity clusters emerged, centered at 31.27%, 58.62%, and 82.20%. Transition rate negatively correlates with "some difficulty" prevalence (r = –0.45, p < .0001), indicating progressive concentration of severity in smaller populations. Heatmaps reveal consistent risk escalation over time, especially in cognitive and self-care disabilities. This study enables policy actors to stratify intervention priorities and monitor disability risk more accurately using dynamic, data-driven indicators. This is the first study in Indonesia to apply a large-scale transition matrix combined with clustering to map functional disability progression. It offers a novel quantitative method to uncover hidden severity patterns and informs future decision-support systems for inclusive health planning.
Multivariate Risk Analysis of Echotoxic Chemicals of Ballast Water Chemicals Based on PCA and DSS Using ECOTOX GISIS Data Setiawan, Ariyono; Widyaningsih , Upik; Pamungkas, Anjar; Bin Abdul Hadi, Abdul Razak; Dewi, Deshinta Arrova
Maritime Park: Journal of Maritime Technology and Society Volume 4, Issue 3, 2025
Publisher : Department of Ocean Engineering, Faculty of Engineering, Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62012/mp.vi.44925

Abstract

This study proposes a multivariate risk classification model for ballast water treatment chemicals by integrating global datasets—ECOTOX (U.S. EPA) and GISIS (IMO). Using Principal Component Analysis (PCA), we analyze 37 substances based on acute toxicity (LC50), chronic toxicity (NOEC), and bioaccumulation potential (BCF). The aim is to provide a practical, data-driven tool to support ecological compliance, early warnings, and regulatory prioritization in maritime chemical management. Results show that 43.24% of substances fall into the high-risk category, while only 8.11% are low risk. PCA effectively reduces dimensionality, explaining 73.63% of variance with just two components. High-risk chemicals such as Dibromoacetic acid and Dichloroacetonitrile exhibit low NOEC and high BCF values—indicating significant ecotoxic potential, often underregulated. Some commonly used oxidants also reveal hidden chronic toxicity, suggesting gaps in current risk frameworks post-BWM Convention. We construct a risk-scoring matrix and chemical heatmap to visualize ecotoxic profiles, enabling real-time risk ranking and decision support. Unlike previous studies that focus solely on toxicity thresholds or narrative reviews, this approach integrates empirical data with decision logic to aid Port State Control (PSC) and IMO policy design. The method is replicable and adaptable to other maritime pollutants, especially in the ASEAN context, enhancing smart port readiness and ecological safeguarding.
Integrating Machine Learning and Internet of Things for Predictive Maintenance Enhancing Operational Efficiency and Maritime Digitalization Setiawan, Ariyono; Handoko, Wisnu; Onn, Choo Wou; Widyaningsih, Upik
Dinamika Bahari Vol 6 No 2 (2025): October 2025 Edition
Publisher : Politeknik Ilmu Pelayaran Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46484/db.v6i2.1031

Abstract

This study explores the implementation of Machine Learning (ML) and the Internet of Things (IoT) in predictive maintenance to enhance the operational efficiency of ships. The primary goal is to evaluate the effectiveness of these technologies in reducing maintenance costs, minimizing unexpected machinery failures, and improving fuel efficiency. The research is based on previous studies on AI-driven predictive maintenance and IoT-based real-time monitoring. It builds upon the work of Kim & Park (2021) and Li et al. (2019), who demonstrated the advantages of deep learning and IoT in improving maritime asset management. A comparative analysis was conducted using multiple ML algorithms, including Random Forest, Support Vector Machine (SVM), K-Means Clustering, and Long Short-Term Memory (LSTM). Data from IoT-enabled sensors on ship machinery were used to evaluate model accuracy, downtime reduction, and cost efficiency improvements. LSTM outperformed other models with an accuracy of 89.1%. Predictive maintenance reduced downtime by 30%, extended machinery lifespan by 20%, and decreased operational costs by 15%. Challenges include IoT infrastructure limitations, data security concerns, and the need for extensive historical data. This study highlights the necessity for shipping companies to invest in IoT infrastructure, cybersecurity measures, and workforce training to optimize predictive maintenance. The research contributes to maritime digitalization by demonstrating how ML and IoT integration can transform maintenance strategies, leading to a more efficient and cost-effective shipping industry.
Analisis Perbandingan Keuntungan Finansial dan Nonfinansial antara Penggunaan Jet Pribadi dan Penerbangan Maskapai Komersial Setiawan, Ariyono; Tri Prasetyo, Kukuh; Suprapto, Yuyun; Rahayu, Sri
Warta Penelitian Perhubungan Vol. 36 No. 1 (2024): Warta Penelitian Perhubungan
Publisher : Sekretariat Badan Penelitian dan Pengembangan Perhubungan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25104/warlit.v36i1.2237

Abstract

Penelitian ini menganalisis keuntungan finansial dan nonfinansial penggunaan jet pribadi versus penerbangan maskapai komersial. Data dari 50 responden dikumpulkan dan dianalisis menggunakan metode kuantitatif. Hasil penelitian menunjukkan bahwa penggunaan jet pribadi memberikan keuntungan finansial yang signifikan. Pengguna jet pribadi menghemat waktu perjalanan dan memiliki nilai waktu yang lebih tinggi dibandingkan dengan pengguna maskapai komersial. Biaya perjalanan jet pribadi juga lebih rendah dalam jangka panjang daripada maskapai komersial. Selain itu, pengguna jet pribadi menikmati tingkat kenyamanan yang lebih baik dengan fasilitas eksklusif. Kesimpulannya, penggunaan jet pribadi memiliki keuntungan finansial berupa efisiensi waktu, nilai waktu yang lebih tinggi, penghematan biaya, dan tingkat kenyamanan yang lebih baik. Keputusan dalam memilih metode perjalanan harus didasarkan pada kebutuhan, preferensi, dan kemampuan finansial individu. Penelitian ini memberikan wawasan berharga bagi individu atau perusahaan yang mempertimbangkan penggunaan jet pribadi.
Analisis Perbandingan Keuntungan Finansial dan Nonfinansial antara Penggunaan Jet Pribadi dan Penerbangan Maskapai Komersial Setiawan, Ariyono; Tri Prasetyo, Kukuh; Suprapto, Yuyun; Rahayu, Sri
Warta Penelitian Perhubungan Vol. 36 No. 1 (2024): Warta Penelitian Perhubungan
Publisher : Sekretariat Badan Penelitian dan Pengembangan Perhubungan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25104/warlit.v36i1.2237

Abstract

Penelitian ini menganalisis keuntungan finansial dan nonfinansial penggunaan jet pribadi versus penerbangan maskapai komersial. Data dari 50 responden dikumpulkan dan dianalisis menggunakan metode kuantitatif. Hasil penelitian menunjukkan bahwa penggunaan jet pribadi memberikan keuntungan finansial yang signifikan. Pengguna jet pribadi menghemat waktu perjalanan dan memiliki nilai waktu yang lebih tinggi dibandingkan dengan pengguna maskapai komersial. Biaya perjalanan jet pribadi juga lebih rendah dalam jangka panjang daripada maskapai komersial. Selain itu, pengguna jet pribadi menikmati tingkat kenyamanan yang lebih baik dengan fasilitas eksklusif. Kesimpulannya, penggunaan jet pribadi memiliki keuntungan finansial berupa efisiensi waktu, nilai waktu yang lebih tinggi, penghematan biaya, dan tingkat kenyamanan yang lebih baik. Keputusan dalam memilih metode perjalanan harus didasarkan pada kebutuhan, preferensi, dan kemampuan finansial individu. Penelitian ini memberikan wawasan berharga bagi individu atau perusahaan yang mempertimbangkan penggunaan jet pribadi.
Comparison Analysis Of Fuel On Manual And Systematic Flight Plan On Citilink Airlines On The Jakarta-Surabaya Route Using Airbus A320 Aircraft Mubarok, Ahmad; Tirtanto, Jadon Pieter Elia; Setiawan, Ariyono; Rumani, Daniel Dewantoro
Journal Research of Social Science, Economics, and Management Vol. 3 No. 5 (2023): Journal Research of Social Science, Economics, and Management
Publisher : Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59141/jrssem.v3i5.599

Abstract

A Flight Plan is an essential element for achieving efficiency. Prior to operating a flight, a Flight Plan must be prepared. The flight operations officers (FOOs) utilize Airbus's NavBlue application to create a systematic Flight Plan. They can also manually generate a Flight Plan using the FCOM (Flight Crew Operating Manual) guidebook. This research focuses on the differences in fuel planning between the systematic and manual methods of Flight Plan creation, as there are variations between the two approaches. Qualitative methodology is used to gather and analyze secondary data, including both manual and systematic Flight Plans, weather and environmental data, as well as aircraft technical documents and fuel tank capacities. The anticipated outcome of this research is to provide valuable insights for the aviation industry in enhancing operational efficiency.
AS Spatiotemporal Analysis of LSCI Variations in ASEAN Using ANOVA and Cluster Techniques (2017–2022) Setiawan, Ariyono; Antoni Arif Priadi; Abdul Razak Bin Abdul Hadi; Erwin Faller
Knowbase : International Journal of Knowledge in Database Vol. 5 No. 1 (2025): June 2025
Publisher : Universitas Islam Negeri Sjech M. Djamil Djambek Bukittinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30983/knowbase.v5i1.9583

Abstract

This study investigates maritime connectivity performance in ASEAN countries using the Liner Shipping Connectivity Index (LSCI) from 2019 to 2023. It aims to identify significant trends, segment national performance, and provide policy-relevant insights on regional maritime development. The research is grounded in transport connectivity and regional integration theory, emphasizing the role of liner shipping as a critical enabler of trade efficiency and economic cooperation in Southeast Asia. The study employs a quantitative approach using longitudinal LSCI data across ten ASEAN member states. It applies descriptive statistics, linear regression modeling for each country, and clustering through k-means (fastclus) to categorize national maritime connectivity performance. Indonesia records the highest average LSCI (49.28), indicating a consistent lead in regional maritime connectivity. Cambodia demonstrates the strongest upward trend with a significant positive slope (β = 0.98; p < 0.01), followed by Myanmar (β = 0.61; p < 0.05) and Laos (β = 0.58; p < 0.01). Cluster results suggest three distinct groups of countries based on average connectivity levels, highlighting disparities and the need for policy harmonization. The regression models explain up to 94% of the variance in several countries' LSCI growth. The findings support regional policy formulation to strengthen weaker maritime economies and align ASEAN maritime strategies with trade facilitation goals. This study presents a novel integration of trend modeling and cluster segmentation of LSCI data within the ASEAN context. It contributes both theoretically to the study of maritime connectivity metrics and practically to policy and infrastructure development.
Analisis Big Data Kesiapan Digital Global Menggunakan PCA dan FASTCLUS Setiawan, Ariyono; Yudianto, Prima Yudha; Ika, Ni Made; Masdiyas, I Gede Susrama
Journal of Practical Computer Science Vol. 5 No. 2 (2025): November 2025
Publisher : DPPM Universitas Pelita Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37366/jpcs.v5i2.6075

Abstract

This study aims to identify global digital readiness patterns using an innovative big data approach by integrating Principal Component Analysis (PCA) and the FASTCLUS clustering algorithm. By analyzing 1,076 observations from 2000 to 2023, this study focuses on four key indicators: secure server deployment and ICT infrastructure index. Referring to the Digital Readiness Framework, this study positions digital infrastructure and cybersecurity as the foundation of national digital capacity. PCA results show that two main components explain 56.35% of the total variance, and the clustering process produces strong segmentation with Pseudo F = 1275.85 and R² = 70.4%. Three digital readiness clusters were successfully identified: advanced (4 countries), moderate (64 countries), and transitional (1008 countries), each exhibiting distinct infrastructure and digital index characteristics. This study contributes a replicable, globally scalable classification framework for comparing digital readiness across countries. Its originality lies in the integration of big data techniques and unsupervised learning into national digital readiness assessments. These findings are important for supporting data-driven digital policy formulation, particularly for developing countries in designing more precise and contextual ICT resource allocation strategies.
Co-Authors ABDUL HADI, ABDUL RAZAK BIN Abdul Razak Bin Abdul Hadi Aji Prasetya Wibawa Antoni Arif Priadi Ardian, Dede Bin Abdul Hadi, Abdul Razak Dana, I Putu Ngurah Krisna Daniel Dewantoro Rumani Dewi, Deshinta Arrova Dwi Kusuma, Irma Efendi Efendi Eppy Yundra, Eppy Erwin Faller Fajar Islam Faller, Erwin Fatmawati Sabur Febiyanti, Herlina Globalisasi, Safitri Era Gusti Agung Ayu Putri Hammad, Jehad A. H Hammad, Jehad A.H Handoko, Wisnu Harianto, Bambang Bagus Ika, Ni Made Ikhwanul Qiram Larasati, Khoirunnisa Luthfiyah Nurlaela Mas Diyasa, I Gede Susrama Mas Diyasa, I Gede Susrama Masdiyas, I Gede Susrama Meini Sondang Mubarok, Ahmad Nahusuly, Barep J. A. I. Ni Made Ika Marini Mandenni Onn, Choo Wou Pambudiyatno, Nyaris Pamungkas, Anjar Patrisia Mintje, Quirina Ariantji Prasetyo, Kukuh Tri Putra, Iwansyah Putri, Fitri Aulia Yuliandi Raditya, Askara Rusdyansyah, Arief Sazali, Abdul Muti SRI RAHAYU Sri Wibawani, Sri Sutoyo Sutoyo Sutralinda, Dety Terza Damaliana, Aviolla Tirtanto, Jadon Pieter Elia Tri Prasetyo, Kukuh Utomo, Tri Rizki Wibowo, Untung Lestari Widyaningsih , Upik Widyaningsih, Upik Wiratama, I Putu Bayu Adhya Yudianto, Prima Yudha Yuniar, Dwi Candra Yuyun Suprapto