:: Abstract List ::

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Computer and Mathematics |
ABS-121 |
Analysis of User Security Awareness in the Smart Home Technology 1)wiryawan@binus.ac.id, 2)JoniS@binus.edu, 3*)anderesgui@binus.edu, 4)rachmat.julianto@agungsedayu.com, 5)satria.adirhah@gmail.com
1,2,3*) Information Systems Department, School of Information Systems,
Bina Nusantara University, Jakarta, Indonesia, 11480.
4) IT Governance Division, PT. Agung Sedayu, Jakarta, Indonesia, 14470
5) Event Organizer, Little Harmony Orchestra, Jakarta, Indonesia, 12180
Abstract
This study aims to analyze how the awareness of users in using Smart Home Technology Security. This study uses the UTAUT2 model with many variables like Performance Expectancy (PE), Effort Expectancy (EE), Social Influence (SI), Facilitating Conditions (FC), Hedonic Motivation (HM), Price Value (PV), Habit (HB) on Behavior Intention (BI). The data was obtained by distributing questionnaires through the Non-Probability Sampling and Snowball Sampling methods as a data collection technique. It processes by SMART PLS 3.2.8 software. The results showed that the user^s security awareness on the use of Smart Home technology was not influenced significantly by Performance Expectancy (PE), Effort Expectancy (EE), Social Influence (SI), Facilitating Conditions (FC), Hedonic Motivation (HM), Price Value (PV) factors, and Habit (HB) on Behavioral Intention (BI) not Habit (Hb) on User Behavior (UB). The main concern of this research was on Habit (HB) itself, where Habit (HB) to User Behavior (UB) was significant than Habit (HB) on Behavior Intention. (UB).
Keywords: Security System, Non-Probability Sampling with Snowball Sampling, UTAUT2, SEM-PLS, Smart Home Technology
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| Corresponding Author (Drajad Wiryawan)
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2 |
Computer and Mathematics |
ABS-164 |
EFFECT OF RETURN ON ASSETS (ROA), EARNINGS PER SHARE (EPS) AND RETURN ON EQUITY (ROE) ON SHARE PRICES Meiryani, Cindy Aprilia
BINA NUSANTARA
Abstract
This study aims to determine the effect of ROA, PER, ROE on stock prices of manufacturing companies in the food and beverage sector. The population in the study was 30 samples. The sample in this study consisted of 10 companies listed on the IDX in the period 2017-2019. The sampling method used in this study was targeted sampling. The data used is secondary data collected using data documentation methods. The analysis technique used is multiple regression analysis and hypothesis test using the partial t-test and simultaneous F-test with a significance level of 5% and the determination of the coefficient of determination.
The results of the analysis show that the data passed the classical assumption test, including normally distributed data, multicollinearity does not occur and heteroscedaticity does not occur. The results of the Return on Asset (ROA) and Return on Equity (ROE) regression have partially no effect on stock prices. Meanwhile, earnings per share (EPS) partially affects stock prices.
The food and beverage sector is a growing industry, so it is expected to be able to properly manage its financial performance to generate large profits and expand its operations even outside Indonesia without having to use large amounts of liabilities.
Keywords: Sampling Method
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| Corresponding Author (Cindy Aprilia)
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3 |
Computer Science |
ABS-2 |
The Selection Process for The Brand Rating of Convertible and Hybrid Laptop with MCDM-AHP Method Recommendations Akmaludin(a*), Erene Gernaria Sihombing(a), Cepi Cahyadi(a), Elin Panca Saputra(b), Adjat Sudradjat(c), Yopi Handrianto(c),Taufik Rahman(d)
a)Information System Department, STMIK Nusa Mandiri, Jakarta, Indonesia.
b)Information System Department, Faculty of Technology Industry of Universitas Bina Sarana Informatika, Jakarta, Indonesia.
c)Information and Technology Department, Faculty of Technic and Informatic of Universitas Bina Sarana Informatika, Jakarta, Indonesia.
d)Information and System Department, Faculty of Information System of Universitas Bina Sarana Informatika, Jakarta, Indonesia.
Abstract
Assessment of a technology product is seen from the performance criteria for its use over a period of one year. Especially for laptop products with the convertible and hybrid categories, it means that one laptop has two functions directly. The purpose of this study was to select the best Brand Rating of Convertible and Hybrid Laptop category in 2019. The method to be used to provide the best assessment is MCDM-AHP with a hierarchical model with four levels that are uniquely related to determine the optimal eigenvector value. The results obtained through a mathematically algebra matrices will be compared with the truth through the Expert Choice Application and provide identical values. The result is that the HP ElliteBook x360 ranks first for Brand Rating of Convertible and hybrid laptops.
Keywords: Algebra Matrices, Brand Rating, Convertible and Hybrid Laptop, Expert Choice, MCDM-AHP
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| Corresponding Author (Akmaludin Akmaludin)
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4 |
Computer Science |
ABS-4 |
Web-based Information System The Offices Bureau of Student Affairs With Database Modeling and Design Melina Melina (a), Wina Witanti (a), Eddie Krishna Putra (a), Asep Id Hadiana (a), Ade Kania Ningsih (a), Hernandi Sujono (a), Anceu Murniati (a), Valentina Adimurti Kusumaningtyas (a*)
(a ) Faculty of Science and Informatics, Universitas Jenderal Achmad Yani, Cimahi, Indonesia.
* Valentina.adimurti[at]lecture.unjani.ac.id
Abstract
Abstract. One of the information media that can be accessed widely and quickly is using a web-based information system. A website requires web developer so that the web is always updated in real-time. In fact, not all organizations have web developers who keep websites updated continuously and are dynamic. The combination of web technology and database called web-based, so that web can be dynamic web. This makes for the easier development and maintenance of larger-scale Web applications. Dynamic web-based information system design requires a database modeling and design.
The major objective of this study is to propose a web-based information system the offices bureau of student affairs with database modeling and design to aid student affairs bureau in capturing, storing, sharing, and publish activities and achievements of students. In this respect, a tool named Sikaromah (Sistem Informasi Kantor Biro Kemahasiswaan). Where users can automatically update the web page content without relying on web developer to edit a web page each time a new content and page is added. A working prototype of the system has been developed based on Hypertext Markup Language, Hypertext Preprocessor and MySQL. The system prototype is built on a n-tier client server architecture based.
Keywords: database modeling and design, dynamic web, information system, php, web-based
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| Corresponding Author (Melina Melina)
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5 |
Computer Science |
ABS-15 |
Home Monitoring System with WhatsApp and Raspberry Pi 3 Muhammad Ayat Hidayat- Holong Marisi Simalango
Unversitas Negeri Makassar - Universitas Universal
Abstract
Security is something that is very important for human life. Today there are several people who justify everything to get their things. Today many criminal acts were very specific to theft and robbery. Such action is not only happening in the street, buses, shops. But even in our homes that things can happen either the homeowner resides in the home or the homeowners were out, so there are many cases for robbery and theft, many people use home security tool on their home, but not a lot of tools or applications that provide real-time alerts to homeowners or users. In the process of making this application will use hardware such as Raspberry Pi, using MySQL for data storage history in a web application, the process flow using UML for the application, and use WhatsApp API to integrate with the Raspberry Pi. The purpose of this research is to design a security system at home in real-time alerts
Keywords: Home Monitoring, MySQL, WhatsApp, Raspberry Pi, WhatsApp API
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| Corresponding Author (Muhammad Ayat Hidayat)
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6 |
Computer Science |
ABS-18 |
Psychometric Analysis Series Ratna Jatnika, Urip Purwono, Achmad Djunaidi, Mustofa Haffas
Univeritas Padjadjaran
Abstract
This study aims to obtain the most appropriate and ^user friendly^ Psychometric Analysis Series software for analyzing tests effectively and efficiently. The specific objectives of this research are obtaining software for maximal performance tests and typical performance test especially for:
1. Scoring items
2. Item Analysis (Discriminant power, Distractor Power and Item Difficulty)
3. Item Distribution (Average, Standard Deviation, Item Proportion)
4. Reliability Analysis (Alpha Cronbach)
5. Correlation Matrix among Items
The results show that the Psychometric Analysis Series is a user-friendly software that can be used to analyze tests. However, this software still needs to be developed, especially to simplify installing the MySQL server program, making installation tutorial videos, and adding the Help menu.
The computer software development method is carried out using the Software Development Life Cycle (SDLC). The development stages consist of: Planning, Analysis, Design, Implementation, Maintenance.
Keywords: Software, Psychometric
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| Corresponding Author (Ratna Jatnika)
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7 |
Computer Science |
ABS-90 |
Intention to use E-Wallet with Cashback System Lianna Wijaya*, Helen, Hardiyansyah
PJJ Manajemen, Binus Online Learning, Bina Nusantara University
Abstract
Recently, there are many e-wallet applications that provide cashback rewards to users after transactions at merchants or online shopping market places. By considering some of the applications of the advantage, such as increased sales and increased customer satisfaction, this research will create a theoretical model based on psychological factors of users to explain their level of acceptance in using e-wallet applications. The theoretical model is developed from the Technology Acceptance Model (TAM), namely trust, perceived risk perception, perceived usefulness, perceived ease to us and last but not least the developer reputation, so those can influence the user^s behavioral intention to accept e-wallet applications with a cashback system. The research findings show that following result. First,
The developer reputation is the most important and very significant to bulid the user^s trust to use the e-wallet application. Second, the e-wallet developer with positive reputation will create intention to use which influenced by trust. Third, the trust of users will create intention to use the e-wallet application.
Keywords: e-wallet- intention to use- technology acceptance model
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| Corresponding Author (Lianna Wijaya)
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8 |
Computer Science |
ABS-95 |
Development of Android-Based Application (Limbahpedia) for Waste Recycling Verrel Aprilianto(a), Erick Gozali(a), Dewi Setyorini(a), Fidelson Tanzil(a*), Alvina Aulia(a), Felix Jingga(a)
a) Computer Science Department, School of Computer Science Bina Nusantara University, Jakarta, 11480, Indonesia
Abstract
The objective of this research is to produce an application that can provide information about waste categories and waste recycle, a reminder to the user to separate their waste by category, monitor information by category and weight of waste, and be able to input new waste and send it to waste management partners. This research has 2 research methods include analysis method and design method. The analysis method was conducted by a literature review, interview, and analysis of similar applications. The design method was conducted by communication, planning, modeling, construction, and deployment (Waterfall method). The evaluation used two approaches, those were five measurable human factors and user-interface evaluation. The result of this research conducted by distributing a questionnaire containing 12 questions to 51 users. The result of this research was the completion of the waste management application. It can be concluded, by using this application can help users to study and monitor their waste disposal and management.
Keywords: waste management-android application-waterfall method
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| Corresponding Author (Fidelson Tanzil)
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9 |
Computer Science |
ABS-98 |
Factor Customer Perception of Augmented Reality in Online Shopping: Systematic Literature Review Silviana Rani Hasna Putri*, Salma Lailatul Alifah, Alexander A S Gunawan
Computer Science Department, School of Computer Science, Bina Nusantara University, Jakarta, Indonesia 11480
*silviana.binus[at]binus.ac.id, salma.alifah[at]binus.ac.id, aagung[at]binus.edu
Abstract
Augmented reality implemented in online shopping as tools for helping customer to eliminates worries from product expectations. Customer perception of implemented augmented reality in online shopping can improve service quality and expectation for buying decision and loyalty. Previous researchers have attempted to examined customer perception of augmented reality in different kind of online shopping and the result are not consistent. Therefore, the purpose of this research is to perform a study on literature related to customer perception of augmented reality in different kind of online shopping and analyze the identified factors under different criteria. Accordingly, the researchers gathered studies related to augmented reality in online shopping between the period 2015 and 2020. The study identified thirty previous studies done by different researchers which revealed thirty-six different factors affecting customer perception in eleven different type of augmented reality that implemented in online shopping. Those thirty-six factors from eleven type implemented augmented reality analyze under different criteria and result presented that ^ease of use^ is the most frequently used factor followed by ^interactive and communicative^. Those result can be used by future researchers in their studies and be a consideration to improve customer perception which can lead to a variety of benefits.
Keywords: Augmented Reality (AR), Online Shopping, Customer Perception, E-commerce
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| Corresponding Author (Silviana Rani Hasna Putri)
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10 |
Computer Science |
ABS-104 |
Customer Churn Prediction in Telecommunication Company Dota Biomantoro, Gede Putra Kusuma*
Computer Science Department, BINUS Graduate Program - Master of Computer Science, Bina Nusantara University, Jakarta, Indonesia, 11480
*inegara[at]binus.edu
Abstract
Churn prediction methods are widely used to anticipate customer churn from services provided by a company for some reasons. This study aims to develop an optimal churn prediction model based on customer data from a telecommunication company in Indonesia. The model development and evaluation processes are performed by following the Cross-Industry Standard Process for Data Mining (CRISP-DM), which consist of business understanding, data understanding, data preparation, modelling, and evaluation. Various combination of data preparation and modelling methods have been evaluated. The evaluation results show that the combination of feature selection and prediction model yields better results compared to prediction model without feature selection. The highest accuracy is achieved by Random Forrest at 97.82%, which is followed by Decision Tree at 97.06%, and Naive Bayes at 90.62%. This result indicates that a prediction model can be reliably used to predict customer churn in a telecommunication company.
Keywords: Churn prediction- CRISP-DM framework- Feature selection- Prediction model- Parameter optimization
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| Corresponding Author (I Gede Putra Kusuma Negara)
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11 |
Computer Science |
ABS-107 |
Similarity Search on Southeast Asian Food Ingredients Using Association Rule Mining Boby Siswanto, Evawaty Tanuar, Yasi Dani, Maria E. E. Deanne
School of Computer Science, Bina Nusantara University
Jakarta, Indonesia
Abstract
Different kinds of data sources can be used for analysis- one of them is youtube. Youtube is a platform where users can share various information in video format. One of the content on youtube is cooking- many people shared how to cook and the recipe. This research aims to find the similarities of ingredients in Southeast Asia cuisine based on the YouTube video dataset. This research finding shows the similarity of several main ingredients from 999 collected data by implementing association rules mining algorithms. The research also able to find out that Myanmar, Indonesia, Brunei, and Vietnam have the highest similarity in the food ingredient compare to other countries. Therefore, for future development, it can be used to recommend the international cuisine recipe based on the ingredient
Keywords: Similarity Search, Food Ingredients, YouTube, Southeast Asia, Association Rule Mining
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| Corresponding Author (Boby Siswanto)
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12 |
Computer Science |
ABS-110 |
Controllable LED for Aquascape Environmental Treatment based on IoT Application Daniel Patricko Hutabarat*, Rudy Susanto, Jonathan Lukas
Computer Engineering Department, Faculty of Engineering
Bina Nusantara University, Jakarta, Indonesia, 11480
*Corresponding author: dhutabarat[at]binus.edu
Abstract
Aquascaping is an activity carried out in an aquarium to produce a beautiful work of art by arranging aquatic plants, rocks, driftwood, and other supporting components. Plants inside the aquarium need light to carry out photosynthesis. However, the light needed has certain parameters and quantities for each type of plants. If the light used is less than the needs of the plants, the plants will not grow up properly, however if the light given exceeds the ability of plants to absorb, algae will start to grow. In this study, LED devices that can emit the light needed by the plants will be developed. The light emitted by this device will be adjusted to the types of plants grown and the light around the aquarium environment. In this study, the system is developed based on IoT application so that the number of LED devices used in the system can be easily adjusted, operated and monitored by using the application developed. This will be used by users to choose the intensity of light that will be emitted by the device according to the type of plants grown in the aquarium. The LED device developed in this research is part of the research on the aquascape environmental treatment devices. The device developed has been successful in maintaining the light emitted according to the light needed by the plants with the accuracy is above 92.3% and maximum standard deviation of 2.32.
Keywords: Aquascape, Adaptive aquascape lighting, IoT Application
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| Corresponding Author (Daniel Patricko Hutabarat)
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13 |
Computer Science |
ABS-112 |
A Design for AI Machine Learning to Predict Economic Recession in Indonesia Umar Tsani Abdurrahman, Wilarso
Sekolah Tinggi Teknologi Muhammadiyah Cileungsi
Abstract
A recent rapid change in World Economic landscape due to Covid-19 pandemic has been given a wake-u call for economists and scientists to be able to predict an upcoming economic recession. Since country Gross Domestic Product (GDP) including Indonesia is measured quarterly then it is required that a team of professionals or a system be able to predict it in upcoming quarter economic performances. Unlike in developed countries especially in US, there is a proven forum called Survey of Professional Forecaster there which has provided a reliable quarterly economic forecast for the country for decades. Indonesia is still lack of dedicated professional to do such job except for a National Survey Agency (BPS) which is a governmental body which its job is to provide economic quarterly statistics and performances for the National government. There is only a handful of economists and university scholars who usually have their opinion and forecast for the late country economic progress. So it will be helpful if we can provide a second opinion using AI Technology especially machine learning (ML) to provide a simple prediction at first. Since this is our first attempt to develop macroeconomic predictors using Machine Learning, we are simplifying the economic parameters to only include GDP and Oil Prices since the data is readily available. Based on previous study for forecasting the American economic recession, we chose the same Machine Learning algorithm known as Random Forrest. And to simplify design implementation we are using latest open source technology in machine learning, TensorFlow 2.0 (TF 2.0). Since its first release TF 1.0 in 2016 TensorFlow has become popular ML engine and as per last update the random Forrest algorithm has been implemented on 2.0. The Python Economic Prediction scripts for TF2.0 implementation we developed are provide here. Since this is considered not a computationally intensive configuration due to the simplified parameters used, we are not using
Keywords: Tensorflow, Random Forest, Indonesia GDP, Economic, Forecast
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| Corresponding Author (Wilarso Arso)
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14 |
Computer Science |
ABS-120 |
Utilizing The Balance Scorecard Perpective to Drive The Performance of The Operational Expenditure System Denny Andwiyan - Erna Astriyani- Oleh Soleh- Ryanthika Serliyanthi Setyaningrum
Raharja University- Sains & Technology- Jl. Jenderal Sudirman No.40, RT.002/RW.006, Cikokol, Kec. Tangerang, Kota Tangerang, Banten 15117
Abstract
Information is a communication tool that is very important for everyone, including information related to monitoring operational expenditure systems. Because the finances issued or used must be well informed and accurate. In this case, in general the monitoring of the operational expenditure system in small and medium-sized companies still has many obstacles, where the obstacles that occur are usually the Technical Operators when submitting a letter of accountability still has a long stage, the input of reports is carried out one by one by an admin using Microsoft Excel and its reports are still tabular. So that the process of monitoring operational expenses takes a long time. And other obstacles, such as frequent errors in classifying the types of operational expenditures. In this research, the writer tries to analyze the use of Balanced Scorecard (BSC) analysis with 4 perspectives in it. The result of this research is the concept of utilization of the perspective Balance Scorecard to be able to encourage the performance of the organization / company in the operational expenditure system. So that the monitoring of the operational expenditure system does not require a long time and is efficient.
Keywords: Balance Scorecard- Performance- Operational- Expenses
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| Corresponding Author (Oleh Soleh)
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15 |
Computer Science |
ABS-123 |
The Collaboration in YouTube Channels to Enhance Viewers for Entertainment Among Popular YouTubers in Indonesia (Case Study: The Performance of a Private University Students^ Choices as YouTube Viewers for Popular YouTubers^ Collaboration) Murty Magda Pane (a*)- Johannes A.A. Rumeser (b)
a) Character Building Development Center, Faculty of Computing, Dept. of Computer Science, Bina Nusantara University.
Kampus Kijang, Jalan Kemanggisan Ilir III no. 45, Jakarta 11480, Indonesia
*murty.pane[at]binus.ac.id
b) Faculty of Humanities, Dept. Psychology, Bina Nusantara University.
Kampus Kijang, Jalan Kemanggisan Ilir III no. 45, Jakarta 11480, Indonesia
Abstract
This study aims to provide an overview of students^ choices about which Indonesian YouTubers to collaborate with amongst them. The research used qualitative method started with a survey in a population of YouTube viewers, especially on top ten popular YouTubers in Indonesia. An ordinary survey was conducted as the beginning of the implementation of this research, based on top ten YouTubers in Indonesia and followed by text analysis to analyze the description of their choices. The 49 respondents from diverse departments mostly chose DC Channel and MB Channel as a pair to collaborate. Most descriptions as the reason for both YouTubers to collaborate were because both have qualified contents, one in the area of discussing trending topics in the society while the other is very humourous. These factors have made the students curious about the performance how entertaining if they work together in the collaboration project for their YouTube channels. The results showed that the students need digital entertainment which is smart yet entertaining.
Keywords: Students^ choices- popular YouTubers- collaboration project- digital entertainment
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| Corresponding Author (Murty Magda Pane)
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16 |
Computer Science |
ABS-125 |
A Review for Palm Oil Fresh Fruit Bunch Ripeness Detection Methods Using Computer Vision Savant Benedict1, Ricky Candra1, Suharjito1,2, Novita Hanafiah2
1School of Computer Science, BINUS Graduate Program - Master of Computer Science, Bina Nusantara University, Jakarta, Indonesia 11480
2Computer Science Department, BINUS Online Learning, Bina Nusantara University, Jakarta, Indonesia 11480
Abstract
One of the determining factors for the quality of palm oil is the level of maturity of the oil palm fruit at harvest. There have been many studies to be able to help the process of determining the maturity of oil palm fruit when harvested. The approach that is often used in determining the level of maturity is based on the color of the fruit using a computer vision approach. There are still many challenges faced with this approach such as lighting, shooting angles, and characteristics of the oil palm fruit. This study aims to review several methods that have been used to determine the maturity of oil palm fruit in order to find out which methods and stages are most optimal to implement efficiently. The method used for this study using a systematic literature review approach. the data used is based on articles published in the last five years (2015 - 2020) from well-known databases such as IEEE, Elsevier, and Google Scholar. The results of this study indicate that the development of an oil palm fruit maturity detection model using machine learning and deep learning approaches produces good performance and tends to have a lot of research leading to the use of this approach. However, in this perspective, there are still some obstacles such as the need for a large enough dataset and a highly capable machine so that further research is needed so that we can get a deep learning model that is lightweight and can be implemented in mobile applications.
Keywords: Palm Oil Fresh Fruit Bunch- Ripeness Detection- Methods- Computer Vision- deep learning
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| Corresponding Author (Suharjito Suharjito)
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17 |
Computer Science |
ABS-127 |
Value Network and SWOT-Based Knowledge Management System on Information Technology Division of The Bank Maria Seraphina Astriani (a*), Indrajani (b)
a) Computer Science Department
Faculty of Computing and Media, Bina Nusantara University
Jakarta, Indonesia 11480
*seraphina[at]binus.ac.id
b) Information Systems Department, School of Information Systems, Bina Nusantara University
Jakarta, Indonesia 11480
indrajani[at]binus.ac.id
Abstract
Information Technology (IT) has been widely used by most companies to improve competitiveness in the business, especially banks. It even becomes a crucial pillar to support business activities and should be managed properly to keep the continuity of its services. To achieve excellent IT services, knowledge among employees in IT division are needed to leverage their skills and shared the same information among them. The targets of this research are to accommodate knowledge procurement tools to record the problems and update the solutions on the helpdesk module, add knowledge presentation for searching solutions feature on agent helpdesk, and library module. The implementation of Knowledge Management System (KMS) based on Value Network and Strength Weakness Opportunity Threats (SWOT) analysis is the answer that has been waiting for to solve the existing problems, especially for human resources which tends to be difficult to manage. This solution gives many great benefits to the company to store the knowledge as the important assets, improve the collaboration between employees, help to search the solution based on the problem, support self-learning culture, make the process easy to do the knowledge sharing and distribution, and facilitating the aspirations and ideas of the employees
Keywords: Bank- IT services- Knowledge Management System- Value Network- SWOT
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| Corresponding Author (Maria Seraphina Astriani)
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18 |
Computer Science |
ABS-128 |
A Review on Speech Emotion Recognition for General Cases and Indonesian Spoken Language Oscar Utomo Kumala, Amalia Zahra
Computer Science Department, BINUS Graduate Program
Master of Computer Science, Bina Nusantara University
Jakarta, Indonesia 11480
Abstract
Emotion recognition is one of many widely studied topics today. Emotions that come from speech can contain a lot information that can be used for many purposes. In this paper, a review is conducted on the studies and researches that have been done in Speech Emotion Recognition (SER) aspects. The important aspects are the speech features (acoustic, prosodic, lexical, linguistic, etc.), speech corpora (for training set and test set), and machine learning algorithms for classification. The review is conducted on the SER studies for general emotion recognition, and later focuses on the case of Indonesian spoken language. From the review, it can be seen that a feature selection method is mandatory in SER studies that involve a large number of speech features. Other findings are the importance of good speech corpus for better training set and test set, and ones of the best-performing machine learning classifier methods for most general cases are Support Vector Machine (SVM) and Extreme Learning Machine (ELM).
Keywords: speech emotion recognition, Indonesian spoken language, speech feature, machine learning
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| Corresponding Author (Amalia Zahra)
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19 |
Computer Science |
ABS-134 |
A Comparison of Machine Learning Methods on Intrusion Detection Systems for Internet of Things Anteng Widodo(1,4,*), Adi Wibowo(2), Budi Warsito(3)
1)Phd student of Doctor of Information System, School of Postgraduate Studies, Diponegoro University, Semarang, Indonesia
2)Department of Informatics, Faculty of Science and Mathematics, Diponegoro University, Semarang, Indonesia
3)Department of Statistics, Faculty of Science and Mathematics, Diponegoro University, Semarang, Indonesia
4)Department of Information System, Faculty of Engineering, Muria Kudus University, Gondangmanis, Bae, Kudus 59324, Indonesia
Abstract
In recent years, the internet of things is prevalent and widely used. The new problem with IoT is security, which needs to be considered carefully because of the technology heterogeneity. These threats can affect IoT performance- therefore, it is necessary for effective monitoring. This paper examines several machine learning methods in intrusion detection systems that possibly run on IoT. Random Forests and Decision Tree are employed in this study for performance comparison. The experimental results show that the Random Forest and Decision tree algorithms application produces good performance with a faster response time and possible running on IoT.
Keywords: Intrusion Detection Systems, Internet of Things, Machine learning
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| Corresponding Author (Anteng Widodo)
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20 |
Computer Science |
ABS-135 |
Bring Your Own Device (BYOD) Restaurant: Self-Service Dining Ordering System Maria Seraphina Astriani (a*), Dezza Rizqi (b), Andreas Kurniawan (a)
Computer Science Department
Faculty of Computing and Media, Bina Nusantara University
Jakarta, Indonesia 11480
*seraphina[at]binus.ac.id
I.T Department
PT. Teknologi Kupon Digital
Jakarta, Indonesia 10730
Abstract
The Coronavirus pandemic is a global health emergency. Strict health protocols are needed to prevent infection. Although many places have implemented lockdowns and restrictions on operating hours, there are still many people who want to be able to do their activities freely, the same as pre-pandemic. To minimize the risk of infection, the application of contactless habits is very crucial in this new adaptation era. The application of the Bring Your Own Device (BYOD) concept in restaurants is a solution to minimize the occurrence of contact on menu cards (printed or using the provided tablets - tabletop ordering systems) and reduce face-to-face contact with waiters when ordering food. A self-service dining ordering system using a web-based application allows customers to order from their own device (smartphone or tablet or laptop). BYOD concept helps companies to ensure mobility and flexibility in their work environment as an Information Technology (IT) policy providing self-service access. Technological developments and features of electronic devices make them an integral component of every aspect of daily activities.
Keywords: Web application- BYOD- dining ordering system-
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| Corresponding Author (Maria Seraphina Astriani)
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21 |
Computer Science |
ABS-136 |
Specify Project Requirement InTo Simplicity (SPIRITS): Freelance Marketplace Integrated with Web-Based Project Management Software Devin Christian, Maria Seraphina Astriani (*), Kevin Djoni, Steve Vinsensius Jo
Computer Science Department
Faculty of Computing and Media, Bina Nusantara University
Jakarta, Indonesia 11480
*seraphina[at]binus.ac.id
Abstract
The current condition of the freelance marketplace today is not catered for a specific specialty such as software engineer freelancers and project owners looking to hire software engineers. Moreover, they often face various difficulties relating to the job posting, user competencies registration, project monitoring issues, time management constraints, and complicated payment processes. Specify Project Requirement InTo Simplicity (SPIRITS), a freelance marketplace integrated with project management tools aim to address these problems and provide benefits for its users by providing a multi-functional platform.
Keywords: Freelance marketplace- Software engineer freelancers- Project owners- Project management system
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| Corresponding Author (Maria Seraphina Astriani)
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22 |
Computer Science |
ABS-145 |
Temperature Controller for Aquascape Environmental Treatment based on IoT Application Daniel Patricko Hutabarat*, Rudy Susanto
Bina Nusantara University
Computer Engineering Study Program
JL. KH. Syahdan No.9
dhutabarat[at]binus.edu
Abstract
Aquascaping is an art to form a natural aquatic environment in an aquarium by organizing aquatic plants, rocks, and driftwood. In aquascaping, we require a system that can maintain the aquascape environment for the plants to grow well. One thing that needs to be maintained in aquascape environment is the temperature required by plants. In this study, a system that consist of heater and fan cooler as the main devices will be developed to maintain the temperature. In this system an android smartphone application was also developed to help users adjust the required temperature for the aquacscape environment. The development of this system aims to provide appropriate temperature for specific types of plants used in the aquarium. The temperature controller system developed in this research is part of the research on the aquascape environmental treatment. The system developed has been successfully maintain the temperature according to the temperature needed by the plants with 100% successfully maintain the temperature within the range set up. The system being developed can also 100% successfully turn on / off the heater and fan cooler according to the specified settings.
Keywords: aquascape, Temperature Controller, ESP32, IoT application
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| Corresponding Author (Daniel Patricko Hutabarat)
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23 |
Computer Science |
ABS-148 |
Implementation of the naive Bayes method to tackle credit fraud at bank bjb, Rangkasbitung Branch, Banten Province Robby Rizky1,Adi Wibowo2,Budi Warsito
1 universitas matlaulanwar banten
2,3 universitas diponegoro
Abstract
Keywords: naivebayes,tackle credit,fraud,bank bjb,provinsi banten
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| Corresponding Author (Robby Rizky)
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24 |
Computer Science |
ABS-156 |
THE EFFECT OF ACCOUNTING INFORMATION SYSTEM OF SALES ON THE EFFECTIVENESS OF INTERNAL CONTROL IN SALES PT DUTA PUTRA LEXINDO (BOLESA) Meiryani, Gisela Gilberta, Risky Arshanty
Department of Accounting, Faculty of Economics and Communication, Bina Nusantara University, Jakarta, Indonesia,
Abstract
ABSTRACT
This goals to determine the effect of variable accounting information system of sales, cash receipts, and accounts receivable on the effectiveness of internal sales controls at PT Duta Putra Lexindo (BOLESA). The research method used is quantitative research methods with primary data obtained from questionnaire data which is measured using a Likert scale. In this study, there are accounting information system of sales (X1), cash receipts (X2), accounts receivable (X3) and effectiveness of internal sales controls (Y) as the dependent variable.
Keywords: Keyword : Accounting Information System of Sales, Cash Receipts, Accounts Receivable, Effectiveness of Internal Sales Controls
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| Corresponding Author (Gisela Gilberta)
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25 |
Computer Science |
ABS-183 |
Domain Knowledge Integration in Hierarchical Learning Model for Accurate Decision Support System Michael Siek
Business Information Systems Program, Information Systems Department, Faculty of Computing and Media, Bina Nusantara University Jakarta, Indonesia 11480
Abstract
In many applications of business, the models produced by computational intelligence algorithms can be quite complex that can capture a set of business processes. The complexity here is because the processes must be treated as multi-stationary ones. The model accuracy on predicting the low or high extremes are crucial in many business applications, like in predicting stock prices or predicting machine maintenance. In such cases, the usage of a global model for a complex process is certainly inadequate. One solution of this issue is to employ several models, each responsible on characterizing a certain sub-process. In hierarchical learning models, an upfront option to include a domain expert is to allow the experts to construct the splitting rules and perform the hard splits of the input space of the training data set. This technique enables the experts to determine split attributes and values in the upper nodes, and then the machine learning algorithm takes care of the rest of the hierarchical model construction. The domain expert is typically interested in defining the split parameters for the nodes of upper two levels of the hierarchical model, which are very essential because they affect the splitting decisions in the lower nodes and impact the performance of the overall model. In the problems of business problems, a more accurate characterization for the detailed behavior of the underlying business system can be expected by incorporating domain expert knowledge into hierarchical-based machine learning algorithm compared to the other standard machine learning models using ANNs or others. This modelling technique can be more suitable and trusted than the purely machine learning predictors or models.
Keywords: model tree algorithms, prior knowledge, multiple local models, decision support system
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| Corresponding Author (Michael Siek)
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26 |
Computer Science |
ABS-184 |
Benchmarking CPU vs. GPU Performance in Building Predictive LSTM Deep Learning Models Michael Siek
Business Information Systems Program, Information Systems Department, Faculty of Computing and Media, Bina Nusantara University, Jakarta, Indonesia 11480
Abstract
Constructing deep recurrent neural network (DRNN) models using back-propagation through time learning algorithm often requires intensive computation. The long short-term memory (LSTM) network as a variation of DRNN has solved the vanishing problem by enforcing constant in the gradient-based algorithm to transfer the error to the internal states of neurons, but not for exploding issue. Such instability in error back-propagated along deep neural network in time and its regularization problem could entail more computational time. Despite these issues, the LSTM network with deep learning has shown much promising results for classification and regression tasks in various applications, which many industries introduce novel AI-based processor products allowing for parallel computation, like Nvidia GPU with CUDA programming. This research aimed at benchmarking CPU vs GPU performance in building LSTM deep learning model for prediction. Several experiments were conducted to optimize hyper parameters, number of epochs, network size, learning rate and others for providing accurate predictive models as a decision support system. The modelling results indicate that the utilization of GPU in LSTM deep learning considerably outperforms the one using CPU.
Keywords: computational intelligence, dynamic neural network, predictive model, parallel computing
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| Corresponding Author (Michael Siek)
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27 |
Computer Science |
ABS-185 |
Investigating Inductive Miner and Fuzzy Miner in Automated Business Model Generation Michael Siek
Business Information Systems Program, Information Systems Department, Faculty of Computing and Media, Bina Nusantara University, Jakarta, Indonesia 11480
Abstract
In the rapid growth of the advanced technologies and digital business competitions, many enterprises must inevitably adopt the new technologies toward strong competitiveness in the changing market. In practice, the business transformation is not that easy to be implemented and this often modifies the current business processes dramatically. Along with these technology adoptions, there is an emerging research field so-called process mining that studies on the utilization of data science principles in business process generation, conformance checking, and bottleneck identification. This paper focuses on investigating the modelling results of inductive miner and fuzzy miner algorithms for automated business model generation from event log data. In relation to data-driven method, the business model generation using process mining could provide a soft adaptation of the new business process implementation in the enterprises through incremental and continuous improvements.
Keywords: business process model, Petri net, data mining, event log data, induction algorithms
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| Corresponding Author (Michael Siek)
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28 |
Education |
ABS-5 |
THE EFFECT OF HYPERCONTENT LEARNING RESOURCES AND CULTURAL AWARENESS ON STUDENT LEARNING OUTCOMES Herlina Herlina
Universitas Tadulako
Abstract
This study aims to determine the effect of hypercontent learning resources and cultural awareness on student learning outcomes. The research was conducted in grade IV SD Madani, Palu City, Central Sulawesi. Using a quantitative approach through the experimental method with a 2 x 2 factorial design, data analysis using 2-way ANOVA. The results showed that 1) there were differences in student learning outcomes using hyper content learning resources and students using online book learning resources- 2) there is an interaction between hypercontent learning resources and students^ cultural awareness- 3) the learning outcomes of students who have high cultural awareness using hypercontent learning resources are higher than students who have high cultural awareness and use online book learning resources- 4) The learning outcomes of students who have low cultural awareness who use online book learning resources are lower than students who have low cultural awareness who use hypercontent learning resources.
Keywords: learning resources- hypercontent- cultural awareness- online books
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| Corresponding Author (Herlina Herlina)
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29 |
Education |
ABS-11 |
The Effectiveness of Student Facilitator And Explaining (SFAE) Learning Models on Mathematics Learning Outcomes of Elementary School Arief Aulia Rahman(a*), Muhammad Yani(b), Nailul Authary(b), Nazariah(b), Muhsin(c)
a), STKIP Bina Bangsa Meulaboh, sirariefaulia[at]mail.com
b) Universitas Muhammadiyah Aceh, muhammad.yani[at]unmuha.ac.id
b) Universitas Muhammadiyah Aceh, nailul.authary[at]unmuha.ac.id
b) Universitas Muhammadiyah Aceh, Nazariah.amin[at]gmail.com
c) Universitas Jabal Ghafur, muhsinbrhm4[at]gmail.com
Abstract
Optimal student learning outcomes also depend on student learning and teacher teaching. The low learning outcomes of Mathematics in grade V SDN Aceh Barat, shown in the test scores of some students still have not reached the minimum completeness criteria standard (CCS). The predetermined CCS score limit is 70. The purpose of this study was to determine the effectiveness of the Student Facilitator And Explaining (SFAE) learning model on the mathematics learning outcomes of grade V SDN Aceh Barat. This type of research is quantitative research. Using purposive sampling in order to obtain a sample of 20 students. The data collection techniques used were tests and observations. Based on the results of the research shows that the percentage of student learning completeness after the application of the Student Facilitator And Explaining (SFAE) learning model is 85% or 17 students who have completed, while those who are not complete are only 3 students or 15% with the average score of students obtained is 77.25. Thus it can be concluded that the application of the Student Facilitator And Explaining (SFAE) learning model is effective on mathematics learning outcomes in grade V SDN Aceh Barat.
Keywords: Effectiveness- Student Facilitator And Explaining (SFAE)- Mathematics Learning Outcomes
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| Corresponding Author (Arief Aulia Rahman)
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30 |
Education |
ABS-12 |
The Role of Parents in Fostering National Character in Early Childhood During the Covid-19 Pandemic Anita Febiyanti (a*), Euis Kurniati (b), Maya lestari (c) Vina Adriany (d)
Universitas Pendidikan Indonesia
Abstract
August 17 is a day full of gratitude and joy for all Indonesian people because it is the independence day of the Indonesian people. Independence is closely related to nationalism and national character, which of course must be absorbed by all Indonesian people, both youth and elder. Parents have an important role in instilling a national character so that the next generation of the nation can become smart, responsible, and beneficial citizens of many people. Based on the available literature, this paper aims to see the importance of national character being introduced from an early age. The author reviews some literature related to the national character of children and conducts a case study by interviewing two mothers and two fathers of early childhood. The main result of this paper is to discuss what things parents can do to stimulate the national character of their children during a pandemic like this.
Keywords: national character, early childhood, pandemic period
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| Corresponding Author (Anita Febiyanti)
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