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All Journal JSI: Jurnal Sistem Informasi (E-Journal) Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Jurnal Teknoinfo Jurnal Nasional Komputasi dan Teknologi Informasi Journal of Information System, Applied, Management, Accounting and Research Jurnal Informatika Ekonomi Bisnis REMIK : Riset dan E-Jurnal Manajemen Informatika Komputer JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Jurnal Teknologi Informatika dan Komputer Journal of Computer Networks, Architecture and High Performance Computing Bulletin of Computer Science Research Bulletin of Information Technology (BIT) Brilliance: Research of Artificial Intelligence Pelita Teknologi : Jurnal Ilmiah Informatika, Arsitektur dan Lingkungan Jurnal Ilmiah SIGMA: Informatics Engineering Journal of UPB Jurnal Inkofar Jurnal Informatika Teknologi dan Sains (Jinteks) Jurnal Pengabdian Mandiri Malcom: Indonesian Journal of Machine Learning and Computer Science Jurnal Lentera Pengabdian Jurnal Informatika Ekonomi Bisnis Riwayat: Educational Journal of History and Humanities VIDHEAS: Jurnal Nasional Abdimas Multidisiplin RECORD Journal of Loyality and Community Development
Butsianto, Sufajar
Universitas Pelita Bangsa
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 Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics Medicine & Pharmacology Neuroscience Public Health Social Sciences Transportation Other

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Prediction of Employee Assessments for Contract Extensions at PT Sagateknindo Sejati Using the Naïve Bayes Algorithm Naya, Candra; Siswandi, Arif; Butsianto, Sufajar; Febriyanti, Febriyanti
Brilliance: Research of Artificial Intelligence Vol. 4 No. 1 (2024): Brilliance: Research of Artificial Intelligence, Article Research May 2024
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v4i1.4170

Abstract

Companies must be selective in conducting employee assessments in order to retain employees with the best performance. When assessing employee performance, it is seen from their perseverance and discipline. However, in reality, good employee performance sometimes gets bad reviews and even gets reprimanded by their superiors. This is caused by the employee assessment monitoring system used, namely only personal assessment without using an assessment system and the data collected is less than optimal. This research uses the Naive Bayes method to process data using a data mining algorithm to obtain predictions that can be used as additional references in making employee performance assessment decisions. Aims to predict employee assessments of contract extensions at PT Sagateknindo Sejati. This research is important because it helps in making more accurate decisions regarding employee contract extensions based on existing historical data. Naive Bayes is a data processing algorithm that is classified as a calculation that is easy to understand but its accuracy results are reliable. It is used because it is efficient in managing data with various attributes and is able to produce predictions based on the probability of each existing attribute. The data used in this research includes various variables, using the Rapidminer supporting application to test the accuracy of the system created. Testing was carried out by preparing 320 data and testing 50 randomly selected data. Test data will be analyzed using the Rapidminer supporting application. The test results produced an accuracy of 83.96%.
Eye Disease Detection and Classification Optimization Using EfficientNet-B5 with Emphasis on Data Augmentation and Fine-Tuning Anggi Muhammad Rifai; Muhammad Fatchan; Ahmad Turmudi Zy; Donny Maulana; Sufajar Butsianto
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 9 No 5 (2025): October 2025
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v9i5.6519

Abstract

Eye diseases such as glaucoma, cataract, and diabetic retinopathy pose significant global health challenges, underscoring the need for accurate and efficient diagnostic systems. This study employed the EfficientNet-B5 model to enhance the detection and classification of eye diseases by incorporating advanced data augmentation and fine-tuning techniques. The research utilizes the Ocular Disease Intelligent Recognition (ODIR) dataset, consisting of 4,217 fundus images categorized into four classes: normal, glaucoma, cataract, and diabetic retinopathy. The methodology comprises three phases: baseline model training, model training with data augmentation, and fine-tuning. The baseline model achieved an accuracy of 60.43%, which improved to 63.03% with data augmentation—an increase of 2.6 percentage points. Fine-tuning further elevated the accuracy to 93.23%, representing a notable improvement of 33.8 percentage points over the baseline. Model performance was evaluated using standard classification metrics including accuracy, precision, recall, and F1-score. These findings demonstrate the technical efficacy of combining augmentation and fine-tuning to enhance model generalization. The proposed approach offers a robust framework for developing dependable AI-driven diagnostic tools to support early detection and facilitate informed clinical decision-making.
Association Relationship Analysis in Finding Sales of Goods With Apriori Algorithm Fathurrahman, Humam; Sunge , Aswan S.; Butsianto, Sufajar
Journal of Computer Networks, Architecture and High Performance Computing Vol. 6 No. 3 (2024): Articles Research Volume 6 Issue 3, July 2024
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v6i3.4258

Abstract

Technology can be designed to help human life from all aspects ranging from agriculture, health science, industry and daily life. Toko Intan, a business engaged in the sale of basic and daily necessities. Every day, Toko Intan records every sales transaction in an archive stored in Microsoft Excel, containing data on goods sold every day. The purpose of this research is to find out what items are bought simultaneously by consumers to manage inventory, with the data mining method used in this research is the Association Rules method. Association Rules is one of the data mining techniques from the a priori algorithm which functions to find a combination pattern of an item. Tests carried out to process data in this study using the RapidMiner application, from tests carried out with the specified parameters, namely minimum support 30% and minimum confidence 65%, resulted in a lift ratio validation rule of 1.206. Personal Care Biscuits with 30.8% support and 90.9% confidence with a validation lift ratio of 1.206. Sales transaction data analysis can be applied well, and is able to generate a new association rule from the sales transaction dataset. With this research, it is hoped that it can provide information to the owner of the Intan store in providing the stock of goods needed by consumers and to find out the combination of item sets from the sales transaction dataset.
Sistem Informasi Asset Management Di Pt. Sinar Sosro Dengan Metode Waterfall Berbasis Mobile Ramadhan, Aldi; Muhidin, Asep; Butsianto, Sufajar; Ermanto, Ermanto; Setyaningrum, Retno Purwani Setyaningrum
Jurnal SIGMA Vol 16 No 1 (2025): Juni 2025
Publisher : Teknik Informatika, Universitas Pelita Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37366/sigma.v16i1.6053

Abstract

Perkembangan teknologi informasi telah mendorong transformasi digital di berbagai bidang, termasuk manajemen aset. Pengelolaan aset yang efektif menjadi krusial bagi perusahaan dan individu untuk memastikan akurasi data, optimalisasi sumber daya, dan pengambilan keputusan yang tepat. Namun, PT. Sinar Sosro masih menghadapi kendala dalam pengelolaan aset secara optimal. Untuk mengatasi hal ini, penelitian ini mengembangkan Aplikasi Asset Management berbasis Android menggunakan metode Waterfall. Aplikasi ini dirancang untuk menyimpan data aset perusahaan, memudahkan staf dalam mengakses informasi aset, serta mendukung pengelolaan yang efisien melalui perangkat mobile. Dengan antarmuka yang intuitif dan berbasis cloud, sistem ini dapat diakses secara fleksibel melalui smartphone, menjadikannya solusi praktis untuk meningkatkan akurasi dan kecepatan dalam manajemen aset.
Web-based Machine Daily Check Application for Preventive Maintenance using Rapid Application Development Putra, Irga Ramadhan; Butsianto, Sufajar; Raharjo, Sugeng Budi
Journal of Information System Research (JOSH) Vol 5 No 4 (2024): Juli 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v5i4.5651

Abstract

In a manufacturing company, preventive maintenance is one of the scheduled programs implemented to reduce the risk of damage, downtime, and repair costs, thus the production targets can be achieved optimally. So that PT. Trimitra Chitrahasta can become a reliable automotive component manufacturer and be able to compete in the Southeast Asia region in the field of Metal Stamping and Die Making. An integrated maintenance system needs to be developed to increase the achievement of the company's production targets. A web-based information system has been created to support the development of a maintenance system which includes features such as master data image, machine data, and master data person in charge, category, master data description, master data sheet, machine inspection, and daily machine reports. The development methods used are Rapid Application Development (RAD) and Unified Modeling Language (UML) to design business processes. The system implementation uses the Laravel framework PHP, HTML, and MySQL as the database. The analysis results show that the application of a web-based information system can increase the effectiveness of managing preventive machine inspections. The number of documented working days increased significantly, which indicates improved inspection discipline. The frequency of machine downtime was reduced, reducing additional costs for repairs, and mold production target achievement increased from 90% to 100%, indicating increased production efficiency.
Penerapan Metode Waterfall pada Sistem Informasi Inventory Berbasis Website Ananda, Angga Thifal; Butsianto, Sufajar; Sulaeman, Asep Arwan
Journal of Information System Research (JOSH) Vol 5 No 4 (2024): Juli 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v5i4.5669

Abstract

PT. Toa Galva Industries is a company that has been established for more than 47 years, which still uses a manual inventory system such as recording goods data and data on goods in and out using ledgers, causing work to be less efficient and inaccurate. To find out what goods the company owns, the admin must check the goods files one by one so that they are prone to errors in the process. Therefore, it is necessary to create a website-based inventory information system application system that helps companies improve the efficiency and effectiveness of goods management. This system is designed to store data on incoming and outgoing goods and create stock reports quickly and accurately. The Waterfall method is used in designing this system because it has a clear and structured flow, where each stage must be completed before moving on to the next stage. And using the Black Box Testing method. The research results show that this system can help companies manage stock of goods effectively and efficiently, as well as provide fast and accurate reports on goods produced.
Sistem Informasi Keamanan Kunci Pintu Pintar Berbasis Internet of Things Notifikasi Real-Time Berbasis WhatsApp Suy, Kaleb; Sufajar Butsianto; Supriyanto
Bulletin of Computer Science Research Vol. 5 No. 5 (2025): August 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v5i5.720

Abstract

Security remains a primary concern in domestic and marketable structures, especially as conventional door cinches come decreasingly vulnerable to duplication and forced access. This study presents the design and perpetration of a smart door lock security system grounded on Internet of Things and Radio frequence Identification technologies. The main ideal is to give a real- time, ever controlled locking medium integrated with a mobile- grounded messaging platform. The development process adopts the nimble methodology, which promotes inflexibility, responsiveness to stoner feedback, and rapid-fire replication in software and tackle integration. The tackle armature utilizes ESP32 and Arduino Nano microcontrollers to manage essential factors, including RFID compendiums, relays, buzzers, solenoid cinches, LED and LCD as display module. On the software side, the system incorporates a pall connected messaging operation to deliver real- time announcements to druggies, including cautions for unauthorized access attempts, successful entries, and low battery warnings. Data communication between the microcontrollers is enforced via periodical protocol, while the commerce with the messaging service is established using the HyperText Transfer Protocol. Testing involved colorful scripts including valid access, unrecorded card attempts, and remote commands. The testing scenario uses three RFID cards and a WhatsApp chatbot, with one card as the master and the other two as access cards, with each card undergoing three trials. Results demonstrate a high success rate in card discovery and command prosecution with an average system response time below one second. The system also allows druggies to register and remove access cards via a master card medium, which enhances usability and control. This exploration contributes a low- cost, customizable, and effective security result suitable for smart homes, boarding houses, and small- scale marketable parcels. It shows the feasibility of integrating open- source microcontrollers with everyday messaging tools to achieve effective, real- time home security. The proposed system provides a foundation for unborn exploration in combining internet grounded control systems with biometric detectors or machine literacy grounded access analytics such as developing a separate mobile application so that it does not use third-party applications, allowing users to obtain more accurate feedback through door leaf detector sensors.
Implementasi Algoritma Apriori dalam Menemukan Pola Asosiasi pada Data Penjualan Produk Retail Butsianto, Sufajar; Candra Naya; Anggi Muhammad Rifa'i
Bulletin of Computer Science Research Vol. 5 No. 5 (2025): August 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v5i5.731

Abstract

This study aims to implement the Apriori algorithm in finding association patterns in retail product sales data, using the Association Rule Mining approach. Evaluating the ruler or association rules formed based on the support, confidence, and lift parameters, in finding association patterns in retail product sales data with a focus on the relationship between product categories. The data used consists of 500 sales data as sample data and 5,972 transactions as test data. The data mining process was carried out on the main product categories such as Milk, Coffee, Tea, Drinks, Detergent, and Biscuit/Snacks, to find association rules that appear simultaneously with the Bulk Products category in one transaction time. The minimum support parameter was set at 0.02 and the minimum confidence was set at 0.5. By using these parameters, several significant association rules were obtained. One of the strongest rules shows that if products in the Milk, Coffee, Tea, Drinks, Detergent, and Biscuit/Snacks categories are purchased together, then there is a 64.3% probability (confidence) that products in the Bulk Products category are also purchased at the same time. The support value of this rule reached 3.8%, and the lift value was 1.49, indicating a positive association and not a coincidence. Evaluation of the test data showed that this pattern was consistently found across 5,972 transactions, with a repeatability rate of 61.7%. The results of this study demonstrate that the Apriori algorithm is effective in identifying consumer purchasing patterns that can be utilized for product placement strategies, bundling offers, and inventory planning in retail management.
Implementasi K-Means Clustering Berbasis RapidMiner untuk Optimalisasi Segmentasi Penjualan Produk dalam Meningkatkan Efektivitas Strategi Pemasaran Butsianto, Sufajar; Siswandi, Arif
Journal of Information System Research (JOSH) Vol 7 No 1 (2025): Oktober 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v7i1.8439

Abstract

The Indonesian electronic retail industry is experiencing rapid growth along with digital transformation. However, available sales data is often only stored as transaction records without further analysis, so it has not been optimally utilized for marketing decision making or customer segmentation. This study aims to implement the RapidMiner-based K-Means Clustering algorithm to analyze segmentation patterns of electronic products at XYZ Store. The dataset used includes the variables Transaction_ID, Product_ID, Product_Name, Category, Quantity, Unit_Price, Revenue, and Recency. The research stages include data collection, preprocessing (filtering, aggregation, and Z-Score normalization), K-Means application, and interpretation of clustering results. Determination of the number of clusters in this study uses the Elbow Method, which shows an optimal point at K = 3, so that number of clusters is chosen for the data grouping process. Based on the results of the application of the K-Means algorithm with the three clusters, the following are obtained: (1) Cluster 0 (High Sales & High Revenue) consisting of Smartphones, Laptops, and Tablets as superior products with a contribution of almost 60% of total revenue; (2) Cluster 1 (Medium Sales & Moderate Revenue) includes Televisions, Refrigerators, and Smartwatches with a stable contribution of around 27%; and (3) Cluster 2 (Low Sales & Low Revenue) contains Washing Machines, Speakers, Headphones, and Printers with a low contribution of only 14%. These findings provide a strategic basis for management in making business decisions, such as procurement priorities, seasonal promotions, product bundling, and clearance strategies. This study proves that the application of data mining with K-Means Clustering is effective in increasing operational efficiency and supporting the competitiveness of the electronics retail business in Indonesia.
Co-Authors . Ermanto Abdul Halim Anshor Agung Nugroho Agus Suwarno Aguswin, Ahmad Ahmad Turmudi Zy Amali, Amali Ananda, Angga Thifal Ananto Tri Sasongko Andre Ardiansyah Andriani Andriani Andriani Andriani Anggi Muhammad Rifa'i Anggi Muhammad Rifai Anisah Purnamasari Aprila Hardi, Resty Arief Nur Hidayat ARIF SUSILO Aris Iskianto Aris Iskianto2 Arwan Sulaeman, Asep Asep Muhidin Asep Muhidin Baharudin, Arya Rifaldi Budi Rahardjo, Sugeng Candra Naya Candra Naya Dewi Sekar Arum Dian Riki Pangestu Dicky Winanda Santoso Donny Maulana Edi Tri Triwibowo Edi Tri Wibowo Edora Edora Edy Widodo Edy Widodo Eka Nur Arifin Eko Putra, Fibi Elkin Rilvani Endah Yaodah Kodratillah Ermanto Ermanto Fathurrahman, Humam Fauzi Ahmad Muda febriyanti febriyanti Herdiyan, Serly Humam Fathurrahman Ikhsan Romli Irfan, Yusuf Kodratillah, Endah Yaodah Makmun Effendi, M. Mamat Casmat Maryani Manik Maulana, Futuh Muhamad Fatchan Muhammad Faisal Muhammad Fatchan Muhammad Fikri Fauzan muhidin, asep Muhtajuddin Danny Naya, Candra Nindi Tya Mayangwulan Nurhali Saepudin Nurhali Saepudin Oktavianti, Risma Nadia Otib Subagja Pratama, Suria Puput Riyanti Purwanto Purwanto Putra, Irga Ramadhan Putri Riandani, Andini Raharjo, sugeng budi Ramadhan, Aldi Retno Fitri Astuti Rifa'i, Anggi Muhammad Romli S. Sunge, Aswan Selviana, Vina Setyaningrum, Retno Purwani Setyaningrum Setyawan, Wisnu Sifa Fauziah Sifa Fauziah, Sifa Siswandi , Arif Siswandi, Arif Siti Rahayu Sulaeman, Asep Arwan Sunge , Aswan S. Supriyanto Supriyanto, Asep Suratman Suratman Suy, Kaleb Syahlan Sugiarto Tedi, Nanang Triwibowo, Edi Turmud Zy, Ahmad Valentin*, M Ryan Bagus Wachid Hasyim, Wachid Widiyatmoko, Arif Tri Wiyanto Wiyanto Wiyanto Yolanda Alviana