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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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Optimization of Personal Protective Equipment Distribution Costs to Health Centers with Stepping Stone Method Arief Budi Nugroho; Meinarini Catur Utami; Suryo Santoso Putro
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.
Redesigning UI/UX of A Mobile Application Using Task Centered System Design Approach Mugi Praseptiawan; Meida Cahyo Untoro; Feri Fahrianto; Pungki Resti Prabandari; M. Syamsuddin Wisnubroto
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.v6i1.24665

Abstract

Digital transformation requires a software system development method to identify and analyze user needs. In this research, software system development uses the Task Centered System Design framework with several stages, including identification, needs analysis, design, and evaluation. The identification stage is carried out by conducting interviews with stakeholders, and then the results of the interviews are analyzed and approved by stakeholders. This study aims to obtain user needs to build an application interface by applying the steps of the Task Centered System Design method and usability evaluation and calculating the weight of the feasibility value by testing the Heuristics method and System Usability Scale on the solution application design. The evaluation phase aims to determine the value of the usability problem in the design that has been designed. The evaluation phase uses the Usability Heuristic method by involving experts in the field of software development and the System Usability Scale method involving end users. After conducting research from the identification to the evaluation stage, the average severity rating of the Heuristic Usability test component scored less than 1 (one) in the second iteration, and the System Usability Scale results scored 70.3 for admin and 73.75 for the customer application. This result is in grade C with an adjective rating of Good.  
Water Quality Assessment of Remote Sensing Techniques: A Comparative Insight Between Yangtze of China and Porong of Indonesia
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.v6i2.31386

Abstract

The river water quality, exceptionally the total suspended solid (TSS) in China and Indonesia, has deteriorated due to human activities. Remote sensing makes it easier for observers to monitor river water quality, especially TSS. However, measuring the river water quality by remote sensing is still in the model and algorithm development stage in China and Indonesia. This study aims to identify the river water quality on remote sensing in China's Yangtze River and Porong River, East Java, Indonesia, and to analyze comparisons of river water quality on remote sensing in Yangtze River, China, and Porong River, East Java, Indonesia. This method uses a literature review based on journals, articles, and primary sources to review related literature on TSS concentrations in rivers and remote sensing in China and Indonesia. River water monitoring methods can measure the TSS in China and Indonesia using remote sensing. Many water quality models for waterways are based on different satellite images. In the Yangtze Downstream River, the algorithm of TSS uses the latest random forest on Landsat-8. The algorithm of TSS in the Porong River estuary used linear regression on sentinel-2 imagery. These TSS algorithms can more precisely assess TSS in water quality for scientific studies. The results show that the latest random forest is a more precise remote sensing algorithm in China than Linear regression in Indonesia. The suspended solid models and remote sensing images such as China's MODIS, Landsat-8, and MERIS are accurate in China. Therefore, developing more precise remote sensing techniques, total suspended solid models composed of Wiggin's Algorithm and Markert Algorithm, NDWI Algorithm, and remote sensing imagery such as Sentinel-2 and Landsat-8 in Indonesia is crucial to determine total suspended solids. The researchers additionally contribute to advanced research toward advancing suitable remote sensing techniques in various areas in Indonesia.
Analysis of the Use of Artificial Neural Network Models in Predicting Bitcoin Prices Muhammad Sahi; Muhammad Faisal; Yunifa Miftachul Arif; Cahyo Crysdian
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%.
Non-Rating Recommender System for Choosing Tourist Destinations Using Artificial Neural Network Yunifa Miftachul Arif; Dyah Wardani; Hani Nurhayati; Norizan Mat Diah
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%.
User Satisfaction on Academic Information System in UIN KH Abdurrahman Wahid Pekalongan Alvita Tyas Dwi Aryani; Ahmad Rosyid; Bill Pangayow
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.
Implementation Chatbot for SMEs Using Artificial Intelligence Markup Language to Improve Customer Integration and Business Performance Lena Magdalena
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 Md. Jahurul Islam; M. Mesbahuddin Sarker; Taslim Taher
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.
Mask Detection App Uses Haar Cascade and Convolutional Neural Network to Alert Comply with Health Protocols Cahya Rahmad; Nurfaidah Nurfaidah; Supriatna Adhisuwignjo; Mamluatul Hani’ah
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.
Analysis of the Effect of Liquidity, Profitability, and Debt to Equity Ratio (DER) on Firm Value in Mining Companies Listed on the Indonesia Stock Exchange Masno Marjohan; Hadi Supratikta; Hilya Hasanah
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.v6i2.34423

Abstract

Firm value is the view of investors when measuring the success rate of a company. ROE is the variable most strongly associated with firm value to calculate the profit level of a company. Liquidity is a ratio to measure the company's ability to meet its short-term obligations. DER is a ratio used to assess debt against equity. The purpose of this study is to analyze the effect of liquidity (CR) on company value, profitability (ROE), and debt-to-equity ratio (DER) on company value and simultaneously in mining companies in the metal and mineral sub-sector listed on the Indonesia Stock Exchange for the period 2012–2021. This type of research is quantitative. The population in this study are mining companies listed on the Indonesia Stock Exchange. Samples were taken from 4 companies that met the criteria, with 10 years of observation totaling 40 sample units. The sampling technique used is the purposive sampling method. Data is downloaded via the website www.idx.co.id and the company's website. Data analysis uses descriptive analysis, the classical assumption test, regression analysis, hypothesis testing, and the determination coefficient test. The results of the study based on statistical calculations obtained simultaneous results that financial performance has no effect on the value of the company, while partial liquidity (CR) debt on equity (DER) has no effect on the value of the company, and profitability (ROE) significantly affects the value of the company.

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