International Journal of Health, Engineering and Technology
International Journal of Health, Engineering and Technology (IJHET) is to provide research media and an important reference for the progress and dissemination of research results that support high-level research in the field of Health, Engineering and technology. Original theoretical work and application-based studies, which contribute to a better understanding of all areas of Health, Engineering and Technology , the journal publishes articles six times a year in May, July, September, November, January and March. Scope: International Journal of Health, Engineering and Technology (IJHET) is to provide a research medium and an important reference for the advancement and dissemination of research results that support high-level research in the fields of Health, Engineering and Technology Research. Original theoretical work and application-based studies, which contributes to a better understanding all fields of Health, Engineering and Technology Research. Healt : Clinical Nutrition, Community Nutrition, Institutional Nutrition, Food Technology, Food Security, Pediatric Physiotherapy, Geriatric Physiotherapy, Cardiovascular and Pulmonary Physiotherapy, Musculoskeletal Physiotherapy, Sports Physiotherapy, Public Health, Community Sanitation, Environmental Health, Nursing, Biology, Medicine, Pharmacy. Engineering : The field of mechanical Engineering include expertise in energy conversion, construction machinery, manufacturing and materials. The field of Electrical Engineering which includes skills power engineering, telecommunications engineering and information, as well as control and instrumentation. The field of Chemical Engineering which includes expertise in the field of new and renewable energy, the environment field. The field of Civil Engineering which includes expertise in the fields of structural, geotechnical, transportation and water. The field of Metallurgical Engineering which includes expertise in extraction, manufacturing and characterization of materials. The field of Industrial Engineering which includes enterprise management system, working system and the ergonomics and manufacturing systems. Technology: Open Source Application, Information Management, Information System, IT & Social Impact, Geographical Information System, Web Engineering, Database Design & Technology, Data Warehouse, Network Security, Data Mining, Computer Architecture Design, Mobile Programming.
Articles
272 Documents
<![CDATA[Analysis of risk factors for failure of hypertension therapy based on medical history and drug consumption using Random Forest ]]>
<![CDATA[Desi Irfan]]>;
<![CDATA[Novica Jolyarni]]>;
<![CDATA[Halimah Tusakdiyah Harahap]]>;
<![CDATA[Baginda Restu Al Ghazali]]>;
<![CDATA[Riswan Syahputra Damanik]]>
<![CDATA[ International Journal of Health Engineering and Technology Vol. 2 No. 4 (2023): IJHET NOVEMBER 2023 ]]>
Publisher : <![CDATA[CV. AFDIFAL MAJU BERKAH ]]>
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DOI: 10.55227/ijhet.v4i1.276
<![CDATA[Computer network performance is very important in supporting various digital activities, but systems often cannot accurately predict changes in performance, which can cause service disruptions and economic losses. This research aims to implement the Support Vector Machine (SVM) algorithm to increase the accuracy of network performance predictions based on parameters such as latency, packet loss, throughput and jitter. Data is collected through network simulation and real data monitoring, then processed with normalization and selection of relevant features. The SVM model is tested with various kernels, including linear, RBF, and polynomial, to find the best configuration. Performance evaluation uses accuracy, precision, recall, F1-score, and ROC-AUC metrics, with cross-validation to increase the reliability of the results. The results show that the RBF kernel provides a prediction accuracy of 92%, higher than baseline methods such as Decision Tree and Logistic Regression. This model shows its potential to be applied in computer network monitoring systems to predict network performance in real-time, with the possibility of wider implementation in artificial intelligence-based network applications. Therefore, this research not only contributes to machine learning theory in the field of computer networks, but also provides practical solutions that can improve the management and optimization of network performance in various environments that require fast and accurate data processing.]]>
<![CDATA[Application of SVM to Speed Up and Accurate Nursing Decisions for Mentally Disordered Patients ]]>
<![CDATA[Santosa Pohan]]>;
<![CDATA[Riyan Agus Faisal]]>;
<![CDATA[Fitriyani Nasution]]>;
<![CDATA[Putri Ramadani]]>;
<![CDATA[Ade Irma Yanti Hasibuan]]>
<![CDATA[ International Journal of Health Engineering and Technology Vol. 3 No. 4 (2024): IJHESS NOVEMBER 2024 ]]>
Publisher : <![CDATA[CV. AFDIFAL MAJU BERKAH ]]>
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DOI: 10.55227/ijhet.v4i1.277
<![CDATA[This study aims to evaluate the application of the Support Vector Machine (SVM) algorithm in increasing the speed and accuracy of nursing decision making in patients with mental health disorders. Fast and accurate decision making is very important in the nursing context, especially in treating patients with complex mental disorders. In this research, patient medical record data is used to train an SVM model, which is then used to predict the severity of the patient's mental disorder, such as Mild, Moderate, or Severe. The model is trained using features such as the patient's age, gender, diagnosis, psychological test scores, and physical condition. The evaluation results show that the SVM model has 100% accuracy, which means the model succeeded in classifying the severity of the patient's mental disorder very accurately. In addition, implementing this model also reduces the time required for decision making, allowing nurses to provide faster and more precise decisions. These results indicate that SVM can be a very useful tool in supporting nursing decision making, increasing the efficiency and quality of care, and reducing diagnostic errors. This research provides important insights into the potential use of artificial intelligence algorithms in clinical decision support systems in the mental health field.]]>
<![CDATA[Sentiment Analysis on Twitter Social Media towards Najwa Shihab Using Naïve Bayes Algorithm and Support Vector Machine (SVM) ]]>
<![CDATA[Fahruzi Sirait]]>;
<![CDATA[Desi Irpan]]>;
<![CDATA[Riszki Fadillah]]>;
<![CDATA[Rizalina Rizalina]]>;
<![CDATA[Riswan Syahputra Damanik]]>
<![CDATA[ International Journal of Health Engineering and Technology Vol. 3 No. 1 (2024): IJHET May 2024 ]]>
Publisher : <![CDATA[CV. AFDIFAL MAJU BERKAH ]]>
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DOI: 10.55227/ijhet.v3i1.280
<![CDATA[With the rapid growth of digital technology, social media has become a key platform for sharing information and opinions. Twitter, one of the most popular platforms in Indonesia, enables users to interact directly with public figures such as Najwa Shihab. This study aims to analyze public sentiment toward Najwa Shihab on Twitter using sentiment analysis, specifically employing the Naïve Bayes and Support Vector Machine (SVM) algorithms. Sentiment analysis is essential to understanding public opinion, as it classifies text into categories like positive, negative, or neutral, providing valuable insights into societal perspectives on public figures. In this study, 10,000 tweets related to Najwa Shihab were collected from January 1, 2023, to January 31, 2023. Data preprocessing steps such as data cleaning, tokenization, stopwords removal, and filtering were conducted to ensure high-quality data for analysis. The Naïve Bayes and SVM algorithms were applied using RapidMiner to classify the sentiment of the tweets. The performance of both algorithms was evaluated based on accuracy, precision, recall, and F1-score.The results revealed that SVM outperformed Naïve Bayes in all metrics, demonstrating its superior ability to classify sentiments correctly. The sentiment distribution indicated a majority of positive opinions toward Najwa Shihab, with fluctuations in negative sentiment during specific events. This study provides insights into public sentiment analysis and contributes to understanding social media opinions on public figures.]]>
<![CDATA[Analysis of Factors Causing Students' Failure to Complete Their Thesis on Time Using the Random Forest Algorithm ]]>
<![CDATA[Riszki Fadillah]]>;
<![CDATA[Intan Nur Fitriyani]]>;
<![CDATA[Nur Indah Nasution]]>;
<![CDATA[Rahadatul 'Aisy Riadi]]>;
<![CDATA[Dinda Salsabila Ritonga]]>
<![CDATA[ International Journal of Health Engineering and Technology Vol. 3 No. 1 (2024): IJHET May 2024 ]]>
Publisher : <![CDATA[CV. AFDIFAL MAJU BERKAH ]]>
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DOI: 10.55227/ijhet.v3i1.281
<![CDATA[This research aims to analyze the factors that influence students' delays in completing final assignments using the Random Forest algorithm. The data used includes variables such as GPA, number of credits, employment status, frequency of guidance, organizational activities, and personal motivation. These variables were analyzed to determine their effect on students' ability to complete their final assignments on time. The Random Forest model is applied to predict whether students complete their final assignments on time or not. The model results show an accuracy of 63.33%, with the frequency of guidance and personal motivation being the most influential factors in completing the final assignment on time. Followed by the number of credits and GPA, which also have a significant but smaller influence. Organizational activity factors and employment status have a lower contribution to tardiness, but are still relevant in the context of student time management. Based on these results, research suggests the importance of academic guidance support and motivation management to help students overcome obstacles in completing their final assignments on time. This research, which uses the case of ITKES Ika Bina students, is expected to provide recommendations for universities in improving the academic mentoring process to support student graduation.]]>
<![CDATA[Implementation of Password Validation using a Combination of Letters, Numbers and Symbols in the New Student Registration Application ]]>
<![CDATA[Sentosa Pohan]]>;
<![CDATA[Putri Ramadani]]>;
<![CDATA[Riszki Fadillah]]>;
<![CDATA[Yusril Iza Mahendra Hasibuan]]>;
<![CDATA[Baginda Restu Al Ghazali]]>
<![CDATA[ International Journal of Health Engineering and Technology Vol. 3 No. 1 (2024): IJHET May 2024 ]]>
Publisher : <![CDATA[CV. AFDIFAL MAJU BERKAH ]]>
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DOI: 10.55227/ijhet.v3i1.282
<![CDATA[This research aims to evaluate the implementation of password validation using a combination of letters, numbers and symbols in new student registration applications in increasing the level of application security. This research method involves implementing a password validation system with strict criteria, as well as testing password strength using brute force attacks. The test results show that passwords that meet the criteria take time 150 seconds to be broken using brute force, while passwords that only use letters only take time 10 seconds. Surveys of users show that 70% feel comfortable with this validation system, though 40% find it difficult to create a valid password. As much 85% users consider this system to improve application security. This research suggests that new student registration applications adopt a strict password validation system to increase the protection of users' personal data, while providing solutions for users to create more secure passwords.complex but easy to remember. The implementation of this system is expected to strengthen application security and increase user confidence in the protection of their personal data.]]>
<![CDATA[Simulation and Detection of Phishing Attacks on Student Academic Emails Using Social Engineering Techniques ]]>
<![CDATA[Santosa Pohan]]>;
<![CDATA[Desi Irfan]]>;
<![CDATA[Intan Nur Fitriyani]]>;
<![CDATA[Yusril Iza Mahendra Hasibuan]]>;
<![CDATA[Indah Chayani]]>
<![CDATA[ International Journal of Health Engineering and Technology Vol. 2 No. 4 (2023): IJHET NOVEMBER 2023 ]]>
Publisher : <![CDATA[CV. AFDIFAL MAJU BERKAH ]]>
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DOI: 10.55227/ijhet.v2i4.283
<![CDATA[Phishing attacks on student academic emails are a serious threat to information security. Social engineering techniques are often used in these attacks to manipulate victims into divulging sensitive information, such as passwords and other personal data. This research aims to analyze and detect phishing attacks that use social engineering techniques on student academic emails. In this research, a phishing attack simulation was carried out with the scenario of falsifying the identity of an academic institution and creating fake emails that appear legitimate. Students as simulated subjects were tested to see how they reacted to deceptive phishing emails, such as clicking on malicious links or downloading infectious attachments. The detection methods used include heuristic analysis and machine learning techniques, where the system is trained to recognize suspicious patterns in emails, including elements such as unusual subjects, links and attachments. The research results show that phishing attacks that utilize social engineering are effective in manipulating victims. On the other hand, detection using machine learning and heuristic analysis can achieve a high level of accuracy in identifying phishing attacks. This research also underscores the importance of increasing awareness about cyber security among students as well as the need to develop more effective phishing detection tools.]]>
<![CDATA[Analysis of risk factors for failure of hypertension therapy based on medical history and drug consumption using Random Forest ]]>
<![CDATA[Desi Irfan]]>;
<![CDATA[Novica Jolyarni D]]>;
<![CDATA[Halimah Tusakdiyah Harahap]]>;
<![CDATA[Baginda Restu Al Ghazali]]>;
<![CDATA[Riswan Syahputra Damanik]]>
<![CDATA[ International Journal of Health Engineering and Technology Vol. 2 No. 4 (2023): IJHET NOVEMBER 2023 ]]>
Publisher : <![CDATA[CV. AFDIFAL MAJU BERKAH ]]>
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DOI: 10.55227/ijhet.v2i4.284
<![CDATA[Cardiovascular disease is a major cause of global morbidity and mortality, with many patients experiencing therapy failure despite treatment. This study analyzes risk factors for failure of antihypertensive therapy based on medical history and drug consumption patterns using the Random Forest algorithm. Retrospective analytical research design using medical record data and structured interviews in hypertensive patients who have undergone treatment for at least one year. The dependent variable was therapy failure, defined as BP ≥140/90 mmHg despite treatment. Independent variables include medical history, drug consumption patterns, and demographic factors. Data is processed by handling missing data, normalization, and feature encoding. The Random Forest model was optimized using GridSearchCV and evaluated based on accuracy, precision, recall and AUC-ROC. Feature importance analysis identifies main risk factors, such as medication adherence, diabetes, and duration of hypertension. The model achieved 86% accuracy (AUC: 0.89), better than logistic regression (accuracy: 78%). These results confirm the importance of patient compliance and comorbidities in hypertension management. This study demonstrates the effectiveness of Random Forest in identifying high-risk patients, with recommendations for prioritization of interventions on medication adherence.]]>
<![CDATA[The Effect Of Product Quality, Price And Promotion On Customer Satisfaction Of Honda Scoopy Motorcycles With Purchase Decisions As Intervening Variables At Honda Mina SPN Dealership, Ranah Batahan District ]]>
<![CDATA[Septriana Sari]]>;
<![CDATA[M. Hamid]]>;
<![CDATA[Romia Romia]]>
<![CDATA[ International Journal of Health Engineering and Technology Vol. 4 No. 1 (2025): IJHET May 2025 ]]>
Publisher : <![CDATA[CV. AFDIFAL MAJU BERKAH ]]>
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DOI: 10.55227/ijhet.v4i1.293
<![CDATA[The results of this research are There is a significant influence of product quality on the decision to purchase a Honda Scoopy motorbike at the Mina Spn Motor Dealer. There is a significant influence of price on the decision to purchase a Honda Scoopy motorbike at the Mina Spn Motor Dealer. There is a significant influence of promotion on the decision to purchase a Honda Scoopy motorbike at the Mina Spn Motor Dealer. There is a significant influence of product quality on customer satisfaction for Honda Scoopy motorbikes at the Mina Spn Motor Dealer. There is a significant influence of price on customer satisfaction for Honda Scoopy motorbikes at the Mina Spn Motor Dealer. There is a significant influence of promotion on customer satisfaction for Honda Scoopy motorbikes at the Mina Spn Motor Dealer. There is an insignificant influence on purchasing decisions on customer satisfaction for Honda Scoopy motorbikes at the Mina Spn Motor Dealer. There is an insignificant influence of product quality on customer satisfaction through the decision to purchase a Honda Scoopy motorbike at the Mina Spn Motor Dealer. There is an insignificant influence of price on customer satisfaction through the decision to purchase a Honda Scoopy motorbike at the Mina Spn Motor Dealer. There is an insignificant effect of promotion on customer satisfaction through the decision to purchase a Honda Scoopy motorbike at the Mina Spn Motor Dealer]]>
<![CDATA[Overview of Outpatient Patient Prescription Completeness in Pharmacy Installation o f General Hospital Indonesia Christian University ]]>
<![CDATA[Lumbantobing, Romauli]]>;
<![CDATA[Hendrika, Wendy]]>;
<![CDATA[Pradnyanata, Made Gandeva]]>
<![CDATA[ International Journal of Health Engineering and Technology Vol. 4 No. 2 (2025): IJHET JULY 2025 ]]>
Publisher : <![CDATA[CV. AFDIFAL MAJU BERKAH ]]>
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DOI: 10.55227/ijhet.v4i2.287
<![CDATA[Medication errors are preventable and endangering events that still occur when patients receive treatment from healthcare professionals. One form of such error is incomplete prescriptions, which can have a negative impact on the effectiveness of therapy and patient safety. This phenomenon is commonly found in various healthcare facilities in Indonesia. Methods: This study aims to determine the completeness of outpatient prescriptions at the Pharmacy Installation of the Indonesian Christian University General Hospital (RSU UKI), especially from the administrative and pharmaceutical aspects. This study is a non-experimental retrospective descriptive study with a quantitative approach. Samples were taken randomly directly from outpatient prescriptions that entered the UKI Hospital Pharmacy Installation during the period October to December 2022. Results: From the evaluation results of the prescriptions studied, data was obtained that the level of completeness in the administrative aspect included: pro (patient and doctor identity) of 73.80%, inscriptio (health care facility identity) 92.85%, invocatio (symbol R/) 100%, and subscriptio (technical instructions for pharmacists) 79.77%. Meanwhile, in the pharmaceutical aspect, the level of completeness of the signatura (instructions for use for patients) reached 91.67% and prescriptio (medicine name, dosage, dosage form, and quantity) was 88.39%. Conclusion: The results of the study indicate that most outpatient prescriptions at the Pharmacy Installation of RSU UKI have met the standards of administrative and pharmaceutical completeness. However, there are still shortcomings in several components, especially in the pro and subscriptio sections. Efforts are needed to improve accuracy in writing prescriptions by medical personnel to minimize the risk of medication errors and improve patient safety.]]>
<![CDATA[The Relationship Between the Level of Knowledge and Patterns of Use of Traditional Medicine As Self-Medication on Health Maintenance in the Kelurahan Cawang, East Jakarta ]]>
<![CDATA[Silaban, Hertina]]>;
<![CDATA[Utomo, Tranggono Yudo]]>;
<![CDATA[Pangestika, Vania]]>
<![CDATA[ International Journal of Health Engineering and Technology Vol. 4 No. 2 (2025): IJHET JULY 2025 ]]>
Publisher : <![CDATA[CV. AFDIFAL MAJU BERKAH ]]>
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DOI: 10.55227/ijhet.v4i2.288
<![CDATA[Many Indonesians use traditional medicine to maintain their health status. Self-medication is a common practice that many people do to overcome minor health problems before seeking professional medical help. The purpose of this study was to determine how well the residents of RW 11 Kelurahan Cawang East Jakarta know about traditional medicine and how to use it to maintain health. The research method was a cross-sectional questionnaire survey with an observational analytic design. In this study, a total of 147 participants were selected using a selective selection strategy, which is not a random sampling procedure. According to the data collected, most of the respondents were male (55.1%), the highest age range was 50-59 years old (33.3%), and the education level was high school (59.9%). The results showed that 76.2% (112 people) had a good level of knowledge in the use of traditional medicine. The majority of Cawang people have used traditional medicine as self-medication, classified as a good group of 78.9% (116 people). To maintain health in the use of traditional medicine is classified as a good group of 59.9% (88 people). The linear graph also shows there is a linear relationship between the extent of the Cawang community's knowledge of traditional medicine and the frequency with which they use it as self-medication to maintain health. There needs to be more emphasis on educating the community about the benefits of traditional medicine and how to use it safely and effectively.]]>
