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RANCANG BANGUN APLIKASI E-COMMERCE BERBASIS WEB PADA TOKO ZIFA BEAUTY Armilia, Puti Selvi; Sasa Ani Arnomo
Computer Science and Industrial Engineering Vol 10 No 3 (2024): Comasie
Publisher : LPPM Universitas Putera Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33884/comasiejournal.v10i3.8512

Abstract

Zifa Beauty is a business that offers a variety of skincare products and fragrances. Data processing in shop management is still done by hand. The aim of this research is to create a web-based e-commerce application for Zifa Beauty Store via design and development. The author employs the V-Model approach, which enables users to assess the system and documentation acceptability at the conclusion of the development phase. The outcomes showed that with an automated sales system, stores can easily track transactions made by specific customers. This information can help in recognizing customer preferences and buying habits, so that stores can provide more personalized and interesting services for customers, Structured transaction data can be used to conduct in-depth sales analysis. Store owners can view sales trends over time, identify best-selling products, and identify new business opportunities. Sales data recorded in the database allows stores to forecast future stock needs. Based on sales trends, stores can project the level of demand for a particular product and organize purchase orders more precisely.
IMPLEMENTASI DEEP LEARNING DENGAN TENSORFLOW UNTUK MENDETEKSI KUALITAS MATERIAL PADA DEPARTEMEN IQC Michael Nasib Jalverin Sinaga; Sasa Ani Arnomo
Computer Science and Industrial Engineering Vol 10 No 3 (2024): Comasie
Publisher : LPPM Universitas Putera Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33884/comasiejournal.v10i3.8525

Abstract

This research utilizes deep learning with tensorflow to enhance the efficiency of incoming quality control (iqc) in material quality inspection. iqc, As a critical stage in the production chain, ensures the quality of incoming materials and plays a significant role in the final product quality. However, iqc effectiveness is often hindered by issues of accuracy and inspection speed. the solution lies in an advanced approach, employing deep learning technology, especially with the use of the tensorflow framework. deep learning is applied for image segmentation, object detection, and material quality classification. The methodology involves cnn on tensorflow, expected to enhance accuracy and inspection efficiency. The objective is to generate an accurate model, reduce inspector involvement, and improve iqc efficiency. The implementation of deep learning is anticipated to create highly accurate models, speed up inspection processes, automate tasks, and reduce operational costs and human error risks. This research has the potential to provide a positive contribution to the advancement of material quality testing technology, making it more sophisticated, efficient, and effective, with a positive impact on final product quality and operational efficiency.
PENERAPAN KLASIFIKASI CITRA PADA IDENTIFIKASI OBJEK DENGAN PAKAIAN SAFETY MENGGUNAKAN CONVOLUTIONAL NEURAL NETWORK DI PT JAYATAMA SAFETINDO. David Caslan Nababan; Sasa Ani Arnomo
Computer Science and Industrial Engineering Vol 12 No 2 (2025): Comasie Vol 12 No 2
Publisher : LPPM Universitas Putera Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33884/comasiejournal.v12i2.9647

Abstract

Construction workers are essential to project execution but face high risks of workplace accidents, often caused by human factors. Advances in artificial intelligence, particularly image processing, provide opportunities to improve the detection of personal protective equipment (PPE), which is currently checked manually and inefficiently. PPE, such asgloves, helmets, and safety shoes, is vital for worker safety but is often neglected due to discomfort. This study uses Convolutional Neural Network (CNN) algorithms to classify images and verify PPE usage at construction sites. CNN processes spatial information through layers for feature extraction, dimension reduction, and classification. A previousstudy with Faster R-CNN achieved accuracies of 72.83% with TensorFlow and 88.07% with Faster R-CNN. Using a dataset of 200 images, this research, conducted at PT JAYATAMA SAFETINDO, applies Python and TensorFlow to improve PPE detection accuracy. The results aim to support safer workplaces, enhance productivity, and advance AI applications in safety and identification.
OPTIMASI IMPLEMENTASI SOFT SKILL BERBASIS TEKNOLOGI INFORMASI DALAM AKADEMIK PENDIDIKAN DI SEKOLAH KEJURUAN Amrizal Amrizal; Rika Harman; Syahril Effendi; Sasa Ani Arnomo
Prosiding Vol 4 (2022): SNISTEK
Publisher : LPPM Universitas Putera Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The implementation of community service activities that will be carried out in the form of soft skill education development for vocational students at SMK Putera Jaya Batam in Batam City. Soft skill s education is very useful for vocational school graduates who will enter the world of work, with this ability it will make it easier for graduates to adapt to the work environment. Besides that, the soft skill competencies possessed by vocational school graduates will help in training a good work ethic and the ability to solve problems with any method and supported by a good leadership spirit, making it easier for graduates to work in a team. There are several soft skill s that need to be mastered by vocational school graduates including creative thinking skills, problem solving skills, interpersonal skills, intrapersonal skills, communication skills, leadership skills. From some of these abilities, an activity is made that is able to optimize the implementation of information technology-based soft skill s in academic education in vocational schools through community service activities by applying design thinking methods, leadership training and implementing simple applications commonly used by the community, with the hope that this activity is able to provide an overview of how to implement soft skill s in the world of work, and students also know the importance of soft skill s in the world of work so as to increase the interest of students to continue to explore and master soft skill s education as an answer to future challenges as quality vocational graduates
Prediksi Kepribadian Mahasiswa Menggunakan Naïve Bayes Muhammat Rasid Ridho; Sasa Ani Arnomo; Fifi Fifi; Khisal Khisal; Vina Fariska
Prosiding Vol 5 (2023): SNISTEK
Publisher : LPPM Universitas Putera Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33884/psnistek.v5i.8056

Abstract

College students are in a transitional phase from youth to adulthood. The transition period makes students still unstable to control their emotions. It makes his curiosity towards new things increase which then shows his personality traits. The purpose of this study was to find out how researchers collect data about personality from students, to find out how to classify personality from the data that has been collected. Research methods start from collecting data using Text Preprocessing questionnaires, Data Training, Classification, Testing, to making predictions. After applying the classification algorithm with the Naïve Bayes algorithm, the Train Score is 0.947 and the Test Score is 0.879. Trials have also been carried out to make predictions with new data whose results are correct.
PELATIHAN PEMANFAATAN AI UNTUK MEMBUAT VIDEO KREATIF Arnomo, Sasa Ani; Kremer, Hendri; Aritonang, Mhd Adi Setiawan; Jabnabillah, Faradiba; Yulia, Yulia
PUAN INDONESIA Vol. 7 No. 1 (2025): Jurnal PUAN Indonesia Vol. 7 No. 1 Juli 2025
Publisher : ASOSIASI IDEBAHASA KEPRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37296/jpi.v7i1.407

Abstract

Lack of support from parents, teachers, or peers can make students feel unmotivated to develop creativity. Therefore, an activity is needed that helps develop students' talents other than academics. AI training in video making has opened up new opportunities for school students to explore creativity. Making videos is not just a hobby, but also has many benefits for student development. It helps students explore new ideas, think out-of-the-box, and find unique ways to express themselves. In addition, it is very important to equip students with digital skills that are in great demand in the modern era, such as operating video editing software, searching for information online, and using various creative applications.
Optimasi Metode Fuzzy Mamdani Dalam Estimasi Kebutuhan Pengadaan Suku Cadang Pada PT.XYZ Yulia; Arnomo, Sasa Ani
The Indonesian Journal of Computer Science Vol. 10 No. 2 (2021): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v10i2.3007

Abstract

Persediaan merupakan hal yang penting bagi perusahaan untuk menjalankan proses bisnis agar efektif dan efisien sesuai dengan tujuan yang hendak dicapai. Salah satu contohnya adalah persediaan suku cadang pada PT. XYZ yang bergerak dibidang pabrikasi dan distribusi logam berat yaitu Cooper Slag di Kota Batam yang sangat dibutuhkan oleh pihak galangan kapal maupun Offshore. Tujuan dari penelitian ini adalah memudahkan PT. XYZ dalam mengambil keputusan optimasi persediaan suku cadang. Sistem yang di pakai adalah Fuzzy Inference System yang penerapannya menggunakan metode Mamdani. Metode ini dapat dengan mudah diterapkan pada sistem yang dibuat dengan bantuan toolbox fuzzy inference system. Fungsi implikasi yang digunakan dalam proses ini adalah fungsi MIN. Hasil yang didapat dalam pengujian FIS sebesar 8, angka ini masih dalam parameter variabel output sedikit dan sedang. Maka, didapat kesimpulan bahwa FIS metode Mamdani dapat membantu PT. XYZ dalam membuat keputusan pada optimasi dalam estimasi pengadaan suku cadang.