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All Journal Data Science: Journal of Computing and Applied Informatics STATISTIKA Konstanta : Jurnal Matematika dan Ilmu Pengelatuan Alam Interdisciplinary Explorations in Research Journal (IERJ)
Sisti Nadia Amalia
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Analisis Faktor-Faktor yang Berhubungan dengan Kejadian Stres Pada Mahasiswa Tingkat Akhir S1 Matematika di Universitas Negeri Medan Sitepu, Eliya; Juliana Tampubolon; Sudianto Manulang; Sisti Nadia Amalia
Statistika Vol. 24 No. 1 (2024): Statistika
Publisher : Department of Statistics, Faculty of Mathematics and Natural Sciences, Universitas Islam Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29313/statistika.v24i1.3257

Abstract

ABSTRAK Stres adalah respons adaptif individual terhadap stimulus yang dianggap mengancam, dapat dialami oleh siapa saja, termasuk mahasiswa tingkat akhir. Penelitian ini fokus pada faktor-faktor yang memengaruhi tingkat stres mahasiswa tingkat akhir S1 Matematika di Universitas Negeri Medan, dengan penekanan pada penyusunan tugas akhir (skripsi). Beberapa faktor, seperti tuntutan akademik, masalah pribadi (manajemen waktu, motivasi, dukungan keluarga), dan aturan batas masa studi, diidentifikasi sebagai penyebab stres.Metode penelitian menggunakan pendekatan kuantitatif non-eksperimental dengan uji korelasi Rank Spearman. Hasil penelitian menunjukkan korelasi cukup kuat (0.380) antara faktor kejadian stres dan tingkat stres mahasiswa. Meskipun tidak mencapai tingkat signifikansi yang umum, temuan ini mengindikasikan bahwa mahasiswa yang mengalami berbagai faktor kejadian stres cenderung memiliki tingkat stres yang lebih tinggi. Penelitian ini memberikan wawasan mendalam tentang kompleksitas faktor-faktor yang berkontribusi terhadap stres mahasiswa tingkat akhir, menunjukkan perlunya pendekatan holistik dan intervensi terintegrasi dari perguruan tinggi untuk membantu mahasiswa mengelola stres dengan lebih efektif. Temuan ini juga memberikan dasar bagi pengembangan program dukungan dan pembinaan untuk membantu mahasiswa mengatasi tantangan akademik dan pribadi. ABSTRACT Stress is an individual adaptive response to a stimulus that is perceived as threatening, can be experienced by anyone, including final year students. This research focuses on the factors that influence the stress level of final year undergraduate mathematics students at Medan State University, with an emphasis on the preparation of the final project (thesis). Several factors, such as academic demands, personal problems (time management, motivation, family support), and study period limit rules, were identified as causes of stress.The research method used a non-experimental quantitative approach with the Spearman Rank correlation test. The results showed a moderately strong correlation (0.380) between stress event factors and students' stress levels. Although not reaching the usual level of significance, this finding indicates that college students who experience multiple stressful event factors tend to have higher stress levels. This study provides an in-depth insight into the complexity of factors contributing to final year university students' stress, suggesting the need for a holistic approach and integrated interventions from universities to help students manage stress more effectively. The findings also provide a basis for the development of support and coaching programs to help college students overcome academic and personal challenges.
Peramalan Prakiraan Cuaca Setiap Hari di Kota Medan dengan Pendekataan Rantai Markov Septia Cahaya Sari Sipayung; Thanaya Lovry Lastiar; Trinita Melyana Hutagalung; Sisti Nadia Amalia
Konstanta : Jurnal Matematika dan Ilmu Pengetahuan Alam Vol. 2 No. 2 (2024): Juni : Jurnal Matematika dan Ilmu Pengetahuan Alam
Publisher : International Forum of Researchers and Lecturers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59581/konstanta.v2i2.3516

Abstract

This research utilizes the Markov Chain method to analyze daily weather data in the city of Medan. The main objective of this study is to forecast weather changes in the future based on the weather conditions of the previous day. Daily weather data was collected from the nearest weather station over a specific period of time. The analysis results indicate that the Markov Chain model provides good estimates of the likelihood of weather changes from one day to the next. The steady state probabilities demonstrate the dominance of partly cloudy and clear weather in the long term. This research provides valuable insights for various sectors related to weather, such as agriculture, transportation, and tourism.
Peramalan Bencana Alam di Kota Semarang dengan Menggunakan Markov Chains Suci Ramadhani; Surya Alenta Nababan; Yasmin Azzahra; Sisti Nadia Amalia
Konstanta : Jurnal Matematika dan Ilmu Pengetahuan Alam Vol. 2 No. 2 (2024): Juni : Jurnal Matematika dan Ilmu Pengetahuan Alam
Publisher : International Forum of Researchers and Lecturers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59581/konstanta.v2i2.3519

Abstract

Indonesia, as a country with complex geological conditions due to the convergence of various tectonic plates, is highly susceptible to natural disasters such as earthquakes, tsunamis, and volcanic eruptions. The city of Semarang, as the capital of Central Java Province, also frequently faces disasters such as floods, landslides, and earthquakes. Predicting the occurrence of natural disasters becomes crucial to mitigate the negative impacts they cause. This study uses the Markov chain method to predict natural disasters in the city of Semarang based on disaster data from 2018-2022. The prediction results indicate a 16% chance of floods, 34% chance of landslides, 10% chance of tornadoes, 22% chance of fires, and 17% chance of falling trees in 2023. Validation of the predictions against actual data for 2023 shows a relatively good match for floods and fires, but there are significant differences in the predictions for tornadoes and falling trees. These results indicate that the Markov chain method has potential in predicting disaster occurrences, but accuracy improvements are needed to account for weather variability and dynamic environmental factors. This research is expected to assist the government and society in enhancing disaster preparedness and mitigation in the future.
Analisis Model Sistem Antrian Pada Pelayanan Konsumen Mie Gacoan Cabang Pancing Kota Medan Yohana Sitorus; Sukma Dermawan Saragih; Wahyuni Susi Sulastri Berasa; Sisti Nadia Amalia
Konstanta : Jurnal Matematika dan Ilmu Pengetahuan Alam Vol. 2 No. 2 (2024): Juni : Jurnal Matematika dan Ilmu Pengetahuan Alam
Publisher : International Forum of Researchers and Lecturers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59581/konstanta.v2i2.3521

Abstract

This research aims to analyze the queuing system model for consumer service at Mie Gacoan Pancing Branch, Medan City. With the increasing popularity of Mie Gacoan, there has been a significant increase in the number of customers, resulting in long queues and long waiting times. This research uses observation and interview methods to collect data regarding the number of customers, arrival time, service time, and number of available waiters. The data is then analyzed using the M/M/1 and M/M/c queuing models to determine queue characteristics such as average queue length, average waiting time in the queue, and waiter utility. The analysis results show that the M/M/c queuing model is more effective in reducing waiting time and queue length compared to the M/M/1 model. By increasing the number of waiters, service efficiency can be increased, thereby increasing customer satisfaction. This research provides strategic recommendations for the management of Mie Gacoan Pancing Branch in optimizing the queuing system to provide better service to consumers.
Evaluasi Perencanaan Produksi Kubis Di Sumatera Utara Dengan Metode Rantai Markov Waktu Diskrit Witri Wardani Hulu; Talitha Nakhwan Hasibuan; Widya Narti Lubis; Sudianto Manullang; Sisti Nadia Amalia
Konstanta : Jurnal Matematika dan Ilmu Pengetahuan Alam Vol. 2 No. 3 (2024): September : Jurnal Matematika dan Ilmu Pengetahuan Alam
Publisher : International Forum of Researchers and Lecturers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59581/konstanta.v2i3.3736

Abstract

This research aims to evaluate cabbage production planning in North Sumatra using the discrete-time Markov chain method. Cabbage is one of the horticultural agricultural products that plays an important role in North Sumatra's exports. Proper evaluation of production plans is necessary to ensure sustainability and increase productivity and export volume. The Discrete Time Markov Chain method is used to predict changes in cabbage production conditions over time by considering the factors that influence them. Data on cabbage production and harvested area in North Sumatra from 2020 to 2022 were analyzed using one-step and n-step transition opportunity matrices. The results of the analysis show that in 2023, cabbage production and harvested land area are predicted to experience a significant increase compared to the previous year. This research provides a more accurate and efficient planning strategy for cabbage production, which can ultimately improve agricultural management in North Sumatra.
Analisis Uji Median K-Sampel Independen untuk Mengidentifikasi Jumlah Penduduk di Sumatera Utara Septi Melani Putri Tambunan; Shalsha Nazillah; Talitha Nakhwan Hasibuan; Sisti Nadia Amalia
Interdisciplinary Explorations in Research Journal Vol. 2 No. 3 (2024)
Publisher : PT. Sharia Journal and Education Center

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

Abstract

This study aims to analyze the distribution of the population in North Sumatra using the Independent K-Sample Median Test on the 2023 data. The statistical test results show that there is no significant difference in the population numbers across the districts/cities in North Sumatra, with a Chi-Square value of 33 and a P-Value of 0.418, which is greater than 0.05. The Post Hoc analysis revealed that all groups have the same value, indicating a relatively even distribution of the population. Additionally, the overall median population in North Sumatra is 312,540, with minimal variation around this value. The study concludes that the population distribution in North Sumatra does not show significant differences among the tested groups.
Hubungan Antara Tingkat Penggunaan Media Sosial dengan Tingkat Produktivitas Mahasiswa dalam Menyelesaikan Tugas Akademik Suci Ramadhani; Surya Alenta Nababan; Yasmin Azzahra; Sisti Nadia Amalia
Interdisciplinary Explorations in Research Journal Vol. 2 No. 3 (2024)
Publisher : PT. Sharia Journal and Education Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62976/ierj.v2i3.790

Abstract

Social media has become an integral part of students' lives, serving as a tool for communication, a source of information, and a means of entertainment. This study aims to analyze the relationship between the level of social media usage and students' productivity in completing academic tasks. The research employs a descriptive correlational quantitative approach, with data collected through online questionnaires using ordinal scales. The respondents were active students from various universities. The analysis was conducted using Spearman's Rank correlation test and the t-test for significance. The results show a moderate positive relationship between social media usage and academic productivity, with a Spearman's Rank correlation coefficient (rₛ) of 0.483. The significance test indicates a t-value of 3.819, which is greater than the critical t-value of 1.677 at the 5% significance level. This demonstrates that the relationship found is statistically significant. The study concludes that prudent use of social media can contribute to enhancing students' productivity in completing academic tasks, although the relationship is not particularly strong. The implications of this study highlight the importance of time management and social media activity regulation to optimally support academic productivity.
Spatial Clustering Analysis of Stunting in North Sumatra Based on Environmental Factors Using K-Means Algorithm Fanny Ramadhani; Dian Septiana; Sisti Nadia Amalia; Putri Maulidina Fadilah; Andy Satria
Data Science: Journal of Computing and Applied Informatics Vol. 9 No. 2 (2025): Data Science: Journal of Computing and Applied Informatics (JoCAI)
Publisher : Talenta Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32734/jocai.v9.i2-17179

Abstract

This research aims to analyze the spatial grouping of stunting events in North Sumatra based on environmental factors using the K-Means algorithm. The data used in this research includes the incidence of stunting, environmental factors (such as access to health services, living environment conditions, water use and sanitation), and spatial data (geographical coordinates). The data comes from Basic Health Research (RISKESDAS 2018, then processed and normalized. The elbow method and silhouette analysis are used to determine the optimal number of clusters, resulting in four different clusters. The application of the K-Means algorithm produces the following cluster characteristics: Cluster 1, with good environmental conditions and access to health services, shows low levels of stunting; Cluster 2, with moderate environmental conditions, shows moderate levels of stunting; Cluster 3, which is characterized by poor living conditions and limited access to health services, has levels high stunting; and Cluster 4, with varied environmental conditions but very limited access to health and sanitation services, also shows a high stunting rate. Validation using the Silhouette Coefficient produces an average score of 0.65 which indicates good clustering quality shows that environmental factors, access to health services, and sanitation conditions have a significant impact on the incidence of stunting. Based on these findings, policy and intervention recommendations are focused on Clusters 3 and 4, which have high stunting rates. The interventions carried out include increasing access and quality of nutrition, health services, sanitation conditions, economic empowerment, and health education.
Co-Authors Andy Satria Dian Septiana Juliana Tampubolon Manullang, Sudianto Putri Maulidina Fadilah Ramadhani, Fanny Septi Melani Putri Tambunan Septia Cahaya Sari Sipayung Shalsha Nazillah Sitepu, Eliya Suci Ramadhani Sudianto Manulang Sukma Dermawan Saragih Surya Alenta Nababan Talitha Nakhwan Hasibuan Thanaya Lovry Lastiar Trinita Melyana Hutagalung Wahyuni Susi Sulastri Berasa Widya Narti Lubis Witri Wardani Hulu Yasmin Azzahra Yohana Sitorus