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All Journal EXPERT: Jurnal Manajemen Sistem Informasi dan Teknologi Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) RABIT: Jurnal Teknologi dan Sistem Informasi Univrab JOURNAL OF APPLIED INFORMATICS AND COMPUTING SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan JPPM (Jurnal Pengabdian dan Pemberdayaan Masyarakat) EDUMATIC: Jurnal Pendidikan Informatika Abdimasku : Jurnal Pengabdian Masyarakat International Journal of Marine Engineering Innovation and Research Jurnal Altifani Penelitian dan Pengabdian kepada Masyarakat
Soni Adiyono
Universitas Muria Kudus
Religion Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mechanical Engineering Medicine & Pharmacology Nursing Physics Public Health Social Sciences Transportation Other

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Artificial Intelligence in Integrated Marine Observing Systems: A Comprehensive Review Soni Adiyono; Muhammad Arifin; Noor Latifah; Eko Darmanto
International Journal of Marine Engineering Innovation and Research Vol. 10 No. 1 (2025)
Publisher : Department of Marine Engineering, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j25481479.v10i1.4754

Abstract

The marine ecosystem is vital for sustaining life on Earth, yet its vastness and complexity present significant challenges for effective monitoring and management. Integrated Marine Observing Systems (IMOS) have emerged as essential tools for understanding and protecting marine environments. This study aims to systematically review the integration of artificial intelligence (AI) into IMOS, focusing on its contributions to data processing, biodiversity monitoring, and environmental change analysis. A systematic literature review (SLR) method is employed to analyze existing research and identify key AI techniques and their applications in marine and oceanographic studies. Results indicate that deep learning is the most widely used AI method, with marine research being the primary application domain. Other areas, such as environmental monitoring and industrial systems, also demonstrate considerable potential. However, data inconsistency, operational limitations, and the lack of standardized frameworks remain significant barriers. This review highlights the transformative role of AI in enhancing IMOS capabilities and provides recommendations for addressing existing challenges to support sustainable marine management.
Smart Port Management in Digital Transformation: A Review for Future Research Syafrie Muhammad Hawari; Triana Rahajeng Hadiprawoto; Ira Iriyanty; Yeshika Alversia; Soni Adiyono
International Journal of Marine Engineering Innovation and Research Vol. 9 No. 3 (2024)
Publisher : Department of Marine Engineering, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j25481479.v9i3.4903

Abstract

Ports are basic center points in worldwide transportation, affecting supply chains and national economies. With the rise of Industry 4.0, joining computerised change such as IoT, huge information, cloud computing, and AI into harbour operations has ended up progressively vital. This study provides a systematic evaluation of 41 selected articles focusing on three critical aspects of smart port development: developments in digital transformation, assessment of smart port implementation, and related challenges and limitations. Utilizing indicators such as technology relevance, operational efficiency, user experience, regulatory barriers, and infrastructure readiness, the analysis reveals that a significant number of articles contributed to digital transformation technologies (average score: 7.61), performance evaluation (average score: 6.63), and challenges and barriers (average score: 6.15). Trend graphs and Pareto diagrams highlight fluctuations in contributions and emphasize that a small number of high-scoring articles have a considerable impact. This research underscores the importance of a thorough and systematic approach in assessing digital transformation technologies and offers valuable insights into the current landscape, opportunities, and challenges. The findings are intended to guide stakeholders in developing effective strategies for achieving sustainable digital transformation in smart ports.
Cyberbullying on Multicultural Education a Coastal Community Perspective: Systematic literature review Nanik Susanti; Soni Adiyono; Zainur Romadhon
International Journal of Marine Engineering Innovation and Research Vol. 9 No. 1 (2024)
Publisher : Department of Marine Engineering, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j25481479.v9i1.5053

Abstract

This research explores the pervasive issue of cyberbullying, primarily targeting children and teenagers due to their close proximity to communication technologies. Cyberbullying manifests through various forms such as flaming, harassment, and identity impersonation, causing significant psychological and academic impacts on victims. The study, based on a selection of 30 Scopus publications, reveals that cyberstalking holds the highest classification at 90%, followed by flaming at 73%. The consequences of cyberbullying are classified into social (67%), psychological (63%), and academic (57%) impacts. The research emphasizes the need for specific knowledge about cyberbullying in coastal communities, where victims experience feelings of insecurity, isolation, and reduced academic concentration. The conclusion highlights the importance of raising awareness, implementing literacy programs, and enforcing regulations to combat cyberbullying, especially in the context of the Fourth Industrial Revolution. The findings provide valuable insights into the coastal community's perception of cyberbullying, urging parents to play an active role in safeguarding their children and promoting digital literacy.
Implementasi Sistem Informasi Retur Barang Rusak Berbasis Web di PT Telkom Akses Kudus Damar Aji Gurowo; Soni Adiyono
ABDIMASKU : JURNAL PENGABDIAN MASYARAKAT Vol 9, No 2 (2026): MEI 2026
Publisher : LPPM UNIVERSITAS DIAN NUSWANTORO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/ja.v9i2.3303

Abstract

Kegiatan pengabdian ini dilaksanakan di PT Telkom Akses Kudus untuk mengatasi pengelolaan retur barang rusak yang masih dilakukan secara manual melalui Microsoft Excel dan aplikasi pesan instan. Kondisi tersebut menyebabkan pencatatan berulang, potensi kesalahan input nomor serial, duplikasi data, serta kesulitan dalam pelacakan status barang dan penyusunan laporan. Oleh karena itu, topik ini penting karena berkaitan langsung dengan efisiensi kerja admin gudang dan ketepatan pengelolaan data retur perangkat rusak. Metode pelaksanaan menggunakan model Waterfall yang meliputi analisis kebutuhan, perancangan sistem, implementasi, pengujian sistem, dan pemeliharaan. Hasil kegiatan menunjukkan bahwa sistem informasi retur barang rusak berbasis web yang dibangun mampu mendukung proses login, registrasi teknisi, input data barang rusak, verifikasi serial number, pengelolaan status barang, serta monitoring melalui dashboard. Penerapan sistem mempermudah pencatatan, pencarian data, pelacakan riwayat, rekapitulasi, dan penyusunan laporan. Evaluasi pengguna juga menunjukkan respons sangat positif, sehingga dapat disimpulkan bahwa sistem ini efektif membantu pengelolaan retur barang rusak secara lebih terintegrasi, tertib, dan efisien.
Optimalisasi kinerja host tiktok melalui pengembangan sistem monitoring live streaming dan rekap konten berbasis web di PT. Aqualux Yita Abadi Lu'lu'il Laili; Soni Adiyono
SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan Vol 10, No 2 (2026): April
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jpmb.v10i2.38935

Abstract

Abstrak      PT Aqualux Yita Abadi, perusahaan yang memanfaatkan platform TikTok untuk pemasaran produk, menghadapi kendala dalam mengevaluasi kinerja host secara objektif akibat proses rekap konten dan monitoring live streaming yang masih dilakukan secara manual menggunakan catatan kertas. Metode ini menyebabkan ketidakakuratan data, tidak adanya dokumentasi terpusat, serta keterlambatan evaluasi kinerja. Kegiatan pengabdian masyarakat ini bertujuan untuk mengembangkan dan mengimplementasikan Sistem Monitoring Live Streaming dan Rekap Konten untuk Evaluasi Kinerja Host TikTok Berbasis Web bagi PT Aqualux Yita Abadi. Mitra sasaran kegiatan ini adalah PT Aqualux Yita Abadi yang melibatkan 9 orang host live streaming, 1 staf HRD, dan 1 Manajer Operasional sebagai peserta kegiatan, berlokasi di Jalan Lingkar Selatan Kec. Mejobo, Kabupaten Kudus. Metode pelaksanaan meliputi analisis kebutuhan sistem, perancangan sistem, pengembangan sistem menggunakan framework Laravel dengan arsitektur MVC, uji coba sistem (testing), evaluasi sistem, serta implementasi dan pelatihan. Hasil kegiatan menunjukkan bahwa sistem berhasil dikembangkan dengan fitur autentikasi berbasis role, dashboard monitoring real-time, fitur validasi data, serta laporan kinerja yang dapat diekspor dalam format Excel. Implementasi sistem meningkatkan efisiensi waktu rekap data dari berhari-hari menjadi hitungan menit, menghilangkan potensi kesalahan pencatatan manual, serta menyediakan dokumentasi terpusat yang memudahkan verifikasi bukti live streaming. Keberhasilan kegiatan ini ditinjau dari kemampuan sistem dalam membantu pengelolaan monitoring live streaming secara lebih terstruktur dan objektif. Kata kunci: sistem monitoring; live streaming; evaluasi kinerja; laravel; pengabdian masyarakat. Abstract      PT Aqualux Yita Abadi, a company utilizing the TikTok platform for product marketing, faces challenges in objectively evaluating host performance due to the manual process of content recapitulation and live streaming monitoring using paper records. This method leads to data inaccuracies, lack of centralized documentation, and delays in performance evaluation. This community service activity aims to develop and implement a Web-Based Live Streaming Monitoring and Content Recapitulation System for Evaluating TikTok Host Performance for PT Aqualux Yita Abadi. The target partner of this activity is PT Aqualux Yita Abadi, involving 9 live streaming hosts, 1 HR staff member, and 1 operational manager as participant, located at Jalan Lingkar Selatan, Mejobo District, Kudus Regency. The implementation methods include system requirements analysis, system design, system development using the Laravel framework with MVC architecture, system testing, system evaluation, as well as implementation and training. The results show that the system has been successfully developed with role-based authentication features, real-time monitoring dashboards, data validation features, and performance reports that can be exported to Excel format. The system implementation improves data recapitulation time efficiency from days to minutes, eliminates the potential for manual recording errors, and provides centralized documentation that facilitates verification of live streaming evidence. The success of this activity is measured by the system's ability to assist in managing live streaming monitoring in a more structured and objective manner. Keywords: monitoring system; live streaming; performance evaluation; laravel; community service
IMPLEMENTASI METODE FP-GROWTH DALAM ANALISA POLA PEMBELIAN PELANGGAN PADA SWALAYAN PANTES PATI BERBASIS WEB: IMPLEMENTATION OF THE FP-GROWTH METHOD IN WEB-BASED ANALYSIS OF CUSTOMER PURCHASE PATTERNS AT PANTES PATI SUPERMARKET Salum Ainayya Alfatikhah; Supriyono Supriyono; Soni Adiyono
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 11 No 1 (2026): Januari
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v11i1.7401

Abstract

Swalayan Pantes, located in Pati Regency, is a retail store that provides daily necessities. However, its current data processing still relies on manual management through Microsoft Excel, which is less efficient for conducting sales analysis. This study aims to develop a web-based purchasing pattern analysis system by employing the Frequent Pattern Growth (FP-Growth) method. The methodological stages include determining support values, constructing the FP-Tree, generating the conditional pattern base, building the conditional FP-Tree, identifying frequent itemsets, and calculating confidence values. Based on 1,725 transaction records collected between January 2025 and July 2025, the study identified 13 items most frequently purchased together, with a confidence threshold of 60% and a minimum support value of 5. The FP-Growth method was subsequently implemented into a web-based system, complemented with additional features such as “Pindah” (Move) and “Promo” (Promotion), to facilitate decision-making and follow-up actions derived from the analysis results.
ANALISIS SENTIMEN ULASAN GOOGLE MAPS UNTUK REKOMENDASI COFFEE SHOP DI KUDUS MENGGUNAKAN TF-IDF DAN LOGISTIC REGRESSION: SENTIMENT ANALYSIS OF GOOGLE MAPS REVIEWS FOR COFFEE SHOP RECOMMENDATIONS IN KUDUS USING TF-IDF AND LOGISTIC REGRESSION Diyas Aditya Adi Saputra; Noor Latifah; Soni Adiyono
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 11 No 2 (2026): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v11i2.7952

Abstract

The rapid growth of the café industry in Kudus has given residents plenty of options for places to hang out. Customer reviews on Google Maps serve as a vital information source, as they contain customer opinions and satisfaction levels regarding a particular cafe. However, the sheer volume of review data makes manual analysis less effective. This study aims to analyze the sentiment of Google Maps reviews for 10 cafés in Kudus (2023–2025) using the TF-IDF method and a Logistic Regression algorithm based on K-Fold Cross-Validation. Research data was obtained through web scraping, comprising 3,393 Google Maps reviews. The research stages included data preprocessing (text normalization, tokenization, stopword removal), feature extraction using TF-IDF, splitting the data into 80% training and 20% testing sets, training the Logistic Regression model, and evaluating model performance using K-Fold Cross-Validation. The experimental results show that the TF-IDF-based Logistic Regression model is capable of classifying positive and negative reviews well, yielding an accuracy of approximately 86,68%, precision of 92,45%, recall of 91,71%, and an F1-score of 92,08%. This study is expected to help the public determine recommendations for the best coffee shops in Kudus based on objective customer opinions, as well as serve as a reference for business owners to improve service quality and customer satisfaction.
ANALISIS KOMPARATIF SISTEM ERP UNTUK USAHA KECIL MENENGAH (UKM) RETAIL MENGGUNAKAN METODE TOPSIS Abdul Azis Al Baehaqi; Supriyono; Soni Adiyono
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 11 No 2 (2026): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v11i2.8023

Abstract

Retail SMEs in Indonesia face significant challenges in selecting the right Enterprise Resource Planning (ERP) system due to budget constraints, limited human resources, and lack of systematic evaluation guidance. This research develops a desktop-based decision support system using Python 3.12 with the Flet framework, implementing the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method to assist retail SMEs in interactively selecting optimal ERP. The research analyzes seven ERP alternatives (SAP Business One, Oracle NetSuite, PeopleSoft, webERP, Compiere, Odoo, and Accurate Online) using eight main criteria with 26 sub-criteria covering Cost, Functionality and Integration, Time and Availability, Usage and Support, Data Management, Reputation and Strategy Vendor, System Quality, and Scalability. Criteria weights are established referring to systematic literature review with System Quality (0.254) and Data Management (0.248) as highest priorities. Each alternative was assessed based on a review of official vendor documentation, verified review platforms, and relevant academic literature. Analysis results show Odoo ranks first (Ci* = 0.7668), followed by Accurate Online (Ci* = 0.6985), indicating the superiority of open-source and local solutions in cost, system quality, and flexibility for Indonesian retail SME context. The developed decision support system provides practical contribution for retail SMEs in strategic ERP selection decision-making while offering an adaptive evaluation framework for various industry contexts.
KOMPARASI KINERJA MACHINE LEARNING TEROPTIMASI SMOTE DAN PSO PADA KLASIFIKASI SENTIMEN ULASAN ROBLOX Amanda Diyas Setiyoadi; Yudie Irawan; Soni Adiyono
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 11 No 2 (2026): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v11i2.8034

Abstract

The emergence of digital platforms like Roblox has led to an increase in the number of user reviews on the Google Play Store. These reviews contain important information regarding public perception, satisfaction levels, and user complaints about the app. However, the large volume of reviews and the unstructured nature of the text make manual analysis inefficient. Therefore, an automated solution in the form of machine learning-based sentiment classification is needed. This study was conducted to evaluate and compare the effectiveness of three machine learning algorithms, namely Logistic Regression, Support Vector Machine (SVM), and Random Forest, in classifying Roblox app review sentiment into three categories: positive, neutral, and negative. The research data consisted of 10,000 reviews collected through a crawling process from the Google Play Store. Synthetic Minority Oversampling Technique (SMOTE) was applied to address class imbalance, while Particle Swarm Optimization (PSO) was used to optimize model parameters. Experimental results show that Random Forest combined with SMOTE achieved the highest performance with an accuracy of 0.7219, a precision of 0.7241, a recall of 0.7219, an F1-score of 0.7228, and an AUC of 0.778. However, the accuracy of 72.19% is still a limitation for direct practical application, so further improvements are needed. This study also developed a Streamlit-based dashboard to monitor sentiment classification results in real-time. Based on these findings, the combination of Random Forest and SMOTE can be considered quite effective, although it still has limitations in the level of model accuracy.
IMPLEMENTASI HYBRID AHP-TOPSIS PADA SISTEM PENDUKUNG KEPUTUSAN EVALUASI PERFORMA PRAMUDI Pratiwi Cahyaningtiyas; Rhoedy Setiawan; Soni Adiyono
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 11 No 2 (2026): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v11i2.8210

Abstract

Subjective bias, delayed data accumulation, and unfair bonus allocation are common issues resulting from the manual pramudi appraisal method at PT Samudra Jaya Transport. To resolve these challenges, this research develops a web-based Decision Support System (DSS) integrating the Analytical Hierarchy Process (AHP) and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). The AHP method is employed to establish priority weights for five core criteria: cargo, attendance, discipline, fuel consumption, and fleet maintenance. Concurrently, TOPSIS is implemented to rank 107 pramudi partitioned into three distinct categories: New Pramudi, Senior Pramudi, and Experienced Pramudi. The AHP evaluation yields a reliable Consistency Ratio (CR) of 0.0259. Furthermore, the TOPSIS analysis identifies the leading preference scores for each cluster, specifically PB-01 at 0.7909, PS-01 at 0.8691, and PSE-01 at 0.9308. Black-Box testing confirms that all core system features function correctly. Ultimately, this system ensures a data-centric evaluation process, eliminates bias, and delivers highly transparent monthly bonus recommendations.
Co-Authors - Supriyono Abdul Azis Al Baehaqi Amanda Diyas Setiyoadi Anita Rahmawati Arya Putra Badruzzaman Bagus Joko Winarso Damar Aji Gurowo Diana Laily Fithri Diyas Aditya Adi Saputra Eko Darmanto Heru Noviyanto Firmansyah Ira Iriyanty Lu'lu'il Laili Muhammad Arifin Noor Latifah Pratiwi Cahyaningtiyas R Rhoedy Setiawan Rizky Adisaputra Salum Ainayya Alfatikhah Sholichatunnita Nita Supriyono Syafrie Muhammad Hawari Triana Rahajeng Hadiprawoto Yeshika Alversia Yudie Irawan Zainur Romadhon