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All Journal JURNAL SISTEM INFORMASI BISNIS Techno.Com: Jurnal Teknologi Informasi Jurnal Simetris Jurnal Sains dan Teknologi Prosiding SNATIF E-Dimas: Jurnal Pengabdian kepada Masyarakat Sistemasi: Jurnal Sistem Informasi RABIT: Jurnal Teknologi dan Sistem Informasi Univrab JOURNAL OF APPLIED INFORMATICS AND COMPUTING JURNAL ILMIAH INFORMATIKA SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan Jurnal DISPROTEK Jurnal Nasional Komputasi dan Teknologi Informasi EDUMATIC: Jurnal Pendidikan Informatika Jurnal SITECH : Sistem Informasi dan Teknologi Jurnal Teknologi Informasi dan Pendidikan bit-Tech JATI (Jurnal Mahasiswa Teknik Informatika) Jatilima : Jurnal Multimedia Dan Teknologi Informasi Jurnal Sistem Komputer dan Informatika (JSON) Community Development Journal: Jurnal Pengabdian Masyarakat Idealis : Indonesia Journal Information System Jurnal Pengabdian kepada Masyarakat Nusantara Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Journal of Information Technology Ampera Indonesian Journal of Technology, Informatics and Science (IJTIS) Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) Jurnal Altifani Penelitian dan Pengabdian kepada Masyarakat International Journal of Management Science and Information Technology (IJMSIT) Muria Jurnal Layanan Masyarakat Jurnal Sistem Informasi Triguna Dharma (JURSI TGD) Jurnal Algoritma Jurnal Pengabdian Masyarakat Bhinneka Malcom: Indonesian Journal of Machine Learning and Computer Science Al-DYAS : Jurnal Inovasi dan Pengabdian kepada Masyarakat Jurnal Masyarakat Madani Indonesia Jurnal Pengabdian Teknik dan Sains (JPTS) semanTIK INOVTEK Polbeng - Seri Informatika Jurnal Pengabdian Masyarakat Indonesia
Yudie Irawan
Universitas Muria Kudus
Religion Aerospace Engineering 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 Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Public Health Social Sciences Transportation Other

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Customer Review Sentiment Classification of Belikopi Products Using the Support Vector Machine (SVM) Method Avin Nuzula Fitranti; R. Rhoedy Setiawan; 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.v6i2.8067

Abstract

The rapid development of information technology and the widespread use of social media have significantly changed the way customers express their opinions and experiences regarding products and services. Platforms such as Instagram, TikTok, and Google Maps have become important sources of customer feedback that can be analyzed to understand public perception and customer satisfaction. Sentiment analysis is one of the text mining techniques that can automatically classify opinions into positive, neutral, and negative sentiments, enabling businesses to make informed decisions based on customer feedback. This study aims to analyze customer sentiment toward Belikopi products using the Support Vector Machine (SVM) classification algorithm. A total of 4,636 customer reviews and comments were collected from Instagram, TikTok, and Google Maps and manually labeled into three sentiment categories: positive, neutral, and negative. Before the classification process, the dataset underwent several preprocessing stages, including case folding, cleaning, tokenizing, stopword removal, and stemming to improve the quality of textual data. Furthermore, the Term Frequency–Inverse Document Frequency (TF-IDF) method was employed to convert text into numerical feature vectors suitable for machine learning classification. The dataset was divided into 80% training data and 20% testing data using a stratified sampling approach to maintain the distribution of sentiment classes. The experimental results showed that the SVM model achieved an accuracy of 93.34%, demonstrating its capability to classify customer sentiment with high performance. The findings indicate that the proposed approach is effective in identifying customer perceptions of Belikopi products and can provide valuable insights for evaluating customer satisfaction, improving product quality, and supporting strategic business decision-making.
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.
Sistem Informasi Manajemen Terintegrasi: Pengelolaan Order, Arus Kas, dan Otomatisasi Penggajian pada UMKM Konveksi Slamet Rahayu; R. Rhoedy Setyawan; Yudie Irawan
IDEALIS : InDonEsiA journaL Information System Vol. 9 No. 2 (2026): Jurnal IDEALIS Juli 2026
Publisher : Universitas Budi Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36080/idealis.v9i2.3844

Abstract

Order tracking, cash flow monitoring, and payroll calculation are still handled manually at many garment Micro, Small, and Medium Enterprises (MSMEs), a practice that leaves considerable room for human error, lost records, and slower administrative processes. This study designs and builds an integrated, web-based management information system tailored for Dims.Collection, examined through a single case study. Development followed the Waterfall model, covering requirements gathering, system design with Unified Modeling Language (UML), coding, verification, and maintenance planning. User permissions for five roles - Administrator, Owner, Sales Staff, Finance Staff, and Human Resources Staff - are managed by a Role-Based Access Control (RBAC) framework to maintain secure system authorization. Ten functional test scenarios were run using Black Box Testing, spanning login authentication, order handling, cash recording, attendance tracking, and automated payroll computation, with every scenario passing (100% success rate). Beyond a working application, this research contributes an RBAC-based business process model that abstracts how order, cash, and payroll functions can be tied together within one centralized-access architecture. Rather than a solution built for one case only, the model is intended to transfer to other MSMEs sharing comparable roles and workflows, functioning as a reusable reference for building access-controlled information systems in the garment sector.
Prediksi Nilai Akhir Sekolah Menggunakan Algoritma Random Forest: Prediction of Final School Grades Using the Random Forest Algorithm Putri, Najwa Hanindya; Nugraha, Fajar; Irawan, Yudie
MALCOM: Indonesian Journal of Machine Learning and Computer Science Vol. 6 No. 4 (2026): MALCOM October 2026
Publisher : Institut Riset dan Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57152/malcom.v6i4.3043

Abstract

Nilai akhir sekolah merupakan indikator penting untuk menilai capaian akademik siswa dan mendukung pengambilan keputusan berbasis data. Penelitian ini menerapkan Random Forest Regression untuk mengestimasi nilai akhir akademik siswa menggunakan data akademik historis SMKN 1 Kudus. Alur penelitian mengikuti Cross-Industry Standard Process for Data Mining (CRISP-DM), yang meliputi pemahaman kebutuhan, pemahaman data, persiapan data, pemodelan, evaluasi, dan penggunaan konseptual hasil untuk pemantauan akademik dini. Dataset berisi 1.530 data siswa dari enam program keahlian dan dibagi menjadi 80% data latih serta 20% data uji. Model menggunakan n_estimators=100, max_depth=10, dan random_state=42, dengan Rata_Rata_Rapor sebagai proksi capaian akhir akademik. Evaluasi pada 306 data uji menghasilkan Mean Absolute Error (MAE) sebesar 0,4556 dan Root Mean Squared Error (RMSE) sebesar 0,5801. Nilai RMSE yang hanya sedikit lebih tinggi daripada MAE menunjukkan bahwa galat yang relatif besar terbatas; titik aktual-prediksi mendekati garis diagonal dan residual berpusat di sekitar nol. BK, PPKn, Matematika, B. Indonesia, dan PKK memiliki skor kepentingan fitur relatif tertinggi. Kebaruan penelitian terletak pada prediksi skor akademik kontinu, bukan hanya kelas lulus atau tidak lulus, serta penggabungan evaluasi berbasis galat dengan analisis kepentingan fitur untuk mendukung pemantauan dini yang dapat diinterpretasikan. 
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.
Pelatihan Sistem Monitoring Performa Customer Sales Berbasis Web pada PT Internusa Master Niaga Pati Nalendra Cahaya Heraditya; Yudie Irawan
JURNAL PENGABDIAN MASYARAKAT INDONESIA Vol. 5 No. 2 (2026): Juni: Jurnal Pengabdian Masyarakat Indonesia (JPMI)
Publisher : Politeknik Pratama Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jpmi.v5i2.7230

Abstract

PT Internusa Master Niaga Pati is an online trading company whose operational activities involve Customer Sales Online (CSO), Admin, and Warehouse divisions in managing customer orders. However, the order management process is still carried out manually, causing several problems such as data recording errors, duplicate orders, delays in order processing, and difficulties in monitoring sales performance in real time. This community service activity aimed to provide training on a web-based customer sales performance monitoring system to improve operational efficiency and support sales monitoring activities within the company. The implementation methods included observation, interviews, system development, training, and user assistance. The system was developed using PHP and MySQL and provides features such as order management, data validation, duplicate detection, shipping management, and a real-time monitoring dashboard. The training activities were conducted for the Owner, Admin, and PIC Customer Sales Online to improve their understanding and ability to operate the system according to their respective responsibilities. The results of this activity indicate that the implementation and training process helped users manage order data more effectively, monitor sales performance more efficiently, and improve the utilization of web-based information systems in supporting company operations
Co-Authors Aditya, Ahsanu 'Amala Amanda Diyas Setiyoadi Amelia Rahmawati Andy Prasetyo Utomo Anteng Widodo Arba Rinata Ardiansyah Ardiansyah Arif Setiawan Arifviando, Muhammad Villa Arina Fawaida Aris Sugiharto Arya Putra Badruzzaman aufa hanif Avin Nuzula Fitranti Bagus Deva Pratama, Mohammad Chalim, Noor Diana Laily Fithri Diana Nur Yasmin Dwi Puspitasari Dwi Puspitasari Eko Darmanto Elsa Violina Damayanti Endang Supriyati Endang Supriyati Endhito Hafiz Meifaza Fadila Ullul Azmie Fajar Nugraha Farhan, Faris Ahmad Fitri Budi Suryani Hakim, Adam Fathul Hikhmah, Fitria Nurul Ida Siti Marfuah Iftikhar Rizqullah Imam Munzagi Ina Kusumawardani Alina Fakhri Indana Fauzul Ula Indriyani, Sofiatul Irsad Nizarudin Itsnain Nur Aderochman Janah, Susi Nor Jhany Feronica Ardina Kalya Agil Prasetya Khilal Arlisna Rahmadani Kurniawan, Aldhi Ari Kurniawan, Rizky Dwi Laili Fitriyani Lukito, Aji Marchela Tri Amanda Mimbar Maulana, Bintang Sultan Mochammad Imron Awalludin Mohammad Rosul Mubarrizi, Nor Muhammad Muhamad Dimas Firmansyah Muhamad Sholikhudin Muhammad Arifin Muhammad Kholid Ridwan Muhammad Rizqi Pradana Mustafid Mustafid Nalendra Cahaya Heraditya Nesicha, Yutia Nia Noor Latifah Nurya Herlina Sari Pratomo Setiaji Priyambodo, Ragil Putri Kurnia Handayani Putri Kurnia Handayani Putri, Najwa Hanindya R Rhoedy Setiawan R. Rhoedy Setyawan Raden Rhoedy Setiawan Rahmatika, Alifia Ayu Rahmawati, Yulinda Robait Tajuddin Romadhon, Zainur Savitri Wanabuliandari Setiawan, Raden Rhoedy Silvia Himmatul Aliyyah Slamet Rahayu Soni Adiyono Syafiul Muzid Syahrul Bagus Andreyan Taufiq, Muhammad Bagas Tsirwatun Nisail Khasanah Vika Aulia Munawaroh Widhiarta, Faris Widiyatmoko, Fahmi Agung Wiwit Agus Triyanto Zulfa Himmatul Ulya Zuyyina Syarifa Yahya