Article Per Year (5 Year)
p-Index From 2020 - 2025
3.604
P-Index
This Author published in this journals
All Journal Media Statistika Jurnal Pendidikan dan Pembelajaran Khatulistiwa (JPPK) Jurnal Sains Matematika dan Statistika BAREKENG: Jurnal Ilmu Matematika dan Terapan JTAM (Jurnal Teori dan Aplikasi Matematika) Zeta - Math Journal QARDHUL HASAN: MEDIA PENGABDIAN KEPADA MASYARAKAT International Journal of Engineering, Science and Information Technology Indonesian Journal of Education Methods Development Dirgamaya: Jurnal Manajemen dan Sistem Informasi Kajian Moral dan Kewarganegaraan Madani: Multidisciplinary Scientific Journal Karimah Tauhid Indonesian Culture and Religion Issues JIPSD Progressus Humanitatis Limits: Journal of Mathematics and Its Applications
Dita Amelia, Dita
Unknown Affiliation
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Physics Public Health Social Sciences Transportation Other

Published : 26 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 26 Documents
Search

 1   2   3 
Pemanfaatan Media Sosial Untuk Mendorong Kesadaran Lingkungan Putri, Riski Dwi; Amelia, Dita; Shabira, Syahla Malika
Madani: Jurnal Ilmiah Multidisiplin Vol 3, No 1 (2025): February
Publisher : Penerbit Yayasan Daarul Huda Kruengmane

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.14597865

Abstract

This study aims to analyze the use of social media in promoting environmental awareness among the public, considering the increasing awareness of the negative impacts of climate change and environmental pollution. This study has three main objectives: first, to identify the most effective types of content in increasing public awareness and participation in environmental issues; second, to evaluate the impact of environmental campaigns on social media platforms on changes in public behavior and attitudes; and third, to examine the role of collaboration with influencers and environmental organizations in expanding the reach of environmental awareness messages. By using quantitative survey methods and qualitative elements, it is hoped that the results of this study can provide valuable insights for the development of more effective communication strategies in increasing awareness and collective action on environmental issues in Indonesia.
Comparison of Vector Error Correction Model Prediction and Multiresponse Fourier Series, Case Study: Open Unemployment Rate in Indones IA Suliyanto, Suliyanto; Amelia, Dita; Raya, Kezya Bato; Evelyn, Jennifer
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 8, No 4 (2024): October
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v8i4.24108

Abstract

Unemployment is someone who has been classified in the active labour force is looking for work at a certain wage level, but not getting the job they want. According to the International Monetary Fund (IMF) 2023, Indonesia is ranked second highest in Southeast Asia, ranked 16th in Asia and ranked 58th in the world with a percentage of 5.45%. The data used in this study is semester data (February and August) regarding the number of open unemployment according to the highest education completed in Indonesia taken from the website of the Central Statistics Agency (BPS) starting from 2000 to 2022. This study using comparison of multi response Fourier series regression with trigonometry method using Gamma and the Vector Error Correction Model (VECM). The result of this study is Fourier series regression method of the cos function with gamma is the best model in predicting because this method has smaller MAPE value compared to VECM method. The MAPE of Fourier Series method is 0.01%, in other hand the MAPE of VECM method is 18.90% which can be categorized as prediction results with the Fourier Series method are very accurate. The results of prediction are expected to be used as reference for government to making ideal future plan to minimalize the rate of open unemployment in Indonesia. 
Analysis of Factor Affecting Tuberculosis Cases in West Java Province Using Panel Data Regression Approach Saifudin, Toha; Aisyah, Arlisya Shafwan; Indrasta, Irma Ayu; Amelia, Dita
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 8, No 4 (2024): October
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v8i4.24795

Abstract

Tuberculosis (TB) is a disease that can cause death with the largest number of sufferers after COVID-19. In Indonesia, the number of TB cases reached 724.309 cases in 2022 with the highest number 184.406 cases in West Java Province. Given this situation, Indonesia must try to achieve the health target from SDGs, namely ending the TB epidemic by 2030. Therefore, this research aims to analyze the factors that have a significant influence on the incidence of TB in Indonesia, especially in West Java Province. The research focuses on four variables: percentage of poverty, number of diabetics, number of HIV/AIDS patients, and population density. To provide a more informative analysis, this research uses a combination of cross-section and time series data from 27 regions between 2020 and 2022. So, the method used according to the type of data is panel data regression including common effect, fixed effect, and random effect models. Based on statistical tests, namely through the chow test, hausman test, and lagrange multiplier test, it was found that the best model was fixed effect with an R-squared value of 90%. The research revealed that all the studied factors significantly influence the incidence of TB cases in West Java. The results of this study are expected to help the West Java government in an effort to reduce the number of TB cases and formulate policies by reducing the percentage of poverty and population density in West Java. By ensuring the availability of health facilities such as establishing health centers in densely populated areas and counseling programs also need to be conducted to underscore the importance of TB control in West Java.
PREDICTION OF CRUDE OIL PRICES IN INDONESIA USING FOURIER SERIES ESTIMATOR AND ARIMA METHOD Rahma, Alma Khalisa; Abidin, Qumadha Zaenal; Prasetyo, Juan Krisfigo; Larasati, Berliani; Amelia, Dita; Chamidah, Nur
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 3 (2024): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol18iss3pp1673-1682

Abstract

Crude oil is one of the non-renewable natural resources that is crucial for countries around the world in driving economic development. However, the availability of crude oil is decreasing over time. The high demand for crude oil results in scarcity which causes price fluctuations. Low oil prices can reduce state revenues, disrupt development programs, and even trigger budget deficits. On the other hand, an increase in crude oil prices can make a positive contribution to state revenues. Crude oil exports become more profitable, which can increase state revenue through royalties and taxes levied on the oil and gas sector. This additional revenue can be used to support infrastructure development, social programs, and investment in key sectors of the economy. High oil prices can also harm the economy. With the many impacts that can be caused by crude oil prices, the government must be able to anticipate and prepare for it. The data used in this study are data on crude oil prices in Indonesia for monthly periods from January 2018 to October 2023 sourced from the official website of the Ministry of Energy and Mineral Resources (ESDM) of the Republic of Indonesia. The researcher tried to compare two analysis methods, namely the Fourier series and the ARIMA estimator. The results of this study show that the best method in predicting crude oil prices in Indonesia is the Fourier series estimator with Cos-Sin function which produces RMSE and MAPE values of 7.93 and 8.4%. The prediction results can be used as a reference for the government to anticipate and make programs or policies that are more focused and targeted toward the impacts that can be caused by changes in crude oil prices.
CHINESE YUAN EXCHANGE RATE AGAINST THE INDONESIAN RUPIAH PREDICTION USING SUPPORT VECTOR REGRESSION Soewignjo, Steven; Septia Sari, Ni Wayan Widya; Mediani, Andini Putri; Kamil, M. Aqil Zaidan; Amelia, Dita; Chamidah, Nur
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 3 (2024): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol18iss3pp1683-1694

Abstract

This study aims to forecast the exchange rate between the Chinese Yuan (CNY) and the Indonesian Rupiah (IDR) using Support Vector Regression (SVR), a machine-learning technique that can handle nonlinear and complex data. The authors utilize the monthly selling exchange rate of CNY against IDR from January 2012 to October 2023 sourced from the “investing” platform. The optimal SVR model is obtained by splitting the data into 113 training samples and 28 testing samples and using the Radial Basis Function (RBF) kernel. The model achieves high accuracy, with a Mean Absolute Percentage Error (MAPE) of 1.738%, a Root Mean Squared Error (RMSE) of 50.661 for the training data and a MAPE of 2.516%, and an RMSE of 64.735 for the testing data. The results of this paper can provide valuable insights for policymakers, investors, and traders who are interested in the CNY/IDR exchange rate dynamics and the economic implications of the Belt and Road Initiative (BRI). The study aligns with the Sustainable Development Goals (SDGs), specifically SDG 8, aiming to promote sustained, inclusive, and sustainable economic growth.
ANALYSIS OF GLOBAL ECONOMIC UNCERTAINTY IMPACT ON INDONESIA’S FINANCIAL AND TRADE VOLATILITY USING VECTOR ERROR CORRECTION MODEL WITH EXOGENOUS VARIABLES Amelia, Dita; Suliyanto, Suliyanto; Nugraha, Galuh Cahya; Suyono, Billy Christandy
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 19 No 4 (2025): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol19iss4pp2963-2980

Abstract

Increasing global economic uncertainty due to the influence of geopolitical dynamics and monetary policy adjustments from major countries has significantly impacted financial and trade stability in Indonesia. This research examines the relationship between global economic uncertainty and the volatility of Indonesia's financial and trade indicators using the Vector Error Correction Model with Exogenous Variables (VECM-X) approach. The model incorporates external factors such as the US Dollar Index (DXY), Volatility Index (VIX), and Trade Policy Uncertainty (TPU), using monthly data from January 2019 to December 2024. The results of the analysis show that each variable has different volatility with patterns that tend to fluctuate, and there is a cointegration relationship between the variables of the Rupiah exchange rate (USD/IDR), Jakarta Composite Index (JCI), interest rates, export, and imports. The causality test results show that exports, JCI, and imports affect interest rates without a reverse relationship, while there is a one-way relationship between exports and imports and JCI and the exchange rate. In addition, imports and JCI have a two-way relationship that affects each other. Impulse Response Function (IRF) results indicate dynamic short-term interactions among endogenous variables, which gradually stabilize over the medium to long term. In addition, the variance decomposition results show that most of the variability of each variable is explained by itself in the short term, with contributions from other variables increasing over time. This research contributes to Sustainable Development Goals (SDGs) point 8: Decent Work and Economic Growth, by providing insight to strengthen Indonesia's macroeconomic resilience. Integrating exogenous global indicators into the VECM-X model offers a more comprehensive understanding of how global shocks affect domestic stability. However, this study is limited to a macro-level analysis using secondary data and does not account for microeconomic or sectoral variations.
Modelling Consumer Price Index Effect on 10-year US Treasury Bond Yields using Least Square Spline Approach Widiyanti, Julia; Salsabila, Safira; Harsanti, Dwika Maya; Amelia, Dita; Rifada, Marisa
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 9, No 4 (2025): October
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v9i4.33020

Abstract

Inflation measured by the Consumer Price Index (CPI) is a critical indicator in the government bond market that directly affects the yields of long-term securities such as the 10-year US Treasury Bond. This study is an explanatory quantitative study that aims to examine the complex dynamics of this relationship using the nonparametric least square spline method. The analysis uses monthly CPI data from FRED and 10-year US Treasury bond yield data from Investing.com for the period 2013-2025. This method divides the data into simple polynomial segments that are smoothly connected at transition points (knots), enabling the modelling of nonlinear patterns without assuming an initial curve shape. The analysis results indicate that a first-degree polynomial spline model (piecewise linear) with three knots successfully represents the bond yield response to inflation shocks with R^2 = 86.48%. Model segmentation identified four regimes: (1) Post-crisis recovery phase, with a negative relationship driven by Fed monetary stimulus suppresing yields despite initial inflation emergence; (2) Policy normalization phase, with a positive relationship aligned with monetary tightening in response to moderate inflation; (3) During the COVID-19 pandemic, a negative relationship due to a surge in demand for safe-haven bonds despite rising inflation; (4) Post-pandemic, the relationship turned positive again following the Fed’s aggressive monetary tightening in response to high global inflation. These findings highlight the urgency of regime-based monitoring for investors and policymakers, while contributing concretely to SDG 8 (decent work and economic growth) through the facilitation of appropriate interest rate policies for sustainable macroeconomic stability, and supporting SDG 9 (industry, innovation, and infrastructure) through the identification of inflation patterns that strengthen shock-resistant infrastructure investment planning and financial innovation during turbulent economic transitions.
Analysis of Unmet Need for Health Services Based on the Percentage of Public Health Complaints with a Kernel Estimator Approach Rifada, Marisa; Amelia, Dita; Setyaningrum, Jeny Praesti; Septiandini, Niswah; Kalista, Yovita Karin; Dwitya, Shabrina Nareswari
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 9, No 4 (2025): October
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v9i4.32555

Abstract

Healthcare services are a fundamental need that governments must guarantee to ensure optimal health outcomes for all citizens. However, many individuals still face significant barriers in accessing necessary healthcare services. This quantitative research employs a spatial analysis to examine the unmet need for health services based on public health complaints, utilizing a nonparametric regression approach with Kernel estimator. The Kernel estimator method was chosen for its flexibility in capturing unstructured data patterns, allowing the analysis to better reflect real-world conditions. The study uses health complaint data from the Central Bureau of Statistics, covering 38 provinces in Indonesia in 2024. However, data from 4 provinces were incomplete, so only 34 provinces were included in the analysis. The independent variable is the percentage of public health complaints, while the dependent variable is the percentage of unmet healthcare needs. A Gaussian kernel function was applied for nonparametric regression, identified as the optimal method based on the lowest Generalized Cross Validation (GCV) value of 1.052939 at a bandwidth of 0.33. The model demonstrates high predictive accuracy, with an R² of 82.44% and a Mean Squared Error (MSE) of 30.7%. These findings provide actionable insights for targeting healthcare disparities and improving service accessibility.
Analisis Biplot pada Persebaran Penduduk Berumur 15 Tahun Ke Atas yang Bekerja Menurut Lapangan Pekerjaan Utama dan Pendidikan Tertinggi yang Ditamatkan Zah, Alfian Iqbal; Sa’idah, Andini; Zuleika, Talitha; Syahfitri, Nabila; Amelia, Dita; Mardianto, M. Fariz Fadillah
Zeta - Math Journal Vol 8 No 1 (2023): Mei
Publisher : Universitas Islam Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31102/zeta.2023.8.1.16-22

Abstract

Angkatan kerja adalah mereka yang memiliki pekerjaan, atau sedang bekerja atau menganggur sementara karena beberapa alasan. Pertumbuhan angkatan kerja dipengaruhi oleh jumlah penduduk dan struktur demografi penduduk salah satunya tingkat pendidikan. Biplot adalah salah satu analisis dalam analisis multivariat untuk menggambarkan baris dan kolom yang terdapat dalam matriks serta menggambarkan hubungan antara objek dan variabel dalam grafik tunggal. Pada penelitian ini akan dilakukan analisis biplot pada data dari BPS yaitu penduduk berumur 15 tahun ke atas yang bekerja menurut lapangan pekerjaan utama yang terdiri 17 sektor dan pendidikan tertinggi yang ditamatkan per Februari 2022. Dari analisis yang telah dilakukan, dapat diketahui bahwa vektor peubah SLTP memiliki nilai keragaman paling besar dan vektor peubah universitas memiliki nilai keragaman paling kecil. Kemudian hubungan antara amatan berupa lapangan pekerjaan dan vektor peubah berupa tingkat pendidikan dapat dikelompokkan menjadi dua kelompok yang masing-masing kelompok terdiri dari pembagian 17 sektor lapangan kerja
Penerapan Analisis Diskriminan terhadap Data Penjualan Ikan Darmawan, Kezia Eunike; Putra, Mochamad Rasyid Aditya; Fitriyani, Mubadi’ul; Dewi, Berlianti Alisa; Amelia, Dita; Mardianto, M. Fariz Fadillah; Ana, Elly
Zeta - Math Journal Vol 8 No 1 (2023): Mei
Publisher : Universitas Islam Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31102/zeta.2023.8.1.30-38

Abstract

Lautan memiliki lebar yang sangat luas dibanding daratan yang ada di bumi kita. Tidak hanya daratan saja yang dihabitati oleh makhluk hidup, tetapi perairan juga. Peraian sendiri dibagi menjadi berbagai macam yaitu air tawar, air laut, dan air payau Banyaknya kelompok dan jenis ikan yang ada membuat kita harus mengelompokkannya berdasarkan kelompok untuk dapat membedakannya. Kelompok ikan didasarkan dengan berbagai macam kelompok seperti habitat, bentuk, anatomi, hingga ukurannya. Mengutip dari data yang didapatkan pada laman kaggle, terdapat jenis ikan yang memiliki bentuk hampir menyerupai satu sama lain. Jenis-jesnis ikan yang disebutkan dalam data yaitu ikan bream, ikan parkki, ikan pearch, ikan smelt, ikan whitefish, ikan pike, dan juga ikan roach. Dilakukanlah analisis diskriminan untuk mengklasifikasikan ikan yang belum dapat dibedakan karena bentuk fisiknya yang hampir menyerupai ke dalam gugus/kelompok yang sudah ditentukan supaya tidak terjadi kerugian dalam penjualan pasar ikan. Pada hasil analisis dengan uji Wilk’s Lambda didapatkan masing-masing jenis ikan memiliki perbedaan yang signifikan, lalu kelima fungsi diskriminan dapat secara nyata membedakan ketujuh kategori target kelompok.
Co-Authors Abidin, Qumadha Zaenal Aisyah, Arlisya Shafwan Alexandra, Victoria Anggia Aliffia, Netha Anggriawan, Muhammad Rizal Apit Priatna Ardi Kurniawan Arif Maulana Yusuf Asfar Muniir, Asfar Awaludin, Dudi Azzahra, Shakilla Dahlan Abdullah Darmawan, Kezia Eunike Dewi, Berlianti Alisa Dimas Pratomo Dwitya, Shabrina Nareswari Elly Ana Evelyn, Jennifer Faizah, Atikah Fatyra, Adisa Fauziah, Nathania Febriani, Regina Firmanda, Ahmad Wahyu Fitria Eka Wulandari Fitriyani, Mubadi’ul Handayani, Nida Nabilah Harsanti, Dwika Maya Indrasta, Irma Ayu Ismunandar Julianto, Agnes Happy Kalista, Yovita Karin Kamil, M. Aqil Zaidan Khairunnisa, Nur Shabrina Kusjono, Gatot Larasati, Berliani M. Fariz Fadillah Mardianto Marisa Rifada Mediani, Andini Putri Mustika Kartika Sari Nafaisah, Lulu Nitasari, Alfi Nur Nugraha, Galuh Cahya Nur Chamidah Prasetyo, Juan Krisfigo Prastyaningrum, Aprilia Pratiwi, Rosidun Nindyo Putra, Mochamad Rasyid Aditya Putri, Riski Dwi Rahma, Alma Khalisa Rahmah , Ade Rakhma , Syavrilia Alfiatur Ramadhanty, Devira Thania Raya, Kezya Bato Salsabila, Fatiha Nadia salsabila, safira Sa’idah, Andini Sediono, Sediono Septia Sari, Ni Wayan Widya Septiandini, Niswah Sesrita, Afridha Setyaningrum, Jeny Praesti Shabira , Syahla Malika Shabira, Syahla Malika Soewignjo, Steven Sri Utami, Irma Inesia Suliyanto Suliyanto Suyono, Billy Christandy Syahfitri, Nabila Syahputra, Bimo Okta Tantry Widiyanarti, Tantry Taufiqur Rahman Teguh Prasetyo Toha Saifudin Uljanah, Lulu Urbach, Verina Widiyanti, Julia Wijayawati, Evi Yosifa, Adelia Frielady Yuliani, Salma Zah, Alfian Iqbal Zahratul Fitri, Zahratul Zuleika, Talitha