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All Journal KLIK (Kumpulan jurnaL Ilmu Komputer) (e-Journal) InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan ILKOM Jurnal Ilmiah Computer Based Information System Journal Jurdimas (Jurnal Pengabdian Kepada Masyarakat) Royal JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) JURNAL TIKAR JUSTIN (Jurnal Sistem dan Teknologi Informasi) Jurnal Puan Indonesia Jurnal Sistim Informasi dan Teknologi Jurnal Desain dan Analisis Teknologi The Indonesian Journal of Computer Science Computer & Science Industrial Engineering Journal Prosiding Seminar Nasional Ilmu Sosial dan Teknologi (SNISTEK)
Arnomo, Sasa Ani
Universitas Putera Batam
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Public Health Social Sciences Other

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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.
Optimalisasi Pemilihan Vendor Suku Cadang Mesin Menggunakan Metode Simple Additive Weighting (SAW) Arnomo, Sasa Ani; Yurnita, Zada Alzena
Jurnal Desain Dan Analisis Teknologi Vol. 4 No. 2 (2025): Juli
Publisher : Aptikom Kepri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58520/jddat.v4i2.80

Abstract

Perusahaan manufaktur otomotif sering menghadapi permasalahan dalam memilih vendor suku cadang mesin, terutama terkait kualitas produk, ketepatan pengiriman, dan harga. Penelitian ini bertujuan untuk mengoptimalkan pemilihan vendor dengan menerapkan metode Simple Additive Weighting (SAW), suatu metode pengambilan keputusan multikriteria (MCDM). Lima kriteria digunakan, yaitu: harga, kualitas produk, waktu pengiriman, fleksibilitas volume, dan layanan purna jual. Bobot masing-masing kriteria diperoleh dari hasil kuisioner kepada lima responden internal. Tiga vendor dievaluasi dan skor akhir dihitung. Vendor A memperoleh nilai tertinggi (0.9161), diikuti Vendor B (0.8863), dan Vendor C (0.7756). Hasil ini menunjukkan bahwa metode SAW efektif dan praktis dalam mendukung keputusan strategis dalam pemilihan vendor.
Implementasi Data Intelligence Pada Proses Pengambilan Keputusan Bisnis: (Studi Kasus: Rekomendasi Kontrak Kerja PT.BATM) Saragih, Saut Pintubipar; Husein, Alice Erni; Arnomo, Sasa Ani; Maslan, Andi
Jurnal Desain Dan Analisis Teknologi Vol. 5 No. 1 (2026): Januari
Publisher : Aptikom Kepri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58520/jddat.v5i1.97

Abstract

Penelitian ini bertujuan untuk menganalisis data karyawan IT dalam rangka mendukung pengambilan keputusan terkait perpanjangan kontrak kerja. Dataset yang digunakan mencakup data karyawan IT selama periode enam tahun dengan 19 atribut utama, termasuk latar belakang pendidikan, jabatan, durasi kontrak, dan status kepegawaian. Metode penelitian dilakukan melalui tahapan analisis data intelligence yang meliputi proses filterisasi, pembersihan data, serta analisis deskriptif dan korelasional. Hasil penelitian menunjukkan bahwa mayoritas karyawan IT memiliki latar belakang pendidikan sarjana (S1), yang mencerminkan standar rekrutmen yang relatif tinggi. Distribusi durasi kontrak didominasi oleh rentang 7–12 bulan, dengan tingkat keberhasilan probation yang dapat diidentifikasi melalui perbandingan status lulus dan diperpanjang terhadap tidak lulus. Korelasi positif yang kuat (0,65) antara kesesuaian pendidikan IT dan durasi kontrak mengindikasikan bahwa latar belakang pendidikan berpengaruh terhadap retensi karyawan. Dari sisi jabatan, peran senior seperti Project Manager memiliki tingkat retensi tertinggi, sementara peran developer menunjukkan durasi kontrak yang konsisten. Penelitian ini juga menemukan bahwa sekitar 60% resign terjadi dalam enam bulan pertama masa kerja, sehingga bulan ke-3 dan ke-6 diidentifikasi sebagai waktu optimal untuk intervensi retensi.
PENINGKATAN SKILL COMPUTATIONAL THINKING SISWA SMK MELALUI PENGENALAN ALGORITMA DAN PEMROGRAMAN PYTHON Arnomo, Sasa Ani; Purba, Abram Yunus; Kremer, Hendri
PUAN INDONESIA Vol. 7 No. 2 (2026): Jurnal Puan Indonesia Vol 7 No 2 januari 2026
Publisher : ASOSIASI IDEBAHASA KEPRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37296/jpi.v7i2.484

Abstract

In today's digital era, computational thinking skills are a crucial competency that vocational high school students must possess to face the challenges of Industry 4.0. This Community Service (PKM) activity aims to improve students' logical, systematic, and analytical thinking skills at SMKS IT Darussalam Boarding School 01 through an introduction to algorithms and the Python programming language. The method of implementing this activity is carried out through three main stages: Socialization and introduction to basic algorithm concepts interactively, a practical Python programming workshop covering data structures, flow control, and simple functions, and mentoring in creating mini-projects based on programming logic. The results of this activity are expected to provide students with a deep understanding of how to solve complex problems through decomposition, pattern recognition, abstraction, and algorithm design. Through mastering the basics of Python, students are expected to not only be able to write code but also have a strong foundation in programming logic that can be implemented in various fields of information technology in the future.
Co-Authors Amrizal Amrizal Andriani Pratiwi Arif Rahman Hakim Armilia, Puti Selvi David Caslan Nababan Deddy Deddy Dwi Ely Kurniawan Fajrin , Alfannisa Annurrullah Fifi Fifi Fifi, Fifi Frangky Silitonga Gaguk Rudianto Harman, Rika Hendra Hendra Heri Nuryanto, Heri Husein, Alice Erni Inzagia Pratama, Irnaldika Jabnabillah, Faradiba Jazuli Jazuli Johan, Faul Jumadril, Jumadril juppren, juppren Karnadi, Very Khisal Khisal Kremer, Hendri Laurence Marpaung, Chindy Marina Clara Maslan, Andi Mhd Adi Setiawan Aritonang Mhd. Johan Michael Ariestian Michael Nasib Jalverin Sinaga Momon Muzakkar Muhammat Rasid Ridho napitupulu, maida Nofriani Fajrah, Nofriani Nopriadi Nopriadi Novri Adhiatma, Novri Octavia, Ecca Yolanda Pradana, Ronaldo Baja Prasetya, Lorensius Bima Ade Purba, Abram Yunus Rendy Rendy Ridho, Muhammat Rasid Sadikin , Siti Fairuz Nur Saputra, Vijay Andika Saragih, Saut Pintubipar Sherly Maisa Putri Sihombing, Rikardo Siti Halijah suwoto, Donna Olivia Syahril Effendi Tuhumena, Melva marsyah adella tukino, tukino Tukino, Tukino Ukas Ukas Vina Fariska wazir, indra Winda Evyanto Yanti, Chagu Hospita Yanti, Srimau Yuli Siyamto, Yuli yulia Yulia Yulia Yulia Yulia Yulia Yulia Yulia Yurnita, Zada Alzena Zakrimal Zakrimal Zia Hisni Mubarak