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All Journal Media Statistika BAREKENG: Jurnal Ilmu Matematika dan Terapan Jurnal Pengabdian Masyarakat Bumi Raflesia Journal of Midwifery Griya Journal of Mathematics Education and Application Journal of Statistics and Data Science
rachmawati, Ramya
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Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Energy Engineering Health Professions Languange, Linguistic, Communication & Media Mathematics Mechanical Engineering Physics Transportation Other

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EFEKTIVITAS AIR REBUSAN DAUN SIRIH MERAH (PIPER CROCATUM) TERHADAP KEPUTIHAN PADA WANITA USIA SUBUR DI PUSKESMAS TELAGA DEWA KOTA BENGKULU APRIANISA, TRI; NOVIANTI, NOVIANTI; MARYANI, DENI; SURIYATI, SURIYATI; RACHMAWATI, RAMYA
Journal Of Midwifery Vol 11 No 2 (2023)
Publisher : UNIVED PRESS, Universitas Dehasen Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37676/jm.v11i2.5117

Abstract

Pendahuluan: Wanita akan mengalami keputihan paling tidak satu kali dalam seumur hidupnya. Keputihan yang berlebihan atau keputihan tidak normal menjadi gejala awal kanker serviks yang dapat menyebabkan kematian pada wanita. Tujuan penelitian ini untuk mengetahui pengaruh air rebusan daun sirih merah terhadap wanita usia subur di Puskesmas Telaga Dewa Kota Bengkulu. Penelitian ini menggunakan sampel sebanyak 44 responden Metode: Rencana penelitian metode eksperimen one group pre-test dan post-test dengan teknik pengambilan sampel menggunakan random sampling, analisa data menggunakan uji univariate distribusi frekuensi dan uji Wilcoxon untuk uji perbedaan. Rata-rata keputihan sebelum pemberian air rebusan daun sirih merah 2,5455 dan rata-rata keputihan setelah perlakuan pemberian air rebusan daun sirih merah sehari sekali selama 5 hari berturut-turut sebesar 4,4525. Sedangkan berdasarkan analisa data diperoleh p=0.000<0.05 maka H1 diterima, artinya terdapat perbedaan keputihan pada wanita usia subur sebelum dan setelah perlakuan pemberian air rebusan daun sirih merah. Hasil dan Pembahasan: Hasil penelitian ini terdapat adanya pengaruh pemberian cebokan air rebusan daun sirih merah (Piper crocatum) terhadap penurunan keputihan pada wanita usia subur di Puskesmas Telaga Dewa Kota Bengkulu.
Forecasting A Weekly Red Chilli Price in Bengkulu City Using Autoregressive Integrated Moving Average (ARIMA) and Singular Spectrum Analysis (SSA) Methods Putriasari, Novi; Nugroho, Sigit; Rachmawati, Ramya; Agwil, Winalia; Sitohang, Yosep O
Journal of Statistics and Data Science Vol. 1 No. 1 (2022)
Publisher : UNIB Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33369/jsds.v1i1.21007

Abstract

Red chili occupies a strategic position in the Indonesian economic structure because its use applies to almost all Indonesian dishes. Therefore, controlling the price of red chili is anecessity to maintain national economic stability. The purpose of this research is to forecast a red chili weekly price using ARIMA and SSA based on the weekly data of chili prices from January 2016 - December 2019 sourced from Statistics Indonseia (BPS) Branch Office of Bengkulu Province. The data have been analyzed using software R. Based on MAPE, ARIMA (2,1,2) provides the best forecasting with value 0.49% while SSA 10.64%.
Agglomerative Nesting (AGNES) Method and Divisive Analysis (DIANA) Method For Hierarchical Clustering On Some Distance Measurement Concepts Wijuniamurti, Susi; Nugroho, Sigit; Rachmawati, Ramya
Journal of Statistics and Data Science Vol. 1 No. 1 (2022)
Publisher : UNIB Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33369/jsds.v1i1.21009

Abstract

Clustering data through hierarchical approach could be performed by Agglomerative Nesting (AGNES) Method and Divisive Analysis (DIANA) Method. The objective of this research is to compare both the methods based on Euclid and Manhattan distance measurements. Of this research the clustering procedures of agglomerative method are conducted by exploring all techniques including single linkage, complete linkage, average linkage, and Ward. The data used are the National Socio-Economic Survey (SUSENAS) data which are selected specifically for the percentage of over 5 year old residents in each province, for both living in urban or rural, who access the internet in the last 3 months in 2017 but classified according purpose of accessing. By applying Mean Square Error (MSE) for 2 and 3 clusters, it can be concluded that the single linkage technique is the best performance of clustering procedure for both Euclidean and Manhattan distances.
A Comparison of Weighted Least Square and Quantile Regression for Solving Heteroscedasticity in Simple Linear Regression Fransiska, Welly; Nugroho, Sigit; Rachmawati, Ramya
Journal of Statistics and Data Science Vol. 1 No. 1 (2022)
Publisher : UNIB Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33369/jsds.v1i1.21011

Abstract

Regression analysis is the study of the relationship between dependent variable and one or more independent variables. One of the important assumption that must be fulfilled to get the regression coefficient estimator Best Linear Unbiased Estimator (BLUE) is homoscedasticity. If the homoscedasticity assumption is violated then it is called heteroscedasticity. The consequences of heteroscedasticity are the estimator remain linear and unbiased, but it can cause estimator haven‘t a minimum variance so the estimator is no longer BLUE. The purpose of this study is to analyze and resolve the violation of heteroscedasticity assumption with Weighted Least Square(WLS) and Quantile Regression. Based on the results of the comparison between WLS and Quantile Regression obtained the most precise method used to overcome heteroscedasticity in this research is the WLS method because it produces that is greater (98%).
SURVIVAL ANALYSIS ON DATA OF STUDENTS NOT GRADUATING ON TIME USING WEIBULL REGRESSION, COX PROPORTIONAL HAZARDS REGRESSION, AND RANDOM SURVIVAL FOREST METHODS Rachmawati, Ramya; Afandi, Nur; Alwansyah, Muhammad Arib
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 19 No 3 (2025): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol19iss3pp2111-2126

Abstract

This article presents a comprehensive study of the factors that influence the length of study data of undergraduate students at FMIPA UNIB class 2018 and 2019. This study is essential because observations show that many students study for more than 8 semesters. The purpose of this study is to determine the factors that significantly influence the length of study of undergraduate students. These factors can be internal and external. Survival analysis is the right method to identify these factors because ordinary regression analysis is unable to estimate survival data. Therefore, methods such as Weibull regression, Cox Proportional Hazards regression, and Random Survival Forest are used. This study does not compare the methods used because these methods are independent of each other, but have the same goal, namely, to determine the factors that influence the length of study of students. The data used in this study are data on the length of study of students from the 2018 and 2019 cohorts sourced from the academic subsection of FMIPA UNIB, with variables of GPA, gender, region of origin, university entry route, parents' occupation, type of study program, and length of study. The results showed that GPA and the type of study program significantly influenced the length of study in Weibull regression analysis. In Cox proportional hazard regression, the GPA variable is an influential factor, while using the Random Survival Forest method, all factors significantly influenced the length of study, with their respective levels of importance.
“Data-Driven Decision Making”: Pengenalan Statistika dan Pemanfaatannya di SMA IT Iqra Kota Bengkulu Firdaus; Rachmawati, Ramya; Hidayati, Nurul; Damayanti, Septri; Yosmar, Siska
Jurnal Pengabdian Masyarakat Bumi Rafflesia Vol. 8 No. 1 (2025): APRIL: Jurnal Pengabdian Kepada Masyarakat Bumi Raflesia
Publisher : Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jpmbr.v8i1.7352

Abstract

Kemampuan mengambil keputusan yang baik merupakan kebutuhan esensial bagi siswa. Terdapat banyak metode dalam mengambil keputusan, salah satunya adalah Data-Driven Decision Making, yaitu pengambilan keputusan berdasarkan analisis data. Pentingnya peran data dalam menentukan pengambilan keputusan berdasarkan data belum utuh dipahami oleh siswa SMA IT Iqra Kota Bengkulu karena kurikulum pada jenjang SMA terbatas pada statistika deskriptif yang meliputi pengenalan ukuran pemusatan, ukuran penyebaran, dan visualisasi data. Program Pengabdian Kepada Masyarakat (PkM) dengan judul “Data-Driven Decision Making”: Pengenalan Statistika dan Pemanfaatannya di SMA IT Iqra Kota Bengkulu bertujuan untuk mengenalkan analisis korelasi dan regresi yang dapat digunakan untuk mendukung pengambilan keputusan. Pelaksanaan PkM dilaksanakan secara klasikal dengan penyampaian materi dan pelatihan langsung dengan memanfaatkan Bahasa pemrograman RStudio. Evaluasi program PkM yang dilakukan dengan memberikan pre-test dan post-test menunjukkan bahwa terdapat perbedaan rata-rata hasil pemahaman sebelum dan setelah mengikuti kegiatan. Hal ini dapat diinterpretasikan bahwa kegiatan PkM memberikan pengaruh terhadap pemahaman siswa pengambilan keputusan berdasarkan analisis data.
Forecasting A Weekly Red Chilli Price in Bengkulu City Using Autoregressive Integrated Moving Average (ARIMA) and Singular Spectrum Analysis (SSA) Methods Putriasari, Novi; Nugroho, Sigit; Rachmawati, Ramya; Agwil, Winalia; Sitohang, Yosep O
Journal of Statistics and Data Science Vol. 1 No. 1 (2022)
Publisher : UNIB Press

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

Abstract

Red chili occupies a strategic position in the Indonesian economic structure because its use applies to almost all Indonesian dishes. Therefore, controlling the price of red chili is a necessity to maintain national economic stability. The purpose of this research is to forecast a red chili weekly price using ARIMA and SSA based on the weekly data of chili prices from January 2016 - December 2019 sourced from Statistics Indonseia (BPS) Branch Office of Bengkulu Province. The data have been analyzed using software R. Based on MAPE, ARIMA K (2,1,2) provides the best forecasting with value 0.49% while SSA 10.64%.
Analisis Kestabilan Global dan Analisis Sensitivitas pada Model Matematika Penyebaran Penyakit Gondongan Widayati, Ratna; Rachmawati, Ramya; Afandi, Nur
Griya Journal of Mathematics Education and Application Vol. 5 No. 2 (2025): Juni 2025
Publisher : Pendidikan Matematika FKIP Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/griya.v5i2.578

Abstract

Mumps is a contagious viral disease transmitted through respiratory droplets and close contact. It can cause symptoms like fever and salivary gland swelling. Despite the MMR vaccine, which offers partial protection, outbreaks persist, especially in college-aged individuals. Epidemiological models can aid in identifying effective prevention strategies for controlling mumps transmission. This paper proposes a mathematical model for mumps spread, considering quarantined individuals and complications. A global stability analysis of the mumps transmission model was performed, considering mortality and quarantine subpopulation. The Disease Free Equilibrium and Endemic Equilibrium Point are globally stable, confirmed by Lyapunov functions. Sensitivity analysis of the basic reproduction number shows that reducing birth rates and contact between infected and susceptible individuals effectively minimizes the infected population. However, increasing the natural death rate can reduce the total population, which may lower infections, but poses potential social and economic challenges for decision-makers.
MODELING THE MANY EARTHQUAKES IN SUMATRA USING POISSON HIDDEN MARKOV MODELS AND EXPECTATION MAXIMIZATION ALGORITHM Alwansyah, Muhammad Arib; Rachmawati, Ramya
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 1 (2024): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol18iss1pp0163-10135

Abstract

Sumatra Island is one of the islands that are prone to earthquakes because Sumatra Island is located at the confluence of three plates, namely the large Indo-Australian plate, the Eurasian plate and the Philippine plate. In general, the number of earthquake events follows the Poisson distribution, but there are cases where there is overdispersion in the Poisson distribution. The Poisson Hidden Markov Models (PHMMs) method is used to overcome overdispersion, then applying the Expectation-Maximization Algorithm (EM algorithm) to each model to obtain the estimated parameters. From the models obtained, the best model will be selected based on the smallest Akaike Information Criterion (AIC) value. The data used is secondary data on earthquake events on the island of Sumatra from January 2000 to December 2022 with a depth of ≤ 70 Km and a magnitude of ≥ 4.4 Mw. From the research, the model with m = 3 is the best estimation model with an AIC value of 1503,286. From the best model, estimates are obtained for Poisson Hidden Markov Models with an average occurrence of earthquakes of 5.7633 ≈ 6 events within one month.
HANDLING OF OVERDISPERSION CASES IN MORBIDITY DATA IN SELUMA REGENCY Sarumpaet, Mey Yanti; Nugroho, Sigit; Rachmawati, Ramya
MEDIA STATISTIKA Vol 16, No 2 (2023): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/medstat.16.2.206-214

Abstract

The problem of overdispersion as a violation of the assumption of equidispersion in Poisson regression is generally caused by  sources of unobserved heterogeneity, missing observations on predictor variables, outliers in the data, errors in the specification of the bridging function, and many observed  values that are zero.  The  purpose of  this study is  to find out the right  model and the variables  that affect data that occurs overdispersion and excess zero in the case of the number of days of disruption at work, school, or other daily activities due to health complaints. The methods used were Poisson Regression, Negative  Binomial Regression, Hurdle  Poisson  Regression,  Zero  Inflated Poisson Regression,  Zero  Inflated  Negative  Binomial Regression, and Hurdle Negative Binomial Regression. The data used were morbidity taken from data on the number of days  of  disruption at  work,  school  or  other daily  activities due  to  health  complaints  in  Seluma district,  Bengkulu Province. It was found that the best model is Zero Inflated Negative  Poisson  with  the  smallest  Akaike  Information Criterion (AIC) value of 1620.609  and the variables that have  a  significant  effect on the  log model and the logit model are marital status and work variables.
Co-Authors Agwil, Winalia Alwansyah, Muhammad Arib APRIANISA, TRI Asmariyah Deni Maryani Dewiani, Kurnia Firdaus Fransiska, Welly Novianti Novianti Nur Afandi Nurul Hidayati Putriasari, Novi Saniyyah, Nabilah Sarumpaet, Mey Yanti Septri Damayanti Sigit Nugroho Siska Yosmar Sitohang, Yosep O Suriyati, Suriyati Widayati, Ratna Wijuniamurti, Susi Yusanti, Linda