Garuda - Garba Rujukan Digital

HUBUNGAN ANTARA ASUPAN KAFEIN, KUALITAS TIDUR DAN STATUS GIZI DENGAN TEKANAN DARAH Khoerunisa, Sarah; Hermanto, Restu Amalia; Aminarista, Aminarista
Journal of Holistic and Health Sciences (Jurnal Ilmu Holistik dan Kesehatan) Vol. 3 No. 1 (2019): Journal of Holistic and Health Sciences (Jurnal Ilmu Holistik dan Kesehatan)
Publisher : Sekolah Tinggi Ilmu Kesehatan Holistik

Background: approximately 9.4% of men and 8.9% of women in developing countries aged 20-24 years experience high blood pressure. In Indonesia the incidence of high blood pressure in the age group over 18 years is 25.8%. Blood pressure in students can be influenced by caffeine intake, sleep quality and nutritional status. Objective: This study aims to determine the relationship between caffeine intake, sleep quality and nutritional status with blood pressure. Method: This research was conducted at STT Wastukancana students using cross sectional research design and 82 subjects were selected by simple random sampling. Caffeine intake was measured using a semi-quantitative food frequency Questionnaire (SQ-FFQ), sleep quality was measured using the Pittsburgh Sleep Quality Index (PSQI) questionnaire, nutritional status was measured using Body Mass Index (BMI), blood pressure was measured using a digital sphygnomanometer. The relationship of each independent variable with systolic blood pressure was tested using Pearson product momment, whereas the relationship between the independent variable and diastolic blood pressure was tested using the Spearman rank. Multivariate test used multiple linear regression test. Results: Most subjects had high systolic blood pressure (61%) and high diastolic blood pressure (74.4%). Caffeine intake, sleep quality and nutritional status each have a relationship with systolic blood pressure and diastolic blood pressure. Factors associated with increased systolic blood pressure were caffeine intake (B = 0.12; p = 0.004), sleep quality (B = 1.36; p = 0.001) and nutritional status (B = 1.25; p = 0.001). Poor sleep quality of the subjects in this study can be caused by disturbances both before falling asleep or during sleep. Conclusion: High blood pressure is influenced by caffeine intake, sleep quality and nutritional status.

Analisis Sentimen Pengguna Twitter dalam Pemilihan Presiden (PILPRES) 2024 dengan Menggunakan Algoritma K-Means Amin, Abdusy Syakur; Kurniadi, Dede; Nurzaman, Muhammad Zein; Nurfadillah, Rifa Sri; Khoerunisa, Sarah; Khaerunisa, Nisrina; Ajiz, Rafi Nurkholiq; Jembar, Tegar Hanafi; Faisal, Ridwan Nur
Jurnal Algoritma Vol 21 No 1 (2024): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.21-1.1596

One form of upholding democracy carried out by the Unitary State of the Republic of Indonesia is through holding presidential elections or often known as presidential elections. which is held every five years to elect the next President. Apart from that, in this digital era, people are increasingly actively using social media to convey their views, opinions and sentiments regarding the presidential election. Ahead of the 2024 presidential election, many groups such as political parties, success teams, buzzers and supporters are using social media as a campaign medium to increase the popularity and electability of their prospective candidates. One of the social media that is widely used in political party promotion media is Twitter. Which is used by people to post various comments that can be positive or negative regarding the election. Sometimes, people also express hoax opinions before or during the election. Considering that comments on Twitter are currently difficult to categorize as positive or negative, sentiment analysis is needed to understand public attitudes towards the presidential election. This research aims to evaluate text documents and determine whether the documents have a positive or negative sentiment orientation. Apart from that, the method used is K-Means to cluster the data. The results of this weighting are in the form of positive and negative sentiment. Data taken from Twitter regarding the 2024 presidential election (pilpres) totaling 1015 tweet data.

Analisis Sentimen Pengguna Twitter dalam Pemilihan Presiden (PILPRES) 2024 dengan Menggunakan Algoritma K-Means Amin, Abdusy Syakur; Kurniadi, Dede; Nurzaman, Muhammad Zein; Nurfadillah, Rifa Sri; Khoerunisa, Sarah; Khaerunisa, Nisrina; Ajiz, Rafi Nurkholiq; Jembar, Tegar Hanafi; Faisal, Ridwan Nur
Jurnal Algoritma Vol 21 No 1 (2024): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.21-1.1596

One form of upholding democracy carried out by the Unitary State of the Republic of Indonesia is through holding presidential elections or often known as presidential elections. which is held every five years to elect the next President. Apart from that, in this digital era, people are increasingly actively using social media to convey their views, opinions and sentiments regarding the presidential election. Ahead of the 2024 presidential election, many groups such as political parties, success teams, buzzers and supporters are using social media as a campaign medium to increase the popularity and electability of their prospective candidates. One of the social media that is widely used in political party promotion media is Twitter. Which is used by people to post various comments that can be positive or negative regarding the election. Sometimes, people also express hoax opinions before or during the election. Considering that comments on Twitter are currently difficult to categorize as positive or negative, sentiment analysis is needed to understand public attitudes towards the presidential election. This research aims to evaluate text documents and determine whether the documents have a positive or negative sentiment orientation. Apart from that, the method used is K-Means to cluster the data. The results of this weighting are in the form of positive and negative sentiment. Data taken from Twitter regarding the 2024 presidential election (pilpres) totaling 1015 tweet data.

Penerapan Teknologi Dalam Program Kerja KKN Tematik di Dusun 1 Desa Wanamekar Fadli, Dicky Muhamad; Gani, Ilham Abdul; Sumarna, Ertansyah Rizal Priadi; Faturrahman, Muhammad; Mubarok, Husni; Khoerunisa, Sarah; Handihastuti, Sri Deti; Aisah, Sri; Ali, Fiqry Maulana; Hilmi, Rifqi Muhammad; Daffa, Muhammad Alfie Diyaulhaq; Mubarok, Erick Husni; Afgani, Farhan Fauzan Al; Awaludin, Anggi; Fadilah, Hikmatul; Fauziah, Syita; Yulianti, Lisna; Nurjaman, Muhammad Miftah; Ilmi, Bahril; Ramdhani, Rifaldi Muhamad; Febriana, Felinda
Jurnal PkM MIFTEK Vol 3 No 2 (2022): Jurnal PkM MIFTEK
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/miftek/v.3-2.1310

Real Work Lecture is a mandatory activity that combines the implementation of the Tri Dharma of Higher Education with the method of providing learning and work experience to students. Wanamekar Village is one of the villages located in Wanaraja District, Garut Regency. The area of ”‹”‹Wanamekar Village is 78.5 hectares. The rapid growth rate has made the development of settlements for the residents of Wanamekar Village so rapid. According to data obtained from the Village Head, the livelihood of most residents is traders in the market. The potential that can be developed in Wanamekar Village, especially in Hamlet 1, is MSME, including salt, knitting and noga. The method used is the ICT volunteer integration approach which consists of four stages. Based on the results of the KKN activities, several benefits were obtained in the economic field, including the knitting business getting a visual display as a form of implementing K3 in the work area. In the health sector, the results show that the environment is clean and encourages the community to carry out community service. In addition, the community is enthusiastic about visiting the posyandu and the community has adopted a healthy life such as carrying out routine healthy exercise. In the field of education, results were obtained based on data that had been collected from seminars and door to door activities of 500 digitally literate people. In the social field the KKN team succeeded in helping the community in welcoming Independence Day.

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