Publisher: Universitas Udayana (Total: 62 journals)   [Sort by number of followers]

Showing 1 - 61 of 61 Journals sorted alphabetically
Advances in Tropical Biodiversity and Environmental Sciences     Open Access   (Followers: 4)
Agrotrop : J. on Agriculture Science     Open Access   (Followers: 1)
Buletin Studi Ekonomi     Open Access   (Followers: 2)
Buletin Veteriner Udayana     Open Access   (Followers: 1)
Bumi Lestari J. of Environment     Open Access  
Cakra Kimia (Indonesian E-J. of Applied Chemistry)     Open Access  
COPING (Community of Publishing in Nursing)     Open Access   (Followers: 1)
E-J. of Cultural Studies     Open Access   (Followers: 1)
e-J. of Linguistics     Open Access   (Followers: 3)
E-J. of Tourism     Open Access   (Followers: 8)
E-Jurnal Agroekoteknologi Tropika (J. of Tropical Agroecotechnology)     Open Access  
E-Jurnal Akuntansi     Open Access  
E-Jurnal Ekonomi dan Bisnis Universitas Udayana     Open Access  
E-Jurnal Ekonomi Pembangunan Universitas Udayana     Open Access  
E-Jurnal Manajemen Universitas Udayana     Open Access  
E-Jurnal Medika Udayana     Open Access  
Ecotrophic : J. of Environmental Science     Open Access  
Indonesia Medicus Veterinus     Open Access  
Indonesian J. of Legal and Forensic Sciences     Open Access   (Followers: 1)
Intisari Sains Medis     Open Access  
Intl. J. of Engineering and Emerging Technology     Open Access  
itepa : Jurnal Ilmu dan Teknologi Pangan     Open Access  
J. of Food Security and Agriculture     Open Access   (Followers: 1)
J. of Health Sciences and Medicine     Open Access  
J. of Marine and Aquatic Sciences     Open Access   (Followers: 2)
J. of Veterinary and Animal Sciences     Open Access  
JBN (Jurnal Bedah Nasional)     Open Access  
Jurnal Analisis Pariwisata     Open Access  
Jurnal Arsitektur Lansekap     Open Access  
Jurnal BETA (Biosistem dan Teknik Pertanian)     Open Access  
Jurnal Biologi Udayana     Open Access  
Jurnal Destinasi Pariwisata     Open Access  
Jurnal Ekonomi Kuantitatif Terapan     Open Access  
Jurnal Energi Dan Manufaktur     Open Access  
Jurnal Ilmiah Akuntansi dan Bisnis     Open Access  
Jurnal Ilmiah Mahasiswa SPEKTRUM     Open Access  
Jurnal Ilmiah Merpati (Menara Penelitian Akademika Teknologi Informasi)     Open Access  
Jurnal Ilmu dan Kesehatan Hewan (Veterinary Science and Medicine J.)     Open Access   (Followers: 1)
Jurnal Ilmu Komputer     Open Access  
Jurnal IPTA     Open Access  
Jurnal Kepariwisataan dan Hospitalitas     Open Access  
Jurnal Kimia (J. of Chemistry)     Open Access  
Jurnal Magister Hukum Udayana (Udayana Master Law J.)     Open Access  
Jurnal Master Pariwisata (J. Master in Tourism Studies)     Open Access  
Jurnal Matematika     Open Access  
Jurnal Rekayasa dan Manajemen Agroindustri     Open Access  
Jurnal Spektran     Open Access  
Jurnal Udayana Mengabdi     Open Access  
Jurnal Veteriner     Open Access   (Followers: 1)
Kertha Patrika     Open Access  
Lingual : J. of Language and Culture     Open Access  
Linguistika : Buletin Ilmiah Program Magister Linguistik Universitas Udayana     Open Access   (Followers: 1)
Lontar Komputer : Jurnal Ilmiah Teknologi Informasi     Open Access  
Majalah Ilmiah Peternakan     Open Access   (Followers: 1)
Majalah Ilmiah Teknologi Elektro : J. of Electrical Technology     Open Access   (Followers: 1)
Matrik : Jurnal Manajemen, Strategi Bisnis dan Kewirausahaan     Open Access  
Piramida     Open Access  
Ruang-Space: Jurnal Lingkungan Binaan (J. of The Built Environment)     Open Access  
Simbiosis : J. of Biological Sciences     Open Access  
Sport and Fitness J.     Open Access   (Followers: 4)
Udayana J. of Law and Culture     Open Access  
Similar Journals
Journal Cover
Lontar Komputer : Jurnal Ilmiah Teknologi Informasi
Number of Followers: 0  

  This is an Open Access Journal Open Access journal
ISSN (Print) 2088-1541 - ISSN (Online) 2541-5832
Published by Universitas Udayana Homepage  [62 journals]
  • Forecasting of Sea Level Time Series using RNN and LSTM Case Study in
           Sunda Strait

    • Authors: Annas Wahyu Ramadhan, Didit Adytia, Deni Saepudin, Semeidi Husrin, Adiwijaya Adiwijaya
      Pages: 130 - 140
      Abstract: Sea-level forecasting is essential for coastal development planning and minimizing their signi'cant
      consequences in coastal operations, such as naval engineering and navigation. Conventional sea
      level predictions, such as tidal harmonic analysis, do not consider the in'uence of non-tidal elements
      and require long-term historical sea level data. In this paper, two deep learning approaches
      are applied to forecast sea level. The 'rst deep learning is Recurrent Neural Network (RNN), and
      the second is Long Short Term Memory (LSTM). Sea level data was obtained from IDSL (Inexpensive
      Device for Sea Level Measurement) at Sebesi, Sunda Strait, Indonesia. We trained the
      model for forecasting 3, 5, 7, 10, and 14 days using three months of hourly data in 2020 from 1st
      May to 1st August. We compared forecasting results with RNN and LSTM with the results of the
      conventional method, namely tidal harmonic analysis. The LSTM’s results showed better performance
      than the RNN and the tidal harmonic analysis, with a correlation coef'cient of R2 0.97 and
      an RMSE value of 0.036 for the 14 days prediction. Moreover, RNN and LSTM can accommodate
      non-tidal harmonic data such as sea level anomalies.
      PubDate: 2021-10-29
      DOI: 10.24843/LKJITI.2021.v12.i03.p01
      Issue No: Vol. 12, No. 3 (2021)
  • Modified KNN-LVQ for Stairs Down Detection Based on Digital Image

    • Authors: Ahmad Wali Satria Bahari Johan, Sekar Widyasari Putri, Granita Hajar, Ardian Yusuf Wicaksono
      Pages: 141 - 150
      Abstract: Persons with visual impairments need a tool that can detect obstacles around them. The obstacles that exist can endanger their activities. The obstacle that is quite dangerous for the visually impaired is the stairs down. The stairs down can cause accidents for blind people if they are not aware of their existence. Therefore we need a system that can identify the presence of stairs down. This study uses digital image processing technology in recognizing the stairs down. Digital images are used as input objects which will be extracted using the Gray Level Co-occurrence Matrix method and then classified using the KNN-LVQ hybrid method. The proposed algorithm is tested to determine the accuracy and computational speed obtained. Hybrid KNN-LVQ gets an accuracy of 95%. While the average computing speed obtained is 0.07248 (s).
      PubDate: 2021-11-23
      DOI: 10.24843/LKJITI.2021.v12.i03.p02
      Issue No: Vol. 12, No. 3 (2021)
  • Water and Air Quality Monitoring System based on the Internet of Things

    • Authors: Komang Try Wiguna Adhitya Primantara, Putu Wira Bhuana, Kyle Doran
      Pages: 151 - 162
      Abstract: Environmental pollution is a global issue that occurs at this time. It is caused by various human activities that produce pollutants that endanger their lives. By utilizing current technology, it is possible to design a Water and Air Quality Monitoring System based on the Internet of Things to monitor air and water quality quickly and in real-time in the surrounding environment. The users can access this system via the web and Android / IOS mobile applications that display the data obtained by the sensor in the form of real-time graphics of water and air conditions. In addition, this system consists of several sensor nodes in charge of providing field data regarding the parameters used as the basis for assessing water and air quality according to the applicable standards in Indonesia. Sensors for water using a Turbidity Sensor, DS18B20 Sensor, PH Sensor, DHT 11, and TDS (Total Dissolved Solids) Sensor. Sensors for air consist of the DHT11 sensor, the MQ-7
      sensor, the MQ-135 sensor, and the dust sensor GP2Y1010AU0F.
      PubDate: 2021-11-23
      DOI: 10.24843/LKJITI.2021.v12.i03.p03
      Issue No: Vol. 12, No. 3 (2021)
  • Propeller Speed Control System on Autonomous Quadcopter with Variations in
           Load Fulcrum Point

    • Authors: Ratna Aisuwarya, Ibrahim Saputra, Dodon Yendri
      Pages: 163 - 174
      Abstract: The need for unmanned vehicles is increasingly needed in certain conditions, such as distribution of disaster supply, distribution of medicines, distribution of vaccines in the affected areas in pandemic situations. The various types of goods to be distributed require a different fulcrum. This research implemented PID control for the quadcopter balance control system to achieve stability during hovering. PID control is used to achieve a certain setpoint to produce the required PWM output for the propeller to reach a speed that can fly the quadcopter tilted until it reaches a steady state. Tests were carried out on the roll and pitch motion of the quadcopter by providing a load. The results show that PID control can be implemented for the quadcopter balance control system during hovering by determining the PID constants for each roll and pitch motion with the constanta of Kp = 0.15, Kd = 0.108, and Ki = 0.05. The quadcopter takes 3 – 6 seconds to return to the 0 degree setpoint when it is loaded.
      PubDate: 2021-11-29
      DOI: 10.24843/LKJITI.2021.v12.i03.p04
      Issue No: Vol. 12, No. 3 (2021)
  • A New Simple Procedure for Extracting Coastline from SAR Image Based on
           Low Pass Filter and Edge Detection Algorithm

    • Authors: Ni Nyoman Pujianiki, I Nyoman Sudi Parwata, Takahiro Osawa
      Pages: 175 - 185
      Abstract: This study proposes a new simple procedure for extracting coastline from Synthetic Aperture Radar (SAR) images by utilizing a low-pass filter and edge detection algorithm. The low-pass filter is used to improve the histogram of the pixel value of the SAR image. It provides better distribution of pixel value and makes it easy to separate between sea and land surfaces. This study provides the processing steps using open-source software, i.e., SNAP SAR processor and QGIS application. This procedure has been tested using dual polarization Sentinel-1 (10x10 meters resolution) and single polarization ALOS-2 (3x3 meters resolution) dataset. The results show that using Sentinel-1 with dual polarization (VH) provides a better result than single polarization (VV). In the ALOS-2 case, only single polarization (HH) is available. However, even using only HH polarization, ALOS-2 provides a good result. In terms of resolution, ALOS-2 provides a better coastline than Sentinel-1 data due to ALOS-2 has better resolution. This procedure is expected to be helpful to detect coastline changes and for coastal area management.
      PubDate: 2021-11-29
      DOI: 10.24843/LKJITI.2021.v12.i03.p05
      Issue No: Vol. 12, No. 3 (2021)
  • Detecting Excessive Daytime Sleepiness With CNN And Commercial Grade EEG

    • Authors: I Putu Agus Eka Darma Udayana, Made Sudarma, Ni Wayan Sri Ariyani
      Pages: 186 - 195
      Abstract: Epworth sleepiness scale is a self-assessment method in sleep medicine that has been proven to be a good predictor of obstructive sleep apnea. However, the over-reliance of the method making the process not socially distancing friendly enough in response to a global covid-19 pandemic. A study states that the Epworth sleepiness scale is correlated with the brainwave signal that commercial-grade EEG can capture. This study tried to train a classifier powered by CNN and deep learning that could perform as well as the Epworth with the objectiveness of brainwave signal. We test the classifier using the 20 university student using the Epworth sleepiness test beforehand. Then, we put the participant in 10 minutes EEG session, downsampling the data for normalization purposes and trying to predict the outcome of the ESS in respect of their brainwave state. The AI predict the reaching 65% of accuracy and 81% of sensitivity with just under 100.000 dataset which is excellent considering small dataset although this still have plenty room for improvement.
      PubDate: 2021-11-29
      DOI: 10.24843/LKJITI.2021.v12.i03.p06
      Issue No: Vol. 12, No. 3 (2021)
School of Mathematical and Computer Sciences
Heriot-Watt University
Edinburgh, EH14 4AS, UK
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