Claim Missing Document
Check
Articles

Found 4 Documents
Search

The QoL of College Students and Its Impact on Stress Level: A Cross-Sectional Study Karimah, Rinda Nurul; Destarianto, Prawidya; Perwiraningrum, Dhyani Ayu; Ardianto, Efri Tri
International Journal of Health and Information System Vol. 2 No. 3 (2025): January
Publisher : Indonesian Journal Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47134/ijhis.v2i3.51

Abstract

The peak of vulnerability to behavioral and mental disorders occurs during college, making this a crucial time for development. College students have a worse quality of life (QoL) in terms of mental health compared to the general population. There is a need for information regarding QoL related to stress in students, as studies discussing QoL and stress in college students are still lacking. This study aims to analyze the relationship between QoL and stress levels in college students. A cross-sectional survey design was used in this study, involving 249 college students at higher education institutions in East Java, Indonesia. The data samples were collected based on demographic characteristics, using the QoL scale from WHOQOL-BREF and the Depression, Anxiety, and Stress Scale-21 to assess the correlation between QoL and stress levels among college students. The results showed that the stress levels of college students were classified as normal (54.6%), mild (17.3%), moderate (17.3%), severe (8.4%), and extremely severe (2.4%). A significant negative correlation was observed between all domains of QoL and stress: Physical (-0.630), Psychological (-0.658), Social Relationship (-0.564), and Environment (-0.584). These results indicate that as QoL increases, stress scores decrease. Attention should be paid to providing appropriate interventions related to college students' quality of life. Further research is needed to gather detailed information on existing QoL domains, particularly those focusing on students’ needs, current information developments, and demographic characteristics.
Diagnosis of Stroke and Diabetes Mellitus With Classification Techniques Using Decision Tree Method Pratama, Mudafiq Riyan; Suryana, Arinda Lironika; Alfiansyah, Gamasiano; Olivia, Zora; Nurmawati, Ida; Destarianto, Prawidya
International Journal of Health and Information System Vol. 2 No. 1 (2024): May
Publisher : Indonesian Journal Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47134/ijhis.v2i1.36

Abstract

: Stroke is a cerebral vascular disease characterized by the death of brain tissue that occurs due to reduced blood and oxygen flow to the brain. Ischemic stroke is associated with diabetes mellitus, therefore it is important to identify the risk factors that cause stroke and DM by diagnostic cause of the disease. This study aimed to classify and compare accuracy tests on medical record data sets for stroke and DM. This study analyzed the diagnosis of stroke and DM using Decision Tree. The risk factors consisted of gender, age, blood pressure, nutritional status, smoking, history of DM, and history of hypertension. The results of the analysis using the Decision Tree method showed that the accuracy rate was 86.67%, which means that the modeling has a good level of correctness of the prediction results. We conclude that the Decision Tree method was an accurate method for detecting stroke and DM.
Diseminasi Sistem Informasi Promosi Wisata Terintegrasi Berbasis Internet+ Choirunnisa, Shabrina; Destarianto, Prawidya; Resya, Fachmi; Hartadi, Didit Rahmat; Agustianto, Khafidurrohman; Kurniawan, Bagus Putu Yudhia; Mahanani, Retno Sari; Galushasti, Andarula; Suranto, Dwi Djoko
Agrimas : Jurnal Pengabdian Masyarakat Bidang Pertanian Vol. 4 No. 2 (2025): OKTOBER
Publisher : Politeknik Negeri Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25047/agrimas.v4i2.66

Abstract

Sektor wisata memiliki nilai ekonomi yang tinggi, hal ini sejalan dengan arah pengembangan Politeknik Negeri Jember menjadi Badan Layanan Umum (BLU). Sebagai agen pemerintah BLU dituntut untuk melakukan langkah-langkah extraordinary di bidangnya masing-masing, sehingga diharapkan dapat berkontribusi untuk mendorong pertumbuhan ekonomi nasional. Namun sektor wisata termasuk didalamnya wisata edukasi memiliki tantangan yaitu arah pengembangan wisata yang bekerkelanjutan. Pengabdian sebelumnya bertujuan untuk menjawab tantangan tersebut dengan mendesiminasikan aplikasi Sistem Educational Tourism Terintegrasi dengan Adopsi Internet + yang memiliki fitur: promosi, reservasi, dan fitur pendukung lainnya. Sistem Educational Tourism Terintegrasi dengan Adopsi Internet + yang didesiminasikan pada pengabdian ini sesuai dengan RIP Politeknik Negeri Jember 2021-2025, Jurusan Teknologi Informasi, Isu Strategis Informasi. Sistem Educational Tourism Terintegrasi dengan Adopsi Internet + yang didesiminasikan pada pengabdian ini bertujuan untuk membuat portal informasi dan pemesanan Wisata Edukasi dilingkungan Politeknik Negeri Jember, sebagai produk unggul dari TEFA JTI Innovation. Melalui pengabdian ini diharapkan dapat menyelesaikan dua permasalahan: a) meningkatkan kualitas manajemen dan promosi pada wisata edukasi TEFA di lingkungan Politeknik Negeri Jember melalui produk unggulan TEFA JTI Innovation, dan b) implementasi Internet+ dengan pendekatan teknologi informasi untuk peningkatan layanan dan ekonomi sebagai bentuk dukungan sebagai tulang punggung perekomian nasional.
Water Quality Modelling (WQM) Using Machine Learning (ML) For Surface Modelling of Shrimp Pond Vehicles Using Smart Water Optimization (SWO) Destarianto, Prawidya; Gemaputri, Ariesia Ayuning; Wijanarko, Denny; Mulyadi, Ely
International Journal of Technology, Food and Agriculture Vol. 3 No. 1 (2026): Pebruary
Publisher : P3M Politeknik Negeri Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25047/tefa.v3i1.6735

Abstract

Indonesia is one of global major aquaculture producer. White leg shrimp is considered a superior commodity due to its growth resilience. Therefore, annual white leg production is increasing from 2018 at 932,698 tons. In regard to these findings, the shrimp farming sector appears to hold great promise. But the quality of the water, which constantly fluctuates, is a key factor in shrimp farming success. However, in line with united nation (UN) sustainable development goals (SDGs) 12 in which requiring optimization on food production. The farming environment such as temperature, pH, and the availability of phytoplankton—a natural source of shrimp food—all have an impact on the water quality. To guarantee ideal circumstances, these parameters have to stay inside predetermined bounds. Automated water quality control is critical to improve shrimp production efficiency. The main goal of this research is to apply a fuzzy algorithm to create surface modelling vehicle for shrimp ponds (SMV-SP) where utilize the same sensor as autonomous surface vehicles (ASVs), but instead of classifying the sensors based on coral reef monitoring, the reference is optimal water condition to support shrimp growth. A 92% accuracy rate is indicated by the test finding. The result confirms ReSMeV-SP is able to improve water quality thus enabling more efficient and enhanced yield of shrimp production.