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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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Journal : JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH)

 1 
Analisis Sentimen Pengguna X Terhadap Isu Adzan Menjadi Running Text Menggunakan Algoritma K-Nearest Neighbors (KNN) Baharudin, Arya Rifaldi; Butsianto, Sufajar; Supriyanto, Asep
Journal of Information System Research (JOSH) Vol 6 No 4 (2025): July 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v6i4.8055

Abstract

Sentiment analysis has become an important method for understanding public opinion on social and religious issues. This study aims to analyze user sentiment regarding the issue of the adzan presented in a running text format using the K-Nearest Neighbors (K-NN) algorithm. The adzan as running text on national television occurred during Pope Francis's mass at Gelora Bung Karno Stadium (GBK) on September 5, 2024. The Ministry of Religious Affairs (Kemenag) advised that the Maghrib adzan, usually broadcast on national television, be replaced with running text. This recommendation was made to facilitate the live broadcast of the mass attended by Christian congregants and to honor the worship without disruption. Some parties, such as the Indonesian Ulema Council (MUI) and the General Chairman of PP Persis, stated that replacing the adzan with running text does not violate Islamic law, while Minister of Communication and Information Budi Arie Setiadi mentioned that the change is merely a suggestion. The research findings indicate that the K-NN algorithm involves several stages, including data collection and labeling, text processing, feature extraction using TF-IDF, and splitting the data into 80% for Training and 20% for Testing. Based on the test results, the K-NN model detected 10 positive sentiments and 168 negative sentiments, indicating a tendency for Twitter users to express more negative sentiments. Analysis using a Confusion matrix shows that this model achieved an accuracy rate of 88%, indicating good performance in sentiment classification.
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.
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): October 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 Arwan, 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 Indradewa, Rhian Irfan, Yusuf Iwan Mulyana 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 Siswandi , Arif Siswandi, Arif Siti Rahayu Sulaeman, Asep Arwan Sunge , Aswan S. Supriyanto Supriyanto, Asep Suratman Suratman Suryadi Suy, Kaleb Syahlan Sugiarto Tedi, Nanang Tri Ngudi Wiyatno Triwibowo, Edi Turmud Zy, Ahmad Valentin*, M Ryan Bagus Wachid Hasyim, Wachid Widiyatmoko, Arif Tri Wiyanto Wiyanto Wiyanto Yolanda Alviana Zehan Prahardika