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All Journal CAUCHY: Jurnal Matematika Murni dan Aplikasi Dharmakarya : Jurnal Aplikasi Ipteks Untuk Masyarakat Kubik Jurnal Matematika: MANTIK Desimal: Jurnal Matematika Teorema: Teori dan Riset Matematika Jurnal Cendekia : Jurnal Pendidikan Matematika JURNAL SILOGISME : Kajian Ilmu Matematika dan Pembelajarannya Eksakta : Berkala Ilmiah Bidang MIPA M A T H L I N E : Jurnal Matematika dan Pendidikan Matematika Jurnal Matematika UNAND Kumawula: Jurnal Pengabdian Kepada Masyarakat Jurnal Ilmiah Matematika dan Pendidikan Matematika (JMP) BERNAS: Jurnal Pengabdian Kepada Masyarakat Jurnal Statistika dan Aplikasinya KUBIK: Jurnal Publikasi Ilmiah Matematika Jurnal Diferensial International Journal of Global Operations Research Leibniz: Jurnal Matematika Jurnal Matematika Integratif In Search (Informatic, Science, Entrepreneur, Applied Art, Research, Humanism)
Nurul Gusriani, Nurul
Departemen Matematika Fakultas MIPA, Universitas Padjadjaran
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Pemrograman Python Untuk Peramalan Data Deret Waktu Menggunakan Metode Seasonal Autoregressive Integrated Moving Average (Sarima) Michelle Selina Buntara; Herlina Napitupulu; Nurul Gusriani
In Search (Informatic, Science, Entrepreneur, Applied Art, Research, Humanism) Vol 22 No 2 (2023): In Search
Publisher : LPPM UNIBI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37278/insearch.v22i2.774

Abstract

Peramalan deret waktu adalah penggunaan model untuk memprediksi nilai masa depan berdasarkan nilai yang diamati sebelumnya. Model Seasonal Autoregressive Integrated Moving Average (SARIMA) merupakan salah satu model yang digunakan untuk peramalan ketika deret waktu univariat menunjukkan variasi musiman. Model SARIMA merupakan bentuk khusus dari model ARIMA yang terdiri dari tiga bagian, yaitu; ‘AR’ yang berarti Autoregressive, ‘I’ yang merupakan bagian differencing, dan ‘MA’ yang berarti Moving Average.Penelitian ini bertujuan untuk memperoleh model SARIMA terbaik melalui beberapa tahap, yaitu; preparasi, identifikasi, penaksiran nilai parameter, dan uji diagnostik. Performa model peramalan diuji menggunakan mean absolute percentage error (MAPE).
Simulasi Perhitungan Analisis Cluster pada Kasus Penyakit Menular Menggunakan Bahasa Pemrograman Python Aulia Wanda Puspitasari; Herlina Napitupulu; Nurul Gusriani
In Search (Informatic, Science, Entrepreneur, Applied Art, Research, Humanism) Vol 22 No 2 (2023): In Search
Publisher : LPPM UNIBI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37278/insearch.v22i2.796

Abstract

Increasing the prevention and control of infectious diseases is currently one of the 2020-2024 health development strategic goals set by the Ministry of Health. If it left unchecked, infectious diseases can become Kejadian Luar Biasa (KLB) which result in many deaths. To optimize the handling of infectious disease transmission, it is necessary to determine which groups are the priority. One of the grouping methods that can be used is cluster analysis. This study aims to find the best cluster based on the Cophenetic Correlation Coefficient (CPCC) and Pseudo-F values. The results showed that the average linkage method was the best method with a CPCC value closest to 1, that is 0.8513. The average linkage method divides districts/cities in West Java into five clusters based on the highest Pseudo-F value.
PENDAMPINGAN USAHA KECIL DALAM PENGGUNAAN MEDIA SOSIAL UNTUK PENINGKATAN PROFIT DAN PRODUKTIVITAS USAHA Chaerani, Diah; Perdana, Tomy; Rusyaman, Endang; Gusriani, Nurul; Firdaniza, Firdaniza; Balqis, Viona P; Irmansyah, Athaya Zahrani; Muslihin, Khoirunnisa R A; Ghiffari, Alif Muhamad
DHARMAKARYA: Jurnal Aplikasi Ipteks untuk Masyarakat Vol 12, No 3 (2023): September, 2023
Publisher : Universitas Padjadjaran

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24198/dharmakarya.v12i3.43472

Abstract

Masalah utama yang diselesaikan dalam PPM Internal Unpad 2022 ini adalah bagaimana memberikan pendampingan pada usaha kecil yang ada di masyarakat untuk dapat membuka usaha secara online dan menggunakan internet atau smartphone  melalui media social sebagai upaya peningkatan manajemen usaha pada unit usaha yang telah berjalan, khususnya pada masa pandemi Covid-19 ini.  Dasar pemikiran merujuk pada kondisi bahwa media sosial telah berevolusi untuk menjadi alternatif cara berkomunikasi dan berbagi informasi serta ketertarikan. Indonesia merupakan negara keempat dengan jumlah pengguna internet terbesar. Pertumbuhan pesat dari sosial media beserta jaringannya terutama di negara-negara berkembang membuka lahan baru untuk adanya kontak antara produsen dan konsumen.Kontak antara produsen dan konsumen inilah yang biasanya dikenal dengan kegiatan berbelanja secara online. Keterkaitan antara penggunaan sosial media dengan kegiatan online shopping sangat erat.Untuk menganalisis data media sosial diperlukan pengetahuan yang dalam mengenai teknologi Internet, media sosial, basis data, struktur data, teori informasi, penambangan data, pembelajaran mesin, sampai kepada teknik visualisasi data dan informasi. Analisis media sosial bertujuan untuk pengembangan dan evaluasi informasi serta mengumpulkan, mengevaluasi, menganalisis, menyimpulkan, dan memvisualisasikan data dari media sosial. Analisis media sosial adalah proses untuk melihat, analisis, mengukur, dan prediksi interaksi digital, relasi, topik, ide-ide atau konten pada media sosial. Selanjutnya dalam rangka mendukung perkembangan perekonomian bangsa, diharapkan pendampingan ini dapat membantu para pelaku usaha kecil dalam bersosial media dalam hal peningkatan profit dan produktivas usaha. Lokasi PPM dipilih Desa Jatimukti yang terletak sekitar 5 KM dari Kampus Unpad Jatinangor.
PERAMALAN INDEKS ULTRAVIOLET DI KOTA BANDUNG MENGGUNAKAN METODE LONG SHORT-TERM MEMORY Satyaputra, Ida Bagus Wira Krishna; Napitupulu, Herlina; Gusriani, Nurul
Jurnal Matematika Integratif Vol 20, No 2: Oktober 2024
Publisher : Department of Matematics, Universitas Padjadjaran

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24198/jmi.v20.n2.58798.249-258

Abstract

Peramalan nilai indeks Ultraviolet (UV) memainkan peran penting dalam menjaga kesehatan masyarakat dan pengelolaan lingkungan. Penelitian ini bertujuan untuk menghasilkan nilai peramalan indeks UV di Kota Bandung pada tanggal 1–30 April 2024 menggunakan Metode Long Short-Term Memory (LSTM). Metode LSTM merupakan pengembangan dari metode Recurrent Neural Network (RNN). RNN diubah dengan menambahkan mekanisme gate untuk menyimpan informasi jangka panjang sehingga mengurangi resiko munculnya exploding gradients dan vanishing gradients. Model LSTM dalam penelitian ini dibangun menggunakan 1 input layer dengan 400 unit cell dan 1 output dense layer dengan fungsi update bobot adam optimizer, randomizer bobot glorot uniform distribution, dan 400 jumlah epoch. Performa model peramalan diuji menggunakan RMSE dan MAPE. Pada data training menghasilkan nilai RMSE sebesar 0,28 dan MAPE sebesar 11%. Untuk data testing menghasilkan nilai RMSE sebesar 0,48 dan MAPE sebesar 14%. Hasil peramalan indeks UV di Kota Bandung menunjukkan bahwa selama bulan April nilai rata-rata indeks UV adalah 2,27, hal ini mengartikan bahwa masyarakat Kota Bandung dapat beraktivitas diluar tanpa perlu mengkhawatirkan bahaya sinar UV.
The Irreducible Unitary Representation of SU(2) and Its Lie algebra Representations Kurniadi, Edi; Badrulfalah, Badrulfalah; Gusriani, Nurul
Mathline : Jurnal Matematika dan Pendidikan Matematika Vol. 9 No. 4 (2024): Mathline : Jurnal Matematika dan Pendidikan Matematika
Publisher : Universitas Wiralodra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31943/mathline.v9i4.653

Abstract

We study the three dimensional special unitary group  whose the Lie algebra is given by   . The research aims to construct a representation of  and  realized on the inner product  space  of all homogeneous polinomials of degree  and  of all homogeneous polinomials of degree  which satisfying  irreducibility and unitarity conditions. Namely, The action of    and  are presented on the spaces  and  respectively. In the first step, we computed all representations of  on  and .   Furthermore, in the second step, by simply connectedness property of  then the irreducible unitary representation of Lie algebra  realized on  can be obtained from the  representation by using derived representation. The results showed the explicit formulas of representations of    and
Analisis Regresi TELBS Untuk Menentukan Pengaruh Lahan Kopi Terhadap Produksi Kopi di Indonesia Tahun 2023 Menggunakan Bahasa Pemrograman Python Ramdhani, Muhammad Dhafin Qinthar; Gusriani, Nurul; Firdaniza, Firdaniza
In Search (Informatic, Science, Entrepreneur, Applied Art, Research, Humanism) Vol 23 No 2 (2024): In Search
Publisher : LPPM UNIBI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37278/insearch.v23i2.889

Abstract

Indonesia, as one of the world's largest coffee producers, is renowned for its diverse range of high-quality coffees such as Arabica, Robusta, and Liberica. Coffee production is influenced by various factors, including the extent of plantation land. Coffee production data may contain outliers due to factors like weather changes, pest attacks, inconsistent farming practices, or recording errors. These challenges can be addressed using robust regression methods, with one such estimation being Tabatabai Eby Li Bae Singh (TELBS) estimation. TELBS estimates model parameters by minimizing an objective function. In this study, a TELBS estimation model was applied to Indonesian coffee production data in 2023, with the dependent variable being coffee production quantity and the independent variable being plantation land area. Parameter testing using t-tests indicated that plantation land area significantly influences coffee production in that year at a significance level of 0.05. The TELBS estimation model yielded a coefficient of determination of 96.51%, demonstrating its capability to explain a substantial portion of the data's variance.
Generalized Additive Models for Modeling Pneumonia Cases in Toddlers in West Java based on the Penalized Spline Estimator Wahyu, Azkanul; Nurul Gusriani; Kankan Parmikanti
EKSAKTA: Berkala Ilmiah Bidang MIPA Vol. 25 No. 02 (2024): Eksakta : Berkala Ilmiah Bidang MIPA (E-ISSN : 2549-7464)
Publisher : Faculty of Mathematics and Natural Sciences (FMIPA), Universitas Negeri Padang, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/eksakta/vol25-iss02/491

Abstract

Acute Respiratory Infections (ARI) are one of the causes of high mortality in the world, such as pneumonia in toddlers. Pneumonia cases in West Java are high compared to other provinces. In this study, pneumonia cases will be modeled with Generalized Additive Models (GAM) based on penalized spline estimators. The optimal number of knots is determined using the full search algorithm and the optimal smoothing parameter is obtained based on the minimum Generalized Cross Validation (GCV) value of order one or two. Then, GAM parameter estimation is performed using the local scoring algorithm. Formed model based on the order, number of knots, and smoothing parameters of each predictor variable with order one, number of knots two, and optimal smoothing parameter one for , order two, number of knots three, and optimal smoothing parameter one for , and order one, number of knots two, and optimal smoothing parameter for  whose parameters were estimated by local scoring resulted in a coefficient of determination of 0.679. This indicates that 67.9% of the factors from the predictor variables affect the percentage of pneumonia cases among under-fives while the remaining 32.1% is influenced by other factors outside the model.
Robust Linear Discriminant Analysis with Modified One-Step M-Estimator Qn Scale for Classifying Financial Distress in Banks: Case Study Nabila Putri; Parmikanti, Kankan; Gusriani, Nurul
EKSAKTA: Berkala Ilmiah Bidang MIPA Vol. 25 No. 02 (2024): Eksakta : Berkala Ilmiah Bidang MIPA (E-ISSN : 2549-7464)
Publisher : Faculty of Mathematics and Natural Sciences (FMIPA), Universitas Negeri Padang, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/eksakta/vol25-iss02/515

Abstract

The COVID-19 pandemic has significantly disrupted the banking sector, leading to a decline in profit growth as an indicator of financial distress. Bank financial health can be evaluated using the RGEC (Risk Profile, Good Corporate Governance, Earnings, Capital) analysis. While Linear Discriminant Analysis (LDA) ideally requires normality and homogeneity of covariance matrices, financial data often fail to meet these assumptions. Therefore, this study employs robust linear discriminant analysis using the Modified One-Step M-Estimator with Qn scale estimator (MOM-Qn) to classify ‘distress’ and ‘non-distress’ bank conditions. Given these challenges, this study acts as a preventive measure for banks to evaluate financial health simultaneously. The objective is to provide a robust discriminant function for more accurate and stable classification, particularly in the presence of outliers. It focuses on conventional private banks listed on the Indonesia Stock Exchange (IDX) during December 2021-2022. The results show a classification accuracy of 69.23% and a Press’s Q value of 11.53846, indicating the method’s effectiveness in classifying real financial data.  
Formulasi Infinitesimal Generators Grup Lie Satu Parameter dari Transformasi Translasi dan Scaling Kurniadi, Edi; Badrulfalah, Badrulfalah; Gusriani, Nurul
Leibniz: Jurnal Matematika Vol. 5 No. 02 (2025): Leibniz: Jurnal Matematika
Publisher : Program Studi Matematika - Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas San Pedro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59632/leibniz.v5i02.496

Abstract

Grup Lie transformasi dapat dikarakterisasi melalui infinitesimal generators yang membentuk aljabar Lie. Infinitesimal generators dapat diaplikasikan untuk menyelesaikan persamaan diferensial biasa (PDB) maupun persamaan diferensial parsial (PDP) baik yang linear maupun nonlinear. Tujuan penelitian ini adalah untuk memberikan rumus ekplisit infinitesimal generators berkenaan dengan transformasi grup Lie satu parameter. Metode penelitian yang digunakan merupakan kombinasi dari metode kualitiatif berupa studi literatur khususnya transformasi translasi dan scaling dan metode kuantitatif dengan menentukan rumus eksplisit infinitesimal generators dan analisisnya. Hasil yang diperoleh adalah bentuk rumus eksplisit infinitesimal generators yang bersesuaian dengan jenis transformasi yang digunakan. Hasil ini bisa digunakan untuk penelitian selanjutnya dalam menyelesaikan model matematika reaksi difusi konveksi (RDK) dalam PDB maupun PDP sebagai salah satu langkah dalam aplikasi simetri Lie.  
Markov average-based weighted fuzzy time series model to predict PT Kimia farma Tbk stock price Azzahra, Rediva; Firdaniza, Firdaniza; Gusriani, Nurul
Desimal: Jurnal Matematika Vol. 4 No. 3 (2021): Desimal: Jurnal Matematika
Publisher : Universitas Islam Negeri Raden Intan Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/djm.v4i3.9675

Abstract

The COVID-19 pandemic impacted various activities in Indonesia, including the stock market. Despite the declining economic condition, people are increasingly interested in investing. Among other companies available on the Indonesia Stock Exchange, companies in the health sector have a particular appeal to potential investors, one of which is pharmaceutical companies. This research used a Markov Average-Based Weighted Fuzzy Time Series model applied to PT Kimia Farma Tbk stock price data. This model develops the previous Markov chain–Fuzzy Time Series model, which has not calculated the weights for recurring events and used the Sturgess rule to determine the interval length. In this research, each recurring event has given a different weight that provides different probability values for transitions from one state to another. The Average-Based method is used to determine the interval length that can reflect the fluctuation of the data used. The stock price prediction of PT Kimia Farma Tbk using this model is categorized as very accurate with a MAPE of 2.632%.
Co-Authors Anita Triska Arif Rahman Aulia Wanda Puspitasari Azzahra, Rediva Badrulfalah Badrulfalah Bagariang, Elizabeth Irene Balqis, Viona P Betty Subartini Budi Nurani Ruchjana Clarita Simar DHEA ARIESTA Diah Chaerani Edi Kurniadi Edi Kurniadi Edi Kurniadi Edi Kurniadi Edi Kurniadi Endang Rusyaman Firdaniza Firdaniza Ghiffari, Alif Muhamad Herlina Napitupulu Herlina Napitupulu Iin Irianingsih Irmansyah, Athaya Zahrani Kaerudin, Nandira Putri Kankan Parmikanti Kusuma, Dianne Amor Luthfi Ghiffari Melda Noereast Talytha Michelle Selina Buntara Milani Destriana Mohamad Nurzaman Muslihin, Khoirunnisa R A Nabila Putri Nasri, Ramadhoni Nursanti Anggriani Ramdhani, Muhammad Dhafin Qinthar Rediva Azzahra Reffa Ayu Anggraeni Reffa Ayu Anggraeni Riaman Samantha Surya Satyaputra, Ida Bagus Wira Krishna Sri Rahayu Sunarta Susanto Syifana, Hani Tiara Aprilia K Tiara Aprilia K, Tiara Tomy Perdana Tomy Perdana Tomy Perdana Wahyu, Azkanul