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All Journal Jurnal Simetris Jurnal Sains dan Teknologi Prosiding SNATIF Jurnal Edukasi dan Penelitian Informatika (JEPIN) Jurnal SIMADA (Sistem Informasi dan Manajemen Basis Data) IKRA-ITH Informatika : Jurnal Komputer dan Informatika Jurnal SITECH : Sistem Informasi dan Teknologi Building of Informatics, Technology and Science Journal of Information Systems and Informatics Abdimas Toddopuli: Jurnal Pengabdian Pada Masyarakat Idealis : Indonesia Journal Information System Journal of Software Engineering Ampera Bima Abdi: Jurnal Pengabdian Masyarakat Jurnal Pengabdian Masyarakat Nusantara Jurnal Pengabdian Masyarakat (ABDIRA) Indonesian Journal of Networking and Security - IJNS Jurnal Altifani Penelitian dan Pengabdian kepada Masyarakat Abdiformatika: Jurnal Pengabdian Masyarakat Informatika International Journal of Management Science and Information Technology (IJMSIT) Jurnal Minfo Polgan (JMP) Bhakti Nagori (Jurnal Pengabdian kepada Masyarakat) Journal of Multimedia Trend and Technology Sabangka Abdimas Jurnal Pengabdian Masyarakat Sabangka Prosiding Seminar Nasional Unimus INOVTEK Polbeng - Seri Informatika
Anteng Widodo
Universitas Muria Kudus
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics Nursing Public Health Social Sciences Other

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Implementasi Sistem Informasi Pelaporan Kerusakan dan Perawatan Inventaris Teknologi Informasi dan Komunikasi di Dinas Kependudukan dan Pencatatan Sipil Kabupaten Pati Chandra Ayu Fatikasari; Anteng Widodo
Bima Abdi: Jurnal Pengabdian Masyarakat Vol. 6 No. 2 (2026): Bima Abdi: Jurnal Pengabdian Masyarakat
Publisher : Yayasan Pendidikan Bima Berilmu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53299/ba-jpm.v6i2.4192

Abstract

Dinas Kependudukan dan Pencatatan Sipil Kabupaten Pati mengelola inventaris Teknologi Informasi dan Komunikasi (TIK) yang tersebar di 21 kecamatan. Proses pelaporan kerusakan inventaris TIK selama ini masih dilakukan secara manual melalui WhatsApp dan komunikasi lisan kepada Bidang Pengelolaan Informasi Administrasi Kependudukan (PIAK), sehingga laporan tidak terdokumentasi dengan baik, status perbaikan sulit dipantau, riwayat perawatan tidak tercatat, dan rekapitulasi data terhambat. Kegiatan pengabdian masyarakat ini bertujuan untuk menerapkan Sistem Informasi Pelaporan Kerusakan dan Perawatan Inventaris TIK Berbasis Web di Disdukcapil Kabupaten Pati sekaligus memberikan pendampingan kepada pengguna sistem. Metode pelaksanaan menggunakan pendekatan kualitatif dengan tahapan System Development Life Cycle (SDLC) yang meliputi analisis kebutuhan, perancangan sistem, implementasi, serta evaluasi dan perbaikan sistem. Sistem dikembangkan menggunakan Framework Laravel dan basis data MySQL dengan alur kerja berjenjang dari pelaporan oleh operator kecamatan, persetujuan oleh Kepala Bidang PIAK, hingga pembaruan status oleh Admin PIAK. Hasil kegiatan menunjukkan bahwa sistem yang diimplementasikan telah berhasil menggantikan proses manual dengan mekanisme digital yang terstruktur dan dapat dipantau secara real-time. Seluruh pengguna dari ketiga kelompok telah mampu mengoperasikan sistem secara mandiri setelah pendampingan. Kegiatan ini terbukti meningkatkan efisiensi, transparansi, dan akuntabilitas pengelolaan inventaris TIK di Disdukcapil Kabupaten Pati. Pengembangan selanjutnya dapat diarahkan pada penambahan fitur notifikasi otomatis serta integrasi dengan sistem pengelolaan aset daerah yang lebih luas guna memperluas manfaat sistem bagi instansi pemerintah lainnya.
Pendampingan Sistem Pengelolaan Surat Berbasis Web sebagai Solusi Digitalisasi Administrasi Inspektorat Kudus Indra Wahyu Mahendra; Anteng Widodo
Jurnal Pengabdian Masyarakat (ABDIRA) Vol 6, No 2 (2026): Abdira, April
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/abdira.v6i2.1623

Abstract

Correspondence administration is a vital component of the operational activities at the Regional Inspectorate of Kudus, which manages a high volume of incoming and outgoing letters. However, archival management is still conducted manually using logbooks and physical storage, leading to data disorganization, risk of document loss, and delays in information retrieval. This community service activity aims to provide assistance in implementing a web-based correspondence management system as a solution for administrative digitalization. The implementation method includes problem analysis, system development using the Waterfall model with PHP Native and MySQL, user training, and implementation assistance. The developed system features incoming and outgoing mail management, digital disposition, and automated report generation. The results indicate that the system improves administrative efficiency, data security, and accessibility of information, thereby supporting a more structured, paperless, and effective archival management process.
A Multicriteria Decision Support System for Used Smartphone Price Determination Using CRITIC–MARCOS Laili Fitriyani; Anteng Widodo; Yudie Irawan
International Journal of Management Science and Information Technology Vol. 6 No. 2 (2026): July - December 2026
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA), Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijmsit.v6i2.7929

Abstract

Used smartphone price determination at FS Phone Store Jepara has relied mainly on the seller’s subjective judgment, resulting in inconsistent valuation across units with comparable specifications and condition. This study developed a multicriteria decision support model that integrates the Criteria Importance Through Intercriteria Correlation (CRITIC) method for objective criteria weighting with the Measurement of Alternatives and Ranking according to Compromise Solution (MARCOS) method for alternative ranking, applied to 100 used smartphone alternatives evaluated on nine criteria: physical condition, RAM, ROM, chipset, camera, battery health, usage age, warranty, and completeness. To align the technical assessment with real market conditions, a market-price correction (85% MARCOS utility score plus 15% normalized market-price score) was applied to the final ranking. The proposed ranking was compared with Weighted Product (WP), MOORA, and Simple Additive Weighting (SAW) using Spearman rank correlation, and the accuracy of the resulting price recommendation was evaluated against an Independent Market Reference Price using Mean Absolute Error (MAE) and Mean Absolute Percentage Error (MAPE). The results show that Usage Age obtained the highest CRITIC weight (21.12%) and Camera the lowest (8.22%). The final price-corrected ranking achieved a strong to very strong correlation with SAW (rₛ = 0.9291), WP (rₛ = 0.8015), and MOORA (rₛ = 0.8256), and produced price recommendations with an MAE of IDR 90,600 and a MAPE of 4.63%, classified as highly accurate. The proposed model was implemented as a web-based decision support system, validated through black-box testing, user acceptance testing, and manual calculation verification, providing FS Phone Store Jepara with an objective, consistent, and market-aware tool for used smartphone price determination.
A Web-Based Gold Price Prediction Model Using Geopolitical Sentiment from Social Media and Gated Recurrent Unit (GRU) Narendra Saputra; Anteng Widodo; Zainur Romadhon
International Journal of Management Science and Information Technology Vol. 6 No. 2 (2026): July - December 2026
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA), Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijmsit.v6i2.8297

Abstract

Gold is widely recognized as a safe-haven asset whose price is sensitive to economic and geopolitical uncertainty. This study develops a web-based international gold price prediction system using the Gated Recurrent Unit (GRU) algorithm and evaluates the contribution of geopolitical sentiment from the X social media platform. The study uses historical XAUUSD data and English-language posts related to the Iran–United States–Israel conflict. Text data were processed through cleaning, case folding, tokenization, stopword removal, lemmatization, TF-IDF transformation, and sentiment analysis using VADER. The resulting daily sentiment scores were integrated with historical gold price features and used as an additional input to the GRU model. Two experimental scenarios were evaluated: GRU without sentiment and GRU with sentiment. The results show that the GRU model without sentiment achieved an MAE of 55.07, RMSE of 69.81, MAPE of 1.17%, and R² of 0.9629, while the model with sentiment achieved an MAE of 80.87, RMSE of 92.93, MAPE of 1.72%, and R² of 0.9342. These findings indicate that incorporating daily aggregated social media sentiment did not improve prediction performance for the dataset used. The developed Flask-based web application provides prediction, sentiment analysis, visualization, and model evaluation features, demonstrating the practical implementation of the proposed approach.
Analysis of Transaction Patterns in Automotive Workshop and Accessories Store Using the FP-Growth Algorithm Putri, Widiya Amelia; Widodo, Anteng; Noor Latifah
JEPIN (Jurnal Edukasi dan Penelitian Informatika) Vol. 12 No. 2 (2026): Volume 12 No 2
Publisher : Program Studi Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Transaction data at automotive workshops and accessory stores holds valuable information about customer purchasing habits, yet is typically used only as an administrative archive without further analysis to support business strategy. This is the case for Impala Variasi, an automotive workshop in Welahan, Jepara, which recorded 1,388 transactions from January 2025 to May 2026 but lacks a mechanism for identifying products customers tend to choose together, leaving service packages based on the owner's intuition. This study applies the FP-Growth algorithm to discover association patterns among components attached to each service, following the CRISP-DM framework and evaluating results using support, confidence, and lift ratio, with a minimum-support threshold of 5% (70 of 1,388 transactions). Results, cross-verified against raw data, show 13 frequent items, 7 frequent 2-itemsets, and 1 frequent 3-itemset (21 itemsets total), yielding 14 association rules. Speaker → Head Unit produced the highest confidence among the genuinely bidirectional rules (81.12%, support 8.36%, lift 7.51), followed by Head Unit → Speaker (77.33%) and Car Shampoo → Wax Polish (75.31%, lift 8.57). Three pairs — Oil Filter/Engine Oil, Spark Plug/Engine Oil, and Tire Valve/4-Tire Nitrogen — showed one-directional 100% confidence, meaning every customer who bought the smaller add-on also bought the base item, while the reverse direction (e.g., Engine Oil → Oil Filter, 53.42%) reveals meaningful upsell headroom. These patterns indicate consistent attach behavior between core services and add-ons, plus a strong bidirectional link between car-audio components. Results can guide service bundles, cross-selling, sparepart stock, and data-driven recommendations for Impala Variasi's management.
Comparison of Hyperparameter Optimization Methods for LSTM-Based XAU/USD Forecasting and Web-Based System Implementation Irsad Nizarudin; Yudie Irawan; Anteng Widodo
INOVTEK Polbeng - Seri Informatika Vol. 11 No. 3 (2026): August
Publisher : P3M Politeknik Negeri Bengkalis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35314/1vywa204

Abstract

Unequal search budgets and single-seed experiments can confound comparisons of hyperparameter optimisation methods in financial forecasting. This study compares grid search, random search, and Bayesian optimisation for tuning a long short-term memory model to forecast the XAU/USD closing price for the next trading day. The dataset comprised 1,705 daily observations from January 2020 to July 2026 using open, high, low, close, and release-date-aligned United States inflation. Each method evaluated the same 32 configurations using three random seeds, resulting in 96 candidate-model evaluations per method. Performance was assessed on 37 independent testing dates and descriptively examined using a five-fold post-selection walk-forward diagnostic without repeating hyperparameter optimisation within each fold. All methods selected the same configuration and produced a mean testing MAPE of 2.785052% and an ensemble MAPE of 2.696161%. Grid Search reached the final-best configuration earlier, but naïve persistence achieved the lowest MAPE of 1.358325%. Thus, optimisation improved the LSTM relative to the predefined baseline but did not outperform persistence. The procedures were also implemented in a Streamlit application. The findings are limited to the examined dataset, search space, seeds, testing period, and computational environment.
Analisis Kinerja Pelayanan Rawat Inap Antar-Bangsal dengan Kombinasi Algoritma AHP dan SAW Farel Dani Arfiyan; R. Rhoedy Setiawan; Anteng Widodo
Jurnal Minfo Polgan Vol. 15 No. 3 (2026): Artikel Penelitian
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/jmp.v15i3.16596

Abstract

Evaluation of hospital service quality is a crucial instrument for continuously improving the quality of public healthcare services. Although patient satisfaction surveys have been conducted periodically, the collected assessment data have generally not been optimally utilized as the basis for evaluating the performance of inpatient wards. This study aims to implement a Decision Support System (DSS) to analyze the performance of inpatient wards objectively, measurably, and comparatively. A hybrid approach was employed by integrating the Analytic Hierarchy Process (AHP) algorithm to determine the weights of six service quality criteria, namely administrative services, medical competence and responsiveness, staff friendliness, inpatient room facilities, environmental cleanliness and comfort, and information and communication, with the Simple Additive Weighting (SAW) method to calculate the ranking of alternatives. To ensure a fair evaluation, the analysis was divided into two categories, namely VIP/VVIP wards and regular wards. The results indicate that Fresia 5 achieved the highest preference value in the regular ward category with a score of 0.9155, while Edelweiss 4 (VVIP) obtained the highest preference value in the VIP/VVIP category with a score of 1.0000. The system also successfully identified six wards while demonstrating stable ranking results through sensitivity analysis of changes in criteria weights. The computational results were integrated into a web-based dashboard to visualize ward rankings interactively. The combination of the AHP and SAW algorithms proved effective in processing multicriteria assessments and reducing subjective bias. The findings facilitate hospital management in mapping unit performance more efficiently to support service quality improvement. In conclusion, the integration of both algorithms produces valid and consistent decision recommendations that can be used to determine priorities for improving hospital service quality.
Integrating IndoBERT-Based Sentiment Analysis and PSI-TOPSIS Into a Decision Support System for Convection Production Prioritization Vitra Surya Ningrum; Anteng Widodo; Noor Latifah
Journal of Information System and Informatics Vol 8 No 4 (2026): August
Publisher : Asosiasi Doktor Sistem Informasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63158/journalisi.v8i4.1809

Abstract

Determining production priorities in the convection industry remains challenging due to the diversity of product alternatives and the complexity of operational and customer-related factors. This study develops a Decision Support System (DSS) by integrating IndoBERT-based customer sentiment analysis with Multi-Criteria Decision Making (MCDM) approaches to identify optimal production priorities at Kenisya Gallery. A total of 371 Shopee customer reviews were analyzed using IndoBERT to extract customer sentiment information, which was then integrated with eight operational criteria. The Preference Selection Index (PSI) method was applied to determine the importance weights of each criterion, while the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method was used to rank 28 product alternatives. The results indicate that 84.4% of customer reviews expressed positive sentiment. Among the evaluation criteria, raw material availability (C8) achieved the highest PSI weight of 25.06%. The PSI-TOPSIS approach identified the Azella Black Series as the highest-priority product for production, achieving a closeness coefficient (Ci) value of 0.8730. This research demonstrates the effectiveness of combining customer sentiment analysis and MCDM techniques to support data-driven production planning. Nevertheless, this study is limited to a single case study and does not yet incorporate expert validation or evaluation of actual production performance.
Comparative Forecasting and Inventory Analytics for Web-Basedd Fabric Stock Control: A Case Study at BKR Textile Kudus Diana Nur Yasmin; Yudie Irawan; Anteng Widodo
International Journal of Management Science and Information Technology Vol. 6 No. 2 (2026): July - December 2026
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA), Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijmsit.v6i2.8403

Abstract

This study develops a web-based Smart Inventory system that integrates inventory recording, demand forecasting, inventory analytics, and replenishment recommendations for fabric stock control at BKR Textile Kudus. A Research and Development approach using the Prototype model was combined with quantitative comparative forecasting. The dataset comprised 400 fabric items and 12 months of stock-out history. Four one-month-ahead methods were tested: three-month Moving Average (MA), Weighted Moving Average (WMA) with 1:2:3 weights, Single Exponential Smoothing (SES) with alpha = 0.30, and rolling three-point Linear Regression (LR)-were evaluated through rolling-origin backtesting using MAD, MSE, and MAPE. Across 14,400 forecast-actual comparisons, MA produced the lowest average errors, with MAD of 5.167 rolls, MSE of 36.881, and MAPE of 5.166%. Inventory analysis identified three Critical items, 78 Low-stock items, 157 Normal items, and 162 Overstock items. The principal contribution is the integration of item-level comparative forecasting, safety stock, reorder points, inventory-status classification, and automated restock recommendations within one operational web platform. The system translates forecasting results into transparent decision information for a local textile company, although the findings remain specific to the one-year dataset and organizational setting examined.
Decision Support System for Determining Signature Menus Using the Integration of BMW, MOORA, and Copeland Scores Meta Ardi Setiawan; Anteng Widodo; Noor Latifah
Building of Informatics, Technology and Science (BITS) Vol 8 No 2 (2026): September 2026
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v8i2.10936

Abstract

Menu optimisation is a crucial yet challenging challenge for business sustainability because the speciality coffee sector is marked by dynamic consumer tastes and a high degree of product diversity. This study tackles a basic operational issue at Inti Coffee, where a subjective, intuition-based method is currently used to identify "signature offerings"the important menu items that ought to be given priority for promotion, inventory, and resource allocation. This current process, which mainly depends on the owner, operational manager, and lead barista's intuition, is intrinsically vulnerable to individual cognitive biases, personal taste preferences, and inconsistent evaluation, which frequently results in less than ideal menu performance and lost revenue opportunities. The main goal of this research is to develop and deploy an online Decision Support System (DSS) that offers a transparent, data-driven, and organised framework for objectively ranking menu items in order to get around these restrictions. A hybrid multi-criteria decision-making (MCDM) technique is included into the suggested system to guarantee group unanimity and robustness. In order to minimise pairwise comparison inconsistencies and capture the knowledge of the three primary decision-makers, the Best-Worst Method (BWM) is first used to systematically extract the relative relevance weights of six different evaluation criteria. Second, a thorough dataset of 500 real sales transactions is used to assess and rank 51 menu alternatives using the MOORA (Multi-Objective Optimisation on the basis of Ratio Analysis) method. Both financial parameters (total items sold, HPP or cost of goods sold, and profit margin) and operational characteristics (uniqueness of taste score, preparation time, and ingredient lifetime) are included in the evaluation criteria. In order to successfully resolve any potential conflicts between decision-makers, the Copeland Score is finally used to combine the individual preference rankings into a single, collective group score. This study makes three main contributions: first, it develops a novel integrated DSS framework that integrates BWM, MOORA, and Copeland Score into a single unified workflow specifically designed for signature menu selection; second, it involves three different stakeholders (owner, operational manager, and head barista) in the group decision-making process, ensuring that the final recommendation reflects a balanced consensus rather than individual bias; and third, it creates a fully functional web-based system with statistical validation tools that empirically verify the accuracy and dependability of the recommendations using Spearman correlation, RMSE, and overlap ratio against actual customer preferences. The creation of a useful, web-based DSS that turns menu curating from an art to a science and offers a reproducible model for other food and beverage businesses is the main contribution of this research. With a MOORA score of 0.249180 and a Copeland Score of 50, the interim results show that the system is able to identify "Kopi Susu Aren" as the best-performing signature item. A poll involving 130 participants was carried out to verify the system's output against human judgement in the actual world. In addition to a low Root Mean Square Error (RMSE) of 5.5734 and an overlap ratio of 66.7%, the results show a strong positive correlation (Spearman's rho = 0.9238) between the system's ranks and participant feedback, proving the system's high accuracy and practical applicability. In order to provide scalability and usability for continuous operational choices, the DSS is implemented using a combination of PHP Native, Python, MySQL, and a testing dashboard based on Streamlit.
Co-Authors Ahmad Abdul Chamid Ahmad Jazuli Ahmad Jazuli Ahmad Zidan Nur Rizqi Andi Agus Setyawan Arif Susanto Budiono, Ragil Chandra Ayu Fatikasari Diana Laily Fithri Diana Nur Yasmin Farel Dani Arfiyan Ferry Gunawan Wijaya Kusuma Fery Ariyana Hadi Supriyo Hesti Sabrila Aulia Indra Wahyu Mahendra Irfan Santiko Irsad Nizarudin Jayanti, Nur Ivo Kharisatun Nisa Kholifatunnisa Kholifatunnisa Laili Fitriyani Meta Ardi Setiawan Muhamad Habli Hukma Muhammad Arifin Muhammad Vikri Mustafa Muhammad Wifqi Aufal Maulana Mukhamad Nurkamid Narendra Saputra Neila Mei Ika Suryani Niken Ayu Ambarwati Nikmatul Khoiriyah Nizarudin, Muhamad Noor Latifah Noor Latifah Noor Latifah Nur Ivo Jayanti Pratomo Setiaji Putri Kurnia Handayani Putri Kusumawati Putri, Widiya Amelia R Rhoedy Setiawan Ragil Budiono Risal Khoirula Syihar Rizki Putra Wicaksono Rizkysari Mei Maharani Rizkysari Mei Maharani, Rizkysari Mei Romadhon, Zainur Romadhon, Zainur Selvi Marcellia Setyawan, Andi Agus Setyawan, Moh Dodi Shinta Ghufriyyah Soni Adiyono Supriyono Supriyono Syariful Ikhwan Tri Listyorini Vitra Surya Ningrum Yudie Irawan