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All Journal Jurnal Manajemen & Keuangan Journal of Applied Data Sciences Media Publikasi Promosi Kesehatan Indonesia (MPPKI) Infolitika Journal of Data Science South East Asian Management Concern Journal
Kruba, Rumaisa
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Engineering Environmental Science Public Health Other

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A Statistical Clustering Approach: Mapping Population Indicators Through Probabilistic Analysis in Aceh Province, Indonesia Sasmita, Novi Reandy; Khairul, Moh; Sofyan, Hizir; Kruba, Rumaisa; Mardalena, Selvi; Dahlawy, Arriz; Apriliansyah, Feby; Muliadi, Muliadi; Saputra, Dimas Chaerul Ekty; Noviandy, Teuku Rizky; Watsiq Maula, Ahmad
Infolitika Journal of Data Science Vol. 1 No. 2 (2023): December 2023
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/ijds.v1i2.130

Abstract

The clustering, one of statistical analysis, can be used for understanding population patterns and as a basis for more targeted policy making. In this ecological study, we explored the population dynamics across 23 districts/cities in Aceh Province. The study used the Aceh Population Development Profile Year 2022 data, focusing on the total population, in-migrants, out-migrants, fertility, and maternal mortality as variables. The study employed descriptive statistics to ascertain the data distribution, followed by the Shapiro-Wilk test to evaluate normality, which is crucial for selecting the appropriate statistical methods. The Spearman test was used to determine correlations between the total population and the variable as indicators. Probabilistic Fuzzy C-Means (PFCM) method is used for clustering. To optimize clustering, the silhouette coefficient was calculated using the Euclidean Distance and the elbow method, with the results analyzed using R-4.3.2 software. This study's design and methods aim to provide a nuanced understanding of demographic patterns for targeted policy-making and regional development in Aceh, Indonesia. Based on the data normality test results, only fertility (p-value = 0.45), while the other variables are not normally distributed. Spearman test was used, and the results showed that only in-migrants (p-value = 1.78 x 10-6) and out-migrants (p-value = 2.30 x 10-6) correlated to the Aceh Province population. Using the population variable and the two variables associated with it, it was found that 4 is the best optimum number of clusters, where clusters 1, 2, 3, and 4 consist of three districts/city, nine districts/city, four districts/city and seven districts/city respectively.
Unraveling Geospatial Determinants: Robust Geographically Weighted Regression Analysis of Maternal Mortality in Indonesia Rahayu, Latifah; Ulfa, Elvitra Mutia; Sasmita, Novi Reandy; Sofyan, Hizir; Kruba, Rumaisa; Mardalena, Selvi; Saputra, Arif
Infolitika Journal of Data Science Vol. 1 No. 2 (2023): December 2023
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/ijds.v1i2.133

Abstract

Maternal Mortality Rate (MMR) in Indonesia has experienced a concerning annual increase, reaching 4,627 deaths in 2020 compared to 4,221 in 2019. This upward trajectory underscores the urgency of investigating the factors contributing to MMR. Recognizing the spatial heterogeneity and outliers in the data, our study employs the Robust Geographically Weighted Regression (RGWR) method with the Least Absolute Deviation approach. Using secondary data from the 2020 Indonesian Health Profile publication, the research seeks to establish province-specific models for MMR in 2020 and identify the key influencing factors in each region. Standard regression analyses fall short in addressing the complexities present in the data, making the RGWR approach crucial for understanding the nuanced relationships. The chosen RGWR model utilizes the Least Absolute Deviation method and a fixed kernel exponential weighting function. Notably, this model maintains a consistent bandwidth value across all locations, showcasing its robustness. In evaluating the model variations, the exponential fixed kernel weighting function emerges as the most optimal, boasting the smallest Akaike Information Criterion (AIC) value of 23.990 and the highest coefficient of determination  value of 93.66%. The outcomes of this research yield 24 distinct models, each tailored to the unique characteristics of every province in Indonesia. This nuanced, location-specific approach is vital for developing effective interventions and policies to address the persistently high MMR. By providing insights into the complex interplay of factors influencing maternal mortality in different regions, the study contributes to the groundwork for targeted and impactful public health initiatives across Indonesia.
Spatial Estimation for Tuberculosis Relative Risk in Aceh Province, Indonesia: A Bayesian Conditional Autoregressive Approach with the Besag-York-Mollie (BYM) Model Sasmita, Novi Reandy; Arifin, Mauzatul; Kesuma, Zurnila Marli; Rahayu, Latifah; Mardalena, Selvi; Kruba, Rumaisa
Journal of Applied Data Sciences Vol 5, No 2: MAY 2024
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v5i2.185

Abstract

Tuberculosis (TB) remains a significant public health challenge globally, with Indonesia being the second-highest country in TB cases worldwide. Aceh Province has one of the highest TB incidence rates in Indonesia. This study aims to estimate and map the spatial distribution patterns of TB relative risk across districts in Aceh Province, Indonesia, to reveal significant variations. The study employed an ecological time-series study design, utilizing the Bayesian Conditional Autoregressive (CAR) approach with the Besag-York-Mollie (BYM) model for spatial estimation and mapping of TB relative risk. TB case data and population data for 23 districts/cities in Aceh Province from 2016 to 2022 were analyzed. Spatial analysis was used to estimate and map TB's relative risk, aiding in identifying areas with higher transmission risks. The results showed that the relative risk of TB varied across districts/cities in Aceh Province over the study period. However, Lhokseumawe and Banda Aceh consistently exhibited high to very high relative risks over the years. In 2022, Lhokseumawe City and Banda Aceh City had the highest relative risks by 2.26 and 2.17, respectively, while Sabang City and Bener Meriah District had the lowest by 0.43 and 0.32, respectively. This study provides valuable insights into the heterogeneous landscape of TB risk in Aceh Province, which can inform targeted interventions and planning strategies for effective TB control. Using the Bayesian CAR BYM model proved effective in estimating and mapping TB's relative risk, highlighting areas requiring prioritized attention in TB prevention and control efforts.
Spatial Estimation of Relative Risk for Dengue Fever in Aceh Province using Conditional Autoregressive Method Rahayu, Latifah; Sasmita, Novi Reandy; Adila, Wulan Farisa; Kesuma, Zurnila Marli; Kruba, Rumaisa
Journal of Applied Data Sciences Vol 4, No 4: DECEMBER 2023
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v4i4.141

Abstract

Dengue Fever (DHF) is a dangerous infectious disease that can cause death in an infected person. DHF is a disease transmitted by the Aedes Aegypti mosquito. Dengue cases have been reported in 449 districts/cities spread across 34 provinces with deaths spread across 162 districts/cities in 31 provinces, one of which is in Aceh Province. However, there are districts and cities in Aceh Province with a large number of cases and population at risk, and there are also districts and cities with fewer cases and population at risk. As a result, the number of cases and population at risk of DHF varies. Therefore, it is important to do planning to see which districts and cities have a high chance of DHF. In this study, the type of data used is secondary data sourced from the Aceh Provincial Health Profile from 2016 to 2022. The approach used is the Bayesian Conditional Autoregressive (CAR) prior model Besag-York-Mollie (BYM). The results of this study showed that mortality in dengue cases in Aceh Province from 2016 to 2022 had the highest mortality values in 2016 and 2022. The results of estimating the relative risk of DHF cases using the Bayesian Conditional Autoregressive (CAR) approach of the Besag-York-Mollie (BYM) Model in Aceh Province fulfill all categories with their relative risk values. Some districts/cities have relative risk values. Some districts/cities have high relative risk values of DHF cases and low relative risk values of DHF cases. Sabang city had the highest relative risk value of 3.54 and Bener Meriah district had the lowest relative risk of 0.2.
Relative Risk and Distribution Assessment of Tuberculosis Cases: A Time-Series Ecological Study in Aceh, Indonesia Sasmita, Novi Reandy; Khairul, Mhd; Fikri, Mumtaz Kemal; Rahayu, Latifa; Kesuma, Zurnila Marli; Mardalena, Selvi; Kruba, Rumaisa; Chongsuvivatwong, Virasakdi; Asshiddiqi, M. Ischaq Nabil
Media Publikasi Promosi Kesehatan Indonesia (MPPKI) Vol. 8 No. 6: JUNE 2025 - Media Publikasi Promosi Kesehatan Indonesia (MPPKI)
Publisher : Fakultas Kesehatan Masyarakat, Universitas Muhammadiyah Palu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56338/mppki.v8i6.7264

Abstract

Introduction: Tuberculosis (TB) remains a critical public health issue, particularly in high-incidence regions like Aceh Province, Indonesia. This study aimed to estimate the Relative Risk (RR) and analyze significant differences in the temporal distribution of TB cases across Aceh Province. Methods: A time-series ecological study was conducted using TB case and population data from 23 districts/cities in Aceh Province between 2016 and 2022. Data were analyzed using R software, applying descriptive and inferential statistics. The Standardized Morbidity Ratio (SMR) method estimates RR and is categorized into five risk levels. The Kolmogorov-Smirnov test assessed data normality, guiding the selection of statistical tests. The Friedman and Wilcoxon Signed-Rank tests examined differences in TB case distribution trends. Results: Significant spatial and temporal variations in TB risk were identified. Districts such as Banda Aceh (RR = 2.29–2.13) and Lhokseumawe (RR = 1.89–2.21) consistently demonstrated high RR from 2016 to 2022, reflecting persistent TB transmission. A general upward trend in TB cases was observed across districts, with significant spatial variation (p < 0.001), highlighting a worsening TB burden. Conclusions: The study emphasizes the urgent need for targeted public health interventions tailored to TB's unique spatial and temporal dynamics in Aceh Province, Indonesia. Applying SMR and robust statistical analyses provides valuable insights to inform localized TB control policies and strengthen management strategies in high-burden areas.
Analisis Biplot pada Pemetaan Provinsi di Indonesia Berdasarkan Indikator Women empowerment Hafidzah, Afrah; Mulyani, Riska; Retha, Siti Reva; Kruba, Rumaisa
South East Asian Management Concern Vol. 2 No. 2 (2025): May
Publisher : Science, Technology, and Education Care

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61761/seamac.2.2.48-55

Abstract

Isu kesetaraan gender merupakan salah satu aspek penting dalam pembangunan manusia berkelanjutan. Dalam konteks Indonesia, pengukuran pembangunan berbasis gender dilakukan melalui dua indikator utama, yaitu Indeks Pembangunan Gender (IPG) dan Indeks Pemberdayaan Gender (IDG). Penelitian ini bertujuan untuk mendeskripsikan serta mengelompokkan provinsi-provinsi di Indonesia berdasarkan karakteristik women empowerment menggunakan metode analisis biplot. Empat indikator utama yang dianalisis adalah angka harapan hidup, rata-rata lama sekolah, keterlibatan perempuan di parlemen, dan sumbangan pendapatan perempuan. Hasil analisis menunjukkan bahwa biplot mampu menjelaskan 72,12% keragaman data secara keseluruhan. Provinsi-provinsi di Indonesia dapat diklasifikasikan ke dalam empat kuadran yang merepresentasikan kemiripan karakteristik women empowerment. Kuadran I didominasi oleh provinsi dengan sumbangan pendapatan perempuan yang rendah, kuadran II didominasi oleh provinsi dengan rata-rata lama sekolah dan keterlibatan perempuan di parlemen yang rendah, kuadran III didominasi oleh provinsi dengan sumbangan pendapatan perempuan yang tinggi namun angka harapan hidup yang rendah, dan kuadran IV dinominasi oleh provinsi dengan angka harapan hidup, rata-rata lama sekolah dan keterlibatan perempuan di parlemen yang tinggi. Karakteristik women empowerment yang paling dominan di Indonesia adalah sumbangan pendapatan perempuan. selain itu, terdapat korelasi positif antara angka harapan hidup dengan rata-rata lama sekolah, angka harapan hidup dengan keterlibatan perempuan di perlemen, rata-rata lama sekolah dengan keterlibatan perempuan di perlemen dan keterlibatan perempuan di perlemen dengan sumbangan pendapatan perempuan, sementara terdapat korelasi negatif antara sumbangan pendapatan perempuan dengan angka harapan hidup dan rata-rata lama sekolah. Temuan ini diharapkan menjadi acuan dalam merumuskan kebijakan yang tepat sasaran untuk meningkatkan pemberdayaan perempuan di Indonesia.
Peramalan Saham Indofood Di Indonesia Menggunakan Metode Seasonal Autoregressive Integrated Moving Average (SARIMA) Kruba, Rumaisa; Sofyan, Hizir; Marshanda, Devira; Rahmadhania; Syazana, Nurul
Jurnal Manajemen dan Keuangan Vol 14 No 1 (2025): JURNAL MANAJEMEN DAN KEUANGAN
Publisher : Program Studi Manajemen Fakultas Ekonomi Universitas Samudra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33059/jmk.v14i1.11501

Abstract

Penelitian ini memperkenalkan sebuah model peramalan harga saham PT Indofood Sukses Makmur Tbk di Indonesia menggunakan analisis time series. Saham menjadi topik perbincangan utama dalam bidang ekonomi karena instrumen investasi ini memiliki risiko yang tinggi. Upaya yang digunakan untuk memprediksi pergerakan harga saham di masa depan adalah dengan peramalan time series. Data yang digunakan dalam penelitian ini berasal dari sumber data Yahoo Finance yang mencakup harga close saham PT Indofood Sukses Makmur Tbk selama periode Januari 2010 hingga Januari 2023. Melalui analisis data, ditemukan bahwa harga saham tersebut bersifat fluktuatif dan memiliki pola trend peningkatan dengan pola musiman yang tidak teratur. Metode analisis yang digunakan adalah SARIMA, yaitu model ARIMA yang mempertimbangkan unsur musiman. Adapun model peramalan yang dikembangkan adalah ARIMA(0,1,0),(1,1,1),12 dengan persamaan . Hasil analisis menunjukkan bahwa model tersebut memenuhi uji signifikansi parameter dan uji diagnostik residual, serta memiliki nilai AIC yang paling rendah dibandingkan dengan model lainnya. Berdasarkan hasil penelitian, model ARIMA(0,1,0),(1,1,1),12 memiliki nilai MAPE sebesar 4.6283% < 10% sehingga dapat digunakan sebagai alat peramalan yang efektif untuk memprediksi harga saham PT Indofood Sukses Makmur Tbk di masa depan. Dengan demikian, hasil penelitian ini dapat memberikan kontribusi pada pengembangan strategi investasi bagi investor dan pengambil keputusan di bidang keuangan.
Co-Authors Adila, Wulan Farisa Ahmad Watsiq Maula Apriliansyah, Feby Arif Saputra, Arif Arifin, Mauzatul Asshiddiqi, M. Ischaq Nabil Chongsuvivatwong, Virasakdi Dahlawy, Arriz Dimas Chaerul Ekty Saputra Fikri, Mumtaz Kemal Hafidzah, Afrah Hizir Sofyan Khairul, Mhd Khairul, Moh Mardalena, Selvi Marshanda, Devira Muliadi Mulyani, Riska Rahayu, Latifa RAHAYU, LATIFAH Rahmadhania Retha, Siti Reva Sasmita, Novi Reandy Syazana, Nurul Teuku Rizky Noviandy Ulfa, Elvitra Mutia Zurnila Marli Kesuma