cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Huzain
Contact Email
huzain.azis@umi.ac.id
Phone
+628114484875
Journal Mail Official
ijodas.journal@gmail.com
Editorial Address
Jln. Paccerakkang, Kel. Berua, Kec.Biringkanaya, Kota Makassar, Propinsi Sulawesi Selatan, 90241
Location
Unknown,
Unknown
INDONESIA
Indonesian Journal of Data and Science
Published by yocto brain
ISSN : -     EISSN : 27159930     DOI : -
Core Subject : Science, Education,
Computer Science & IT Decision Sciences, Operations Research & Management Mathematics
IJODAS provides online media to publish scientific articles from research in the field of Data Science, Data Mining, Data Communication, Data Security and Data Representation
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 5 Documents
 1 
Search results for , issue "Vol. 3 No. 3 (2022): Indonesian Journal of Data and Science" : 5 Documents clear
[WITHDRAWN] Automatic Face Mask Detection on Gates to Combat Spread Of Covid_19 Dima Genemo, Musa
Indonesian Journal of Data and Science Vol. 3 No. 3 (2022): Indonesian Journal of Data and Science
Publisher : yocto brain

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56705/ijodas.v3i3.51

Abstract

The COVID-19 pandemic has spread across the globe, hitting almost every country. To stop the spread of the COVID-19 pandemic, this article introduces face mask detection on a gate to assure the safety of Instructors and students in both class and public places. This work aims to distinguish between faces with masks and without masks. A deep learning algorithm You Only Look Once (YOLO) V5 is used for face mask detection and classification. This algorithm detects the faces with and without masks using the video frames from the surveillance camera. The model trained on over 800 video frames. The sequence of a video frame for face mask detection is fed to the model for feature acquisition. Then the model classifies the frames as faces with a mask and without a mask. We used loss functions like Generalize Intersection of Union for abjectness and classification accuracy. The datasets used to train the model are divided as 80% and 20% for training and testing, respectively. The model has provided a promising result. The result found shows accuracy and precision of 95% and 96%, respectively. Results show that the model performance is a good classifier. The successful findings indicate the suggested work's soundness.
Analisis Quality of Service Layanan Video Surveillance Area Traffic Control System (ATSC) Pada Jaringan Internet Dinas Perhubungan Kota Kendari Nur bahri, Nur Bahri; Salim, Yulita; Azis, Huzain
Indonesian Journal of Data and Science Vol. 3 No. 3 (2022): Indonesian Journal of Data and Science
Publisher : yocto brain

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56705/ijodas.v3i3.52

Abstract

Dinas Perhubungan Kota Kendari menjadi salah satu kota yang telah menerapkan teknologi ATCS. Proses pemantau dilakukan menggunakan CCTV melalui jaringan internet yang dipantau secara real time melalui ruang kontrol Dinas Perhubungan Kota Kendari. Penerapan layanan video surveilance ATCS pada dinas perhubungan kota Kendari masih sering terjadi kendala seperti akses video surveillance yang dilakukan secara real-time mengalami buffering sehingga kualitas video yang ditampilkan tidak optimal. Permasalahan yang terjadi tersebut perlu dilakukan tindak lanjut penanganan dengan melakukan analisa layanan atau yang dikenal dengan Quality of Service. untuk menentukan apakah kualitas jaringan pada Layanan Video surveillance ATCS yang digunakan telah sesuai atau perlu dilakukan peningkatan kualitas sesuai standarisasi Tiphon dengan menggunakan metode Action Research (AR). Hasil penelitian menunjukkan hasil dari penguuran jaringan dinas Perhubungan Kota Kendari mendapatkan nilai QoS “3,55” dengan indeks “memuaskan” dan Pada Provider data (Tri) dengan nilai QoS “3,31” dengan kategori “memuaskan” yang telah di kategorikan pada standarisasi Tiphon.
[WITHDRAWN] Deep Reinforcement Learning for Tehran Stock Trading Yousefi, Neda
Indonesian Journal of Data and Science Vol. 3 No. 3 (2022): Indonesian Journal of Data and Science
Publisher : yocto brain

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56705/ijodas.v3i3.53

Abstract

One of the most interesting topics for research and also for making a profit is stock trading. Artificial intelligence has had a great impact on this path. A lot of research has been done to investigate the application of machine learning, and deep learning methods in stock trading. Despite the large amount of research done in the field of prediction and automation trading, stock trading as a deep reinforcement-learning problem remains an open research area. The progress of reinforcement learning as well as the intrinsic properties of reinforcement learning make it a suitable method for market trading in theory. In this paper, single stock trading models are presented based on the fine-tuned state-of-the-art deep reinforcement learning algorithms (Deep Deterministic Policy Gradient (DDPG) and Advantage Actor Critic (A2C)). These algorithms are able to interact with the trading market and capture the financial market dynamics. The proposed models are compared, evaluated, and verified on historical stock trading data. Annualized return and Sharpe ratio have been used to evaluate the performance of proposed models. The results show that the agent designed based on both algorithms is able to make intelligent decisions on historical data. The DDPG strategy performs better than the A2C and achieves better results in terms of convergence, stability, and evaluation criteria.
Analisis Performa Metode Gaussian Naïve Bayes untuk Klasifikasi Citra Tulisan Tangan Karakter Arab Nurul A'ayunnisa; Salim, Yulita; Azis, Huzain
Indonesian Journal of Data and Science Vol. 3 No. 3 (2022): Indonesian Journal of Data and Science
Publisher : yocto brain

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56705/ijodas.v3i3.54

Abstract

Berdasarkan penelitian yang dilakukan oleh Herman dkk., peneliti mencoba mengangkat kembali metode yang diterapkan dengan menggunakan dataset yang berbeda dan dengan jumlah yang lebih banyak. Penelitian ini bertujuan untuk menghitung performa metode (akurasi, presisi, recall, dan f-measure) Gaussian Naïve Bayes. Dataset yang digunakan adalah citra tulisan tangan karakter arab. Berdasarkan hasil perhitungan performa menunjukkan tingkat akurasi tertinggi sebesar 12%, presisi 10%, recall 12%, dan f-measure 8%.
Design of a Sales Performance System for SMEs based on Business Intelligence and Data Warehouse Saputra, Dhanar; Subarkah, Pungkas; Afifah, Erika Luthfi; Muflikhatun, Siti; Ramadani, Nevita Cahaya; Utami, Melida Ratna; Aunillah, Puteri Johar
Indonesian Journal of Data and Science Vol. 3 No. 3 (2022): Indonesian Journal of Data and Science
Publisher : yocto brain

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56705/ijodas.v3i3.58

Abstract

The influence of information technology today is powerful. It impacts people's lives because technological changes are running so fast and affect the way of thinking and behaving in competition in the business world and organizations. Small and Medium Enterprises (SMEs) must be able to adapt to this technology to maintain their business. It means that digitizing SMEs means integrating technology into all business activities. In this study, Toko Cerme is the object of research. The Toko Cerme is a SMEs in the form of a minimarket located in Central Java, Indonesia. The Toko Cerme takes advantage of technology to help run business processes so that they can be managed optimally. In running its business, The Toko Cerme is currently using an information system to input product data and transaction activities. The purpose of this research is to propose a Design of a Sales Performance System based on Business Intelligence and a Data Warehouse to support business processes at the Toko Cerme so that it can efficiently process data and information in the future. From the research that the authors conducted, it can be concluded that the results of this study are the creation of a data warehouse and business intelligence design using the nine steps Kimbal method. At the same time, Pentaho Data Integration (PDI) is a tool. The design is used as a reference in producing information relating to sales transactions.

Page 1 of 1 | Total Record : 5

 1 

Filter by Year

2022 2022


Reset
Filter By Issues
All Issue Vol. 6 No. 2 (2025): Indonesian Journal of Data and Science Vol. 6 No. 1 (2025): Indonesian Journal of Data and Science Vol. 5 No. 3 (2024): Indonesian Journal of Data and Science Vol. 5 No. 2 (2024): Indonesian Journal of Data and Science Vol. 5 No. 1 (2024): Indonesian Journal of Data and Science Vol. 4 No. 3 (2023): Indonesian Journal of Data and Science Vol. 4 No. 2 (2023): Indonesian Journal of Data and Science Vol. 4 No. 1 (2023): Indonesian Journal of Data and Science Vol. 3 No. 3 (2022): Indonesian Journal of Data and Science Vol. 3 No. 2 (2022): Indonesian Journal of Data and Science Vol. 3 No. 1 (2022): Indonesian Journal of Data and Science Vol. 2 No. 3 (2021): Indonesian Journal of Data and Science Vol. 2 No. 2 (2021): Indonesian Journal of Data and Science Vol. 2 No. 1 (2021): Indonesian Journal of Data and Science Vol. 1 No. 3 (2020): Indonesian Journal of Data and Science Vol. 1 No. 2 (2020): Indonesian Journal of Data and Science Vol. 1 No. 1 (2020): Indonesian Journal of Data and Science More Issue