Article Per Year (5 Year)
p-Index From 2020 - 2025
1.383
P-Index
This Author published in this journals
All Journal BAREKENG: Jurnal Ilmu Matematika dan Terapan EPSILON Jurnal Pendidikan Matematika Jurnal Pengabdian kepada Masyarakat Nusantara VARIANSI: Journal of Statistics and Its Application on Teaching and Research Journal of Applied Statistics, Mathematics, and Data Science Sipakaraya : Jurnal Pengabdian Masyarakat
Rahayu, Putri Indi
Unknown Affiliation
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Energy Engineering Mathematics Mechanical Engineering Physics Social Sciences Transportation Other

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

Found 7 Documents
Search

 1 
PENERAPAN REGRESI NONPARAMETRIK KERNEL DAN SPLINE DALAM MEMODELKAN RETURN ON ASSET (ROA) BANK SYARIAH DI INDONESIA Rahayu, Putri Indi; Sihombing, Pardomuan Robinson
Epsilon: Jurnal Pendidikan Matematika Vol 2 No 2 (2020): Epsilon: Jurnal Pendidikan Matematika
Publisher : LPPM STKIP PGRI Bandar Lampung

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

Abstract

Abstract: Sharia Bank Return On Assets (ROA) modeling in Indonesia in 2018 aims to analyze the relationship pattern of Return On Assets (ROA) with interest rates. The analysis that is often used for modeling is regression analysis. Regression analysis is divided into two, namely parametric and nonparametric. The most commonly used nonparametric regression methods are kernel and spline regression. In this study, the nonparametric regression used was kernel regression with the Nadaraya-Watson (NWE) estimator and Local Polynomial (LPE) estimator, while the spline regression was smoothing spline and B-splines. The fitting curve results show that the best model is the B-splines regression model with a degree of 3 and the number of knots 5. This is because the B-splines regression model has a smooth curve and more closely follows the distribution of data compared to other regression curves. The B-splines regression model has a determination coefficient of R^2 of 74.92%, meaning that the amount of variation in the ROA variable described by the B-splines regression model is 74.92%, while the remaining 25.8% is explained by other variables not included in the model.
Pembuatan dan Pelatihan Pengelolaan Website Desa di Desa Tapango Kabupaten Polewali Mandar Yanti, Reski Wahyu; Rahayu, Putri Indi
Sipakaraya : Jurnal Pengabdian Masyarakat Vol 2 No 2 (2024): Sipakaraya : Jurnal Pengabdian Masyarakat
Publisher : Universitas Sulawesi Barat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31605/sipakaraya.v2i2.3484

Abstract

This community service aims to provide training to village officials on how to create and manage websites. Based on survey and interview results, the administrative services provided are still traditional in nature. This is a slow process compared to other villages in the context of rapidly developing technology. Tapango Village residents need faster administrative services via the village website. Village officials' human resources must be immediately strengthened to create and manage this website optimally. The implementation of this community service is carried out through several stages, namely the communication stage, discussing with partners regarding the problems faced, and the next stage is communication with the Head of Tapango Village to explain and ensure that using the website is the right solution, the stage of agreeing on the training schedule, the stage of document design , the preparation stage for implementing training, the implementation stage for website creation and management training as well as the monitoring and evaluation activity stage to measure the success of the training provided. The results obtained from these systematic steps have been able to achieve the PKM objectives as stated above.
EKSPLORASI JENIS KURIKULUM PENDIDIKAN BERDASARKAN LITERASI MATEMATIKA PELAJAR INDONESIA MELALUI ANALISIS CLUSTER Mayapada, Retno; Rahayu, Putri Indi; Muzakir, Nurul Azizah
ESTIMATOR : Journal of Applied Statistics, Mathematics, and Data Science Vol. 2 No. 2 (2024):
Publisher : Program Studi Statistika Universitas PGRI Argopuro Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31537/estimator.v2i2.2140

Abstract

Literasi matematika merupakan kemampuan seseorang untuk merumuskan, menggunakan, dan menafsirkan matematika dalam berbagai konteks. Penurunan skor literasi matematika pada studi Programme for International Student Assessment (PISA) tahun 2022 menegaskan perlunya eksplorasi peran kurikulum pendidikan dalam membentuk kemampuan tersebut. Penelitian ini bertujuan untuk mengelompokkan jenis kurikulum pendidikan berdasarkan kemampuan literasi matematika pelajar Indonesia yang diukur melalui nilai PISA menggunakan metode analisis clustering. Analisis clustering dilakukan dengan metode average linkage, Ward’s method, centroid, dan McQuitty. Berdasarkan nilai koefisien korelasi Cophenetic, metode average linkage dipilih sebagai metode terbaik. Hasilnya, cluster pertama terdiri dari KBK dan Kurikulum Merdeka dengan rata-rata nilai PISA matematika sebesar 363. Cluster kedua terdiri dari KTSP 2009, KTSP 2012, dan Revisi K-13 dengan rata-rata nilai PISA matematika sebesar 375. Cluster ketiga terdiri dari KTSP 2006 dan Kurikulum 2013 dengan rata-rata nilai PISA matematika sebesar 383. Hal ini menunjukkan bahwa KBK dan Kurikulum Merdeka memiliki karakteristik yang sama pada nilai PISA matematika siswa dan diantara ketiga cluster kurikulum yang diperoleh, cluster dari kedua kurikulum ini memiliki nilai PISA matematika terendah. Temuan ini dapat menjadi bahan evaluasi bagi pemerintah dalam merumuskan kurikulum pendidikan yang lebih efektif untuk meningkatkan kemampuan literasi matematika pelajar di Indonesia.
ANALYSIS OF THE RELATIONSHIP BETWEEN WATER QUALITY AWARENESS AND DRINKING WATER CONSUMPTION BEHAVIOR (CASE STUDY: MAJENE CITY AND CAMPALAGIAN VILLAGE, WEST SULAWESI) Musafira, Musafira; Syahrir, Nur Hilal A.; Rahayu, Putri Indi
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/barekengvol19iss3pp1933-1944

Abstract

The declining quality of drinking water sources due to contamination poses significant health risks, particularly in rural areas where public awareness about water quality and its impact on health is often limited. In Majene City and Campalagian Village, West Sulawesi, drinking water is predominantly sourced from wells and springs, but these sources have shown elevated levels of pollutants, such as manganese and coliforms, exceeding government standards. This study explores the relationship between water quality awareness and drinking water consumption behavior in these regions using Structural Equation Modeling-Partial Least Squares (SEM-PLS). Data were collected through household surveys and laboratory testing of water samples, focusing on physical, chemical, and biological parameters. SEM-PLS was employed for its ability to analyze latent variables and handle small sample sizes effectively. Results reveal that water quality awareness explains 78.6% of the variance in drinking water consumption behavior (R² = 0.786), with key indicators such as knowledge of water quality standards and contamination risks strongly predicting positive behavioral changes. Hypothesis testing confirmed a significant positive relationship (path coefficient = 0.887, p < 0.001), underscoring the importance of awareness in promoting healthy consumption behaviors. These findings highlight the need for targeted public education campaigns and policy interventions to improve water quality awareness and consumption practices. The study also contributes to the growing application of SEM-PLS in environmental and public health research, offering insights into the complex interplay between awareness and behavior. Future research should consider integrating socio-economic and cultural factors to develop a more holistic understanding of drinking water consumption patterns.
Analisis Support Vector Regression untuk Meramalkan Saham Perusahaan Dss di Indonesia Mahgfirah, Aulya Atika; Hikmah, Hikmah; Rahayu, Putri Indi
VARIANSI: Journal of Statistics and Its application on Teaching and Research Vol. 7 No. 01 (2025)
Publisher : Program Studi Statistika Fakultas MIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/variansiunm356

Abstract

Forecasting is the process of estimating future events based on past information. In this study, the Support Vector Regression (SVR) method with the grid search time series cross-validation algorithm was used to analyze time series data. SVR is an extension of Support Vector Machine (SVM) for regression. This research aims to obtain the best model for predicting and forecasting the daily stock time series data of DSS company in Indonesia. The study compares four types of kernels—linear, polynomial, RBF, and sigmoid—to determine the best model. Model accuracy evaluation was conducted using RMSE, MSE, MAPE, and R-squared, where the model with the lowest error value was considered the best. The results show that SVR with a linear kernel, parameter C = 100, and epsilon = 0.01 produced an RMSE of 0.0583, MSE of 0.0034, MAPE of 10.53%, and R-squared of 0.99. Based on the MAPE value, this model is considered suitable for forecasting DSS stock, showing a downward trend in predictions
Pendampingan Pengelolaan Website Kelurahan : Kunci Membuka Potensi Kelurahan dan Reformasi Pelayanan kepada Masyarakat Hidayatullah, Muhammad; Hijrah, Muh.; Rahayu, Putri Indi; Presda, Ignasius; B, Ihsan; Apriana, Apriana; Nuraviat, Sitti; Kartini, Kartini
Jurnal Pengabdian kepada Masyarakat Nusantara Vol. 6 No. 1 (2025): Jurnal Pengabdian kepada Masyarakat Nusantara Edisi Januari - Maret
Publisher : Lembaga Dongan Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55338/jpkmn.v6i1.5172

Abstract

Perkembangan teknologi informasi telah mendorong transformasi digital di berbagai sektor, termasuk di pemerintahan lokal seperti kelurahan. Namun, banyak kelurahan di Indonesia, termasuk Kelurahan Lembang, Kabupaten Majene, belum memanfaatkan teknologi digital secara optimal untuk meningkatkan pelayanan kepada masyarakat. Pengabdian ini bertujuan untuk mendampingi pengelolaan website Kelurahan Lembang sebagai upaya untuk membuka potensi kelurahan dan mereformasi pelayanan publik. Metode pelaksanaan kegiatan terdiri atas tiga tahap: (1) persiapan, meliputi survei kebutuhan dan pengembangan website kelurahan; (2) implementasi, berupa pelatihan dan pendampingan pengelolaan website kepada aparatur kelurahan; serta (3) evaluasi, dengan menggunakan kuesioner kepuasan peserta untuk menilai efektivitas kegiatan. Hasil kegiatan menunjukkan bahwa pengelolaan website kelurahan mampu meningkatkan efisiensi pelayanan, transparansi, dan akses informasi bagi masyarakat. Selain itu, website ini menjadi media promosi potensi sumber daya alam dan budaya yang dimiliki oleh Kelurahan Lembang.
APPLICATION OF SUPPORT VECTOR MACHINE FOR CLASS IMBALANCE LEARNING TO PREDICT ANTICANCER COMPOUNDS OF MEDICINAL PLANTS IN WEST SULAWESI Hikmah, Hikmah; A Syahrir, Nur Hilal; Rahayu, Putri Indi
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/barekengvol18iss1pp0141-0150

Abstract

Indonesian medicinal plants, such as turmeric and soursop, have shown promising anticancer properties through their bioactive compounds, like curcumin and extracts from soursop. Despite many extensive studies on medicinal plants in Indonesia, research revealing the activity of natural products in West Sulawesi is still limited, and the studies focus mainly on ethnobotanical research. In this work, we propose a machine-learning approach to predict the anticancer activity of compounds in medicinal plants in West Sulawesi by leveraging high throughput-screening data, especially molecular information from a public database. We applied Support Vector Machine (SVM) with five sampling techniques to address data imbalance. We also evaluated the performance in selecting the best combination in handling class imbalance learning in our dataset. The result shows that undersampling and ADSYN methods can improve the prediction of anticancer activity. Based on the two methods of balancing data, we have ten potential anticancer compounds from three medicinal plants in West Sulawesi.
Co-Authors A Syahrir, Nur Hilal Apriana Apriana B, Ihsan Hidayatullah, Muhammad Hijrah, Muh. Hikmah Hikmah Kartini Kartini Mahgfirah, Aulya Atika Mayapada, Retno Musafira Musafira Muzakir, Nurul Azizah Nuraviat, Sitti Pardomuan Robinson Sihombing Presda, Ignasius Syahrir, Nur Hilal A. Yanti, Reski Wahyu