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All Journal Jurnal Masyarakat Informatika MATEMATIKA SAINS DAN MATEMATIKA JURNAL SISTEM INFORMASI BISNIS Telematika : Jurnal Informatika dan Teknologi Informasi Jurnal Teknologi Informasi dan Ilmu Komputer Jurnas Nasional Teknologi dan Sistem Informasi INTEGER: Journal of Information Technology INOVTEK Polbeng - Seri Informatika Indonesian Journal of Medicine JURTEKSI Aptisi Transactions on Technopreneurship (ATT) J-Kesmas: Jurnal Kesehatan Masyarakat (Indonesian Journal of Public Health) Journal of Soft Computing Exploration Journal of Renewable Energy, Electrical, and Computer Engineering Journal of Indonesian Health Policy and Administration Scientific Journal of Informatics JuTISI (Jurnal Teknik Informatika dan Sistem Informasi) Integra: Journal of Integrated Mathematics and Computer Science
Aris Puji Widodo
Undip
Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Health Professions Mathematics Medicine & Pharmacology Public Health Social Sciences

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IDENTIFICATION OF CAPABILITY LEVELS OF MEDIS CARE INFORMATION SYSTEM USING COBIT 2019 Pamungkas, Ardian; Fardana, Nouvel Izza; Widodo, Aris Puji; Adi, Kusworo
JURTEKSI (Jurnal Teknologi dan Sistem Informasi) Vol 10, No 4 (2024): September 2024
Publisher : STMIK Royal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33330/jurteksi.v10i4.3257

Abstract

Abstract: In the health sector, information technology was initially used for exchanging information between patients and doctors, health services, and exchanging health documents. The aim of applying information technology to the health sector is to increase the effectiveness and efficiency of the performance of doctors and clinic staff. This research uses COBIT 2019 as a framework for evaluating information technology governance. Primary data is collected directly from the research subjects through observation and interviews, while secondary data is sourced from other materials, such as documents or websites related to the research subject. This research focuses on Risk Profile and I&T Related Issues, with domains: APO11 – Managed Quality, and APO13 – Managed Security. Through interviews and evaluation, each priority objective was found to be at capability level 2 with ratings of 100% and 86% respectively. There are no significant gaps between the current capability levels; both are at level 2. Keywords: auditing; COBIT 2019; telemedicine  Abstrak: Di sektor kesehatan, teknologi informasi awalnya digunakan untuk pertukaran informasi antara pasien dan dokter, layanan kesehatan, dan pertukaran dokumen kesehatan. Tujuan penerapan teknologi informasi di sektor kesehatan adalah untuk meningkatkan efektivitas dan efisiensi kinerja dokter dan staf klinik. Penelitian ini menggunakan COBIT 2019 sebagai kerangka kerja untuk mengevaluasi tata kelola teknologi informasi. Data primer dikumpulkan langsung dari subjek penelitian dengan melakukan pengamatan dan interaksi langsung, sementara data sekunder diperoleh dari sumber lain. didapatkan dari jurnal atau situs website yang berkaitan dengan subjek penelitian. Penelitian ini berfokus pada Risk Profile dan I&T Related Issues, dengan domain : APO11 – Managed Quality, dan APO13 – Managed Security. Melalui wawancara dan evaluasi, setiap tujuan prioritas ditemukan berada pada level kapabilitas 2 dengan nilai masing-masing 100% dan 86%. Tidak ada kesenjangan signifikan antara tingkat kapabilitas saat ini; keduanya berada pada level 2. Kata kunci: audit; COBIT 2019; telemedis
Car insurance segmentation prediction based on the most influential features using random forest and stacking ensemble learning Vianita, Etna; Wibowo, Adi; Surarso, Bayu; Widodo, Aris Puji
Journal of Soft Computing Exploration Vol. 2 No. 2 (2021): September 2021
Publisher : SHM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52465/joscex.v2i2.39

Abstract

In addition to financial transaction services, the Bank also provides insurance services by conducting regular campaigns to attract new customers such as car insurance based on market segmentation, which is one of the main aspects of marketing used in financial services based on demographic data. One way to analyze the market is to predict the likely target market based on the campaign's target demographic data. Therefore, this study aims to find the best classification method for predicting campaign targets using historical data from 4000 customers of a bank in the United States. The market segmentation analysis process uses the best feature selection and ensemble learning. The best feature selection is selected using important features for Random Forest. The ensemble learning used is a stacking model consisting of the basic model of Logistic Regression, Support Vector Classifier, Gradient Boosting, Extra Tree, Bagging, Adaboost, Gaussian Naive Bayes, MLP, XBoost, LGBM, KNeighbors, Decision Tree, and Random Forest. The accuracy results of the stacking model can exceed the accuracy of the basic model with an accuracy rate of 78.80%.
Information System Policy of Web-based Patient Safety Incident Reporting Information System at RSJ Prof Dr. Soerojo Magelang Purnomo, Setyo; Widodo, Aris Puji; Setyaningsih, Yuliani
Journal of Indonesian Health Policy and Administration Vol. 5, No. 3
Publisher : UI Scholars Hub

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

To provide security to their patients, healthcare providers use a system for patient safety which includes risk reporting and analysis of incidents, identification and management of risks, and the ability to learn about events that have occurred. According to the 2017 patient safety data at Prof. Dr. Soerojo Psychiatric Hospital, 7% of patient safety incidents at the hospital required a Root Cause Analysis. To aid the process, an online information system is necessary. This research was qualitative research that used the waterfall method for the information syntax. This involved planning, analysis, design, implementation, and system. From there, the data was then evaluated based on its accessibility, completeness, accuracy, and speed. The qualitative data was gathered through questionnaires, in-depth interviews, and unstructured interviews with selected informants. 26 informants were involved in this research, this included the reporters, the Patient Safety (KPRS) Team, and the hospital management board. Results of the would then produce recommendations on how to handle the problems found. Based on the data gathered, we discovered that after the application of the information system, the hospital experienced a 53.8% increase in patient safety.
The Effect of Physical Exercise on Quality of Life of Breast Cancer Survivors: A Systematic Review Jadmiko, Arief Wahyudi; Kristina, Tri Nur; Sujianto, Untung; Prajoko, Yan Wisnu; Dwiantoro, Luky; Widodo, Aris Puji
Indonesian Journal of Medicine Vol. 6 No. 4 (2021)
Publisher : Masters Program in Public Health, Universitas Sebelas Maret, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (31.337 KB)

Abstract

Background: Exercise generally improves the quality of life (QoL) in adult populations especially for patients with chronic health problems such as breast cancer. The purpose of this study was to investigate the effect of physical exercise/activity on the quality of life of breast cancer survivors. Subjects and Method: This was a systematic review study that used articles from online data­bases, such as  PubMed, Science Direct, ProQuest dan Medline, which was published from 2000 to 2021. The author used keywords of “physical exercise”, “physical activity”, “quality of life”, “breast cancer survivor”. The dependent variable was quality of life. The independent variable was physical exercise/ activity. As many as 5 articles were selected for this study from 837 articles located in South Korea, Iran, Malaysia, and China.Results: Moderate or high levels of physical activity had positive relationship on the quality of life related to overall physical health among breast cancer survivors.Conclusion: Moderate to high physical activity improve the quality of life among breast cancer survivors.Keywords: physical exercise, physical activity, quality of life, breast cancer survivor Correspondence: Arief Wahyudi Jadmiko. Nursing Department, Faculty of Health, Universitas Pembangunan Nasional Veteran Jakarta. Jl. Raya Limo Depok 16515 West Java, Indonesia Email: ariefw­jadmiko­@gmail.com. Mobile: 085647213628. ORCID ID https://orcid.org/0000-0002-9691-0986.Indonesian Journal of Medicine (2021), 06(04): 377-386https://doi.org/10.26911/theijmed.2021.06.04.03
Benefits and Challenges of ERP Implementation in Higher Education Institutions: A Systematic Literature Review Sholeh, Moch. Badrus; Samodra, Renita Fauziah; Widodo, Aris Puji
Jurnal Sistem Informasi Bisnis Vol 15, No 1 (2025): Volume 15 Number 1 Year 2025
Publisher : Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/vol15iss1pp21-33

Abstract

This study aims to identify the benefits and challenges of Enterprise Resource Planning (ERP) implementation in higher education institutions through a Systematic Literature Review (SLR). Based on the analysis of 37 relevant articles, the findings show that ERP implementation provides significant benefits, such as reducing operational costs, increasing efficiency, and enhancing decision-making. However, challenges such as system complexity, resistance to change, and technological infrastructure limitations remain major obstacles. To address these challenges, increased training, coordination, and management support are required, along with adequate budget allocation. The findings of this study are expected to provide higher education management with insights into the importance of thorough planning in ERP implementation to achieve successful outcomes.
Komparasi COBIT 2019 dan ISO 27001 Terhadap Audit ISO 21001 untuk Akurasi Rekomendasi Audit SI/TI Pendidikan Anggraeni, Retno Setya; Rochim, Adian Fatchur; Widodo, Aris Puji
Jurnal Sistem Informasi Bisnis Vol 15, No 1 (2025): Volume 15 Number 1 Year 2025
Publisher : Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/vol15iss1pp142-151

Abstract

ISO 21001 refers to the standardization of educational organization management and is an international standard, making it mandatory to be implemented in higher education institutions. Along with this, the rapid development of Information Systems and Information Technology (IS/IT) today has changed the paradigm of education and provided a new perspective that IS/IT support not only aids the learning process but also various other areas in higher education. Standardization focusing on this field includes IT Governance (ITG) COBIT 2019 and ISO 27001. Therefore, the researcher conducted a study to analyze which tools are most correlated with the implementation of ISO 21001, so that the findings of this research can provide recommendations that can serve as a basis for policy in selecting the appropriate standardization tools. The research method used is ex post facto. The analysis was conducted using SmartPLS. The researcher designed a questionnaire instrument to be distributed to the population of the Department of Computer Engineering and Informatics Engineering, UNDIP Semarang. The results of the questionnaire will then be tested for validity and reliability, followed by a correlation test while considering the T-Value. Based on the analysis results, it was concluded that both COBIT 2019 and ISO 27001 have an influence on ISO 21001. The influence of COBIT 2019 on ISO 21001 is significant, with a path coefficient and p-value of 0.000, while the influence of ISO 27001 shows a p-value of only 0.091.
COBIT 2019 Framework in IT Governance: A Systematic Literature Review of Implementation Challenges and Benefits Across Various Industry Sectors Antariksa, Muhammad Deagama Surya; Angin, Maria Perangin; Widodo, Aris Puji
Journal of Renewable Energy, Electrical, and Computer Engineering Vol. 5 No. 1 (2025): March 2025
Publisher : Institute for Research and Community Service (LPPM), Universitas Malikussaleh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/jreece.v5i1.19501

Abstract

Information technology (IT) governance is a critical factor in ensuring that IT investments align with business objectives, improve operational efficiency, and mitigate risks across various industries. COBIT 2019, a widely used IT governance framework, has been adopted in numerous sectors to address these needs. This study explores the implementation of COBIT 2019 by conducting a systematic literature review (SLR) of 23 relevant articles published between 2020 and 2024, sourced from internationally indexed journals. The research focuses on identifying the challenges, benefits, success factors, and strategies to mitigate the issues encountered during the implementation of COBIT 2019. The findings indicate that COBIT 2019 has been successfully applied in diverse industries such as education, healthcare, logistics, and mineral mining, demonstrating its flexibility and adaptability to different organizational contexts. Key benefits include improved alignment of IT with business strategies, enhanced risk management, better resource optimization, and increased operational efficiency. However, challenges such as the complexity of the framework, limited resources, and a lack of understanding of the frameworks terminology have been identified. Successful implementation is largely dependent on strong management support, stakeholder engagement, and adequate resource allocation. Mitigation strategies such as ongoing training, development of comprehensive communication plans, and regular evaluation of IT governance practices have been suggested to overcome these challenges. This study provides practical insights into the implementation of COBIT 2019, offering organizations guidance on maximizing its benefits while addressing the barriers to successful implementation.
Review of Systematic Literature about Sentiment Analysis Techniques Sasongko, Cornelius Damar; Isnanto, Rizal; Widodo, Aris Puji
Jurnal Sistem Informasi Bisnis Vol 15, No 2 (2025): Volume 15 Number 2 Year 2025
Publisher : Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/vol15iss2pp227-236

Abstract

Sentiment analysis, also known as opinion mining, is an important task in natural language processing and data mining. It involves extracting and analyzing subjective information from textual data to determine the sentiment or opinion expressed by the author. With the advancement of technology and the widespread use of social media and online review platforms, it is increasingly important to understand users' opinions and sentiments regarding a particular product, service or issue. The purpose of this research is to present a comprehensive literature review on sentiment analysis techniques. This research utilizes the systematic literature review method. This method involves systematic steps in searching, evaluating, and analyzing relevant literature in the field of sentiment analysis. The literature search was conducted through scientific databases and other reliable sources. Relevant articles were then selected based on pre-determined inclusion and exclusion criteria. The data from the selected articles were then comprehensively analyzed to identify the sentiment analysis techniques used and the key findings in the research. The results show that there are various techniques and approaches that have been developed and tested in sentiment analysis, some of the commonly used techniques include rule-based methods, classification-based methods, and machine learning-based methods.
Resolving Data Imbalance using SMOTE for the Analysis and Prediction of Hate Speech Sentences Sutikman, Sutikman; Sutanto, Heri; Widodo, Aris Puji
Jurnal Sistem Informasi Bisnis Vol 15, No 2 (2025): Volume 15 Number 2 Year 2025
Publisher : Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/vol15iss2pp198-203

Abstract

Hate speech is characterized as a form of communication that expresses hostility or discontent towards particular individuals, groups, or ethnicities, with the intent to belittle one party. This research aims to examine hate speech expressions on Twitter, assessing their categorization as hate speech through the application of machine learning methodologies. The study incorporates feature engineering techniques, such as Term Frequency-Inverse Document Frequency (TF-IDF) and the Synthetic Minority Over-sampling Technique (SMOTE), to mitigate challenges related to data imbalance. The machine learning models utilized include Logistic Regression (LR), Decision Tree (DT), Gradient Boosting (GB), and Random Forest (RF). Among these models, Logistic Regression (LR) demonstrated the highest efficacy, achieving an accuracy of 91.43%, precision of 88.83%, recall of 93.99%, and an F1 score of 97.10%.
Implementation of the Ensemble Machine Learning Algorithm for Student Dropout Prediction Analysis Winarsih, Winarsih; Sutanto, Heri; Widodo, Aris Puji
Jurnal Sistem Informasi Bisnis Vol 15, No 2 (2025): Volume 15 Number 2 Year 2025
Publisher : Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/vol15iss2pp159-166

Abstract

Educational Data Mining provides an effective approach to tackle numerous issues within the education sector, including the capacity to perform predictive analyses regarding student attrition based on academic information. In this research, data from the Open University Learning Analytics dataset (OULAD), which is publicly accessible, has been employed, which encompasses student information collected during online learning. We apply various Machine Learning models, including Decision Trees, Naïve Bayes, Logistic Regression, and ensemble approaches like Random Forest and AdaBoost. Among the models tested, Random Forest (RF) achieved the highest accuracy of 89.37%, along with a precision of 89.57% and a recall of 93.86%, using the data splitting approach. When employing an alternative evaluation model, specifically K-Fold Cross Validation, the maximum F1 score achieved was 9.45%. In summary, the ensemble machine learning algorithm, specifically Random Forest (RF), exhibited strong performance in predicting student academic achievement quality.
Co-Authors Adi Wibowo Adian Fatchur Rochim Ahmad Zaini Alvianto, Muhammad Nur Hendra Anggraeni, Retno Setya Angin, Maria Perangin Antariksa, Muhammad Deagama Surya Arief Wahyudi Jadmiko arif, erman Arkan, Muhammad Naufal Aryasa, Jiyestha Aji Dharma Bayu Surarso Catur Edi Widodo Dahur, Arnoldus Janssen Dinar Mutiara Kusumo Nugraheni Dwiantoro, Luky Eko Adi Sarwoko Eko Sediyono Fardana, Nouvel Izza Farid Agushybana Febriandi, Agistra Firdaus, Zulfia Guruh Aryotejo, Guruh Heri Sutanto Iwan Purwanto Jazi Eko Istiyanto Kusuma, Teja Kusworo Adi Nabiel Putra Adam, Nabiel Putra Nikken Prima Puspita Nurdin Bahtiar Oktaviana, Aulia Pamungkas, Ardian R Rizal Isnanto Roziana Roziana, Roziana Samodra, Renita Fauziah Sanjaya, Daniel Robi Sasongko, Cornelius Damar Setyo Purnomo Sholeh, Moch. Badrus Sodik, Ilham Akbar Suherman, Suherman Sutikman, Sutikman Sutopo Patria Jati Tanjung, Dio Febrilian Tri Nur Kristina Untung Sujianto Vianita, Etna Wicaksono, Januar Agung Winarsih Winarsih Woro Ningrum, Eva Liyan Yan Wisnu Prajoko Yuliani Setyaningsih Zahrasita Nur Indira Zukhruf, Afriza Meigi