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All Journal JURNAL MATEMATIKA STATISTIKA DAN KOMPUTASI Jurnal Ilmu Sosial dan Humaniora Jurnal Ketahanan Nasional Jurnal Ilmiah Pangabdhi Jurnal Sains Matematika dan Statistika BAREKENG: Jurnal Ilmu Matematika dan Terapan JTAM (Jurnal Teori dan Aplikasi Matematika) Zeta - Math Journal J Statistika: Jurnal Ilmiah Teori dan Aplikasi Statistika Jurnal Varian Jurnal ABDINUS : Jurnal Pengabdian Nusantara Inferensi Elastisitas Jurnal Ekonomi Pembangunan Journal of Mathematics Education and Science Eksponensial Limits: Journal of Mathematics and Its Applications International Journal of Computing Science and Applied Mathematics-IJCSAM
Dita Amelia
Fakultas Sains Dan Teknologi, Universitas Airlangga
Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Energy Engineering Environmental Science Industrial & Manufacturing Engineering Mathematics Mechanical Engineering Physics Social Sciences Transportation Other

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ANALISIS BIPLOT PADA BERBAGAI FAKTOR KEMISKINAN DI INDONESIA BERDASARKAN PROVINSI Wieldyanisa, Ezha Easyfa; Ismi, Ferissa Maulida; Putri, Refa Berliana; Dwitya, Shabrina Nareswari; Elly Pusporani; Amelia, Dita
Elastisitas : Jurnal Ekonomi Pembangunan Vol. 7 No. 2 (2025): Elastisitas, September 2025
Publisher : Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/e-jep.v7i2.09

Abstract

Kemiskinan merupakan permasalahan kompleks yang dipengaruhi oleh berbagai faktor sosial dan ekonomi. Berdasarkan hal tersebut, penelitian ini bertujuan untuk melihat hubungan antara provinsi di Indonesia dan berbagai faktor yang berpengaruh terhadap kemiskinan seperti pendidikan, kesehatan, dan infrastruktur dasar menggunakan analisis biplot. Data sekunder tahun 2024 dari BPS digunakan dengan delapan variabel utama, meliputi usia harapan hidup, produk domestik regional bruto (PDRB) per kapita, angka melek huruf, rumah tangga dengan sanitasi layak, akses air layak, akses listrik, angka partisipasi sekolah, dan rata-rata lama sekolah. Hasil analisis menunjukkan bahwa 81,772% keragaman data dapat dijelaskan oleh dua komponen utama dalam grafik biplot. Provinsi-provinsi dikelompokkan ke dalam empat kuadran berdasarkan kesamaan karakteristik kemiskinan. Faktor dengan keragaman tertinggi adalah rumah tangga dengan sanitasi layak, sedangkan faktor dengan keragaman terendah adalah PDRB per kapitaKorelasi antar variabel menunjukkan bahwa angka melek huruf dan akses listrik memiliki hubungan paling kuat, yang berarti semakin tinggi tingkat melek huruf suatu daerah, semakin besar pula kemungkinan masyarakatnya memiliki akses terhadap listrik. Sebaliknya, hubungan terlemah terdapat antara PDRB dan akses listrik. Penelitian ini menunjukkan bahwa memahami kemiskinan memerlukan pendekatan terhadap berbagai faktor yang saling berkaitan serta perlunya kebijakan pembangunan yang disesuaikan dengan karakteristik daerah masing-masing.
Identifikasi Faktor yang Mempengaruhi Kemiskinan di Papua dengan Principal Component Analysis Ain, Dzuria Hilma Qurotu; Kusuma, Shalwa Oktavia; Zahrani, Vista Vanadya; Suryono, Alda Fuadiyah; Mardianto, M. Fariz Fadillah; Amelia, Dita; Ana, Elly
Journal of Mathematics Education and Science Vol. 7 No. 1 (2024): Journal of Mathematics Education and Science
Publisher : Universitas Nahdlatul Ulama Sunan Giri Bojonegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32665/james.v7i1.1336

Abstract

Penelitian ini bertujuan untuk menganalisis faktor-faktor kemiskinan terhadap pengentasan kemiskinan di Provinsi Papua. Metode yang digunakan yaitu Analisis Komponen Utama (AKU). Cakupan data yang digunakan dalam penelitian ini adalah data statistik kesejahteraan rakyat Provinsi Papua pada bulan Maret tahun 2021 yang diperoleh dari Badan Pusat Statistik (BPS). Hasil penelitian ini menunjukkan bahwa faktor-faktor yang mempengaruhi kemiskinan di Kabupaten dan Kota Provinsi Papua dapat dikategorikan menjadi tiga komponen yaitu Komponen 1 : “Pendidikan dan Kependudukan“, Komponen 2 : ”Fasilitas Imunisasi dan Penerangan”, serta Komponen 3 :  “Fasilitas Teknologi dan Kesehatan”. Dengan demikian,  penelitian  ini  bermanfaat  bagi  para  pembuat  kebijakan  baik pemerintah  pusat maupun  daerah  untuk  memperhatikan  faktor-faktor  yang  mempengaruhi terjadinya peningkatan kemiskinan di Provinsi Papua. Kemiskinan merupakan prioritas pada SDGs yang dinyatakan pada poin pertama yaitu no poverty (tanpa kemiskinan).
Pengelompokan Provinsi di Indonesia berdasarkan Ketimpangan Akses Layanan Kesehatan Tahun 2024 Menggunakan Pendekatan Cluster Hirarki Nabila Rahma Na’ifa, Ariza; Rohayah, Dewi; Yuliati, Intan; Tsabita Amalia Shofa, Nayla; Pusporani, Elly; Amelia, Dita
EKSPONENSIAL Vol. 16 No. 2 (2025): Jurnal Eksponensial
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30872/v16i2.1560

Abstract

Health disparities remain a major challenge in Indonesia, particularly in terms of access to healthcare services across provinces. This study aims to classify 38 Indonesian provinces based on inequality in healthcare access in 2024 using a hierarchical clustering approach. Three key indicators were used: the number of hospitals, the number of medical personnel, and the percentage of people experiencing health complaints who opted for self-medication. The analysis identified the average linkage method as the most suitable model, supported by the highest cophenetic correlation coefficient (0,911). The results revealed two distinct clusters. The first cluster includes most provinces outside Java Island, characterized by limited healthcare infrastructure and personnel. The second cluster comprises four provinces on Java Island with advanced healthcare facilities but a high rate of self-medication. These findings suggest that healthcare access inequality is influenced not only by infrastructure but also by social and behavioral factors. Therefore, policy recommendations should be tailored accordingly: infrastructure improvement and equitable distribution of medical personnel for the first cluster, and health education interventions for the second. This study contributes to evidence-based policy design in line with the Sustainable Development Goals (SDGs), particularly the goal of ensuring equitable healthcare access for all.
BAYESIAN ESTIMATION OF THE SCALE PARAMETER OF THE WEIBULL DISTRIBUTION USING THE LINEX AND ITS APPLICATION TO STROKE PATIENT DATA Rahmanita, Tentri Ryan; Kurniawan, Ardi; Ana, Elly; Sediono, Sediono; Amelia, Dita
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 20 No 1 (2026): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol20iss1pp0413-0426

Abstract

Survival analysis is used to study the timing of an event, such as recovery or death, in the context of medical data. One of the diseases that many people suffer from is stroke. Based on the survey results, the number of stroke sufferers in Indonesia reached 8.3% of 1000 people in Indonesia continues to increase every year, especially among the elderly. The research conducted aims to model the estimation of the type III censored Weibull distribution parameters with the Bayesian Linear Exponential Loss Function (LINEX) method. This study uses secondary data on stroke patients in the period January-November 2024 with a sample of 62 patients at the Haji Surabaya Regional General Hospital. Weibull distribution model with Bayesian approach using Linear Exponential Loss Function (LINEX) was applied to estimate the distribution parameters and survival function. The estimation results show that the parameter α is 6.32342 with an average hospitalization time of 5.9151646 days. MSE value is 0.000270555, which indicates that the estimation model is more accurate in predicting data for the length of hospitalization for stroke patients at the Haji Surabaya Regional General Hospital. The probability value of the survival function of stroke patients who have been hospitalized on the 5th day shows a probability of 82.4% so that no further hospitalization is needed, which indicates that the patient's health condition is improving. In addition, the hazard function analysis shows that the longer a patient is hospitalized, the greater the risk of the patient not recovering.
Analisis Survival Distribusi Lomax dengan Estimasi Maximum Likelihood Victoria Anggia Alexandra; Aprilia Prastyaningrum; Ardi Kurniawan; Dita Amelia
Limits: Journal of Mathematics and Its Applications Vol. 22 No. 1 (2025): Limits: Journal of Mathematics and Its Applications Volume 22 Nomor 1 Edisi Ma
Publisher : Pusat Publikasi Ilmiah LPPM Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/limits.v22i1.3373

Abstract

Survival analysis is a statistical technique used to test the durability and reliability of a component. Life time data obtained from a life test experiment is often in the form of type III censored data, which occurs when observations enter at different times and last for varying durations. In survival analysis, data is expected to follow a certain probability distribution. To determine the characteristics of a population, a point estimate of the probability distribution parameters is conducted. This study aims to obtain parameter estimators of the Lomax distribution on type III censored data with the Maximum Likelihood Estimation (MLE) and Newton Raphson methods. Application of parameter estimation results on post-heart surgery survival data in one of the Jakarta hospitals. The result of estimating the parameter value in the post-heart surgery patient data is 1.552 and the result of estimating the parameter in the post-heart surgery patient data is 20.38. Based on these results, it can be concluded that the estimated probability of survival of a post-heart surgery patient for more than 49 days is 14.94%.
Pengaruh Suplementasi Vitamin D dan BMI terhadap LVEF dengan Pendekatan Generalized Additive Models Longitudinal Dita Amelia; Suliyanto Suliyanto; Victoria Anggia Alexandra; Adelia Frielady Yosifa; Syavrilia Alfiatur Rakhma; Agnes Happy Julianto
Limits: Journal of Mathematics and Its Applications Vol. 22 No. 1 (2025): Limits: Journal of Mathematics and Its Applications Volume 22 Nomor 1 Edisi Ma
Publisher : Pusat Publikasi Ilmiah LPPM Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/limits.v22i1.3378

Abstract

Cardiovascular diseases (CVD) are the leading cause of global mortality, with Left Ventricular Ejection Fraction (LVEF) being a key indicator of heart function. This study explores the impact of vitamin D supplementation and Body Mass Index (BMI) on LVEF using Generalized Additive Models (GAM) in longitudinal data from 47 elderly patients with hypovitaminosis D undergoing orthopedic surgery. LVEF was measured before surgery and at 1, 3, and 6 months post-intervention. GAM was employed to capture nonlinear relationships between variables with working correlation structures such as Independence, Exchangeable, Unstructured, and Autoregressive-1 (AR-1). The findings revealed a significant increase in vitamin D levels and LVEF following supplementation, while BMI remained relatively stable throughout the observation period. The best GAM model with AR-1 correlation structure achieved the lowest Quasi Information Criterion (QIC) score of 443.47, indicating a complex relationship between vitamin D and LVEF and a linear relationship between BMI and LVEF. Vitamin D demonstrated a significant nonlinear effect on LVEF improvement, whereas a 1-point increase in BMI raised LVEF by 0.291%. This study underscores the importance of vitamin D supplementation in enhancing heart function among elderly patients with hypovitaminosis D, supporting the development of evidence-based health policies
Indeks Pembangunan Gender Indonesia dalam Perspektif Pendekatan Spasial dengan Pembobot Queen Contiguity Dita Amelia; Made Riyo Ary Permana; Adelia Frielady Yosifa; Ardi Kurniawan; Suliyanto
Limits: Journal of Mathematics and Its Applications Vol. 21 No. 2 (2024): Limits: Journal of Mathematics and Its Applications Volume 21 Nomor 2 Edisi Ju
Publisher : Pusat Publikasi Ilmiah LPPM Institut Teknologi Sepuluh Nopember

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

Abstract

Isu gender menjadi fokus global karena ketimpangan dalam hak-hak dan kontribusi laki-laki dan perempuan dalam pembangunan. Pencapaian Indeks Pembangunan Gender (IPG) menjadi tolok ukur penting dalam upaya mencapai kesetaraan gender dan pembangunan manusia yang inklusif di Indonesia. Penelitian ini bertujuan untuk memodelkan Indeks Pembangunan Gender di Indonesia dengan pendekatan regresi spasial dengan variabel-variabel yang diduga mempengaruhi IPG. Metode yang digunakan dalam penelitian ini adalah regresi spasial dengan pembobot Queen Contiguity . Berdasarkan penelitian yang telah dilakukan dengan tiga jenis pemodelan didapatkan model terbaik dalam pemodelan Indeks Pembangunan Gender di Indonesia adalah model regresi spasial error dengan nilai AIC sebesar 154,950 dan nilai R 2 sebesar 0,6643. Analisis spasial mengungkapkan adanya korelasi dan heterogenitas spasial antar wilayah, menyoroti pentingnya mempertimbangkan aspek spasial dalam merancang kebijakan untuk meningkatkan pembangunan gender di Indonesia. Dengan demikian, upaya perbaikan dan kesetaraan gender sebaiknya diterapkan dengan mempertimbangkan variabilitas spasial serta fokus pada aspek-aspek yang telah diidentifikasi melalui pemodelan ini.
Analisis Nilai Inflasi Bulanan Indonesia Menggunakan Regresi Nonparametrik Estimator Kernel Azzah Nazhifa Wina Ramadhani; Adelia Sukma Dwiyanto; Nuzulia Anid; Muhammad Hafidzuddin Nahar; Dita Amelia
Limits: Journal of Mathematics and Its Applications Vol. 21 No. 2 (2024): Limits: Journal of Mathematics and Its Applications Volume 21 Nomor 2 Edisi Ju
Publisher : Pusat Publikasi Ilmiah LPPM Institut Teknologi Sepuluh Nopember

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

Abstract

High levels of inflation are plaguing Indonesian society. Inflation occurs due to price increases as indicated by the increase in most expenditure group indices. This can lead to a higher poverty rate in Indonesia. This study aims to identify the best method that can be used to estimate Indonesia's monthly inflation value based on a nonparametric regression approach with a kernel estimator and analyze the results of predicting Indonesia's monthly inflation value for the next four months. The data used in this study is secondary data sourced from Bank Indonesia, with the variable used is the value of Indonesian inflation during the period January 2019 to July 2024. The collected data were analyzed using descriptive statistics and analytical statistics in the form of nonparametric regression with kernel estimators and predictions using kernel estimator and non-seasonal ARIMA methods. The results showed that triweight kernel regression was the best kernel function model with a minimum bandwidth value of 1.214, value of 99.990, MSE of 0.00016, and MAPE of 0.348%. The results of data prediction for the next thirteen months provide that triweight kernel estimator was better than non seasonal ARIMA method, with a MAPE value of 10.92%, so that the nonparametric regression method with the triweight kernel function is good or accurate in predicting data, which also can be used to analyze and predict Indonesia's monthly inflation data.
Assessment of Dietary Intervention Effects on Food Intake in Mus musculus using Repeated Measures ANOVA Suliyanto, Suliyanto; Amelia, Dita; Arrofah, Aini Divayanti; Alisiah, Rindiani Ahmada; Anida, Nuzulia; Maulidya, Utsna Rosalin
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 10, No 2 (2026): April
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v9i4.32467

Abstract

The prevalence of type 2 diabetes, metabolic syndrome, along with obesity that causes disturbances in the body's metabolic processes are the main triggers of chronic liver disease or in scientific language called Non-Alcoholic Fatty Liver Disease (NAFLD), getting out of control. This makes managing this disease an increasingly serious global health challenge. One of the main factors influencing this condition is a high-fat diet and an unhealthy lifestyle. Therefore, evaluation of high-fat diet programs on metabolic parameters such as food intake patterns is important as a preventive measure. This study aims to analyze the differences in food intake levels with seven different types of dietary treatments for 28 days, which were tested on mice (Mus musculus) which have physiological and biochemical characteristics that almost resemble humans. The method used was analysis of variance (ANOVA) for longitudinal data to evaluate the dynamics of food consumption across diet groups and observation periods. The results showed that the type of dietary treatment significantly influenced food intake patterns over time, indicating that diet composition plays a crucial role in shaping eating behavior. These findings highlight the importance of both diet type and treatment duration in influencing consumption patterns. However, since this study has not yet identified the most effective dietary regimen, future research is recommended to investigate diet types with high variability, while considering additional factors such as age, sex, and physiological characteristics, as well as extending the observation period to better understand long-term impacts.
Analyzing the Influence of Gross Domestic Product on the Human Development Index Worldwide in 2021 Using a Nonparametric Regression Approach Based on Penalized Spline Estimator Dita Amelia; Azizah Atsariyyah Zhafira; Bryan Given Christiano Ginzel; Fery Yulian Putra; Yoga Setya Wibawa
(IJCSAM) International Journal of Computing Science and Applied Mathematics Vol. 11 No. 2 (2025)
Publisher : LPPM Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j24775401.ijcsam.v11i2.8851

Abstract

People’s welfare is a universal goal that is the main focus of all countries in the world. One of the indicators used to measure welfare is the Human Development Index (HDI), which includes education, health and per capita income. On the other hand, Gross Domestic Product (GDP) is the main measure of a region’s economic growth. This research aims to highlight how regional economic dynamics affect human welfare in the world in 2021 and the data source was obtained from OurWorldInData. This research uses nonparametric regression with a penalized spline estimator approach. Penalized Spline analysis shows that the best model for predicting HDI based on GDP per capita is to use 2 knot points, namely k1=8000 and k2=50000. This model produces a Mean Squared Error (MSE) value of 0.0018 and Generalized Cross Validation (GCV) of 0.0019. In addition, this model has the ability to explain response variability of R2=91.58%. The grouping of countries by GDP per capita reveals that economic improvement impacts human development differently across income levels. By tailoring strategies to specific income groups, policymakers can more effectively enhance human development outcomes, fostering a more equitable and prosperous society
Co-Authors Abdillah, Adrian Wahyu Adelia Frielady Yosifa Adelia Frielady Yosifa Adelia Sukma Dwiyanto Aditya Syarifudin Akbar Adma Novita Sari Aflaha, Nabila Shafa Agnes Happy Julianto Agnes Happy Julianto Ain, Dzuria Hilma Qurotu Aini Divayanti Arrofah Alisiah, Rindiani Ahmada Alya Rahma Inneztiana Ameliatul 'Iffah Ana, Elly Andi Vania Ghalliyah Putrie Anida, Nuzulia Anida, Nuzulia Anisa Laila Azhar Annisa Putri Nayumi Aprilia Prastyaningrum Ardi Kurniawan Ardi Kurniawan Ardi Kurniawan Ariyawan, Jovansha Arrofah, Aini Divayanti Aulia Ramadhanti Aulia, Niswa Faizah Azizah Atsariyyah Zhafira Azzah Nazhifa Wina Ramadhani Azzah Nazhifa Wina Ramadhani Bintang Alyaa Sabila Bryan Given Christiano Ginzel Budijono, Gabriella Agnes Cynthia Anggelyn Siburian Davina Shafa Vanisa Deshinta Arrova Dewi Doni Muhammad Fauzi Dwitya, Shabrina Nareswari Dwiyanto, Adelia Sukma Dwiyanto, Adelia Sukma Elly Ana Elly Ana Elly Ana Elly Ana Elly Pusporani Faradilla Harianto Farah Fauziah Putri Fery Yulian Putra Firda Aulia Pratiwi Fortunata, Regina Ghasani, Anisah Nabilah Grace Lucyana Koesnadi Humaira, Edla Putri Ismi, Ferissa Maulida Isna Nurul Izza Amalia Karina Rubita Makhbubah Karina Tri Handayani Kurniawan, Ardi Kusuma, Shalwa Oktavia M. Fariz Fadillah Mardianto M. Nabil Saputra Made Riyo Ary Permana Mahadesyawardani, Arinda Marbun, Barnabas Anthony Philbert Maria Setya Dewanti Marthabakti, CitraWani Maulidya, Utsna Rosalin Mochammad Baihaqi Muhammad Fikry Al Farizi Muhammad Hafidzuddin Nahar Muhammad Rizaldy Baihaqi Muhammad Rosyid Ridho Az Zuhro Muhammad Rosyid Ridho Az Zuhro Muhammad Walid Jumlat Mutyaravica, Astrid Na'imatul Lu'lu'a Nabila Rahma Na’ifa, Ariza Nadia Dwi Marwanda Nahar, Muhammad Hafidzuddin Nur Chamidah Nurdin, Nabila Nurrohmah, Zidni ‘Ilmatun Nuzulia Anid Pambudi, Daffa Satrio Permana, Made Riyo Ary Pratama, Fachriza Yosa Pressylia Aluisina Putri Widyangga Previan, Anggara Teguh Putri Masyita Qomaryah Putri Nur Farida Putri, Ferdiana Friska Rahmana Putri, Refa Berliana Putu Eka Andriani Rahmada, Indrastanto Oktodian Rahmanita, Tentri Ryan Ramadhan, Achmad Wahyu Ramadhani, Azzah Nazhifa Wina Ramadhani, Maulana Syah Putra Rani, Lina Nugraha Rohayah, Dewi Sanda Insania Dewanty Sediono, Sediono Siagian, Kimberly Maserati Simamora, Antonio Nikolas Manuel Bonar Siregar, Naufal Ramadhan Al Akhwal Sofia Andika Nur Fajrina Suliyanto Suliyanto Suliyanto Suliyanto Suliyanto Suliyanto Suliyanto, Suliyanto Suryono, Alda Fuadiyah Syavrilia Alfiatur Rakhma Tagawa, Dustin Nathanael Toha Saifudin Toha Saifudin Tsabita Amalia Shofa, Nayla Victoria Anggia Alexandra Victoria Anggia Alexandra Wibawa, Yoga Setya Wieldyanisa, Ezha Easyfa Wulandari, Indana Zulfa Yoga Setya Wibawa Yosifa, Adelia Frielady Yuliati, Intan Zah, Alfian Iqbal Zahrani, Vista Vanadya Zhafirab, Azizah Atsariyyah