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All Journal Media Statistika JURNAL MATEMATIKA STATISTIKA DAN KOMPUTASI Edumatsains AKSIOMA BAREKENG: Jurnal Ilmu Matematika dan Terapan JTAM (Jurnal Teori dan Aplikasi Matematika) Jurnal Pengabdian Masyarakat Bumi Raflesia Journal of Midwifery Jurnal Kesehatan Tambusai Griya Journal of Mathematics Education and Application Indonesian Journal of Community Empowerment and Service Journal of Statistics and Data Science Journal for Quality in Women's Health
Ramya Rachmawati
Jurusan Matematika Fakultas Matematika Dan Ilmu Pengetahuan Alam Universitas Bengkulu
Agriculture, Biological Sciences & Forestry Humanities Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Education Energy Engineering Health Professions Languange, Linguistic, Communication & Media Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Physics Public Health Social Sciences Transportation Other

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Journal : Edumatsains

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ANALYSIS OF THE ANALYTIC HIERARCHY PROCESS (AHP) METHOD IN DETERMINING PRIORITY DECISIONS FOR HANDLING STUNTING IN BENGKULU PROVINCE Rewan Jayadi; Ramya Rachmawati; Siska Yosmar
EduMatSains : Jurnal Pendidikan, Matematika dan Sains Vol 8 No 2 (2024): Januari
Publisher : Fakultas Keguruan dan Ilmu Pendidikan, Universitas Kristen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33541/edumatsains.v8i2.5577

Abstract

Statistical Processing Data 2021 shows that technical efficiency in stunting intervention costs in Bengkulu Province always achieves efficient results in the technical system, however, for that reason, it is technically inefficient in costs. This research aims to analyze the Analytical Hierarchy Process (AHP) method in deciding to determine priorities for handling stunting in Bengkulu Province, which will then get results according to the level of needs of each district/city. This study used the AHP method to determine priorities for handling stunting by collecting primary data directly from respondents, namely the Bengkulu Province Health Service. Validity and reliability tests are used before researching to obtain good research results suitable for development. The results of the consistency test showed that the Consistency Ratio (CR) value for each criterion and the alternative was, which means that the filling and results of the questionnaire for respondents had obtained results that met the requirements. The results of the analysis of preferences for criteria/alternatives show that the main priority in making decisions for handling stunting in Bengkulu Province is North Bengkulu as the main priority, followed by South Bengkulu, Seluma, Rejang Lebong, Kepahiang, Central Bengkulu, Bengkulu, Mukomuko, Lebong, and finally Kaur. Keywords: Analytic Hierarchy Process, Consistency Ratio, stunting, Bengkulu Province.
Using Ant Colony Optimization to Solve a Vehicle Routing Problem: Waste Transportation Routes in Bengkulu City Case Study Ramya Rachmawati; Siska Yosmar
EduMatSains : Jurnal Pendidikan, Matematika dan Sains Vol 9 No 2 (2025): January
Publisher : Fakultas Keguruan dan Ilmu Pendidikan, Universitas Kristen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33541/edumatsains.v9i2.6635

Abstract

The waste problem is one of the serious problems faced by every city in Indonesia, including Bengkulu City. To overcome the problem of waste production which continues to increase every day, the government's role is needed in efforts to transport waste with various facilities and support from the surrounding community. One effort to solve the problem of waste piling up in Temporary Disposal Sites (TPS) is to schedule effective transportation to Final Disposal Sites (TPA). To do the scheduling, one possible approach is a mathematical approach. The purpose of this research is to build a Vehicle Routing Problem (VRP) model using Ant Colony Optimization (ACO), and determine the solution of this model to determine the optimal solution to the problem of transporting waste from all TPS to TPA. This research involved 29 TPS in Bengkulu City. This model is solved using Python 2.7 programming language and PuLP modeller and CPLEX Solver. With 2000 iterations, solutions were found in a relatively short time, which is less than 10 minutes. There are 6 garbage transportation routes in Bengkulu City which are considered as a VRP problem by using ACO which can transport garbage and considering the capacity of garbage trucks. From this route, a total distance of 128 km is obtained.
Markov Chain Model for Daily Rainfall Modeling in Bengkulu City Rachmawati, Ramya; Firdaus; Ratna Widayati; Siska Yosmar; Risfa Fadila; Ajeng Siti Nurul Kharima
EduMatSains : Jurnal Pendidikan, Matematika dan Sains Vol 10 No 4 (2026): April
Publisher : Fakultas Keguruan dan Ilmu Pendidikan, Universitas Kristen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33541/edumatsains.v10i4.8000

Abstract

Bengkulu City is a region in Indonesia that is particularly vulnerable to shifts in rainfall patterns, which can have significant impacts on the agricultural sector, water resource management, and disaster mitigation. The uncertainty in rainfall patterns often complicates long-term planning. Hence, it is necessary to adopt a statistical approach that can model and predict rainfall characteristics with greater accuracy. This research aims to develop a Markov Chain model to represent the daily rainfall regime in Bengkulu City. The daily rainfall data are categorized into rainfall intensity states, namely: no rain, light, moderate, heavy, or very heavy rainfall. By leveraging historical daily rainfall data, this model is expected to identify the transition probabilities between these states. Based on the obtained steady-state probabilities, it can be concluded that regardless of today’s rainfall condition in Bengkulu City, the long-term probabilities for tomorrow’s weather are as follows: 38% for no rain, 43% for light rain, 13.8% for moderate rain, 4.2% for heavy rain, and 1% for very heavy rain.
Co-Authors Abda Abda Agwil, Winalia Ajeng Siti Nurul Kharima Alwansyah, Muhammad Arib APRIANISA, TRI Asmariyah Deni Maryani Dewiani, Kurnia Dwi Kumala, Siska Faisal, Fahri Fakhry Asad Agusfrianto Firdaus Fransiska, Welly Jose Rizal Jumeysi Herlina Irawan Muhammad Chairul Imam Novianti Novianti Nur Afandi Nurul Hidayati Putriasari, Novi Rafflesia, Ulfa Ratna Widayati Ratna Widayati Rewan Jayadi Rina Filia Sari Rina Widyasari Risfa Fadila Saniyyah, Nabilah Sarumpaet, Mey Yanti Septa, Oon Septri Damayanti Setiawan, Aisyah Nooravieta Sigit Nugroho Siska Yosmar Sitohang, Yosep O Suci Rahmawati Wijuniamurti, Susi Yusanti, Linda