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All Journal PROSIDING SEMINAR NASIONAL Speed - Sentra Penelitian Engineering dan Edukasi Jurnal Teknologi Informasi dan Ilmu Komputer INFORMATIKA JOIV : International Journal on Informatics Visualization RABIT: Jurnal Teknologi dan Sistem Informasi Univrab Bianglala Informatika : Jurnal Komputer dan Informatika Akademi Bina Sarana Informatika Yogyakarta Jurnal Ilmiah FIFO Jurnal Pilar Nusa Mandiri JITK (Jurnal Ilmu Pengetahuan dan Komputer) Techno Nusa Mandiri : Journal of Computing and Information Technology JOURNAL OF APPLIED INFORMATICS AND COMPUTING Journal of Information Systems and Informatics Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Jurnal Infortech Jurnal Pengabdian kepada Masyarakat Nusantara Abditeknika - Jurnal Pengabdian Kepada Masyarakat Wasana Nyata Jurnal Abdimas Ekonomi dan Bisnis Journal Basic Science and Technology Indonesian Journal of Networking and Security - IJNS SPEED - Sentra Penelitian Engineering dan Edukasi Jurnal Media Computer Science Paradigma Indonesian Journal Computer Science (ijcs) Dikdimas : Jurnal Pengabdian Kepada Masyarakat WASANA NYATA Pelayanan Unggulan: Jurnal Pengabdian Masyarakat Terapan Prawara Jurnal Pengabdian Masyarakat
Heribertus Ary Setyadi
Universitas Bina Sarana Informatika
Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mechanical Engineering Nursing Public Health Social Sciences Veterinary Other

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Innovating Information Management System for Cow's Milk Distributor Sutanto, Yusuf; Al Amin, Budi; Setyadi, Heribertus Ary
Journal of Information System and Informatics Vol 5 No 4 (2023): Journal of Information Systems and Informatics
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v5i4.615

Abstract

This study explores the recent advancements in cattle farming, focusing on the significant role of dairy farming in bolstering the economy, particularly in rural communities. It highlights how dairy farming enhances the economic value for farmers, with an emphasis on Banyuanyar Boyolali, where residents predominantly engage in this practice. The research underscores the profitability of selling cow's milk, noting the local milk prices, and aims to develop a web-based milk data management system. This system seeks to bring transparency and accessibility to milk production data, benefiting both farmers and collectors. Utilizing the Rapid Application Development (RAD) method, which involves minimal personnel, the study demonstrates how this web-based system streamlines data entry and access, facilitating better record-keeping and decision-making in dairy farming.
Implementation Economic Order Quantity and Reorder Point Methods in Inventory Management Information Systems Setyadi, Heribertus Ary; Al Amin, Budi; Widodo, Pudji
Journal of Information System and Informatics Vol 6 No 1 (2024): March
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v6i1.647

Abstract

Inventory control is at the core of supply management to balance inventory needs and demand. With an inventory system, management can control stock of materials and goods, production process and sales transactions can even stop the production process if necessary. Sari Gamping building materials store that sells various building needs including building materials and tools. Data management of goods, transactions and inventory processing still uses conventional methods using Microsoft Office. The purpose of this research is to analyze the ongoing inventory management process to create an inventory management information system so that it can help the Sari Gamping store in controlling inventory. The Economic Order Quantity (EOQ) and reorder point methods were chosen to optimize inventory to avoid shortages or excess inventories, to fulfill customer orders, to achieve cost efficiency and to prevent problems that may occur. The developed system can manage data on goods, categories, suppliers, manage purchase and sales transactions and can generate information from EOQ calculations, safety stock and reorder points. From the results of testing the calculations of the two methods used with 15 samples of catylac paint variants, the average inventory cost saving in June 2023 was 65.33%.
Improving Junk Sale and Purchase Transactions Using a Spiral Model-Based System Setyadi, Heribertus Ary; Supriyanta, Supriyanta; Nurohim, Galih Setiawan
Journal of Information System and Informatics Vol 6 No 4 (2024): December
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v6i4.871

Abstract

Traditionally, individuals looking to sell junk or recyclable materials often rely on waiting for roaming junk collectors, a process that is inefficient and lacks transparency. Furthermore, the fluctuating prices of junk goods frequently leave sellers uninformed, creating uncertainty in transactions. To address these issues, this research developed a smartphone-accessible system designed to facilitate junk goods transactions. The system was developed using the Spiral Model, ensuring iterative refinement and reliability. Key features of the system include real-time price updates for junk items, enabling customers to stay informed about the latest market values, and a Location-Based Service (LBS) feature that allows customers to share their location with collectors. This feature enhances the efficiency of junk collection by providing real-time location tracking, enabling collectors to locate and reach customers seamlessly. The implementation of this system aims to make junk buying and selling transactions more effective, transparent, and satisfying for customers. The results of this study demonstrate that the developed system significantly streamlines the transaction process, ensuring improved service delivery and customer satisfaction.
Knowledge-Based Intelligent System for Diagnosing Three-Wheeled Motorcycle Engine Faults Ary Setyadi, Heribertus; Supriyanta, Supriyanta; Nurohim, Galih Setiawan; Widodo, Pudji; Sutanto, Yusuf
JOIV : International Journal on Informatics Visualization Vol 8, No 4 (2024)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.8.4.2487

Abstract

Three-wheeled motor engine damage is one of the most serious problems with all motorcycles. When problems appear, it becomes difficult for users to repair and diagnose faults because knowledge about machine breakdown symptoms is minimal. Most motorcycle repair shops don’t have mechanics who understand tricycle motorbike engines, so they are less accurate in diagnosing damage symptoms, only based on estimates. Three-wheeled motorbikes have several differences in structure and spare parts compared to motorcycles because tricycle motorbikes have an axle like a car. For this problem, an information system is needed with a method that combines an expert's experience, expertise, and knowledge to develop expert system applications based on several cases that have been experienced and are known as case-based reasoning. This research aims to produce a web-based expert system to diagnose and solve tricycle motorbike engine damage problems. The case-based reasoning method with the K-Nearest Neighbor algorithm is used to assist in analyzing engine damage and give solutions to the issues in three-wheeled motorbike engines. Using two methods is appropriate because of the answers found and the similarities calculated by the cosine similarity method, which experts then review to get the proper solution. From testing using 20 samples of diagnostic data, an accuracy percentage of 85% was obtained. The calculation result for precision is 85%, and recall is 85%.
Effectiveness And Efficiency Of LLM Models Vs Traditional Machine Learning In Sentiment Analysis Of Indonesian Language Product Reviews Nurohim, Galih Setiawan; Amin, Budi Al; Setyadi, Heribertus Ary
Jurnal Media Computer Science Vol 4 No 2 (2025): Juli
Publisher : LPPJPHKI Universitas Dehasen Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37676/jmcs.v4i2.8681

Abstract

This research aims to conduct a comparative analysis of the performance and efficiency of several machine learning models in the task of sentiment analysis on Indonesian language customer reviews. In the digital business era, a quick and accurate understanding of customer opinions is a strategic asset for making decisions, from product development to marketing strategy. Four models were evaluated: two Transformer-based models (agufsamudra/indo-sentiment-analysis and ayameRushia/bert-base-indonesian-1.5G-sentiment-analysis-smsa), Naive Bayes, and K-Nearest Neighbors (KNN) on a dataset of 5,400 product reviews. The evaluation metrics used are Accuracy, Precision, Recall, and F1-Score. The results show that the Naive Bayes model and the Transformer model 'agufsamudra/indo-sentiment-analysis' achieve the highest performance with an F1-Score and accuracy of around 95%, significantly outperforming other Transformer models (90%) and KNN (47%). The crucial finding of this research is that the performance of the classical Naive Bayes model is equivalent to the state-of-the-art Transformer model. From an accounting and business perspective, this implies that solutions with much higher computational efficiency (Naive Bayes) can provide a more optimal Return on Investment (ROI) for large-scale implementation of customer sentiment monitoring systems.
Penentuan Kelayakan dan Jenis Lembaga Keuangan dalam Pemberian Modal UMKM Menggunakan Metode AHP dan Decision Tree Setyadi, Heribertus Ary; Nurohim, Galih Setiawan; Nugroho, Wawan
Jurnal Ilmiah FIFO Vol 16, No 1 (2024)
Publisher : Fakultas Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/fifo.2024.v16i1.007

Abstract

Terdapat beberapa kendala dibalik kehadiran UKM dalam pengelolaan usaha tersebut, antara lain kesulitan memperoleh pinjaman dari perbankan karena kurangnya pengetahuan pegawai yang ada, kurangnya perkembangan teknologi informasi, dan beberapa syarat yang tidak dapat terpenuhi. Tujuan penelitian ini untuk mengembangkan sistem pendukung keputusan yang dapat membantu dalam menentukan kelayakan UMKM dan lembaga keuangan yang sesuai untuk melakukan pinjaman. Terdapat 25 sampel UMKM yang berada di Kota Surakarta untuk dijadikan bahan penelitian. Algoritma decision tree dan metode Analytic Hierarchy Process (AHP) digunakan dalam penelitian ini. Tahap pertama untuk penentuan kelayakan suatu UMKM yang akan diberi pinjaman menggunakan algoritma decision tree. Penentuan rekomendasi jenis lembaga keuangan yang sesuai menerapkan metode AHP. Dari hasil pengujian diperoleh tingkat akurasi penerapan algoritma decision tree sebesar 80%. Pengujian tingkat akurasi penerapan metode AHP menghasilkan nilai 76,9%. Dari kedua pengujian tersebut, dapat dikatakan bahwa sistem yang dibuat sudah baik atau akurat.
Tips dan Trik Pemasaran Digital Bagi BUMDes Banaran Kulon Progo Untuk Meningkatkan Minat Beli Masyarakat Annida Purnamawati; Heribertus Ary Setyadi; Yulianto; Eka Rahmawati
PRAWARA Jurnal ABDIMAS Vol 3 No 4 (2024): PRAWARA JURNAL ABDIMAS
Publisher : CV. Manha Digital

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63297/abdimas.v3i4.124

Abstract

Hadirnya revolusi digital ditandai dengan terus berkembangnya media sosial, teknologi smartphone, serta kemudahan dalam akses internet telah merubah cara kerja bisnis dan konsumen secara dramatis. BUMDes berorientasi pada pemanfaatan ekonomi yang dapat memberikan manfaat sosial dan non-ekonomi untuk pembangunan desa. Manfaat ekonomi antara lain dapat meningkatkan pendapatan desa dengan semakin meluasnya lapangan kerja, dan aktivitas ekonomi pedesaan. Terdapat sentra kuliner lele asap yang sudah banyak dikenal dan digemari para wisatawan yang datang ke desa Banaran yang terletak dekat dengan pantai. Di desa Banaran juga banyak tumbuh industri kecil menengah yang mengolah berbagai jenis kuliner berbahan ikan, baik ikan yang dibudidayakan oleh masyarakat maupun ikan hasil tangkapan laut para nelayan. Konsumen saat ini berperan di garis terdepan dalam penyampaian secara digital yang tidak hanya mengkonsumsi data dan informasi namun juga menjadikan konten dalam pemasaran sebagai alat bantu yang penting. Diadakannya kegiatan pengabdian masyarakat untuk memberikan wawasan juga tips trik tentang pemasaran digital di era industri 5.0. dalam kegiatan ini juga mengajak peserta untuk memasarkan bisnisnya menggunakan fitur google maps. Hasil dari kegiatan ini adalah pemahaman dalam pemararan digital dan sudah dipublikasikannya bisnis di google maps.
Enhance Artificial Intelligence Literacy for Islamic Boarding School Students Using the Asset Based Community Development Method Setyadi, Heribertus Ary; Agustina, Candra; Haryanto, Wawan; Rousyati, Rousyati
WASANA NYATA Vol 9, No 1 (2025)
Publisher : STIE AUB Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36587/wasananyata.v9i1.1970

Abstract

Use of artificial intelligence (AI) in teaching and learning has become an increasingly important topic in modern education context. AI offers a wide range of potential to enhance students' learning experiences through better personalization and adaptation to individual needs. From initial observations in several Islamic boarding schools in Banjarsari Surakarta, it was found that understanding of students and teachers about AI and AI supporting applications was still lacking. As part of efforts to improve education quality and community readiness to face a digital era, Bina Sarana Informatika University, Surakarta City Campus, took an initiative to implement a community service program in form of training on using AI in education for students. Community service method used in this activity is the Asset Based Community Development (ABCD) approach which aims to empower communities by utilizing existing potential and resources. Implementation stages include needs analysis (Discovery), expectations formulation (Dream), design of training modules (Design), finalization of plans with FGD (Define), and training implementation (Destiny). AI workshop for Islamic boarding schools has been successfully implemented with good results. From questionnaires that have been filled out by all participants, it shows that workshop materials presented are very useful, materials and tutors delivery method are satisfactory. Workshop participants who are satisfied or rate it good are 63% and those who rate it as very satisfied or very good are 32%.
UTILIZING END USER DEVELOPMENT METHOD FOR DEVELOPING PENCAK SILAT ORGANIZATION INFORMATION SYSTEMS Setyadi, Heribertus Ary; Wahyuningsih, Hartati Dyah; Nurohim, Galih Setiawan; Sundari, Sundari
Jurnal Pilar Nusa Mandiri Vol. 21 No. 2 (2025): Pilar Nusa Mandiri : Journal of Computing and Information System Publishing Pe
Publisher : LPPM Universitas Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/pilar.v21i2.6487

Abstract

Gondang is one of the PSHT sub-branches located in Sragen Regency, Central Java, Indonesia. In managing member data from recruitment to promotion, conventional methods are still used using office applications and information dissemination is still using brochures and social media. This research aims to develop an information system that can help manage data and disseminate information at PSHT Gondang. The system developed can manage the registration of prospective member to become a member and the process of promotion. Delivery of information in the form of organizational structures, announcements, activity schedules, services for member and community, activity galleries containing photos and videos can also be accessed through the system.EUD was chosen as a method in system development because time required is quite short with a relatively small cost allocation. The system is created using Laravel framework and Firebase as a database with a responsive display so that it can be accessed using a smartphone. By using the EUD method, users can modify the appearance and existing information if there is a change in data from the organization which was not available in previous research.
Extreme Learning Machine Method Application to Forecasting Coffee Beverage Sales Sutanto, Yusuf; Setyadi, Heribertus Ary; Nugroho, Wawan; Al Amin, Budi
Journal of Applied Informatics and Computing Vol. 9 No. 5 (2025): October 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i5.10465

Abstract

Sales estimates can be used to set product prices and increase expected profits. Flyover coffee shop Karanganyar does not have a methodical forecasting method to estimate and predict their need/demand for coffee beverage products. Two previous research that used Extreme Learning Machine (ELM) method in other predictions stated that ELM method has high accuracy and fast compilation time. Another research predicted jeans sales using the ARIMA model and produced an accuracy of 17.05% based on the MAPE (Mean Absolute Percentage Error) method. Menstrual cycle prediction using the Long Short-Term Memory (LSTM) method produces a MAPE value of 7.5%. Two advantages of ELM method from two previous research were used as the basis for selecting ELM method used in our study. To help predict sales of coffee beverage menus, this research utilized an artificial neural network method using ELM algorithm. ELM method consists of an input layer and an output layer connected through a hidden layer. Data used for the test was daily sales data for a month. Data used for this study consisted of 215 data samples. Daily sales data at the Flyover coffee shop were collected from June to December 2024. Based on the results and analysis of error values using MAPE method, an average error value was 8.274%. From comparison of original data results and prediction data, an average MAPE error value the best number of features and hidden neurons is 5.65%.
Co-Authors - STIE AUB Surakarta, Yusuf Sutanto Agung Nugroho Agus Kristianto Agus Kristianto Ahmad Fauzi Akhmad Syukron Al Amin, Budi Amin, Budi Al Annida Purnamawati Bambang Eka Purnama Bambang Eka Purnama Budi Al Amin Cahyo Nugroho, Ernes Candra Agustina Dahlan Susilo Doddy Satrya Perbawa Ernes Cahyo Nugroho - STMIK AUB Surakarta Fauzi Ahmad Muda Galih Setiawan - UBSI Galih Setiawan Nurohim Galih Setyawan Nurohim Haryanto, Wawan Nugroho, Wawan Nurohim, Galih S Pudji Widodo Pudji Widodo Rahmawati-Universitas Bina Sarana Informatika, Eka Rousyati, Rousyati Sardiarinto Sardiarinto Satrya Perbawa, Doddy Sri Rejeki Sundari . Sundari Sundari Supriyanta Supriyanta Sutanto Sutanto Sutanto Sutanto Wahyuningsih, Hartati Dyah Wawan Haryanto Wawan Nugroho Yulianto Yusuf Sutanto Yusuf Sutanto