Article Per Year (5 Year)
p-Index From 2020 - 2025
1.168
P-Index
This Author published in this journals
All Journal Jurnal Nasional Holistic Science EduMatika: Jurnal MIPA EDUCTUM: Journal Research Trigonometri: Jurnal Matematika dan Ilmu Pengetahuan Alam
Hutapea, Risca Octaviyani
Unknown Affiliation
Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Education Languange, Linguistic, Communication & Media Mathematics Physics Social Sciences Other

Published : 7 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 7 Documents
Search

 1 
ANALISIS FAKTOR - FAKTOR YANG MEMENGARUHI HARGA PROPERTI Amalia, Seila; Lubis, M. Shadri; Putri, Alya Nabilla; Napitupulu, Rusmawanty; Hutapea, Risca Octaviyani; Sianturi, Ardicha
Trigonometri: Jurnal Matematika dan Ilmu Pengetahuan Alam Vol. 5 No. 2 (2024): Trigonometri: Jurnal Matematika dan Ilmu Pengetahuan Alam
Publisher : Cahaya Ilmu Bangsa Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.3483/trigonometri.v5i2.8254

Abstract

Artikel ini membahas berbagai faktor yang memengaruhi harga properti, dengan fokus pada aspek fisik dan lingkungan yang langsung terkait dengan karakteristik properti itu sendiri. Faktor-faktor yang dianalisis meliputi harga properti, ukuran bangunan, jumlah kamar tidur dan kamar mandi, usia bangunan, lokasi properti, serta fasilitas yang tersedia di sekitar properti. Ukuran dan jumlah ruang dalam properti, seperti jumlah kamar tidur dan kamar mandi, berpengaruh langsung terhadap penilaian nilai properti. Begitu pula, usia bangunan menjadi indikator penting yang menunjukkan kondisi fisik dan potensi renovasi yang diperlukan, yang dapat memengaruhi harga jual. Lokasi properti tetap menjadi faktor utama dalam menentukan harga, karena kedekatannya dengan fasilitas umum, pusat bisnis, transportasi, dan area yang berkembang pesat sangat berpengaruh. Fasilitas seperti kolam renang, taman, atau sistem keamanan juga turut meningkatkan nilai properti. Analisis ini bertujuan untuk memberikan pemahaman yang lebih mendalam tentang bagaimana faktor-faktor tersebut saling berinteraksi dalam menentukan harga pasar properti, serta memberikan panduan bagi pembeli, penjual, dan investor dalam membuat keputusan yang tepat.
Prediction of Increase in House Prices Using Newton's Divided Difference Method Hutapea, Risca Octaviyani; Sinaga, May Rani Tabitha; Lubis, Muhammad Shadri Ismaun; Aqil, Muhammad Fachri
Holistic Science Vol. 4 No. 3 (2024): Jurnal Nasional Holistic Science
Publisher : Lembaga Riset Mutiara Akbar NOMOR AHU-0003295.AH.01.07 TAHUN 2021

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56495/hs.v4i3.771

Abstract

This research predicts house price increases using Newton's Divided Difference Method based on historical datasets from the Melbourne Housing Snapshot (2016–2017). A pattern of rising home prices that is consistent with a linear trend is revealed by preliminary investigation. By building an interpolation polynomial using Newton's Divided Difference Method, home prices in 2025 are predicted to be AUD 1,753,391.53. This technique works well for spotting upward price trends in data that is continuously distributed linearly. These results offer crucial information to help with strategic choices in market research and real estate investing. This approach may accurately simulate the link between year (an independent variable) and house prices (a dependent variable) by using Newton polynomials. The impact of market demand and other economic factors on sharply rising property prices is reflected in these projections.
Analysis of Book Production Quality Using Ewma Control Chart: Comparison of Alpha Parameters, Trend Prediction, and Production Correlation Putri, Amelia; Hani, Aulia; Faradhilla, Anatasia; Hutapea, Risca Octaviyani
EduMatika: Jurnal MIPA Vol. 5 No. 2 (2025): EduMatika: Jurnal MIPA
Publisher : Lembaga Riset Mutiara Akbar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56495/emju.v5i2.1106

Abstract

In the printing industry, maintaining product quality is a critical factor for ensuring customer satisfaction and competitive advantage. This study applies the Exponentially Weighted Moving Average (EWMA) control chart to monitor and control the quality of book production at CV Renjana Offset. Using secondary data from November 2023 to July 2024, the analysis focuses on the percentage of rejected products as a key indicator of quality performance. The EWMA method, with a smoothing constant of ? = 0.3, effectively highlights small shifts in the production process. Results show that all EWMA values lie within the control limits (UCL = 22.54%, LCL = 0.00%), indicating the process is statistically under control. Furthermore, comparison of different alpha values demonstrates the trade-off between sensitivity and stability. A moderate negative correlation (r = -0.505) between production volume and reject percentage suggests increased efficiency at higher production scales. The predicted reject percentage for August 2024 is 4.74%, indicating process stability. Overall, EWMA proves to be a valuable tool in continuous quality monitoring and data-driven decision-making in book production.
Analysis of the Most Dominant Causing Factors of Divorce in 34 Provinces in Indonesia Using the XGBoost Algorithm Amalia, Seila; Banjarnahor, Riski Melanton; Hutapea, Risca Octaviyani; Sitorus, Gabriel Fernando; Domini, Gracia; Arnita, Arnita
EduMatika: Jurnal MIPA Vol. 5 No. 2 (2025): EduMatika: Jurnal MIPA
Publisher : Lembaga Riset Mutiara Akbar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56495/emju.v5i2.1135

Abstract

Divorce in Indonesia shows a significant increasing trend and has a broad social impact. This study aims to identify the most dominant causes of divorce in 34 provinces in Indonesia using the Extreme Gradient Boosting (XGBoost) machine learning algorithm. Secondary quantitative data from the Central Bureau of Statistics in 2024 were analyzed by pre-processing, data sharing, model training, and performance evaluation. The results showed that constant disputes and quarrels were the main causes of divorce, followed by substance abuse and forced marriage. The developed XGBoost model achieved 75% accuracy in classifying the level of divorce risk. These findings provide new insights into understanding the social factors that influence divorce and can be the basis for designing more effective prevention strategies.
Spatial Analysis of Earthquake Distribution Patterns in North Sumatera in 2022 Using Moran's Test and Moran Scatter Plot Mapping Hutapea, Risca Octaviyani; Sinaga, May Rani Tabitha; Lubis, Muhammad Shadri Ismaun; Aqil, Muhammad Fachri
EDUCTUM: Journal Research Vol. 4 No. 2 (2025): Eductum: Journal Research
Publisher : Lembaga Riset Mutiara Akbar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56495/ejr.v4i2.1006

Abstract

This study aims to analyze the spatial distribution patterns of earthquake occurrences in North Sumatra during 2022 using spatial statistical approaches, namely the global Moran’s I autocorrelation test and Local Indicators of Spatial Association (LISA), visualized through a Moran Scatter Plot. The data used in this study are secondary data obtained from the official earthquake catalog released by the Meteorology, Climatology, and Geophysics Agency (BMKG), including information on geographic location, time of occurrence, magnitude, and depth of earthquakes. The analysis was conducted using R and QGIS software, applying three types of spatial weighting: inverse distance, k-nearest neighbors (KNN), and adaptive Gaussian kernel functions. The results of the Moran’s I test revealed significant global spatial autocorrelation, indicating that earthquakes with similar magnitudes tend to cluster geographically. In contrast, the LISA analysis showed that most points did not exhibit significant local spatial association, although a few clusters of high-high, low-low, high-low, and low-high types were identified. These findings confirm the presence of spatial patterns in the distribution of earthquakes in North Sumatra, which are relevant for supporting mitigation efforts and spatially-based disaster management planning.
The Relationship Between the Human Development Index (HDI) and Poverty Rate in North Sumatra in 2023: Spearman Correlation Analysis Hutapea, Risca Octaviyani; Triyunita, Gizka; Amalia, Sisti Nadia
Holistic Science Vol. 5 No. 2 (2025): Jurnal Nasional Holistic Sciences
Publisher : Lembaga Riset Mutiara Akbar NOMOR AHU-0003295.AH.01.07 TAHUN 2021

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56495/hs.v5i2.1133

Abstract

This study aims to analyze the relationship between the Human Development Index (HDI) and poverty levels in 33 regencies/cities across North Sumatra Province in 2023. The background of this research is rooted in the regional disparities in welfare and the strategic role of human development in poverty alleviation efforts. The data used are secondary data sourced from Statistics Indonesia (BPS), comprising HDI scores and poverty rates. The analytical methods applied include descriptive analysis, the Shapiro-Wilk normality test, and the Spearman rank correlation test, which is appropriate for non-normally distributed data. The findings reveal a significant negative correlation between HDI and poverty with a Spearman correlation coefficient of -0.5936 and a p-value of 0.0003. This indicates that regions with higher HDI tend to have lower poverty rates. The results highlight the importance of improving education quality, healthcare services, and living standards as key strategies in reducing poverty. This study is expected to contribute to the formulation of inclusive regional development policies that prioritize human well-being.
Comparison of Cox Proportional Hazards and Weibull Regression Models in Survival Analysis of Heart Failure Patients Using UCI Repository Data Sianturi, Ardicha Appu; Hutapea, Risca Octaviyani; Sinaga, May Rani Tabitha
EduMatika: Jurnal MIPA Vol. 5 No. 3 (2025): EduMatika: Jurnal MIPA
Publisher : Lembaga Riset Mutiara Akbar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56495/emju.v5i3.1327

Abstract

Heart failure is a leading cause of death worldwide, with a high mortality rate due to decreased heart function and systemic complications. Survival analysis is used to understand factors that influence patient survival and estimate the risk of death based on clinical characteristics. This study aims to analyze factors that influence survival time in heart failure patients and compare the performance of the Cox Proportional Hazards (CoxPH) model with the Weibull Accelerated Failure Time (AFT) in predicting the risk of death. Data are from the Heart Failure Clinical Records Dataset (UCI Repository) which includes 299 patients with variables such as age, anemia, hypertension, serum creatinine levels, and ejection fraction. The analysis was performed using the Kaplan–Meier, CoxPH, and Weibull AFT methods with evaluation through AIC and C-index values. The results show that age, anemia, hypertension, and creatinine increase the risk of death, while ejection fraction is protective. The CoxPH model performed better (AIC 958.46; C-index 0.741) than the Weibull AFT (AIC 1282.24; C-index 0.259). Therefore, CoxPH is recommended for estimating relative risk between patients, while Weibull AFT is more suitable for estimating absolute survival duration.
Co-Authors Amalia, Seila Amalia, Sisti Nadia Aqil, Muhammad Fachri Arnita Arnita Banjarnahor, Riski Melanton Domini, Gracia Faradhilla, Anatasia Hani, Aulia Lubis, M. Shadri Lubis, Muhammad Shadri Ismaun Napitupulu, Rusmawanty Putri, Alya Nabilla Putri, Amelia Sianturi, Ardicha Sianturi, Ardicha Appu Sinaga, May Rani Tabitha Sitorus, Gabriel Fernando Triyunita, Gizka