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Department of Information System, Faculty of Science and Technology, Universitas Islam Negeri Syarif Hidayatullah Jakarta Jl. Ir. H. Juanda No.95, Cempaka Putih, Ciputat Timur. Kota Tangerang Selatan, Banten 15412
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Applied Information System and Management
Published by Universitas Islam Negeri Syarif Hidayatullah Jakarta
ISSN : 26212536     EISSN : 26212544     DOI : 10.15408/aism
Core Subject : Education,
Languange, Linguistic, Communication & Media
Arjuna Subject : -
Articles 227 Documents
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The Comparison of Sentiment Analysis of Moon Knight Movie Reviews between Multinomial Naive Bayes and Support Vector Machine Ajhari, Abdul Azzam
Applied Information System and Management (AISM) Vol. 6 No. 1 (2023): Applied Information System and Management (AISM)
Publisher : Depart. of Information Systems, FST, UIN Syarif Hidayatullah Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/aism.v6i1.26045

Abstract

Online movie streaming platforms have changed the current pattern of watching movies. Besides providing convenience in watching anywhere and anytime, this service is provided at a lower cost to moviegoers. The increase in moviegoers on online streaming platforms has resulted in easy-to-find reviews. This review can determine whether they decide to watch the film or not. The moviegoers' reviews can be easily and quickly found for analysis using sentiment analysis to find a film's worthiness. This study used sentiment analysis in classifying Twitter data predictions using the Multinomial Naive Bayes (MNB) and Support Vector Machine (SVM). In the sentiment analysis of labeling with positive and negative categories, a distilled version of BERT (DistilBERT) was used in this study. With a little human assistance in preprocessing, the model worked objectively with an overall accuracy performance on the confusion matrix of 64.50% for the Multinomial Naive Bayes model and 64.12% for the Support Vector Machine model. Performance evaluation was also carried out by calculating the cross-validation accuracy, which resulted in an accuracy of 72.38% for the MNB. Meanwhile, the SVM model obtained an accuracy of 70.19%.
Non-Rating Recommender System for Choosing Tourist Destinations Using Artificial Neural Network Arif, Yunifa Miftachul; Wardani, Dyah; Nurhayati, Hani; Diah, Norizan Mat
Applied Information System and Management (AISM) Vol. 6 No. 2 (2023): Applied Information System and Management (AISM)
Publisher : Depart. of Information Systems, FST, UIN Syarif Hidayatullah Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/aism.v6i2.26741

Abstract

The development of tourist destinations in Batu City makes it hard for the tourists to decide their destinations. The recommender system is a solution that provides a lot of information or tourist attraction data. Collaborative filtering is often used in recommender systems. However, it has drawbacks; one of which is the cold-start problem, where the system cannot recommend items to new users. It was caused by the new user who had no history of rating on any item, or the system had no information. This study aims to apply a non-rated travel destination recommendation system to address the cold-start problem for new users. We use a multi-layer perceptron or artificial neural networks to overcome the problem by training user preference data to produce high training accuracy. Based on four experiments in the training data, the network architecture shows 5 – 7 – 5 – 3 –14, which is the highest accuracy. The architecture uses five variables as inputs and three hidden layers, with each layer was activated using the ReLU activation function. The output layer produces 14 binary outputs and is activated using the sigmoid activation function. The system can give recommendations to new users using feedforward from test data with updated values in weights and biases. The test results from 46 test data showed an accuracy of 67.235%.
Analysis of the Use of Artificial Neural Network Models in Predicting Bitcoin Prices Sahi, Muhammad; Faisal, Muhammad; Arif, Yunifa Miftachul; Crysdian, Cahyo
Applied Information System and Management (AISM) Vol. 6 No. 2 (2023): Applied Information System and Management (AISM)
Publisher : Depart. of Information Systems, FST, UIN Syarif Hidayatullah Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/aism.v6i2.29648

Abstract

Bitcoin is one of the fastest-growing digital currencies or cryptocurrencies in the world. However, the highly volatile Bitcoin price poses a very extreme risk for traders investing in cryptocurrencies, especially Bitcoin. To anticipate these risks, a prediction system is needed to predict the fluctuations in cryptocurrency prices. Artificial Neural Network (ANN) is a relatively new model discovered and can solve many complex problems because the way it works mimics human nerve cells. ANN has the advantage of being able to describe both linear and non-linear models with a fairly wide range. This research aims to determine the best performance and level of accuracy of the ANN model using the Back-Propagation Neural Network (BPNN) algorithm in predicting Bitcoin prices. This study uses Bitcoin price data for the period 2020 to 2023 taken from the CoinDesk market. The results of this study indicate that the ANN model produces the best performance in the form of four input nodes, 12 hidden nodes, and one output node (4-12-1) with an accuracy rate of around 3.0617175%.
Optimization of Personal Protective Equipment Distribution Costs to Health Centers with Stepping Stone Method Nugroho, Arief Budi; Utami, Meinarini Catur; Putro, Suryo Santoso
Applied Information System and Management (AISM) Vol. 6 No. 1 (2023): Applied Information System and Management (AISM)
Publisher : Depart. of Information Systems, FST, UIN Syarif Hidayatullah Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/aism.v6i1.29753

Abstract

This study aims to apply the Stepping Stone transportation method to optimize transportation costs for sending personal protective equipment (PPE) to thirteen health centers in Pamekasan. The method used is the Stepping Stone transportation method because it can manage the distribution of several warehouses that provide products to be sent to places in need optimally, which was previously a problem due to the length of time for sending medicines and PPE to each health centre and shipping operational costs are increasing because the distance of each warehouse to each health centre in each sub-district is very influential for cost as well as time. Based on the results of transportation simulations with this method, the results of the distribution cost of PPE delivery to each health centre in Pamekasan were obtained with distribution to Pamekasan warehouses of 30,000 units, Pakong warehouses of 15,000 units, Tlanakan warehouses of 10,000 units, and Pasean warehouses of 19,500 units, with optimal costs of IDR 37,000,000. The contribution of this research can be used by the Pamekasan District Health Office as an alternative policy for distributing PPE to each health centre in Pamekasan at an optimal cost.
Classification of Sign Language in Real Time Using Convolutional Neural Network Tamam, Moh. Badri; Hozairi, Hozairi; Walid, Miftahul; Bernardo, Januario Freitas Araujo
Applied Information System and Management (AISM) Vol. 6 No. 1 (2023): Applied Information System and Management (AISM)
Publisher : Depart. of Information Systems, FST, UIN Syarif Hidayatullah Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/aism.v6i1.29820

Abstract

Communication between people is essential for daily life activities. However, humans are created with their own strengths and weaknesses. One of them is the difficulty of communication and interaction for people with hearing and speech impairments. Sign language is a language for people who have difficulty hearing and speaking. However, sign language is not popular in society, and people who have it will have more difficulties. This research aims to classify hand gestures of sign language into letters using a convolutional neural network (CNN). The dataset is obtained from Kaggle, with a total of 34,627 data divided by the ratio of training and testing data of 80:20. From the test results, the letters of the alphabet that can be translated are: A, B, C, D, E, F, G, H, I, J, K, L, M, N, O, P, Q, S, T, U, V, W, X, Y, and Z. Furthermore, validation accuracy is obtained. In this study, a very high validation accuracy was obtained. The easiest letters to guess are V and N, while the most difficult letters to guess are n, c, j, and z. With different preprocessing, the loss value can be reduced, giving a higher accuracy of 95.4%.
TOE Framework for E-Commerce Adoption by MSMEs during The COVID-19 Pandemic: Can Trust Moderate? Religia, Yoga; Ekhsan, Muhamad; Huda, Miftakul; Fitriyanto, Anton Dwi
Applied Information System and Management (AISM) Vol. 6 No. 1 (2023): Applied Information System and Management (AISM)
Publisher : Depart. of Information Systems, FST, UIN Syarif Hidayatullah Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/aism.v6i1.30954

Abstract

Currently, there are still many MSMEs in the regions that have not been connected to the digital ecosystem. This results in limited market reach, a lack of visibility, a lack of operational efficiency, and difficulty competing in the digital market. The purpose of this study is to review the adoption of e-commerce among MSMEs during the COVID-19 pandemic within the scope of the organization. Integrating the TOE framework (technology, organization, environment) with trust is carried out to explain the key parameters behind the adoption of e-commerce by MSMEs. This study collected samples using a saturated sample technique from 181 people who were members of the population. There were 153 questionnaires that were returned in full for further analysis using SEM-PLS modeling. The test results showed that technology did not have a significant influence on the adoption of e-commerce. Organizations, the environment during the pandemic, and trust have had a significant influence on the adoption of e-commerce. In addition, organizations that are moderated by trust have no significant effect on e-commerce adoption. The role of trust is as a moderation predictor. This research shows that the TOE framework is still strong enough to be used in explaining the adoption of e-commerce by MSMEs. This research also expands the TOE framework, where trust can also influence MSMEs to adopt e-commerce. Researchers and managers can use the set of variables that have been identified to strategize the adoption of e-commerce by MSMEs. This study presents a series of variables that can be used to study the adoption of e-commerce by MSMEs in the future.
User Satisfaction on Academic Information System in UIN KH Abdurrahman Wahid Pekalongan Aryani, Alvita Tyas Dwi; Rosyid, Ahmad; Pangayow, Bill
Applied Information System and Management (AISM) Vol. 6 No. 2 (2023): Applied Information System and Management (AISM)
Publisher : Depart. of Information Systems, FST, UIN Syarif Hidayatullah Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/aism.v6i2.31245

Abstract

The aim of this research is to evaluate the satisfaction level of students, lecturers, and educational staff towards the integrated academic information system, Sistem Informasi Akademik Terpadu (SIKADU), at UIN KH Abdurrahman Wahid Pekalongan, and to test whether there are any differences in satisfaction levels among these three groups. Additionally, this study aims to identify any issues encountered by users while utilizing it. The population for this research consists of users of SIKADU in UIN KH Abdurrahman Wahid Pekalongan. A convenience sampling technique was employed, and 162 respondents were selected as the sample. The data was analyzed using descriptive statistics, Kruskal Wallis and Cronbach's alpha test. The findings revealed that (1) there are significant differences in satisfaction levels among these three groups (2) 61.8% of the respondents were satisfied with the performance of SIKADU (3) only 17.3% of respondents accessed SIKADU on a daily basis (4) the majority of respondents (67.3%) accessed SIKADU through their mobile phones while at home (5) all dimensions of satisfaction measurement were deemed valid and reliable (6) the primary obstacles faced by the academic community were related to inputting data during course input and downloading scoring forms using SIKADU.
Mask Detection App Uses Haar Cascade and Convolutional Neural Network to Alert Comply with Health Protocols Rahmad, Cahya; Nurfaidah, Nurfaidah; Adhisuwignjo, Supriatna; Hani’ah, Mamluatul
Applied Information System and Management (AISM) Vol. 6 No. 2 (2023): Applied Information System and Management (AISM)
Publisher : Depart. of Information Systems, FST, UIN Syarif Hidayatullah Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/aism.v6i2.31396

Abstract

This study aims to identify the face of a person whether wearing a mask or not wearing a mask accompanied by an appeal to the importance of wearing a mask. The contribution of this paper to science is to provide an overview of the results of accuracy, precision, recall used by the method used with data that can be accessed by many people, so that it can be developed further or can be compared. This system uses two techniques, namely the classification of whether a person is wearing a mask or not using the Convolutional Neural Network (CNN) model. The architecture used is DenseNet-12 to detect human face objects. The data used has a total of 2332 data sets, 200 of which were retrieved manually as research objects, and the rest were obtained from Kaggle. All data is evaluated using the camera in real-time. The test results show that testing scenario one has the highest score with an accuracy of 85% while testing scenario two gets results of 80%, the precision value in testing scenario one gets results of 75%, and testing scenario two has results of 88%. Scenarios 1 and 2 also have the same recall value of 100%. Based on the data analysis, it can be concluded that the use of the Haar Cascade approach and the Convolutional Neural Network with the DenseNet-121 architecture produces good performance in the case of real-time detection of masked and non-masked facial objects.
Implementation Chatbot for SMEs Using Artificial Intelligence Markup Language to Improve Customer Integration and Business Performance Magdalena, Lena
Applied Information System and Management (AISM) Vol. 6 No. 2 (2023): Applied Information System and Management (AISM)
Publisher : Depart. of Information Systems, FST, UIN Syarif Hidayatullah Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/aism.v6i2.31847

Abstract

Chatbots have been extensively adopted to produce more positive customer experiences as customers now spend more time in digital surroundings. Despite the technological advancement and benefits of chatbots for client service, exploration of chatbot operations for small and medium-sized enterprises (SMEs) is limited. The absence of exploration explaining the struggles faced by SMEs contributes to the gap in SMEs’ chatbot adoption. This exploration determines the features and rudiments that fit with SMEs’ characteristics and their guests' interactions with chatbots. A mixed-methods approach is used to understand SMEs’ needs. The first study uses interviews with SME business owners and their customers in order to explore the features that chatbots should offer for SME by identifying combinations between chatbots' generic features and SMEs' customer characteristics. The second study tests features identified in SMEs customers to empirically test featured chatbots’ influence on anthropomorphism, perceived enjoyment, perceived ease of use, perceived usefulness, and how they affect SMEs’ customer intentions to use chatbots and their shopping intentions. This paper contributes to the emerging service literature on the use of chatbots for service interactions, particularly for SMEs using Artificial Intelligence Markup Language. The data that has been obtained was analyzed using a Likert scale. As a result, the accuracy of using Artificial Intelligence Markup Language is 84.8%.
Dotriacontal Number System in Computer and Error Detection Islam, Md. Jahurul; Sarker, M. Mesbahuddin; Taher, Taslim
Applied Information System and Management (AISM) Vol. 6 No. 2 (2023): Applied Information System and Management (AISM)
Publisher : Depart. of Information Systems, FST, UIN Syarif Hidayatullah Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/aism.v6i2.33291

Abstract

n this this paper for the first time, we have formulated the dotriacontal number system using existing number systems like binary, and hexadecimal numbers. The dotriacontal number is one with a base of 32, containing 32 single-character digits or symbols. Each symbol contains five binary digits. This number system can be used in computers for reducing memory consumption and for memory specification. Generally, the computer memory addresses are displayed in five hexadecimal integers. If the computer memory addresses can be showed in four dotriacontal integers rather of five hexadecimal integers, the memory consumption will be reduced. It also can be used to increase the number of MAC addresses, IPv4 and IPv6 addresses. MAC (Media Access Control) address can be constructed as six deckles or 12 integers of the dotriacontal numbers instead of six octet hexadecimal digits. The IPv4 address can be defined in 8 integers of dotriacontal number that is 240 that is 1099511627776 address, and also the IPv6 address can be designed in 32 digits of the dotriacontal number that is 2160 or 1.46150164E48 addresses. The dotriacontal number system can be effective to detect error message using the checksum method. Typically, the checksum method is used by a binary or hexadecimal number system but the checksum method can be easily applied in the dotriacontal number system to detect error messages. The proposed work of this paper will be implemented if the dotriacontal code is executed and the memory specification is defined as a 10 bits deckle system instead of 8 bits byte.

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