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All Journal MATEMATIKA JURNAL MATEMATIKA STATISTIKA DAN KOMPUTASI Bulletin of Electrical Engineering and Informatics Jurnal Ketahanan Nasional Jurnal Sains Matematika dan Statistika Syntax Literate: Jurnal Ilmiah Indonesia MUST: Journal of Mathematics Education, Science and Technology BAREKENG: Jurnal Ilmu Matematika dan Terapan JTAM (Jurnal Teori dan Aplikasi Matematika) Zeta - Math Journal J Statistika: Jurnal Ilmiah Teori dan Aplikasi Statistika Fair Value: Jurnal Ilmiah Akuntansi dan Keuangan Variance : Journal of Statistics and Its Applications Jurnal Varian Inferensi Jurnal Keselamatan Transportasi Jalan (Indonesian Journal of Road Safety) Journal of Mathematics Education and Science Journal of Scientific Research, Education, and Technology Jurnal Statistika dan Komputasi (STATKOM) Eksponensial Economic Development Analysis Journal PARADIGM : JOURNAL OF MULTIDISCIPLINARY RESEARCH AND INNOVATION Jurnal Keselamatan Transportasi Jalan
Ana, Elly
Statistics Study Program, Faculty Of Science And Technology, University Of Airlangga, Surabaya, Indonesia
Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Mechanical Engineering Physics Social Sciences Transportation Other

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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.
Reduksi Faktor-Faktor yang Mempengaruhi Kualitas Air Hujan dengan Metode Analisis Komponen Utama Nitasari, Alfi Nur; Salsabila, Fatiha Nadia; Ramadhanty, Devira Thania; Anggriawan, Muhammad Rizal; 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.2023.8.1.7-15

Abstract

The increase in air pollution that occurs due to industrial and economic activities will affect the rainwater content. The vital function of one of the sources of clean, namely rainwater, makes the urgency of research on indications of a decrease in rainwater quality by analyzing the substances contained. The parameters used for the determination of rainwater quality are the degree of acidity, conductivity, calcium, magnesium, sodium, potassium, ammonium, sulfate ions, nitrate ions, chloride ions, total hardness, and acidity. The data source used is data from the Central Statistics Agency (BPS) entitled "Indonesian Environmental Statistics 2022". By using the main component analysis method to reduce the variables of rainwater quality influence factors in 35 city/station samples in Indonesia, results were obtained, namely rainwater quality influence factors that can be formed into three main components with each containing 10 variables consisting of acidity, conductivity, magnesium, sodium, potassium, chloride ions, sulfate ions, nitrate ions, total hardness, and acidity capable of explaining 73.695% of the total variance.
ANALISIS FAKTOR KEMISKINAN DI PROVINSI SUMATERA UTARA BERDASARKAN REGRESI KOMPONEN UTAMA Aldawiyah, Najwa Khoir; Astuti, Aprillia; Kurnia, Rizky Dwi; Amalia, Nadinta Kasih; Amelia, Dita; Mardianto, M. Fariz Fadillah; Ana, Elly
VARIANCE: Journal of Statistics and Its Applications Vol 6 No 1 (2024): VARIANCE: Journal of Statistics and Its Applications
Publisher : Statistics Study Programme, Department of Mathematics, Faculty of Mathematics and Natural Sciences, University of Pattimura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/variancevol6iss1page63-74

Abstract

Kemiskinan merupakan permasalahan terkait kesejahteraan masyarakat yang serius dan menjadi indikator keberhasilan ekonomi dari suatu negara. Provinsi Sumatera Utara merupakan salah satu provinsi dengan jumlah penduduk miskin terbanyak dengan total 1,2 juta jiwa di pulau Sumatera pada tahun 2022. Tujuan penelitian ini yaitu menangani masalah multikolinearitas pada faktor-faktor yang mempengaruhi kemiskinan di Provinsi Sumatera Utara dengan menggunakan analisis komponen utama. Data yang diperoleh merupakan data yang didapatkan dari Badan Pusat Statistik Provinsi Sumatera Utara. Terdapat 8 variabel prediktor yang digunakan dan terbentuk 3 komponen utama dengan keragaman total sebesar 84,5%. Komponen utama yang terbentuk kemudian diregresikan dan diperoleh persamaan . Model regresi tersebut terbebas dari masalah multikolinearitas dan ketiga komponen secara signifikan berpengaruh terhadap jumlah penduduk miskin di Provinsi Sumatera Utara.
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).
Classification Classification of Criminal Events Based on Biplot Analysis Fauzi, Doni Muhammad; Dewanty, Sanda Insania; Putri, Farah Fauziah; Inneztiana, Alya Rahma; Mardianto, M. Fariz Fadillah; Amelia, Dita; Ana, Elly
Jurnal Varian Vol. 7 No. 2 (2024)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/varian.v7i2.3795

Abstract

Kriminalitas merupakan suatu perilaku yang melanggar hukum dan aturan dalam masyarakat. Penelitian ini dilakukan untuk menganalisis data biplot jumlah kejahatan di berbagai provinsi di Indonesia. Biplot merupakan analisis yang berguna untuk menafsirkan hubungan antara variabel dan objek dalam bentuk grafik tunggal. Sumber data dalam penelitian ini adalah data sekunder yang berasal dari website Badan Pusat Statistik yang berjudul “Statistik Kriminal 2022”. 34 kepolisian daerah yang mewakili setiap provinsi di Indonesia menjadi objek pengamatan dan 9 klasifikasi kejahatan menjadi variabel. Metode penelitian ini menggunakan analisis biplot dengan bantuan fiton. Dari nilai Dekomposisi Nilai Singular, keragaman data yang dapat dijelaskan sebesar 73,714%. Pada grafik analisis biplot hubungan antar observasi diperoleh bahwa observasi atau objek polda dari setiap provinsi tersebar terpusat pada satu kuadran. Hubungan antar variabel yang paling tinggi adalah korelasi antara variabel kejahatan narkotika dengan kejahatan yang berkaitan dengan penggelapan, penipuan, dan korupsi, sedangkan hubungan yang paling rendah adalah korelasi antara kejahatan narkotika dengan kejahatan terhadap ketertiban umum. Dalam hubungan observasi dengan variabel diperoleh 4 kelompok. Keberagaman variabel yang paling tinggi terletak pada kejahatan terhadap kebebasan masyarakat, sedangkan keberagaman variabel yang paling rendah terletak pada kejahatan terhadap kesusilaan.
Analyzing Gender Equality Indicators Using Principal Component Analysis in Central Papua and Papua Highland Shafira Renianti, Fayza; Suliyanto; Amelia, Dita; Mardianto, M. Fariz Fadillah; Ana, Elly
Journal of Scientific Research, Education, and Technology (JSRET) Vol. 4 No. 4 (2025): Vol. 4 No. 4 2025
Publisher : Kirana Publisher (KNPub)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58526/jsret.v4i4.972

Abstract

The Gender equality is one of the key targets in Sustainable Development Goal (SDG) 5 and remains a major challenge in Central Papua and Papua Highland, where gender development indicators are among the lowest in Indonesia. This study aims to identify the dominant factors influencing gender equality in these two provinces using Principal Component Analysis (PCA) on seven indicators representing education, health, economic conditions, and political representation of women. The analysis results show that two main factors are formed with a total variance explained of 77.248%. The first factor reflects women’s economic participation and basic living conditions, while the second factor represents resource capacity and socio-political representation. These findings suggest that limited access to education, health services, and participation in the labor market and political institutions are the primary contributors to gender inequality in this region. Therefore, empowerment-oriented policies and improved service accessibility are required to achieve more equitable gender development in Papua.
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.
PREDICTION OF STUDENT LEARNING MASTERY IN INFORMATICS USING A MACHINE LEARNING APPROACH Tianda, Izhar Muhammad; Ana, Elly
PARADIGM : Journal Of Multidisciplinary Research and Innovation Vol 3 No 02 (2025): PARADIGM : Journal Of Multidisciplinary Research and Innovation
Publisher : Pusat Studi Ekonomi Publikasi Ilmiah dan Pengembangan SDM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62668/paradigm.v3i02.1994

Abstract

This study aims to develop a robust machine learning framework for predicting student learning mastery in Informatics subjects. The research employs a supervised learning approach using assessment-based features derived from student academic records. Due to limitations commonly found in real educational data, including imbalance and data leakage risks, synthetic data generation and feature engineering were applied to support controlled experimentation. Several classification models were implemented to evaluate the stability and consistency of the proposed framework. The results indicate that the models were able to consistently distinguish between students who achieved learning mastery and those who did not. The comparable performance across different modeling approaches suggests that the predictive capability is driven by the methodological design rather than dependence on a specific algorithm. This study demonstrates that machine learning can provide a reliable and interpretable tool to support data-driven evaluation and early intervention in Informatics education.
Analisis Hubungan Faktor Ekonomi dan Sosial dengan Kabahagiaan Dunia Berdasarkan Korelasi Kanonik Julia Widiyanti; Cantika Dhiya; Ganesya Intantalia; Maulana Syah Putra Ramadhani; Elly Pusporani; Elly Ana
Journal of Mathematics Education and Science Vol. 9 No. 1 (2026): 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.v9i1.5076

Abstract

This study aims to analyze the multivariate relationship between socioeconomic factors and global happiness indicators. Data taken from the 2019 World Happiness Report, which covers 125 countries, was analyzed using canonical correlation methods. The socio-economic dimension is represented by four variables, namely social support, freedom to make life choices, log GDP per capita, and healthy life expectancy. Meanwhile, the second group of variables representing happiness indicators includes ladder score, positive affect, and negative affect. The first canonical function shows a very strong and statistically significant relationship between the two sets of variables. The resulting canonical correlation is very high, namely rho_1=0.9243 with a p-value < 0.001, and this function is able to explain 85.4% of the overlapping variance. The main contributing variables are social support with a loading of 0.983 and log GDP per capita of 0.914 in the socio-economic set, as well as ladder score with a loading of 0.997 in the happiness set. Meanwhile, the second and third canonical functions generated in this analysis show relatively limited contributions. The results of this analysis confirm that social support and economic prosperity play a fundamental role in a country's happiness. The policy implications of these findings emphasize the need for integrated interventions that simultaneously strengthen social capital and promote sustainable economic growth.
Co-Authors Abdillah, Adrian Wahyu Adma Novita Sari Aflaha, Nabila Shafa Agnes Happy Julianto Ain, Dzuria Hilma Qurotu Aini Divayanti Arrofah Aldawiyah, Najwa Khoir Alya Rahma Inneztiana Amalia, Nadinta Kasih Ameliatul 'Iffah Anggriawan, Muhammad Rizal Aniq Atiqi Anisa Laila Azhar Annisa Putri Nayumi Ardi Kurniawan Ardi Kurniawan Ariyawan, Jovansha Astuti, Aprillia Aulia Ramadhanti Aulia, Niswa Faizah Ayuning Dwis Cahyasari Azzah Nazhifa Wina Ramadhani Bintang Alyaa Sabila Budi Lestari Budijono, Gabriella Agnes Cantika Dhiya Christopher Andreas Cynthia Anggelyn Siburian Darmawan, Kezia Eunike Davina Shafa Vanisa Dewanty, Sanda Insania Dewi, Berlianti Alisa Dita Amelia Dita Amelia Dita Amelia, Dita Doni Muhammad Fauzi Dwiyanto, Adelia Sukma Elly Pusporani Erfiana Erfiana Faradilla Harianto Farah Fauziah Putri Fauzi, Doni Muhammad Fitri, Marfa Audilla Fitriyani, Mubadi’ul Fortunata, Regina Ganesya Intantalia Ghasani, Anisah Nabilah Grace Lucyana Koesnadi Gunawan, Syifa' Azizah Putri Hardiansyah, Fernanda Rizky Humaira, Edla Putri Ilma Amira Rahmayanti Inneztiana, Alya Rahma Isna Nurul Izza Amalia Julia Widiyanti Karina Rubita Makhbubah Karina Tri Handayani Khairian, Farhan Aldan Khoirun Niswatin Kurnia, Rizky Dwi Kusuma, Shalwa Oktavia M. Fariz Fadillah Mardianto M. Nabil Saputra Mahadesyawardani, Arinda Marbun, Barnabas Anthony Philbert Marcel Laverda Subiyanto Maria Setya Dewanti Marpaung, Josua Ronaldo Davico Marthabakti, CitraWani Maulana Syah Putra Ramadhani Mochammad Baihaqi Muhammad Fikry Al Farizi Muhammad Rizaldy Baihaqi Muhammad Rosyid Ridho Az Zuhro Muhammad Walid Jumlat Na&#039;imatul Lu&#039;lu&#039;a Nadia Dwi Marwanda Nitasari, Alfi Nur Noviatus Sholihah Nugroho, Hariawan Widi Nur Chamidah Nur chamnidah Nurdin, Nabila Pambudi, Daffa Satrio Pratama, Fachriza Yosa Putra, Mochamad Rasyid Aditya Putri Fardha Asa Oktavia Hans Putri Masyita Qomaryah Putri, Farah Fauziah Rahmada, Indrastanto Oktodian Rahmanita, Tentri Ryan Ramadhan, Achmad Wahyu Ramadhani, Maulana Syah Putra Ramadhanty, Devira Thania Salsabila, Fatiha Nadia Salsabylla Nada Apsariny Sanda Insania Dewanty Sari, Ni Wayan Widya Septia Sediono, Sediono Shafira Renianti, Fayza Siagian, Kimberly Maserati Siti Maghfirotul Ulyah Sofia Andika Nur Fajrina Suliyanto Suliyanto Suliyanto Suliyanto Suryono, Alda Fuadiyah Syaugi Sungkar, Salman Tagawa, Dustin Nathanael Tianda, Izhar Muhammad Toha Saifudin Vanisa, Davina Shafa Wibawa, Yoga Setya Wulandari, Indana Zulfa Yolanda Swastika Yonani Zahrani, Vista Vanadya Zhafirab, Azizah Atsariyyah