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CommIT (Communication & Information Technology)
Published by Universitas Bina Nusantara
ISSN : 19792484     EISSN : 24607010     DOI : -
Core Subject : Science,
Computer Science & IT
Journal of Communication and Information Technology (CommIT) focuses on various issues spanning: software engineering, mobile technology and applications, robotics, database system, information engineering, artificial intelligent, interactive multimedia, computer networking, information system audit, accounting information system, information technology investment, information system development methodology, strategic information system (business intelligence, decision support system, executive information system, enterprise system, knowledge management), e-learning, and e-business (e-health, e-commerce, e-supply chain management, e-customer relationship management, e-marketing, and e-government). The journal is published in affiliation with Research Directorate, Bina Nusantara University in online and free access mode.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 478 Documents
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Color Extraction and Edge Detection of Nutrient Deficiencies in Cucumber Leaves Using Artificial Neural Networks Arie Qur'ania; Prihastuti Harsani; Triastinurmiatiningsih Triastinurmiatiningsih; Lili Ayu Wulandhari; Alexander Agung Santoso Gunawan
CommIT (Communication and Information Technology) Journal Vol. 14 No. 1 (2020): CommIT Journal
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/commit.v14i1.5952

Abstract

The research aims to detect the combined deficiency of two nutrients. Those are nitrogen (N) and phosphorus (P), and phosphorus and potassium (K). Here, it is referred to as nutrient deficiencies of N and P and P and K. The researchers use the characteristics of Red, Green, Blue (RGB) color and Sobel edge detection for leaf shape detection and Artificial Neural Networks (ANN) for the identification process to make the application of nutrient differentiation identification in cucumber. The data of plant images consist of 450 training data and 150 testing data. The results of identifying nutrient deficiencies in plants using backpropagation neural networks are carried out in three tests. First, using RGB color extraction and Sobel edge detection, the researchers show 65.36% accuracy. Second, using RGB color extraction, it has 70.25% accuracy. Last, with Sobel edge detection, it has 59.52% accuracy.
The Optimization of Website Visibility and Traffic by Implementing Search Engine Optimization (SEO) in Palembang Polytechnic of Tourism Agus Setiawan; Zulkifli Harahap; Dedy Syamsuar; Yesi Novaria Kunang
CommIT (Communication and Information Technology) Journal Vol. 14 No. 1 (2020): CommIT Journal
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/commit.v14i1.5953

Abstract

This research is a case study of Search Engine Optimization (SEO) in Palembang Polytechnic of Tourism website. The main objective of this research is to establish a plan for SEO in Palembang Polytechnic of Tourism (http://poltekpar-palembang.ac.id/) and to improve online visibility and ranking position in search engines (Google). It aims to bring in more international traffic and students to visit the website. SEO is a digital marketing technique to increase web accessibility. In the globalization world, people use search engines, such as Google, to know or find out more about various topics quickly and visually. Through a bibliographic review and qualitative analysis, the research focuses on the understanding of what SEO is and its implementation for the Palembang Polytechnic of Tourism website. The results show that the most important thing in making SEO plans is to increase visibility and branding on search engines (Google). SEO is done by developing website content and setting keywords as backlinks.
Lung Nodule Texture Detection and Classification Using 3D CNN Ivan William Harsono
CommIT (Communication and Information Technology) Journal Vol. 13 No. 2 (2019): CommIT Journal
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/commit.v13i2.5995

Abstract

Following artificial intelligence implementation in computer vision field, especially deep learning, many Computer-Aided Diagnosis (CAD) tools are proposed to help to detect lung cancer by the scoring system or by identifying the characteristics of nodules. However, lung cancer is a clinical diagnosis which does not provide detailed information needed by radiologists and clinician to prevent unnecessary invasive diagnostic procedures compared to lung nodule texture detection and classification. Hence, to answer this problem, this research explores the steps needed to implement 3D CNN on raw thorax CT scan datasets and usage of RetinaNet 3D + Inception 3D with transfer learning. The 3D CNN CAD tools can improve the speed, performance, and ability to detect lung nodule texture instead of malignancy status done by previous studies. This research implements 3D CNN on Moscow private datasets acquired from NVIDIA Asia Pacific. The proposed method of data conversion can minimize information loss from raw data to 3D CNN input data. On training phase, after 100 epochs, the researchers conclude that the best-proposed model (3D CNN with transfer learning of pretrained LIDC public datasets weight) provides 22.86% of mean average precision (mAP) detection capability and 70.36% of Area Under the Curve (AUC) in Moscow private dataset lung texture detection tasks. It outperforms non-transfer learning 3D CNN model (trained from scratch) and 3D CNN with transfer learning of pre-trained ImageNet weight.
Hydroponic Nutrient Control System Based on Internet of Things Herman Herman; Demi Adidrana; Nico Surantha; Suharjito Suharjito
CommIT (Communication and Information Technology) Journal Vol. 13 No. 2 (2019): CommIT Journal
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/commit.v13i2.6016

Abstract

The human population significantly increases in crowded urban areas. It causes a reduction of available farming land. Therefore, a landless planting method is needed to supply the food for society. Hydroponics is one of the solutions for gardening methods without using soil. It uses nutrient-enriched mineral water as a nutrition solution for plant growth. Traditionally, hydroponic farming is conducted manually by monitoring the nutrition such as acidity or basicity (pH), the value of Total Dissolved Solids (TDS), Electrical Conductivity (EC), and nutrient temperature. In this research, the researchers propose a system that measures pH, TDS, and nutrient temperature values in the Nutrient Film Technique (NFT) technique using a couple of sensors. The researchers use lettuce as an object of experiment and apply the k-Nearest Neighbor (k-NN) algorithm to predict the classification of nutrient conditions. The result of prediction is used to provide a command to the microcontroller to turn on or off the nutrition controller actuators simultaneously at a time. The experiment result shows that the proposed k-NN algorithm achieves 93.3% accuracy when it sets to k = 5.
Analysis of Decision Support System in Determining the Nutritional Status of Toddlers Using Simple Additive Weighting Ofan Sofian; Joseph Joseph; Fauziyah Fauziyah
CommIT (Communication and Information Technology) Journal Vol. 14 No. 1 (2020): CommIT Journal
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/commit.v14i1.6069

Abstract

The problem that currently happens in the decision process of the nutritional status for toddlers is often based on manual calculation. However, the manual calculation is prone to data duplication, insufficient data, and a lack of availability of the data itself, which can hinder the monitoring status and the report. Therefore, to ease the determination and calculation process of the nutritional status of toddlers, the researchers conduct a study using the Simple Additive Weighting (SAW) method. The SAW method is selected because it defines the best alternative and some other alternatives based on specified or preferred criteria. This research is conducted by finding the weight value of each attribute and rating the data to determine the nutritional status of toddlers. For the result, the researchers find there are no toddlers with malnutrition in Pemberdayaan Kesejahteraan Keluarga, Program Kerja Kelompok Kerja IV (PKK POKJA IV) of Depok.
Playing the SOS Game Using Feasible Greedy Strategy Abas Setiawan
CommIT (Communication and Information Technology) Journal Vol. 14 No. 1 (2020): CommIT Journal
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/commit.v14i1.6167

Abstract

The research aims to make an intelligent agent that can compete against the human player. In this research, the feasible greedy strategy is proposed to make an intelligent agent by checking all possible solutions in the limited tree levels to find effective movement. Several matches are conducted to evaluate the performance of the feasible greedy agent. The board size for the evaluation consists of 33, 44, 55, 66, 77, and 88 squares. From the result, the feasible greedy agent never loses against the random agent and the pure greedy agent. In 3 3 squares match, the agent can compensate against the human player, so the game always ends with a draw. In 44, 55, 66, 77, and 88 squares matches, the feasible greedy agent slightly outplays the human player.
Analysis of Deauthentication Attack on IEEE 802.11 Connectivity Based on IoT Technology Using External Penetration Test Yogi Kristiyanto; Ernastuti Ernastuti
CommIT (Communication and Information Technology) Journal Vol. 14 No. 1 (2020): CommIT Journal
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/commit.v14i1.6337

Abstract

The research aims to know the level of security of WiFi connectivity against deauthentication attacks on Internet of Things (IoT)-based devices. It is done through testing using an external penetration test method. The external penetration test simulates a real external attack without information about the target system and network given. The process starts from accessing the device through Internet or WiFi by the test target. At the same time, the attacker performs Denial-of-Service (DoS) attacks onWiFi. The attacker uses Arduino ESP8266 NodeMCU WiFi with Lua programming. To record WiFi activities, the researchers use CommView for WiFi V. 7.0, and the target is Internet Protocol (IP) camera device. The result shows that the communication of the test target with the gateway is lost, but the Media Access Control (MAC) of the test target is still registered at the gateway. Deauthentication attacks cause communication paralysis, and several changes occur, such as an increase in data rate, and change in frequency channel, Distribution System (DS) status, retry bits in frame management, and the sequence number.
How Twitter Works in Public Transportation: A Case Study of Bus Rapid Transit in Jakarta and Semarang Surya Hidayat Bokings; Achmad Nurmandi; Mohammad Jafar Loilatu
CommIT (Communication and Information Technology) Journal Vol. 14 No. 2 (2020): CommIT Journal
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/commit.v14i2.6400

Abstract

The research focuses on using social media (Twitter) as a medium for public transportation services (Bus Rapid Transit - BRT) in Semarang and Jakarta. The research uses Nvivo 12 Plus as a tool in qualitative research methods. The results show that the function regarding Twitter accounts of BRT in Semarang and Jakarta has several differences. The difference is based on information integration services, interaction information and transparency, and adaptive and responsive information services. In conclusion, the information integration on Twitter accounts of BRT in Semarang and Jakarta services works well, but a more dominant function is found in BRT in Jakarta. The Twitter account of BRT in Jakarta provides more information on transportation routes, such as the number of routes and fleets. BRT in Jakarta is a responsive account, responding to questions or mentions given by its users. The high level of activity makes the BRT Jakarta account more active. Moreover, the form of information conveyed by the Twitter account of BRT Semarang has its characteristics because it shows more the character of the region (Central Java).
Visual Recognition to Identify Helmet on Motorcycle Rider Using Convolutional Neural Network Kevin Alexander; Rayhan Ardiya Dwantara; Raihan Muhammad Naufal; Derwin Suhartono
CommIT (Communication and Information Technology) Journal Vol. 14 No. 2 (2020): CommIT Journal
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/commit.v14i2.6564

Abstract

The amount of motorcycle accidents is increasing each year. The main reason is that the riders do not wear a helmet. The research aims to minimize the accident by training the machine learning using the IBM Watson Studio. It trains the data about “wearing helmet” and “not wearing helmet”. The used method is Convolutional Neural Network (CNN). About 170 image datasets are used. CNN is conducted on the input image using a kernel or filter. The filter will multiply its values with the overlapping values of the image while also sliding and adding them all to produce a single value for each of them until the entire images have passed and finished. After CNN method is done, the researchers can classify the images by using supervised learning. It can identify whether the rider is wearing a helmet or not simply by scanning a picture on the street. The result shows high accuracy of 92.87%. The method can be used to minimize the percentage of motorcycle accidents caused by not wearing a helmet.
The Determinant Factors of E-Commerce Usage Behavior During Flash Sale Program Arta Moro Sundjaja; Gladys Valentina Arisanto; Sarah Fatimah
CommIT (Communication and Information Technology) Journal Vol. 14 No. 2 (2020): CommIT Journal
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/commit.v14i2.6582

Abstract

The research objective is to analyze the determinant factors of the purchase intention during a flash sale program. It is conducted from October 2018 to January 2019. The researchers apply a quantitative approach. The sampling technique is snowball sampling. The survey data are collected from 210 respondents who shop online in Indonesia using questionnaires. The data are examined using Structural Equation Modelling (SEM) with AMOS ver. 25. The research results indicate that the effect of perceived usefulness, information quality, and web quality on purchase intention are mediated by attitude. The flash sale program has a moderating impact on purchase intention. The effect of perceived ease of use and trust in the purchase intention mediated by attitude is not significant. The R-squared value of attitude on e-commerce is 0.527, and purchase intention is 0.369. These research results are important for e-commerce management to understand the essential factors of purchase intention during a flash sale program.

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