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All Journal TRIHAYU: Jurnal Pendidikan Ke-SD-an International Journal of Health, Engineering and Technology Sevaka: Hasil Kegiatan Layanan Masyarakat
Intan nur Fitriyani
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Agriculture, Biological Sciences & Forestry Humanities Chemical Engineering, Chemistry & Bioengineering Dentistry Education Engineering Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Public Health Social Sciences Veterinary

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PENINGKATAN KETERAMPILAN MENULIS PARAGRAF MELALUI MEDIA PUZZLE PADA SISWA KELAS III SD N REJOWINANGUN 1 YOGYAKARTA Intan nur Fitriyani; Siti Anafiah
TRIHAYU: Jurnal Pendidikan Ke-SD-an Vol 3 No 3 (2017)
Publisher : Universitas Sarjanawiyata Tamansiswa

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (497.007 KB) | DOI: 10.30738/trihayu.v3i3.1878

Abstract

This research was aimed at describing the improvement of skill in writing paragraph using puzzle for students of grade III at SD Negeri Rejowinangun 1 Yogyakarta. The type of this research was  Classroom Action  Research  (CAR)  which  was  conducted  in  two  cycles.  The  result  of  this research showed that by using puzzle as the media could improve the skill in writing paragraph for students in class IIIA at SD Negeri Rejowinangun 1 Yogyakarta. The students’ mean score obtained in the pre-test was 65,08 and increased into 78,4 in the post-test of Cycle I and then become 83,16 in the post-test of Cycle II. Based on the result of the research above, it could be concluded that the use of puzzle as the media could improve third grade students’ skill in writing paragraphs at SD Negeri Rejowinangun 1 Yogyakarta.
Edukasi Tentang Pemanfaatan Internet dan Teknologi Internet Of Things (IoT) di Kelurahan Padang Matinggi, Kecamatan Rantau Utara Riszki Fadillah; Intan Nur Fitriyani
Sevaka : Hasil Kegiatan Layanan Masyarakat Vol. 3 No. 1 (2025): Februari : Sevaka : Hasil Kegiatan Layanan Masyarakat
Publisher : STIKES Columbia Asia Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62027/sevaka.v3i1.311

Abstract

The utilization of internet technology and the Internet of Things (IoT) has become an integral part of various aspects of modern life, including the development of Community Social Worker (PSM) cadres' capacity. This study aims to provide education on the use of the internet and IoT to PSM cadres in Padang Matinggi Village, Rantau Utara Subdistrict, so they can optimize these technologies in supporting their social work activities. This community service activity is carried out through counseling and training that covers the basics of internet usage, the introduction of IoT concepts, and their application in social data management and community activities. The results of this activity showed a significant improvement in the participants' understanding of the technology provided, measured through pre-test and post-test evaluations. With a better understanding of technology, it is expected that PSM cadres can be more effective in performing their duties and contribute to improving the welfare of the community in Padang Matinggi Village.
Analysis of Factors Causing Students' Failure to Complete Their Thesis on Time Using the Random Forest Algorithm Riszki Fadillah; Intan Nur Fitriyani; Nur Indah Nasution; Rahadatul 'Aisy Riadi; Dinda Salsabila Ritonga
International Journal of Health Engineering and Technology (IJHET) Vol. 3 No. 1 (2024): IJHET May 2024
Publisher : CV. AFDIFAL MAJU BERKAH

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55227/ijhet.v3i1.281

Abstract

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.
Simulation and Detection of Phishing Attacks on Student Academic Emails Using Social Engineering Techniques Santosa Pohan; Desi Irfan; Intan Nur Fitriyani; Yusril Iza Mahendra Hasibuan; Indah Chayani
International Journal of Health Engineering and Technology (IJHET) Vol. 2 No. 4 (2023): IJHET NOVEMBER 2023
Publisher : CV. AFDIFAL MAJU BERKAH

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55227/ijhet.v2i4.283

Abstract

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.
Penyuluhan Penerapan Metode Naive Bayes Untuk Kalsifikasi Data Pasien Tipus Di RSUD Rantauprapat Intan Nur Fitriyani; Quratih Adawiyah; Rika Handayani; Fitriyani Nasution; Dinda Salsabila Ritonga
Sevaka : Hasil Kegiatan Layanan Masyarakat Vol. 2 No. 4 (2024): November: Sevaka : Hasil Kegiatan Layanan Masyarakat
Publisher : STIKES Columbia Asia Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62027/sevaka.v2i4.524

Abstract

Typhoid fever is an infectious disease caused by the bacterium Salmonella typhi, commonly found in developing countries, including Indonesia. Prompt and accurate treatment is crucial to prevent serious complications in patients. One way to assist in diagnosing typhoid fever is by applying machine learning methods to classify patient data. The Naive Bayes method is one of the machine learning algorithms frequently used in medical data classification due to its strong ability to handle large and complex datasets. This article discusses the application of the Naive Bayes method for classifying typhoid patient data at Rantauprapat General Hospital (RSUD Rantauprapat). By utilizing medical data that includes clinical symptoms, laboratory test results, and patients’ medical histories, the Naive Bayes model can provide fairly accurate predictions regarding the likelihood of a person having typhoid fever. The research findings indicate that Naive Bayes is reliable in predicting typhoid diagnoses with adequate accuracy, thereby supporting healthcare professionals in making faster and more precise decisions. It is expected that the implementation of this method can accelerate the diagnostic process and improve the quality of healthcare services at RSUD Rantauprapat, as well as in other regions.
Penyuluhan Penerapan K-Means Clustering Dalam Pengelompokan Data Keuangan Rumah Sakit Untuk Pengelolaan Anggaran Di RSUD Rantauprapat Intan Nur Fitriyani; Evri Ekadiansyah; Indah Cahyani
Sevaka : Hasil Kegiatan Layanan Masyarakat Vol. 2 No. 2 (2024): Mei : Sevaka : Hasil Kegiatan Layanan Masyarakat
Publisher : STIKES Columbia Asia Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62027/sevaka.v2i2.536

Abstract

Financial management in hospitals is a crucial aspect to ensure the sustainability of quality health services. However, the complexity of financial data, which involves various budget components, often creates challenges for hospital management in conducting accurate analysis and budget planning. Therefore, a data-driven approach is required to present financial information in a structured and comprehensible manner. This study examines the application of the K-Means Clustering method to classify hospital financial data based on expenditure characteristics and patterns, with a case study at RSUD Rantau Prapat as part of a community service program. The financial data were analyzed through pre-processing stages, determination of the optimal number of clusters using the Elbow Method, and the implementation of the K-Means algorithm to generate more representative budget groups. The results indicate that clustering hospital financial data into three main categories—routine operational costs, medical service costs, and administrative/personnel costs—provides clearer insights into budget distribution. This supports hospital management in identifying budget allocation priorities, detecting potential inefficiencies, and improving the overall efficiency of financial governance. The limitation of this study lies in the data scope, which only involved a single hospital, thus restricting its generalizability. Future research is recommended to expand the scope to multiple hospitals and integrate alternative clustering methods to obtain more comprehensive results.
Co-Authors Desi Irfan Dinda Salsabila Ritonga Evri Ekadiansyah Fitriyani Nasution INDAH CAHYANI Indah Chayani Nur Indah Nasution Quratih Adawiyah Rahadatul 'Aisy Riadi Rika Handayani Riszki Fadillah Santosa Pohan Siti Anafiah Yusril Iza Mahendra Hasibuan