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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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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.
RANCANG BANGUN APLIKASI RENTAL PERANGKAT ELEKTRONIK BERBASIS MERN Ariestian, Michael Ariestian; Arnomo, Sasa Ani
Computer Based Information System Journal Vol. 13 No. 1 (2025): CBIS Journal
Publisher : Universitas Putera Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33884/cbis.v13i1.9631

Abstract

The rapid increase in the demand for flexible and economical access to electronic devices has made electronic device rental services an increasingly popular solution. However, these services still face various challenges, such as limited access to information, manual rental processes, and inefficient payment systems. This study aims to design and develop an electronic device rental application based on the MERN stack (MongoDB, Express.js, React.js, Node.js) integrated with a payment gateway to enhance operational efficiency and user experience. The software development method used is Scrum, which enables rapid iteration through a series of sprints, from user interface design to implementing core features such as inventory management, online booking, and integrated online payments. The development results demonstrate that the application can provide a more structured system for device management, information transparency, and fast and secure transactions. This study contributes an innovative web-based rental system and serves as a reference for the development of similar applications in the future. With its offered features, this application is expected to improve access to electronic devices, support societal needs, and foster the growth of the electronic device rental industry in Indonesia..
Building The Prediction of Sales Evaluation on Exponential Smoothing using The OutSystems Platform Arnomo, Sasa Ani; Yulia, Yulia; Ukas, Ukas
ILKOM Jurnal Ilmiah Vol 15, No 2 (2023)
Publisher : Prodi Teknik Informatika FIK Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v15i2.1529.222-228

Abstract

To get a large profit in a company or business is to determine sales predictions for the next period. Prediction or forecasting is one of the keys to the success of sales because the predicted value of sales can be used as a reference to determine the order of goods, so there is no loss. Exponential smoothing method is a fairly superior forecasting method in long-term, medium-term and short-term forecasting. The data to be processed is sales data for the 2020-2022 period. The single exponential smoothing method was chosen because it can determine sales predictions for the next period with the smallest error value. The evaluation method used is MAPE, ME, MAD and MSE where this forecasting method is used to find the smallest error value. Based on the calculation results, the smallest error value obtained is ME at 62.8, MAD at 179.9, MSE at 55564.5, and MAPE at 9.20%. The value is at alpha 0.3. The next stage is to design a prediction system using the out-systems platform version 11.14.1 as a place to design the system. The test results of the system that has been designed to assist business owners in making decisions on product inventory estimates.
Co-Authors Amrizal Amrizal Andriani Pratiwi Ariestian, Michael Ariestian 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 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