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All Journal Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Seminar Nasional Informatika (SEMNASIF) JURNAL MEDIA INFORMATIKA BUDIDARMA SEIKO : Journal of Management & Business Jiko (Jurnal Informatika dan komputer) International Journal of Supply Chain Management EconBank : Journal Economics and Banking Jurnal Ilmiah Edunomika (JIE) Jurnal Informatika Ekonomi Bisnis JTIULM (Jurnal Teknologi Informasi Universitas Lambung Mangkurat) Abdimas Galuh : Jurnal Pengabdian Kepada Masyarakat Jurnal Darma Agung Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Brilliance: Research of Artificial Intelligence Jurnal Inovasi Masyarakat Computing Jurnal Informatika International Journal of Multidisciplinary Sciences and Arts Jurnal Informatika Ekonomi Bisnis
Fitrah Rumaisa
Universitas Widyatama
Agriculture, Biological Sciences & Forestry Humanities 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 Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Nursing Social Sciences Transportation Other

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Analysis of the Impact of the Pre-Employment Card Program and Clustering of Unemployment Rates in West Java Using Spectral Clustering Khoirunnisa, Fathimah Fadhilah; Rumaisa, Fitrah
Brilliance: Research of Artificial Intelligence Vol. 5 No. 1 (2025): Brilliance: Research of Artificial Intelligence, Article Research May 2025
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v5i1.5917

Abstract

The Pre-Employment Card Program is an initiative launched by the Indonesian government to enhance workforce skills and reduce unemployment. In West Java Province, where population density and socio-economic diversity are high, assessing the effectiveness of this program is particularly relevant. This study aims to cluster regions in West Java based on participation in the Pre-Employment Card Program and unemployment rates using the spectral clustering method, as well as to analyze the program’s impact on regional unemployment levels.The dataset consists of variables such as unemployment rate, labor force size, education level, and program participation, obtained from the Central Bureau of Statistics (BPS) and the official Pre-Employment Program website (2020–2024). The clustering results identified two primary groups: regions with high unemployment and low participation, and those with low unemployment and high participation. The clustering structure achieved a Silhouette Score of 0.2808, indicating a reasonably good cluster separation. Correlation analysis revealed a weak positive relationship between program participation and unemployment reduction (r = 0.34), with the strongest correlation observed among senior high school and vocational school graduates. Regions with high participation experienced a decrease in the average unemployment rate from 10.39% to 8.36%, while those with low participation saw a decline from 9.16% to 7.21%. These findings suggest that the Pre-Employment Card Program holds potential in contributing to unemployment reduction in West Java. Nonetheless, further policy support is required, taking into account factors such as educational background, access to training, and local socio-economic dynamics to optimize the program’s impact.
Application of the Mean-Shift Method in Grouping the Influence of Labor Market Information on Labor Absorption in West Java Province Ulfah, Khaerani; Rumaisa, Fitrah
Brilliance: Research of Artificial Intelligence Vol. 5 No. 1 (2025): Brilliance: Research of Artificial Intelligence, Article Research May 2025
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v5i1.5920

Abstract

The imbalance between the number of job seekers and the availability of jobs is a challenge in the labor market in West Java Province. This study aims to group districts/cities based on the influence of labor market information on labor absorption using the Mean-Shift algorithm. Data were obtained from BPS for the 2019–2023 period, covering the number of job seekers, vacancies, and job placements. Data were processed through cleaning, transformation, normalization, and aggregation of a five-year average. Clustering was carried out using the Mean-Shift algorithm with an optimal bandwidth of 0.474611, resulting in two clusters with a Silhouette Score of 0.4943. The first cluster consists of areas with low labor absorption rates, characterized by the number of job seekers that are not comparable to vacancies and job placements. The second cluster includes areas with higher and more balanced labor absorption. The results of the study show that the Mean-Shift algorithm is able to group regions based on labor market characteristics. These findings suggest that labor market information can be used to map regions based on labor absorption rates in a more targeted manner, as well as support the formulation of data-based employment policies.
Course Learning Recommendation System Using Neural Collaborative Filtering Mulyana, Hadist Laroibafi; Rumaisa, Fitrah
Brilliance: Research of Artificial Intelligence Vol. 4 No. 2 (2024): Brilliance: Research of Artificial Intelligence, Article Research November 2024
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v4i2.4699

Abstract

The proliferation of e-learning platforms has created a need for sophisticated course recommendation systems. This paper presents an innovative online course recommendation system using Neural Collaborative Filtering (NCF), a deep learning technique designed to surpass traditional methods in accuracy and personalization. Our system employs a hybrid NCF architecture, integrating matrix factorization with multi-layer perceptron to capture complex user-course interactions. The proposed NCF-based recommendation system aims to address key challenges in the e-learning domain, such as diverse user preferences, varying course content, and evolving learning patterns. By leveraging the power of neural networks, our approach seeks to provide more relevant and personalized course suggestions to learners. Our research contributes to the intersection of deep learning and educational technology, offering new insights into how advanced machine learning techniques can be applied to improve online learning experiences. The proposed system has the potential to enhance the quality of course recommendations, leading to more effective learning pathways for users. This work has important implications for e-learning platforms, educational institutions, and lifelong learners navigating the vast landscape of online courses. By improving the match between learners and courses, we aim to increase engagement, completion rates, and overall satisfaction in online education. Future work will explore the long-term impact of such personalized recommendations on learning outcomes and skill development.
Membangun Learning Management System di SDN 162 Warung Jambu sebagai Media Belajar di Era Digital berbasis Moodle Sulianta, Feri; Rumaisa, Fitrah; Puspitarani, Yan; Violina, Sriyani; Rosita, Ai
Abdimas Galuh Vol 7, No 2 (2025): September 2025
Publisher : Universitas Galuh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25157/ag.v7i2.21000

Abstract

Pada era digital, sekolah dituntut untuk meningkatkan kualitas pembelajaran sekaligus memperkuat visibilitas daring sebagai media komunikasi, informasi, dan sarana belajar. Namun, SDN 162 Warung Jambu, Kota Bandung, masih menghadapi kendala karena pembelajaran didominasi metode konvensional dan informasi sekolah belum terintegrasi secara online. Untuk menjawab permasalahan tersebut, kegiatan pengabdian ini mengembangkan platform Learning Management System berbasis Moodle versi 4.3 dengan metode Research and Development menggunakan model Waterfall. Proses pengembangan meliputi analisis kebutuhan, desain sistem, implementasi, pengujian menggunakan metode Black Box, serta pemeliharaan. Hasil pengembangan menghasilkan website e-learning dengan domain https://elearning.sdn162bandung.sch.id/ yang memfasilitasi pembelajaran daring, mulai dari akses materi, pengumpulan tugas, kuis, forum diskusi, hingga pemantauan nilai secara transparan. Pengujian menunjukkan bahwa seluruh fitur pada peran admin, guru, dan siswa berfungsi sesuai kebutuhan tanpa kendala signifikan. Implementasi platform ini meningkatkan efisiensi pembelajaran, memperluas akses informasi akademik, serta memperkuat citra digital sekolah. Dengan demikian, pengembangan e-learning berbasis Moodle terbukti menjadi solusi efektif untuk mendukung transformasi digital sekolah dasar sekaligus mendorong terciptanya ekosistem pendidikan yang modern, adaptif, dan transparan.
Implementation of Kanban Method in Transactional System Design in the “Mr. Sneakers” Shoe Laundry Business Puspitarani, Yan; Violina, Sriyani; Rumaisa, Fitrah; Sulianta, Feri
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.v4i1.3859

Abstract

Laundry information system design using Kanban method is a strategic step to improve operational efficiency and responsiveness to customer needs in the laundry business. The study aims to design an information system that is integrated with the Kanban method to optimize the transaction process from receiving orders to returning to customers. The study outlines the process of designing a laundry information system using Kanban principles, including workflow mapping, suitable Kanban board design and integration with existing information systems. The results of this information system design show that the application of Kanban can provide a clear visualization of the workflow in the process, improve operational efficiency by speeding up the order cycle time, reducing waiting times, and minimizing errors in the transactions process. Good integration between the information system and the Kanban board allows managers to monitor order status in real time and respond quickly to changing customer requests. In conclusion, designing a laundry information system using the Kanban method can improve business performance, strengthen customer relationships, and create significant added value.
Co-Authors Ai Rosita Akhmad Rafi Oktavian Azizah Zakiah Benny Susanto Galih Raspati Iwan Rijayana Khoirunnisa, Fathimah Fadhilah Muchsam, Yoki Muhamad Hadziq Ilham Mulyana, Hadist Laroibafi Nurul Fiona Damayanti Obsatar Sinaga Rosita, Ai Rosmawati Rumondor, Aaron Sriyani Violina Sulianta, Feri Susanto, Benny Tanti Nurafianti Ulfah, Khaerani Vincentius Westley Dimitrius Thomas Wahdiaman, Wahdiaman Yan Puspitarani Yenny Maya Dora Yuningsih , Yuyun Yuniati Zainudin, Zalina