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All Journal Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) International Journal for Applied Information Management International Journal Software Engineering and Computer Science (IJSECS) Indonesian Journal of Multidisciplinary Science Jurnal Sosial dan Sains Jurnal Indonesia : Manajemen Informatika dan Komunikasi Journal Innovations Computer Science
Aula, Raisah Fajri
Sekolah Tinggi Ilmu Komputer Cipta Karya Informatika
Humanities Astronomy Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Physics Public Health Social Sciences

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Implementation of the Naive Bayes Method in Looker Studio for data on the achievement of Great IDN in IDN Akhwat School Akbar, Yuma; Az-Zahra, Haura Salsabila; Setiawan, Kiki; Fajri, Raisah
Indonesian Journal of Multidisciplinary Science Vol. 3 No. 11 (2024): Indonesian Journal of Multidisciplinary Science
Publisher : International Journal Labs

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55324/ijoms.v3i11.981

Abstract

The IDN Hebat program is an important tool for schools to track and analyze student achievement data. However, with the targeted activities in the IDN program, challenges arise in managing and measuring achievement data efficiently. The research aims to develop a Web Cloud-based data management system for IDN Hisbat achievements at IDN Akhwat School by utilizing Google Looker Studio and the Naive Bayes Algorithm. The data source used in this study is by applying a classification dataset obtained from student achievement information data in the Great IDN Program. The results of this analysis show that the highest accuracy of teaching achievement fell on the status of exceeding the target with a percentage of 89%, and the highest class that placed the status above the target was class 9A with an average percentage of 35%. In addition, the results from this analysis can help coordinators and schools in planning more effective and strategic programs in the future. Overall, this study provides important benefits in improving the quality of teaching and student coaching, as well as supporting data-driven decision-making. This study is expected to enhance the efficiency, accuracy, and effectiveness of managing student achievement, while also supporting the attainment of optimal educational goals for each student to achieve extraordinary results.
Automatic Purchase Order Classification Using SVM in POS System at Skus Mart Sri Lestari; Muhamad Zaeni Nadip; Yuma Akbar; Aditya Zakaria Hidayat; Raisah Fajri Aula
International Journal Software Engineering and Computer Science (IJSECS) Vol. 5 No. 2 (2025): AUGUST 2025
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v5i2.4564

Abstract

In retail business processes, decision-making regarding Purchase Order PO submissions often remains manual and subjective, creating risks that impede procurement efficiency. The study develops an automatic classification model to predict PO approval status using Support Vector Machine SVM algorithm integrated within Point of Sale POS systems. Historical purchase transaction data was obtained from SKUS Mart POS database containing 133 entries, including attributes such as item quantity, purchase price, previous stock levels, and total purchase amounts. The research applies CRISP-DM methodology, encompassing business understanding, data exploration, preprocessing normalization using StandardScaler, model training, evaluation, and deployment phases. The model was trained using linear kernel and validated through holdout technique with 80:20 ratio for training and testing. Test results demonstrate that the SVM model achieves 76.69% accuracy, 82.21% precision, 76.69% recall, and 78.51% F1-score. The model was implemented in a web-based POS system CodeIgniter 3 combined with Python scripts to generate automatic classifications displayed directly in the user interface. Although the model demonstrates adequate performance, the study has not compared its effectiveness against other machine learning algorithms such as Random Forest or K-Nearest Neighbor. These findings establish initial groundwork for machine learning integration to support decision automation in procurement systems.
Implementation of Decision Support System for Seed Award Recipient Student Selection at Madrasah Ibtidaiyah Baiturrahman, Bandung, West Java Salma Latifa Azzahra; Raisah Fajri Aula; Nadiya Herdiana Putri
International Journal Software Engineering and Computer Science (IJSECS) Vol. 5 No. 2 (2025): AUGUST 2025
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v5i2.4604

Abstract

The selection process for Seed Award recipients at Madrasah Ibtidaiyyah Baiturrahman Bandung encounters challenges related to subjective assessment and perceived inequity. The evaluation system applies uniform criteria across all students from grades 1 to 6 without accounting for developmental differences between grade levels. To address these issues, we designed and implemented a web-based Decision Support System utilizing the VIKOR method. We selected VIKOR for its ability to generate optimal compromise solutions in multi-criteria problems involving conflicting considerations. The DSS employs four primary criteria: Religious Practice 20%, Character 20%, Discipline 20%, and Grade Level 40%, with the latter formulated as a cost criterion to ensure fairness across educational levels. We built the system using Laravel framework and tested it with 17 teachers and 20 students as trial participants. Implementation results demonstrate substantial improvements in selection objectivity, evidenced by increased representation of lower-grade students from grades 1 to 2 as award recipients from 18% to 42%. Furthermore, 94% of teachers reported the system as more objective and user-friendly, 75% of students expressed increased motivation following system deployment, and parental complaints were eliminated previously ranging from 5 to 7 cases per semester. These findings indicate that VIKOR-based DSS successfully establishes fairer, more transparent, and accountable selection processes while enhancing stakeholder confidence in evaluation mechanisms within madrasah environments.
Implementation of a Chatbot Using the Waterfall Method to Improve Helpdesk Service Efficiency at IT Consulting Companies Sri Lestari; Eka Putri Aprillia; Raisah Fajri Aula
International Journal Software Engineering and Computer Science (IJSECS) Vol. 5 No. 3 (2025): DECEMBER 2025
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v5i3.5207

Abstract

PT XYZ is a company engaged in information and communication technology services, supporting customers' digital transformation. The effectiveness of helpdesk services plays a crucial role in maintaining operations and fostering customer relationships. However, the issue reporting process is still handled manually through platforms such as WhatsApp and email, causing several problems, including inefficient ticket management, delays in ticket number assignment, and limited historical data. This study developed a chatbot based on Microsoft Copilot Studio to automate ticket creation, supported by Power Apps to address the lack of two-way communication features, aiming to support Customer Relationship Management (CRM) efforts. The system was developed using Waterfall methodology. The results showed significant improvements in service efficiency: the previous average initial response time of 2 days, 19 hours, and 13 minutes was eliminated due to automatic ticket number assignment; the average issue resolution time decreased from 5 days, 6 hours, and 20 minutes to 42 minutes; and ticket history search time improved from 14 minutes to 2 seconds. The chatbot successfully accelerated the reporting process, enhanced data recording, and reduced the workload of the helpdesk team. This solution significantly improved helpdesk efficiency and strengthened customer engagement.
Transformasi Digital UMKM Batik Melalui Penerapan Teknologi IT Berbasis Sistem Katalog Musalim Yusuf; Raisah Fajri Aula; Tio Risnanto; Faradj Farizi
Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 9 No 3 (2025): JULI-SEPTEMBER 2025
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jtik.v9i3.3807

Abstract

Digital transformation is one of the important steps for MSMEs (Micro, Small, and Medium Enterprises) in facing the era of globalization and market competition, especially in the creative economy sector such as batik. This study aims to analyze the digital transformation strategy of MSME Batik Banyumasan through the application of IT technology based on a catalog system. The research method used is qualitative with an observation, interview, and SWOT analysis approach to understand the needs and challenges faced by business actors. The results of the study show that the application of a catalog website can increase customer attraction and facilitate the marketing process of batik products. This website is equipped with features such as a homepage, new products, collections, and complete products designed to make it easier for visitors to explore and buy batik products. This study concludes that digital transformation through technology based on a catalog system not only helps MSME Batik Banyumasan in increasing sales, but also preserves the cultural heritage of batik as part of the creative economy.
Co-Authors Aditya Zakaria Hidayat Adzani, Adinda Mutiara Aimar, Muqorrobin Akbar, Yuma Az-zahra, Haura Salsabila Azhar, Anisah Nurul Eka Putri Aprillia Eldina, Ratih Faradj Farizi Hidayat, Aditya Zakaria Hutauruk, Lucas Namora Muhamad Zaeni Nadip Musalim Yusuf Nadiya Herdiana Putri Permatasari, Veren Nita Salma Latifa Azzahra Setiawan, Kiki Sodik Sri Lestari Tio Risnanto Tundo, Tundo