Article Per Year (5 Year)
p-Index From 2020 - 2025
6.938
P-Index
This Author published in this journals
All Journal Media Statistika BIMASTER Epsilon: Jurnal Matematika Murni dan Terapan Jurnal Statistika Universitas Muhammadiyah Semarang BAREKENG: Jurnal Ilmu Matematika dan Terapan JTAM (Jurnal Teori dan Aplikasi Matematika) Jambura Journal of Mathematics Sarwahita : Jurnal Pengabdian Kepada Masyarakat Variance : Journal of Statistics and Its Applications Jurnal Pengabdian kepada Masyarakat Nusantara JAMBURA JOURNAL OF PROBABILITY AND STATISTICS Jurnal Forum Analisis Statistik STATISTIKA
Evy Sulistianingsih
Department Of Mathematics, Universitas Tanjungpura, Jl. Prof. Dr. H. Hadari Nawawi, Pontianak, Indonesia 78124
Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Energy Engineering Environmental Science Mathematics Mechanical Engineering Physics Social Sciences Transportation Other

Published : 97 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 97 Documents
Search

 4   5   6   7   8 
PERBANDINGAN ESTIMASI VOLATILITAS HARGA OPSI BELI SAHAM APPLE INC. (AAPL) DENGAN METODE BISECTION DAN SECANT Radinasari, Nur Ismi; Sulistianingsih, Evy; Martha, Shantika
EPSILON: JURNAL MATEMATIKA MURNI DAN TERAPAN (EPSILON: JOURNAL OF PURE AND APPLIED MATHEMATICS) Vol 18, No 1 (2024)
Publisher : Mathematics Study Program, Faculty of Mathematics and Natural Sciences, Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/epsilon.v18i1.11638

Abstract

Stock price volatility is a measure of how far a stock price moves in a given Stock price volatility is a measure of how far a stock price moves in a given time. The theory developed by Black-Scholes states that every option price with the same 'underlying asset' and the same time to maturity but with different exercise values will have the same Implied Volatility value. However, this is not always the case in the market. Therefore, it is necessary to estimate volatility known as Implied Volatility, which is considered an appropriate method in estimating volatility values. This study compares the Bisection and Secant methods to estimate the volatility of Apple Inc. (Aapl) stock. This study uses data on the closing price of the stock in the period September 29, 2022 to September 29, 2023. Volatility estimation for the Bisection and Secant methods by determining the initial approximation and limiting it to a maximum of 100 simulations and iteration stops if it has produced a relative error smaller than  = . The  is an error tolerance limit, the smaller the error tolerance, the more accurate it is. According to the research results, the Bisection method produces an estimated volatility value of 0.498212 at the 9th iteration, while the Secant method produces an estimated value of 0.498590 at the 10th iteration. The Secant method produces a smaller relative error value of 0.000096, indicating that the Secant method is more accurate than the Bisection method.
CLUSTERING DISTRICT/CITY IN WEST KALIMANTAN BASED ON FACTORS CAUSING STUNTING USING K-HARMONIC MEANS METHOD Imanni, Rahmania Andarini Hatti; Sulistianingsih, Evy; Perdana, Hendra
Jurnal Statistika Universitas Muhammadiyah Semarang Vol 12, No 1 (2024): Jurnal Statistika Universitass Muhammadiyah Semarang
Publisher : Department Statistics, Faculty Mathematics and Natural Science, UNIMUS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/jsunimus.12.1.2024.%p

Abstract

Stunting is a chronic nutritional problem caused by inadequate dietary intake over time. The results of the Indonesian Nutrition Status Survey (SSGI) 2021 show that the percentage of stunting in West Kalimantan is 29.8%, higher than the national average. Based on the high number of stunting cases in West Kalimantan, it is necessary to group districts/cities in West Kalimantan based on the factors that cause stunting. This study aims to analyze the clustering of districts/cities in West Kalimantan based on the factors that cause stunting using the K-Harmonic Means method and analyze the number of optimal clusters using the silhouette coefficient. The percentage of households without access to clean drinking water , the rate of exclusive breastfeeding , the percentage of low birth weight babies born safely , the percentage of households without proper sanitation facilities  in 2021 are the variables analyzed in this study. The analysis results show that the optimal number of clusters is 4 with a silhouette coefficient value of 0.744, indicating a solid structure in the grouping. Cluster 1 is a cluster with a very high causal factor for stunting. The most influential factors in cluster 1 are households without access to clean drinking water, lack of exclusive breastfeeding, and low birth babies born safely.
PEMODELAN FAKTOR-FAKTOR YANG MEMPENGARUHI JUMLAH KEMATIAN IBU HAMIL DENGAN REGRESI ZERO INFLATED GENERALIZED POISSON (ZIGP) Perangin Angin, Christi Alemsa; Debataraja, Naomi Nessyana; Sulistianingsih, Evy
BIMASTER : Buletin Ilmiah Matematika, Statistika dan Terapannya Vol 13, No 4 (2024): Bimaster : Buletin Ilmiah Matematika, Statistika dan Terapannya
Publisher : FMIPA Universitas Tanjungpura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/bbimst.v13i4.77971

Abstract

Angka Kematian Ibu (AKI) adalah parameter kesejahteraan wanita, parameter kesejahteraan sebuah negara serta menggambarkan hasil capaian pembangunan sebuah negara. Sejak tahun 2018 hingga 2021 AKI di Kapuas Hulu mengalami peningkatan. Pada tahun 2018 AKI di Kapuas Hulu sebesar 71 per 100.000 kelahiran hidup (KH) dan tahun 2021 naik menjadi 173 per 100.000 KH, sedangkan target Sustainable Development Goals (SDGs) adalah kurang dari 70 per 100.000 KH. Data AKI tersebut merupakan data diskrit yang berdistribusi Poisson. Namun jika dilihat berdasarkan kecamatan yang ada di Kapuas Hulu, masih terdapat AKI yang nol kematian. Proporsi data nol yang berlebihan pada variabel respon dapat menyebabkan adanya masalah zero inflation. Nilai nol yang berlebihan dalam Regresi Poisson dapat menyebabkan terjadinya pelanggaran asumsi equidispersi. Hal tersebut dapat diatasi dengan Regresi ZIGP. Penelitian ini bertujuan untuk memodelkan dan menentukan faktor kematian ibu hamil di Kabupaten Kapuas Hulu tahun 2018-2021 menggunakan Regresi ZIGP. Data yang digunakan pada penelitian ini adalah data profil kesehatan di 23 kecamatan yang ada di Kabupaten Kapuas Hulu. Variabel respon ( ) yang digunakan yaitu jumlah kematian ibu hamil. Data tersebut terlebih dahulu dilakukan pengujian asumsi equidispersi. Jika terjadi pelanggaran asumsi equidispersi, maka langkah selanjutnya yaitu melakukan pengujian asumsi Zero Inflation. Apabila terjadi pelanggaran asumsi Zero Inflation, maka pemodelan dapat dilakukan dengan menggunakan Regresi ZIGP. Proporsi nilai nol pada variabel tersebut sebanyak 92%, sehingga terdapat masalah Zero Inflation dan mengindikasikan terjadinya overdispersi pada Regresi Poisson. Berdasarkan hasil pemodelan terbaik dengan Regresi ZIGP, persentase kunjungan ibu hamil pertama (K1) merupakan faktor yang berpengaruh terhadap jumlah kematian ibu hamil.  Kata Kunci: AKI, ZIGP, Overdispersi.
MODERATED PLS-SEM: PERAN IHSG SEBAGAI MODERATOR DI ANTARA RASIO KEUANGAN DAN NILAI PERUSAHAAN PERBANKAN Rifqi, Bhima Fairul; Sulistianingsih, Evy; Imro’ah, Nurfitri
BIMASTER : Buletin Ilmiah Matematika, Statistika dan Terapannya Vol 13, No 5 (2024): Bimaster : Buletin Ilmiah Matematika, Statistika dan Terapannya
Publisher : FMIPA Universitas Tanjungpura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/bbimst.v13i5.84970

Abstract

Perusahaan merupakan satu dari sekian banyak aset yang sangat berharga dan bernilai. Semakin bagus kinerja suatu perusahaan, semakin naik pula harga dan nilai dari perusahaan tersebut. Hasil kinerja suatu perusahaan dimuat di dalam laporan keuangan yang dalam bentuk rasio-rasio keuangan. Salah satu metode yang dapat diterapkan untuk melakukan analisis nilai perusahaan ialah Moderated Partial Least Squared-Structural Equation Modeling (Moderated PLS-SEM). Moderated PLS-SEM merupakan metode PLS-SEM yang melibatkan variabel moderator. PLS-SEM adalah teknik analisis multivariat berbasis varian yang tidak memerlukan asumsi normalitas dan bisa digunakan pada sampel yang berjumlah relatif kecil, sedangkan variabel moderator merupakan variabel yang bisa meningkatkan atau menurunkan tingkat hubungan antara variabel laten eksogen (ξ) dan variabel laten endogen (η), melalui pembentukan variabel interaksi. Variabel interaksi adalah variabel yang terbentuk dari interaksi antara variabel laten eksogen dan variabel moderator. Penelitian ini berfokus pada analisis pengaruh rasio-rasio keuangan (profitabilitas, likuiditas, dan solvabilitas) terhadap nilai perusahaan perbankan, serta peran Indeks Harga Saham Gabungan (IHSG) dalam memoderasi hubungan antara rasio-rasio keuangan dan nilai perusahaan. Kesimpulan yang didapat ialah hanya profitabilitas yang memberikan pengaruh signifikan terhadap nilai perusahaan perbankan dan IHSG dapat memperkuat hubungan antara rasio solvabilitas dan nilai perusahaan.  Profitabilitas dan variable interaksi yang terbentuk antara solvabilitas dan IHSG mempengaruhi nilai perusahaan sebesar 46,2%.Kata Kunci:  Rasio Keuangan, Interaksi, Moderasi.
PENGELOMPOKAN PROVINSI DI INDONESIA BERDASARKAN INDIKATOR KESEJAHTERAAN MASYARAKAT DENGAN ALGORITMA K-MEANS++ Nabilah, Niken Aushaf; Perdana, Hendra; Sulistianingsih, Evy
BIMASTER : Buletin Ilmiah Matematika, Statistika dan Terapannya Vol 13, No 3 (2024): Bimaster : Buletin Ilmiah Matematika, Statistika dan Terapannya
Publisher : FMIPA Universitas Tanjungpura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/bbimst.v13i3.77795

Abstract

Pemerataan kesejahteraan masyarakat masih menjadi salah satu fokus bagi pemerintah Indonesia hingga sekarang. Kesejahteraan masyarakat merupakan suatu konsep yang mencakup berbagai aspek kehidupan, sehingga menjadi salah satu indikator dalam mengukur kemajuan suatu negara. Oleh karena itu, analisis cluster diperlukan untuk mengelompokkan provinsi di Indonesia berdasarkan indikator kesejahteraan masyarakat. Analisis cluster merupakan metode pengelompokan objek berdasarkan karakteristik objek tersebut. Algoritma K-Means++ digunakan dalam penelitian ini untuk mengkaji pengelompokan provinsi-provinsi di Indonesia berdasarkan indikator kesejahteraan masyarakat. Selain itu, untuk menganalisis jumlah cluster optimal yang terbentuk digunakan silhouette coefficient. Data dalam penelitian ini merupakan data 10 indikator kesejahteraan masyarakat tahun 2022. Berdasarkan hasil analisis, diperoleh jumlah cluster optimal yaitu 3 cluster dengan nilai silhouette coefficient terbesar, yaitu 0,2777. Cluster 1 merupakan cluster dengan tingkat kesejahteraan masyarakat menengah dan terdiri dari 27 provinsi. Cluster 2 terdiri dari 3 provinsi dan merupakan cluster dengan tingkat kesejahteraan masyarakat rendah. Dan cluster 3 yaitu cluster dengan tingkat kesejahteraan masyarakat yang tinggi dan terdiri dari 4 provinsi.  Kata Kunci : kesejahteraan, analisis cluster, kemiskinan, silhouette coefficient
METODE ENSEMBLE K-NEAREST NEIGHBOR UNTUK PENINGKATAN AKURASI PREDIKSI INDEKS HARGA SAHAM GABUNGAN DI INDONESIA Ananda, Adelia; Sulistianingsih, Evy; Yundari, Yundari
BIMASTER : Buletin Ilmiah Matematika, Statistika dan Terapannya Vol 13, No 3 (2024): Bimaster : Buletin Ilmiah Matematika, Statistika dan Terapannya
Publisher : FMIPA Universitas Tanjungpura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/bbimst.v13i3.77705

Abstract

Indeks Harga Saham Gabungan (IHSG) merupakan gabungan dari berbagai saham yang terdapat di Indonesia dan tercatat di bursa efek Indonesia yang dihitung nilai rata-rata dari beberapa saham tersebut. IHSG adalah alat yang membantu investor melacak keseluruhan pergerakan nilai saham dari waktu ke waktu. Metode analisis diperlukan untuk meramalkan bagaimana harga saham akan berkembang di masa depan. Metode yang umum digunakan untuk memprediksi IHSG adalah metode K-Nearest Neighbor. Penelitian ini menggunakan kombinasi dari beberapa hasil prediksi KNN untuk mendapatkan sebuah hasil prediksi akhir, yaitu dengan menambahkan teknik Ensemble. Penelitian ini bertujuan untuk menganalisis hasil akurasi metode KNN yang dioptimasi dengan teknik Ensemble. Variabel respon yang digunakan dalam penelitian ini adalah Indeks Harga Saham Gabungan, sedangkan variabel prediktornya adalah harga emas, indeks Nikkei 225 dan nilai tukar rupiah terhadap dolar. Data yang digunakan adalah data mingguan dari Januari 2021 sampai Maret 2022 sebanyak 64 periode, untuk data training dan testing masing-masing sebanyak 52 periode dan 12 periode. Nilai k yang digunakan pada penelitian ini yaitu 3, 5, 7, 9, dan 11. Hasil analisis yang telah dilakukan diperoleh nilai Mean Absolute Percentage Error (MAPE) yaitu sebesar 10,656%. Berdasarkan nilai tersebut maka nilai prediksi IHSG di Indonesia dengan metode K-Nearest Neighbor yang dioptimasi dengan teknik Ensemble memiliki akurasi yang baik. Dari hasil tersebut dapat disimpulkan bahwa ketika metode KNN dioptimasi dengan teknik Ensemble memiliki nilai MAPE yang lebih besar dibandingkan dengan nilai MAPE KNN tunggal yang memiliki nilai MAPE terkecil pada k=11. Oleh karena itu metode KNN yang dioptimasi dengan teknik ensemble tidak memberikan peningkatan akurasi pada prediksi Indeks Harga Saham Gabungan (IHSG).  Kata Kunci : ensemble KNN, indeks harga saham gabungan, prediksi.
APPLICATION OF THE QUEST AND CHAID METHODS IN CLASSIFYING STUDENT GRADUATION Banu, Syarifah Syahr; Sulistianingsih, Evy; Debataraja, Naomi Nessyana; Satyahadewi, Neva
VARIANCE: Journal of Statistics and Its Applications Vol 6 No 2 (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/variancevol6iss2page155-164

Abstract

Graduation is the final result of the learning process during the course. Student graduation time is affected by many factors. Whether or not the time of student graduation is appropriate is an important thing that must be considered. Graduating well and on time is one measure of success in the learning process. This research aims to build a student graduation classification model by applying the QUEST (Quick, Unbiased, and Efficient, Statistical Tree) and CHAID (Chi-squared Automatic Interaction Detection) methods, examining the factors that affect student graduation, and comparing the classification results of the two methods. Both methods produce output in the form of tree diagrams, making it easier to interpret. Based on the classification tree formed from the two methods, four final nodes of the classification tree were generated, and three categories were grouped. Factors that affect student graduation include age and IPK. The classification results show that the percentage of classification accuracy for student graduation with QUEST and CHAID methods is 76.1%.
APPLICATION OF C4.5 ALGORITHM WITH FEATURE SELECTION IN CLASSIFICATION OF DISCHARGE STATUS OF HEAD INJURY PATIENTS ., Putri; Sulistianingsih, Evy; Imro'ah, Nurfitri; Debataraja, Naomi Nessyana
VARIANCE: Journal of Statistics and Its Applications Vol 6 No 2 (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/variancevol6iss2page165-174

Abstract

Head trauma is a medical emergency that can cause brain damage and disability, leading to death. The discharge status of injured patients is classified into two: alive and dead. The purpose of this study is to apply the C4.5 algorithm without feature selection and by using Chi-Square and Mutual Information feature selection to show independent variables that significantly influence the discharge status of head injury patients. This research data is secondary data of patients who suffered head injuries at Dr. Abdul Aziz Hospital, Singkawang City, in 2019-2021. The independent variables used were age, gender, length of hospitalization, etiology of head injury, Suprasellar Cistern, and Glasscow Coma Scale, with the dependent variable being discharge status. Based on the study results, the Chi-Square feature selection results identified two variables that had a significant effect. In contrast, for the Mutual Information feature selection results, five variables had a significant impact on the dependent variable. The C4.5 Algorithm classification model without feature selection produces an accuracy of 88.57%, the C4.5 Algorithm classification model with Chi-Square feature selection produces an accuracy of 88.57%, and the C4.5 Algorithm classification model with Mutual Information feature selection produces an accuracy value of 91.42% with the highest accuracy obtained from the results of the C4.5 Algorithm model formation with Mutual Information feature selection.
ANALISIS CONDITIONAL VALUE AT RISK PORTOFOLIO SAHAM DENGAN COPULA CLAYTON Karlina, Sela; Sulistianingsih, Evy; Satyahadewi, Neva
EPSILON: JURNAL MATEMATIKA MURNI DAN TERAPAN (EPSILON: JOURNAL OF PURE AND APPLIED MATHEMATICS) Vol 18, No 2 (2024)
Publisher : Mathematics Study Program, Faculty of Mathematics and Natural Sciences, Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/epsilon.v18i2.13261

Abstract

Conditional Value at Risk (CVaR) is known as a risk measurement tool to estimate losses in investing. Financial data tends not to be normally distributed so that the flexible Copula method can be used to analyze financial data without requiring the assumption of normality. This study aims to analyze the CVaR of a stock portfolio with Clayton's Copula. The study began with collecting daily stock closing price data for the period October 3, 2022 to November 3, 2023. After the data was collected, the return value of the closing stock price was calculated. Furthermore, autocorrelation and heteroscedasticity tests were carried out on the closing stock price return data. Then, the Kendall's Tau correlation was calculated to obtain the Clayton Copula parameters. After that, the stock weights in the portfolio were calculated using the Mean Variance Efficient Portfolio (MVEP) method and new return data was generated using the Clayton Copula parameters. Furthermore, the portfolio return was calculated to obtain the VaR value of the formed portfolio. Then, it was repeated by generating data up to the VaR calculation 1000 times to obtain the average value of the portfolio VaR. Then, the same thing was done to CVaR. The results of the CVaR analysis of the stock portfolio with Copula Clayton on the two stocks, namely PT Aneka Tambang Tbk (ANTM) and PT Timah Tbk (TINS), obtained losses of 3.04%, 3.56%, and 4.57% with a confidence level of 90%, 95%, and 99%. This value indicates the percentage of investment risk that may be obtained in the next one-day period. This shows that the higher the level of confidence, the greater the CVaR value will be.
ESTIMASI VALUE AT RISK (VAR) DENGAN METODE MONTE CARLO UNTUK MENGUKUR RISIKO KERUGIAN PETANI KETIMUN DI KABUPATEN KAPUAS HULU Arsanti, Resti; Sulistianingsih, Evy; Septiawan, Anggi
EPSILON: JURNAL MATEMATIKA MURNI DAN TERAPAN (EPSILON: JOURNAL OF PURE AND APPLIED MATHEMATICS) Vol 18, No 2 (2024)
Publisher : Mathematics Study Program, Faculty of Mathematics and Natural Sciences, Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/epsilon.v18i2.11433

Abstract

Measurement of an estimated loss needs to be done by every business actor. The measurement can be done by calculating the Value at Risk (VaR). VaR is an estimate of the maximum loss that is assumed to be experienced in a certain period at the confidence interval used. Three forms of calculation methods can be used in calculating VaR estimates, namely parametric methods, methods with Monte Carlo simulation approaches, and Historical Simulation Methods. The data used is the average monthly producer price data of cucumber commodities with a period range starting from January 2020 to December 2022. The VaR calculation method in this analysis is the Monte Carlo simulation approach method which has the condition that the return data from the average producer price is normally distributed. The results of the VaR calculation with the Monte Carlo simulation method show that after generating return data with repetition 1000 times for an investment of 1 rupiah, the probability that cucumber farmers in Kapuas Hulu Regency, West Kalimantan Province will experience maximum losses is 5.79% for a confidence level of 80%, 9.08% for a confidence level of 90%, 11.39% for a confidence level of 95%, and 14.81% for a confidence level of 99%.
Co-Authors ., Putri Agustono, Hendri Alsa Muarti Amalia, Disya Recita Ananda, Adelia Andani, Wirda Anisa Shafarianti Ardhitha, Tiffany Arsanti, Resti Atlantic, Virginnia AYU ASTUTI, AYU Banu, Syarifah Syahr Dadan Kusnandar Debataraja, Naomi Nessyana Desdianti, Maycandra Deva Kurnia Aristi Dhandio, David Jordy Dinanti, Rahila Dara Eka Lestari Eka Wahyuning Dhewanty Elga Fitaloka Fadhilah Rizky Aulia Febryanti, Winda Fiqriani, Rizha Aynul Fransiska Fransiska Gristia Aldilla Gunawan, Risky Hafifah, Nanda Hanin, Noerul Hendra Perdana Imanni, Rahmania Andarini Hatti Imro'ah, Nurfitri IMRO’AH, NURFITRI Kamila, Diva Rahma Karlina, Sela Laksono Trisnantoro Lisa Lestari Maga, Fahmi Giovani Maharani, Cinta Priscillia Maresha Widya Muliadiasti Martha, Shantika Matius Robi Meilandra, Irvan Meliana Pasaribu Melvin, Melvin Misno Misno Mutiara Nurisma Rahmadhani Nabilah, Niken Aushaf Nanda Shalsadilla Naomi Nessyana Debataraja Natalia, Desa Ayu Neva Satyahadewi Nurfitri Imro’ah Oktaviani, Indah Oktitannia, Dea Panawaristia, Brigitha Pebriyandi, Rifki Perangin Angin, Christi Alemsa Pratama, Aditya Nugraha Pratama, Yogi Priani, Wina Putra, Fajar Rahmana Radinasari, Nur Ismi Rahmah, Mhaulia Rahmania Andarini Hatti Imanni Rifqi, Bhima Fairul Risma Junian Salsabila, Hana Salsabila, Yumna Hanum Septiawan, Anggi Setyo Wir Rizki Setyo Wira Rizki Shantika Martha Siti Aprizkiyandari, Nurul Qomariyah, Shantika Martha, Sriyana Sriyana Sulya Hikma Yulandari Supandi Supandi Susanti Susanti Syafitri Wulandari Tamtama, Ray Tiara, Dinda Umiati, Wiji Wahyu Kurniasari Wati, Setio Kusumo Westi Widiyatari Wicaksono, Juwan Prioabil Dwi Wirda Andani Wulandari, Afrilia Putri Yundari, Yundari Yustosio, Darwis Zakiah, Ainun Zaria, Della