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The IJICS (International Journal of Informatics and Computer Science)
Published by Sekolah Tinggi Manajemen Informatika dan Komputer Budi Darma
ISSN : 25488449     EISSN : 25488384     DOI : https://doi.org/10.30865/ijics
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering
The The IJICS (International Journal of Informatics and Computer Science) covers the whole spectrum of intelligent informatics, which includes, but is not limited to : • Artificial Immune Systems, Ant Colonies, and Swarm Intelligence • Autonomous Agents and Multi-Agent Systems • Bayesian Networks and Probabilistic Reasoning • Biologically Inspired Intelligence • Brain-Computer Interfacing • Business Intelligence • Chaos theory and intelligent control systems • Clustering and Data Analysis • Complex Systems and Applications • Computational Intelligence and Soft Computing • Cognitive systems • Distributed Intelligent Systems • Database Management and Information Retrieval • Evolutionary computation and DNA/cellular/molecular computing • Expert Systems • Fault detection, fault analysis and diagnostics • Fusion of Neural Networks and Fuzzy Systems • Green and Renewable Energy Systems • Human Interface, Human-Computer Interaction, Human Information Processing • Hybrid and Distributed Algorithms • High Performance Computing • Information storage, security, integrity, privacy and trust • Image and Speech Signal Processing • Knowledge Based Systems, Knowledge Networks • Knowledge discovery and ontology engineering • Machine Learning, Reinforcement Learning • Memetic Computing • Multimedia and Applications • Networked Control Systems • Neural Networks and Applications • Natural Language Processing • Optimization and Decision Making • Pattern Classification, Recognition, speech recognition and synthesis • Robotic Intelligence • Rough sets and granular computing • Robustness Analysis • Self-Organizing Systems • Social Intelligence • Soft computing in P2P, Grid, Cloud and Internet Computing Technologies • Stochastic systems • Support Vector Machines • Ubiquitous, grid and high performance computing • Virtual Reality in Engineering Applications • Web and mobile Intelligence, and Big Data
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 6 Documents
 1 
Search results for , issue "Vol 6, No 2 (2022): July 2022" : 6 Documents clear
Debtors Prospective Assessment Application using Naive Bayes at Mitra Sejahtera Cooperative Indra Griha Tofik Isa; Beni Junedi
The IJICS (International Journal of Informatics and Computer Science) Vol 6, No 2 (2022): July 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/ijics.v6i2.3990

Abstract

Utilization of historical data into new knowledge can increase added value for its users, including Mitra Setia Cooperative (KMS) which has debtor data that is not utilized. “Not Paid Off” potentioal of debtors cannot be detected as early as possible. In this study using the Naive Bayes algorithm in classifying the feasibility of prospective debtors based on the classification of "Paid Off" and "Not Paid Off" based on parameter of Age, Sex, Amount of Loan, Occupation, Income, and Repayment Period. The research stages consist of (1) Research Initiation, (2) Data Selection, (3) Data Preprocessing, (4) System Design, (5) Program Implementation and (6) Program Testing. The purpose of this study is to minimize the increase in bad loans by implementing the Naive Bayes method in the application of the assessment of prospective debtors. The final result is a debtors prospective assessment application at Mitra Sejahtera Cooperative with an accuracy rate of 86%
Google Data Studio Implementation for Visualizing West Java Province Toddler Stunting Data Muhammad Rizqi Sholahuddin; Firas Atqiya; Husna Faridah; Nuri Nurianti
The IJICS (International Journal of Informatics and Computer Science) Vol 6, No 2 (2022): July 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/ijics.v6i2.4696

Abstract

One of the world's most critical nutritional issues, stunting is particularly prevalent in impoverished and emerging nations, including Indonesia. West Java is one of the provinces having a relatively high proportion of children with stunted growth. This study intends to conduct data visualization about the number of stunted children under the age of five in each West Java city or district. The data visualization is an interactive dashboard with several interconnected charts that was created using Google Data Studio. This is intended to aid the analysis of the distribution of stunting among children under the age of five in West Java by city and district from 2014 to 2021. Open Data Jabar is the source of the data used to create the visualization of data on toddlers with stunting in West Java. The result of this research is a dashboard that can be facilitate data analysis process. From the dashboard, we can determine that the total number of cases of toddler stunting in West Java reduced between 2014 and 2021. Despite an increase in the number of instances between 2019 and 2020, the number of cases has reduced again in 2021
Identification of Resistor Types Using Extreme Learning Machine Algorithms and Morphological Operation Rini Nuraini
The IJICS (International Journal of Informatics and Computer Science) Vol 6, No 2 (2022): July 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/ijics.v6i2.4499

Abstract

Electronic components are the basic elements to form a series of electronic devices that are usually used in everyday life. For someone who studies the field of electricity, knowledge of electrical components is an important thing. One of the components whose use is most often found in electronic circuits is a resistor. However, some people do not know about these types of resistors. Especially for someone or a student who will learn about electronic components. This study aims to develop an image processing system that can identify transistor type images using the Extreme Learning Machine (ELM) algorithm. This algorithm performs integrated learning through a special form of feedforward perceptron which has one hidden layer. In order for the ELM algorithm to work properly, information about the features contained in the object to be identified is needed. So, in this study the ELM algorithm is combined with morphological characteristics through parameters such as area, perimeter, eccentricity, major axis length, and minor axis length. Based on these parameters, features will be obtained which will be input in the identification process. At the evaluation stage, the precision value was 87%, recall was 84.47% and accuracy was 85.5%.
Multi-Criteria Decision Making Using Additive Ratio Assessment in Digital Voice Recorder Selection System Nurhasan Nugroho
The IJICS (International Journal of Informatics and Computer Science) Vol 6, No 2 (2022): July 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/ijics.v6i2.4686

Abstract

Digital Voice Recorder has many uses, usually used for interviews, recording voices and songs, recording meeting results, and can be used for learning. Currently, various Digital Voice Recorder products have been circulating and have different functions and specifications that are created according to the needs of users. For this reason, users must be observant in choosing a Digital Voice Recorder to support their work. So, we need a system that can provide recommendations and help in making decisions to choose the right Digital Voice Recorder. This study aims to develop a decision support system with Multiple Criteria Decision Making (MCDM) using Additive Ratio Assessment (ARAS) to assist in selecting a Digital Voice Recorder, so that it can assist in selecting the best solution appropriately and according to user needs. The ARAS method is used as a model that can select the best alternative based on the utility level of each alternative to determine the best alternative. Based on the case studies conducted, the utility values of each alternative were obtained, namely: Zoom Handy Recorder with a value of 0.5672, Sony PX470 with a value of 0.6147, Ruizu X52 with a value of 0.4664 and Tascam DR-22ML with a value of 0.9096. So, the best alternative is the Tascam DR-22ML. Based on testing through the black-box testing method, it shows that the system built has been running well
Comparison of Apriori, Apriori-TID and FP-Growth Algorithms in Market Basket Analysis at Grocery Stores Andi Ilhamsyah Idris; Eliyah A M Sampetoding; Valian Yoga Pudya Ardhana; Irene Maritsa; Adrisumatri Sakri; Hidayatullah Ruslan; Esther Sanda Manapa
The IJICS (International Journal of Informatics and Computer Science) Vol 6, No 2 (2022): July 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/ijics.v6i2.4535

Abstract

Market Basket Analysis is an analysis of consumer behavior specifically from a certain group/group. Market Basket Analysis is generally used as a starting point for seeking knowledge from a data transaction when we do not know what specific pattern we are looking for. Market Basket Analysis in this study is applied to the search for patterns of purchasing groceries at grocery stores and then analyzed by season. This study aims to compare the Apriori, Apriori TID and FP-Growth methods in determining consumer transaction behavior and calculating the quantity of consumer transactions in several seasons based on data obtained from the Market Basket Analysis database. In the results of this study, it is known that FP-Growth has the best performance among the other two algorithms, but uses more memory than other algorithms. The Apriori-TID algorithm uses lighter and faster memory than the Apriori Algorithm
Analysis and Identification of International Tourist Visits to Indonesia Based on Data Warehouse Implementation Indira Septianita Larasati; Valian Yoga Pudya Ardhana; Alika Oktaviani; Yulita Sirinti Pongtambing; Eliyah A M Sampetoding; Lopinta Sarungallo; Rahmi Rahmi
The IJICS (International Journal of Informatics and Computer Science) Vol 6, No 2 (2022): July 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/ijics.v6i2.4537

Abstract

Foreign tourist visits to Indonesia play an important role in the economic growth of the tourism sector. In increasing the interest of visitors, development resources are needed as a tourism sector. The development carried out must be carried out optimally with the growth trend of tourist visits so that development is right on target, effective and efficient. This study aims to visit foreign tourists to Indonesia using the implementation of a data warehouse. The dataset used is data on foreign tourist arrivals by nationality in 2021 sourced from the Central Statistics Agency (BPS). This is done to determine the interest and potential of tourism to support the country's economy. The steps taken in this analysis and identification are Choosing the Process, Choosing the Grain, Identifying and confirming the dimension, Choosing The Facts, Rounding out the dimension table, Choosing the duration of database, Tracking Slowly changing Dimensions, Deciding the query priorities and the query mode, and the last Storing pre-calculation in the fact information. The result can be seen Foreign Tourism Visits in Indonesia using the Application of OLAP Data Warehouse for analysis. So that in 2021 it can be analyzed that monthly tourist visits tend to be stable with the periods of July-August and January-December increasing. These results in the future can be used as a policy reference in increasing tourist visits to foreign tourist targets in certain countries. This is done to determine the interest and potential of tourism to support the country's economy through the tourism sector

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