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Taqwa Hariguna
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Puri Mersi Baru, Jl.Martadireja II, Gang Sitihingil 3 Blok A No 2, Purwokerto Timur, Jawa Tengah
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INDONESIA
IJIIS: International Journal of Informatics and Information Systems
Published by Bright Publisher
ISSN : -     EISSN : 25797069     DOI : https://doi.org/10.47738/ijiis
Core Subject : Science,
Computer Science & IT
The IJIIS is an international journal that aims to encourage comprehensive, multi-specialty informatics and information systems. The Journal publishes original research articles and review articles. It is an open access journal, with free access for each visitor (ijiis.org/index.php/IJIIS/); meanwhile we have set up a robust online platform and use an online submission system to ensure the international visibility and the rigid peer review process. The journal staff is committed to a quick turnaround time both in regards to peer-review and time to publication.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 5 Documents
 1 
Search results for , issue "Vol 7, No 2: March 2024" : 5 Documents clear
Examining IT Service Management at Company XYZ through the Lens of ITIL V3 Service Operation Domain Mutikno, Wiwit Gayuh Mugi; Rizaldi, Dani; Syanahieskara, Razel; Pratiwi, Widya Dian; Muntaqo, Firman; Aeni, Aisyah Nur; Jeenduang, Nutjaree
International Journal of Informatics and Information Systems Vol 7, No 2: March 2024
Publisher : International Journal of Informatics and Information Systems

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/ijiis.v7i2.199

Abstract

The rapid development of information technology and good technology services is an expectation for all people, organisations, institutions, and universities in order to support activities, facilitate their activities and business processes. A business organisation needs to adapt to the current development of information technology. IT service management is a method of managing information technology systems that is centred on the consumer perspective of information technology services on the company's business. Company XYZ has implemented information technology that is intended for users to be able to carry out service management activities as well as processing company administrative data. Service Operation is a lifecycle phase that includes all the day-to-day operations of IT service management. Based on the results of research on 3 processes, namely Event Management, Request Fulfilment and Problem Management, it is necessary to increase the need for adequate hardware, software and infrastructure in meeting the needs of Company XYZ in working more effectively. Then the need for proper application of SOPs and modules to employees is somewhat more efficient in using information technology.
Prediction of Waste Generation in Yogyakarta Special Region Province Using ARIMA Model Nur Azizah, Resti; Aji, Ranggi Praharaningtyas
International Journal of Informatics and Information Systems Vol 7, No 2: March 2024
Publisher : International Journal of Informatics and Information Systems

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/ijiis.v7i2.200

Abstract

Waste is a problem in big cities in Indonesia, including in the Special Region of Yogyakarta which has a high population. In addition, the large tourism potential triggers waste problems that are often experienced by the Special Region of Yogyakarta. The average increase in waste reaches 11.53% per year. This causes an imbalance in the ability to manage the waste system in the province. To overcome this, an analysis is needed to project waste generation to support waste management strategies and processes. This research uses the CRISP-DM framework to facilitate the stages of analysis and effective and efficient decision making. The data used is a time series of waste generation per year in tons from districts or cities from 2016 to 2022. The model used to make predictions is the ARIMA model. This model was chosen because it is suitable for time series analysis and is the most commonly used model. The result of this prediction is that the projected waste generation from 2023 to 2025 in each district or city in the Special Region of Yogyakarta has increased significantly. Based on the ARIMA model, it is projected that the average waste generation of DIY Province will increase from a total of 638 thousand tons in 2022 to 642 thousand tons in 2023, and is expected to continue to increase by 5-7 thousand tons per year.
Evaluation of Online Admissions Information System Utilizing the Technology Acceptance Model Lian, Chuan De; Yuzhak, Nauval Dwi
International Journal of Informatics and Information Systems Vol 7, No 2: March 2024
Publisher : International Journal of Informatics and Information Systems

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/ijiis.v7i2.201

Abstract

Admission of New Students covers the entire process, from registration and administrative selection to graduation announcement. This activity is an annual routine that is the first step in finding quality prospective students. Therefore, there is a need for a valuable and user-friendly online PMB website. Based on these problems, it is necessary to assess the success of implementing the PMB Online system at Amikom Purwokerto University using the Technology Acceptance Model (TAM) approach. This system development method refers to TAM, which emphasizes user perceptions of two main variables: usefulness and ease of use. Variables that describe user acceptance of the PMB Online system include Perceived Ease of Use, Perceived Usefulness, Perceived Enjoyment, Attitude Towards Using, and Intention to Use. The results of this study indicate that Perceived Ease of Use has a positive effect on Perceived Usefulness, and Perceived Usefulness has a positive effect on Attitude Towards Using and Intention to Use. Meanwhile, Perceived Enjoyment also has a positive effect on Attitude Towards Using. The results of this study are expected to identify weaknesses and improve certain aspects to optimize the implementation of PMB Online at Amikom Purwokerto University.
Implementation of Big Data Analytics and its Challenges in Digital Transformation Era: A Literature Review Susanto, Firsty Larastiyana; Maulani, Agustin; Nuri, Siti Nuran
International Journal of Informatics and Information Systems Vol 7, No 2: March 2024
Publisher : International Journal of Informatics and Information Systems

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/ijiis.v7i2.204

Abstract

The reliance on technology to support various aspects of human life has become very relevant and significant. The steadily increasing volume of data (called big data) plays an important role in machine learning, Internet of Things (IoT) and other intelligence applications. The interaction between big data and operations in various aspects of human life is a concern, this systematic literature review provides a descriptive aspect of the literature review, the research results offer a comprehensive overview of existing big data implementations ranging from 2019 to 2023. Other than this, we discuss the general challenges for researchers in using various big data sources in different crises. This study, especially revealing the implementation and challenges of big data in general, is expected to provide a knowledge base for researchers to delve deeper and more specifically.
Skin Cancer Detection Approach Using Convolutional Neural Network Artificial Intelligence Hayat, Sabda Norman; Watef, Lulu'ul; Indraswari, Rarasmaya
International Journal of Informatics and Information Systems Vol 7, No 2: March 2024
Publisher : International Journal of Informatics and Information Systems

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/ijiis.v7i2.196

Abstract

Skin cancer is a type of cancer that can cause death, where skin cancer is included in the 15 common cancers that occur in Indonesia. The number of skin cancer sufferers was around 6,170 cases of non-melanoma skin cancer and 1,392 cases of melanoma skin cancer in 2018 in Indonesia. Therefore, research related to skin cancer classification is increasing. This is done as an initial step in detecting whether a lesion can be said to be cancerous or not. The deep learning approach has certainly shown promising results in carrying out classification, so this research proposes a deep learning-based method used for skin cancer classification. The proposed approach involves Convolutional Neural Networks with the ISIC 2017 dataset. The models used for skin cancer classification are InceptionV3, EfficientNetB0, ResNet50, MobileNetV2, and NASNetMobile. The highest accuracy of the single model produced reached 69.3% using the MobileNetV2 model. An ensemble model combining the five models was also tested and produced the highest accuracy compared to other single models with an accuracy result of 80.6%.

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