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All Journal STATISTIKA Konstanta : Jurnal Matematika dan Ilmu Pengelatuan Alam
Sisti Nadia Amalia
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Biochemistry, Genetics & Molecular Biology Chemistry Decision Sciences, Operations Research & Management Earth & Planetary Sciences Immunology & microbiology Mathematics

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Journal : Konstanta : Jurnal Matematika dan Ilmu Pengelatuan Alam

 1 
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.
Co-Authors Juliana Tampubolon Manullang, Sudianto Septia Cahaya Sari Sipayung 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