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Edi Sutoyo
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journalijadis@gmail.com
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Indonesian Scientific Journal (Jurnal Ilmiah Indonesia) Jl. Pasar Atas No 3, Kompleks Setramas Kota Cimahi, Bandung
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International Journal of Advances in Data and Information Systems
Published by Indonesian Scientific Journal
ISSN : -     EISSN : 27213056     DOI : https://doi.org/10.25008/ijadis
Core Subject : Science, Engineering,
Computer Science & IT Electrical & Electronics Engineering
International Journal of Advances in Data and Information Systems (IJADIS) (e-ISSN: 2721-3056) is a peer-reviewed journal in the field of data science and information system that is published twice a year; scheduled in April and October. The journal is published for those who wish to share information about their research and innovations and for those who want to know the latest results in the field of Data Science and Information System. The Journal is published by the Indonesian Scientific Journal. Accepted paper will be available online (free access), and there will be no publication fee. The author will get their own personal copy of the paperwork. IJADIS welcomes all topics that are relevant to data science, and information system. The listed topics of interest are as follows: Data clustering and classifications Statistical model in data science Artificial intelligence and machine learning in data science Data visualization Data mining Data intelligence Business intelligence and data warehousing Cloud computing for Big Data Data processing and analytics in IoT Tools and applications in data science Vision and future directions of data science Computational Linguistics Text Classification Language resources Information retrieval Information extraction Information security Machine translation Sentiment analysis Semantics Summarization Speech processing Mathematical linguistics NLP applications Information Science Cryptography and steganography Digital Forensic Social media and social network Crowdsourcing Computational intelligence Collective intelligence Graph theory and computation Network science Modeling and simulation Parallel and distributed computing High-performance computing Information architecture
Arjuna Subject : Ilmu Komputer (semua kategori) - Kecerdasan Buatan
Articles 6 Documents
 1 
Search results for , issue "Vol. 1 No. 1 (2020): April 2020 - International Journal of Advances in Data and Information Systems" : 6 Documents clear
Application of K-Means Clustering Algorithm for Determination of Fire-Prone Areas Utilizing Hotspots in West Kalimantan Province Nabila Amalia Khairani; Edi Sutoyo
International Journal of Advances in Data and Information Systems Vol. 1 No. 1 (2020): April 2020 - International Journal of Advances in Data and Information Systems
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25008/ijadis.v1i1.13

Abstract

Forest and land fires are disasters that often occur in Indonesia. In 2007, 2012 and 2015 forest fires that occurred in Sumatra and Kalimantan attracted global attention because they brought smog pollution to neighboring countries. One of the regions that has the highest fire hotspots is West Kalimantan Province. Forest and land fires have an impact on health, especially on the communities around the scene, as well as on the economic and social aspects. This must be overcome, one of them is by knowing the location of the area of ??fire and can analyze the causes of forest and land fires. With the impact caused by forest and land fires, the purpose of this study is to apply the clustering method using the k-means algorithm to be able to determine the hotspot prone areas in West Kalimantan Province. And evaluate the results of the cluster that has been obtained from the clustering method using the k-means algorithm. Data mining is a suitable method to be able to find out information on hotspot areas. The data mining method used is clustering because this method can process hotspot data into information that can inform areas prone to hotspots. This clustering uses k-means algorithm which is grouping data based on similar characteristics. The hotspots data obtained are grouped into 3 clusters with the results obtained for cluster 0 as many as 284 hotspots including hazardous areas, 215 hotspots including non-prone areas and 129 points that belong to very vulnerable areas. Then the clustering results were evaluated using the Davies-Bouldin Index (DBI) method with a value of 3.112 which indicates that the clustering results of 3 clusters were not optimal.
Analysis of Malware Impact on Network Traffic using Behavior-based Detection Technique Adib Fakhri Muhtadi; Ahmad Almaarif
International Journal of Advances in Data and Information Systems Vol. 1 No. 1 (2020): April 2020 - International Journal of Advances in Data and Information Systems
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25008/ijadis.v1i1.14

Abstract

Malware is a software or computer program that is used to carry out malicious activity. Malware is made with the aim of harming user’s device because it can change user’s data, use up bandwidth and other resources without user's permission. Some research has been done before to identify the type of malware and its effects. But previous research only focused on grouping the types of malware that attack via network traffic. This research analyzes the impact of malware on network traffic using behavior-based detection techniques. This technique analyzes malware by running malware samples into an environment and monitoring the activities caused by malware samples. To obtain accurate results, the analysis is carried out by retrieving API call network information and network traffic activities. From the analysis of the malware API call network, information is generated about the order of the API call network used by malware. Using the network traffic, obtained malware activities by analyzing the behavior of network traffic malware, payload, and throughput of infected traffic. Furthermore, the results of the API call network sequence used by malware and the results of network traffic analysis, are analyzed so that the impact of malware on network traffic can be determined.
Impact Analysis of Malware Based on Call Network API With Heuristic Detection Method One Tika Suryati; Avon Budiono
International Journal of Advances in Data and Information Systems Vol. 1 No. 1 (2020): April 2020 - International Journal of Advances in Data and Information Systems
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25008/ijadis.v1i1.176

Abstract

Malware is a program that has a negative influence on computer systems that don't have user permissions. The purpose of making malware by hackers is to get profits in an illegal way. Therefore, we need a malware analysis. Malware analysis aims to determine the specifics of malware so that security can be built to protect computer devices. One method for analyzing malware is heuristic detection. Heuristic detection is an analytical method that allows finding new types of malware in a file or application. Many malwares are made to attack through the internet because of technological advancements. Based on these conditions, the malware analysis is carried out using the API call network with the heuristic detection method. This aims to identify the behavior of malware that attacks the network. The results of the analysis carried out are that most malware is spyware, which is lurking user activity and retrieving user data without the user's knowledge. In addition, there is also malware that is adware, which displays advertisements through pop-up windows on computer devices that interfaces with user activity. So that with these results, it can also be identified actions that can be taken by the user to protect his computer device, such as by installing antivirus or antimalware, not downloading unauthorized applications and not accessing unsafe websites.
Analysis of User Acceptance of ERP System on After Sales Function Using Unified Theory of Acceptance and Use of Technology (UTAUT) Model Andwika, Verina Risky; Witjaksono, R. Wahjoe; Azizah, Anik Hanifatul
International Journal of Advances in Data and Information Systems Vol. 1 No. 1 (2020): April 2020 - International Journal of Advances in Data and Information Systems
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25008/ijadis.v1i1.178

Abstract

Unified Theory of Acceptance and Use of Technology (UTAUT) is a model used to describe user behavior towards the acceptance of information technology. UTAUT is a development of eight previous leading theories. UTAUT has four constructs that can be a significant direct determinant of behavioral intention and use behavioral, ie performance expectancy, effort expectancy, social influence, and facilitating conditions. This model is then used to analyze user acceptance of Enterprise Resource Planning (ERP) at PT Wijaya Toyota Dago. ERP is a system that can help companies to integrate one process with another process, in order to achieve company goals. This research will explain about the relation of factors influencing acceptance and usage of ERP by using UTAUT model. This research is an explanative research with data analysis technique using PLS (Partial Least Square). Data obtained comes from respondents who are employees of After Sales function of PT Wijaya Toyota Dago, data obtained by way of distributing the questionnaire tertuup. The sample size in this study was 37 resondents and analyzed using SPSS and SmartPLS applications. The analysis results are as follows: (1) Variable Performance Expectancy (PE) has a positive and significant influence on Behavioral Intention (BI); (2) Variable Effort Expectancy (EE) has a positive and significant influence on Behavioral Intention (BI);(3) Social Influence Variables (SI) have a positive and significant influence on Behavioral Intention (BI); (4) Variable Facilitating Conditions (FC) has a positive and significant influence on Use Behavior; (5) Social Influence (SI) variable has positive but not significant influence on Behavioral Intention (BI).
Design of Cooling and Air Flow System Using NDLC Method Based on TIA-942 Standards in Data Center at CV Media Smart Semarang Septian Sony Hermawan; Rd Rohmat Saedudin
International Journal of Advances in Data and Information Systems Vol. 1 No. 1 (2020): April 2020 - International Journal of Advances in Data and Information Systems
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25008/ijadis.v1i1.179

Abstract

CV Media Smart is a company that involved in the procurement of IT tools in schools and offices. With wide range coverage of schools and companies, CV Media Smart want to add more business process, therefore data center is needed to support existing and added later business process. The focus of this research is on cooling system and air flow. To support this research, NDLC (Network Development Life Cycle) is used as research method. NDLC is a method that depend on development process, like design of business process and infrastructure design. The reason why this research is using NDLC method is because NDLC is method that depend on development process. The standard that used in this research is TIA-942. Result of this research is a design of data center that already meet TIA-942 standard tier 1.
Impact of Covid-19 Pandemic School Close Down on the Research Programme of Higher Institutions Ogunode Niyi Jacob
International Journal of Advances in Data and Information Systems Vol. 1 No. 1 (2020): April 2020 - International Journal of Advances in Data and Information Systems
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25008/ijadis.v1i1.189

Abstract

The purpose of this study is to examine the impact of covid-19 pandemic school close down on the research programme of higher institutions in Abuja, Nigeria. Descriptive survey design was used for the study and 4 research questions was developed for the study. Random sampling method was used to select 120 researchers in the four sampled institutions. The instrument used for collection of data was a structured questionnaire. Result collected revealed that 100% of the respondents agreed that Covid-19 pandemic school closure have impact on research program of higher institutions in FCT, 100% of the respondents agreed that Covid-19 pandemic will affects the flow of international research grants into higher institutions in FCT, 92% of the respondents agreed that Covid-19 pandemic will affects government funding of research higher institutions in FCT and 100% agreed that higher institutions as part of their community services by creating awereness to the general public on prevention of covid-19.The study also showed that 100% of the respondents agreed that higher institutions in Federal Capital Territory are collaborating with other institutions on the research for covid-19 vaccine while 69.17% of the respondents agreed that higher institutions in FCT are producing face masks for free distributions for the people to protect them from containing the covid-19 in Abuja. Based on this finding, this paper thereby recommends that government should increase the funding of research programme in Abuja and other higher institutions in the country.

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