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All Journal JUITA : Jurnal Informatika Kubik Jurnal Sains Matematika dan Statistika Seminar Nasional Variansi (Venue Artikulasi-Riset, Inovasi, Resonansi-Teori, dan Aplikasi Statistika) Desimal: Jurnal Matematika BAREKENG: Jurnal Ilmu Matematika dan Terapan JTAM (Jurnal Teori dan Aplikasi Matematika) Saintifik : Jurnal Matematika, Sains, dan Pembelajarannya Journal of Science Innovare EKOLOGIA : Jurnal Ilmiah Ilmu Dasar dan Lingkungan Hidup BERNAS: Jurnal Pengabdian Kepada Masyarakat Jurnal Statistika dan Matematika (Statmat) KUBIK: Jurnal Publikasi Ilmiah Matematika Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi Jurnal PkM (Pengabdian kepada Masyarakat) Jurnal Eurekamatika Jurnal Karya Abdi Masyarakat Jurnal Indonesia Sosial Sains Jurnal Matematika Integratif Pelita: Jurnal Pengabdian kepada Masyarakat JMT (Jurnal Matematika dan Terapan) Jurnal Jendela Matematika
Embay Rohaeti
Universitas Pakuan
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Analisis Faktor-Faktor yang Mempengaruhi Ketahanan Hidup Pasien Tuberculosis dengan Model Regresi Cox (Studi kasus : Rumah Sakit Paru Bogor) Andriyati, Ani; Rohaeti, Embay
KUBIK Vol 4, No 1 (2019): KUBIK : Jurnal Publikasi Ilmiah Matematika
Publisher : Jurusan Matematika, Fakultas Sains dan Teknologi, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/kubik.v4i1.5674

Abstract

Ketahanan hidup penderita tuberculosis dipengaruhi oleh faktor eksternal maupun internal. Beberapa faktor yang dapat mempengaruhi ketahanan hidup seorang penderita tuberculosis diantaranya yaitu usia, jenis kelamin, tingkat pendidikan, sanitasi lingkungan, kebiasaan merokok dan pencahyaan rumah. Analisis survival dapat menganalisis ketahanan hidup seorang penderita penyakit. Dalam mengetahui faktor-faktor yang mempengaruhi ketahanan hidup penderita tuberculosis menggunakan analisis survival dengan model regresi cox. Adapun hasil dari analisis survival untuk ketahanan hidup pasien yaitu faktor sanitasi lingkungan, kebiasaan merokok dan mempunyai pencahayaan rumah  mempengaruhi ketahanan hidup penderita tuberculosis. Data waktu survival berdistribusi 3-parameter weibull dengan parameter , , dan  masing-masing bernilai 1.36794, 8.48634 dan -0.05489. Hasil dari model regresi cox  menunjukkan sanitasi lingkungan menjadi faktor yang paling mempengaruhi terhadap ketahanan hidup penderita tuberculosis Penderita dengan sanitasi lingkungan kurang baik akan meningkatkan fungsi hazard sebesar e1.237. Nilai Hazard ratio sanitasi sebesar 1/1.237 atau 0.8084 menunjukkan bahwa risiko untuk sembuh penderita yang memiliki sanitasi kurang baik adalah 0.8084 kali dari penderita dengan sanitasi lingkungan yang baik.
Peningkatan Kompetensi Pembelajaran Matematika Melalui Rumus Cepat Integral Bagi Siswa Ma Al Falak Kamila, Isti; Widyastiti, Maya; Andriyati, Ani; Rohaeti, Embay
Jurnal Karya Abdi Masyarakat Vol. 4 No. 3 (2020): Jurnal Karya Abdi Masyarakat
Publisher : LPPM Universitas Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (304.419 KB) | DOI: 10.22437/jkam.v4i3.11582

Abstract

Madrasah Aliyah Al Falak adalah suatu lembaga pendidikan yang berada di Kota Bogor. Berdasarkan informasi dari guru matematika madrasah tersebut, permasalahan yang terjadi di madrasah ini adalah rata-rata nilai matematika siswa tergolong rendah yaitu 50 yang masih dibawah KKM yaitu 60. Hal ini menjadikan kami para tim pelaksana pengabdian untuk melakukan pelatihan rumus cepat integral sehingga dapat meningkatkan minat siswa untuk belajar integral dan meningkatkan kompetensi pembelajaran matematika khususnya pada materi integral. Sebelum dilakukan pelatihan rumus cepat integral, diberikan pretest untuk melihat kemampuan awal siswa dan diperoleh rata-rata pretest adalah 31. Selanjutnya dilakukan pelatihan rumus cepat integral dan diakhiri dengan pemberian posttest. Berdasarkan hasil posttest, diperoleh nilai rata-rata siswa meningkat menjadi 80.75 dan setelah dilakukan uji-t berpasangan diperoleh thitung = -87.179 < -ttabel = -0.209302 maka thitung terletak pada daerah H0 ditolak. Oleh karena itu, bisa disimpulkan ada perbedaan nilai antara sebelum dan sesudah pemberian pelatihan rumus cepat integral.
Analysis of Optimal Stock Performance Using the Discounted Cash Flow Method and Stock Price Forecasting Using the Holt-Winters Method: (Case Study: Shares of PT Perusahaan Gas Negara Tbk) Sekar Miasih; Embay Rohaeti; Hagni Wijayanti
Jurnal Indonesia Sosial Sains Vol. 5 No. 11 (2024): Jurnal Indonesia Sosial Sains
Publisher : CV. Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59141/jiss.v5i11.1515

Abstract

The high liquidity of PT Perusahaan Gas Negara Tbk shares and significant fluctuations in share prices create uncertainty that requires in-depth analysis. Stock performance analysis is carried out with 2 stages in outline, namely the stages of fundamental analysis and technical analysis. Fundamental analysis is carried out to analyze optimal stock performance, one of which is by using the discounted cash flow (DCF) method. Technical analysis is used to determine the condition of stock performance in the future by forecasting stock prices using the Holt-Winters forecasting method. The objectives of this study are to analyze optimal stock performance, forecast stock prices, and evaluate forecasting results. The data used is PGN's 2023 annual report and daily data on PGN's stock price for the period January 1, 2019, to December 31, 2023, totalling 1,231 data. The results of the optimal stock performance analysis show that PGN's stock performance is declared optimal with an intrinsic value of 3,149.18, which is greater than the current stock price (undervalued). The results of stock price forecasting show that the forecasting results follow the actual data pattern, with an accuracy value using MAPE (mean absolute percentage error ) of 10.9%, it is stated that the forecasting performance has performed well.
A comparison benefit reserves of an n–year term life insurance between using the vasicek model and cox-ingersoll-ross model Kamila, Isti; Andriyati, Ani; Rohaeti, Embay
Desimal: Jurnal Matematika Vol. 7 No. 1 (2024): Desimal: Jurnal Matematika
Publisher : Universitas Islam Negeri Raden Intan Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/djm.v7i1.20607

Abstract

The purpose of this study was to determine benefit reserves with the premium sufficiency method that would be applied to types of term insurance with non-constant interest rates by using the Vasicek and Cox-Ingersol-Ross models. The novelty of this study is in determining term insurance benefit reserves by comparing benefit reserves using the Vasicek and Cox-Ingersol-Ross interest rate models so that it can be a decision-maker for insurance companies. The stages of this research activity started by estimating the parameters for the Vasicek and Cox-Ingersoll-Ross (CIR) interest rates. The next step was to estimate the interest rate on Vasicek and CIR. Then, estimate the reserve value of term insurance benefits using the premium sufficiency method with non-constant interest rates. At the final stage, the results of the reserve value of benefits with non-constant interest rates and CIR would be interpreted and compared. The results of the research obtained by the CIR interest rate were always positive, and the difference in interest rates between each time was not too large compared to Vasicek. This was in line with the reserve results of the benefits obtained. The difference in benefit reserves between times using Vasicek was greater than that of the CIR interest rate model.
ANALYSIS OF THE IMPACT OF COVID IN THE SECOND YEAR ON INCOME OF WORKERS IN WEST JAVA WITH MULTINOMIAL LOGISTIC REGRESSION Andriyati, Ani; Rohaeti, Embay; Kamila, Isti
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 16 No 1 (2022): BAREKENG: Jurnal Ilmu Matematika dan Terapan
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (685.566 KB) | DOI: 10.30598/barekengvol16iss1pp181-188

Abstract

The COVID-19 pandemic that hit Indonesia had a huge impact on the economy. The long period of restriction of population mobility impacted the changes of people's income. West Java is the province with the most workers affected by this pandemic. The income of workers in West Java in the first five months of the pandemic decreased by 50.1%. The existence of these problems shows that an analysis of the impact of covid on changes in worker income is very necessary. This study aims to determine the factors that have a significant effect on changes in workers' income in West Java. Based on the results of the multinomial logistic model suitability test, it was found that there was no difference in the model between the observed results and the predicted results for male workers, therefore the model could be used. In the second year of the covid pandemic, the opportunity for a person's income to decrease in West Java is still very high, at 0.9891. The factors with the highest opportunities that affect income changes in the reduced category are self-employed employment status, changes in work hours, the implementations of WFH, and workers working at terminal/station/airport locations.
THE PROMINENCE OF VECTOR AUTOREGRESSIVE MODEL IN MULTIVARIATE TIME SERIES FORECASTING MODELS WITH STATIONARY PROBLEMS Rohaeti, Embay; Sumertajaya, I Made; Wigena, Aji Hamim; Sadik, Kusman
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 16 No 4 (2022): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (688.398 KB) | DOI: 10.30598/barekengvol16iss4pp1313-1324

Abstract

One of the problems in modelling multivariate time series is stationary. Stationary test results do not always produce all stationary variables; mixed stationary and non-stationary variables are possible. When stationary problems are found in multivariate time series modelling, it is necessary to evaluate the model's performance in various stationary conditions to obtain the best forecasting model. This study aims to get a superior multivariate time series forecasting model based on the goodness of the model in various stationary conditions. In this study, the evaluation of the model's performance through simulation data modelling is then applied to the actual data with a stationary problem, namely Bogor City inflation data. The best model in simulation modelling is based on the stability of RMSE and MAD in 100 replications. The results are that the VAR model is the best in various stationary conditions. Meanwhile, the best model on actual data modelling is based on evaluation in 4 folds for model fitting power and model forecasting power. The Bogor City inflation data modelling with the mixed stationary problem resulted in the best model, namely the VAR(1) model. This means the VAR model is good enough to be used as a forecasting model in mixed stationary conditions. Thus, in this study, based on the goodness of the model in two modelling scenarios in various stationary conditions, overall, it was found that the VAR model was superior to the VARD and VECM models.
Biclustering Performance Evaluation of Cheng and Church Algorithm and Iterative Signature Algorithm Sumertajaya, I Made Sumertajaya; Ningsih, Wiwik Andriyani Lestari; Saefuddin, Asep; Rohaeti, Embay
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 7, No 3 (2023): July
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v7i3.14778

Abstract

Biclustering has been widely applied in recent years. Various algorithms have been developed to perform biclustering applied to various cases. However, only a few studies have evaluated the performance of bicluster algorithms. Therefore, this study evaluates the performance of biclustering algorithms, namely the Cheng and Church algorithm (CC algorithm) and the Iterative Signature Algorithm (ISA). Evaluation of the performance of the biclustering algorithm is carried out in the form of a comparative study of biclustering results in terms of membership, characteristics, distribution of biclustering results, and performance evaluation. The performance evaluation uses two evaluation functions: the intra-bicluster and the inter-bicluster. The results show that, from an intra-bicluster evaluation perspective, the optimal bicluster group of the CC algorithm produces bicluster quality which tends to be better than the ISA. The biclustering results between the two algorithms in inter-bicluster evaluation produce a deficient level of similarity (20-31 percent). This is indicated by the differences in the results of regional membership and the characteristics of the identifying variables. The biclustering results of the CC algorithm tend to be homogeneous and have local characteristics. Meanwhile, the results of biclustering ISA tend to be heterogeneous and have global characteristics. In addition, the results of biclustering ISA are also robust.
Perbandingan Kinerja Multinomial Naïve Bayes Classifier dan Naïve Forecasting dalam Klasifikasi dan Peramalan Jumlah Opini Kenaikan Harga BBM Oktaviani, Nita; Rohaeti, Embay; Widyastiti, Maya; Andriyati, Ani
Jurnal Sains Matematika dan Statistika Vol 10, No 2 (2024): JSMS Juli 2024
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/jsms.v10i2.28309

Abstract

Data opini pengguna X terhadap topik kenaikan harga Bahan Bakar Minyak (BBM) memiliki nilai sentimen yang dapat menentukan kelas opini dominan sebagai gambaran penilaian dari sisi masyarakat pengguna X. Opini pengguna X akan diklasifikasi dalam tiga kelas yaitu kelas opini positif, negatif dan netral menggunakan model Multinomial Naïve Bayes Classifier (MNBC). Hasil klasifikasi yang diperoleh dilanjutkan pada tahapan peramalan jumlah opini dengan metode Naïve Forecasting (NF). Tujuan dari penelitian ini yaitu mengklasifikasikan opini dengan MNBC, meramalkan jumlah opini untuk jangka waktu satu minggu kedepan dengan NF, dan mengevaluasi hasil klasifikasi serta hasil peramalan. MNBC merupakan salah satu algoritma machine learning yang digunakan untuk klasifikasi teks. NF merupakan salah satu metode peramalan untuk data time series. Perhitungan pada penelitian ini dilakukan dengan penggunaan bantuan software R. Data yang digunakan berupa data sekunder sebanyak 2500 data. Periode pengambilan data selama satu minggu dimulai dari 20 Oktober 2022 hingga 27 Oktober 2022. Hasil dari pemodelan MNBC didapatkan tiga kelas yaitu sebanyak 775 dokumen diklasifikasikan sebagai opini negatif, 475 dokumen diklasifikasikan sebagai opini netral, dan 581 dokumen diklasifikasikan sebagai opini positif. Akurasi model MNBC dikategorikan sangat baik sebesar 92% untuk keseluruhan kelas. Hasil peramalan tiga kelas klasifikasi dengan NF yaitu jumlah opini kelas positif sebanyak 44 opini dengan nilai RMSE sebesar 8,96, jumlah opini kelas negatif sebanyak 25 opini dengan nilai RMSE sebesar 14,87, dan jumlah opini kelas netral sebanyak 21 opini dengan nilai RMSE sebesar 11,45. Hal ini menunjukkan Peramalan dengan NF dikategorikan cukup baik. Kata Kunci:  MNBC, NF, Opini, Klasifikasi, Peramalan.
Pemodelan Pengaruh Nilai Tukar Rupiah Terhadap Dollar Dengan Indeks Harga Saham Gabungan Kompas 100 menggunakan metode Gauss Newton Triyanto, Muhammad; Andriyati, Ani; Kamila, Isti; Rohaeti, Embay
JURNAL JENDELA MATEMATIKA Vol. 2 No. 01 (2024): Jurnal Jendela Matematika: Edisi Januari 2024
Publisher : CV. Jendela Edukasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57008/jjm.v2i01.669

Abstract

Penelitian bertujuan untuk memodelkan hubungan antara nilai tukar Rupiah terhadap Dollar dengan Indeks harga saham kompas 100. Berdasarkan informasi penelitian terdahulu bahwa hubungan nilai tukar mata uang terhadap harga saham bersifat non linier. Pemodelan regresi non linier pada penelitian ini dilakukan dengan pendekatan numerik melalui algoritma Gauss Newton. Metode Gauss Newton merupakan metode sederhana yang sangat efisien yang digunakan untuk menyelesaikan masalah pendugaan kuadrat terkecil. Metode Gauss Newton digunakan untuk menduga parameter dengan meminimalkan jumlah nilai dari suatu fungsi, dimana dalam menyelesaikannya tidak memerlukan perhitungan atau estimasi dari turunan kedua fungsi f(x) karena secara numerik lebih efektif dengan proses langsung atau iteratif. Proses pendugaan dimulai dengan fungsi f=(x,β_0,β_1 )=β_0 (1-e^(-β_1 X)) dengan dugaan awal parameter β_0=0,1 dan  β_1=1 dan JKG awal sebesar 0,000250. Pembentukan nilai awal pada iterasi pertama diperoleh β_0,1=-2,16 dan β_1,1=25,16 dengan JKG  sebesar 268,173. Perhitungan diulang secara terus menerus sampai konvergen yaitu pada iterasi ketiga. Nilai pendugaan parameter pada iterasi ketiga yaitu  β_0,3=0,0066 dan  β_1,3=216,55 dengan nilai JKG terkecil yaitu 0,001769.
Analysis of Optimal Stock Performance Using the Discounted Cash Flow Method and Stock Price Forecasting Using the Holt-Winters Method: (Case Study: Shares of PT Perusahaan Gas Negara Tbk) Miasih, Sekar; Rohaeti, Embay; Wijayanti, Hagni
Jurnal Indonesia Sosial Sains Vol. 5 No. 11 (2024): Jurnal Indonesia Sosial Sains
Publisher : CV. Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59141/jiss.v5i11.1515

Abstract

The high liquidity of PT Perusahaan Gas Negara Tbk shares and significant fluctuations in share prices create uncertainty that requires in-depth analysis. Stock performance analysis is carried out with 2 stages in outline, namely the stages of fundamental analysis and technical analysis. Fundamental analysis is carried out to analyze optimal stock performance, one of which is by using the discounted cash flow (DCF) method. Technical analysis is used to determine the condition of stock performance in the future by forecasting stock prices using the Holt-Winters forecasting method. The objectives of this study are to analyze optimal stock performance, forecast stock prices, and evaluate forecasting results. The data used is PGN's 2023 annual report and daily data on PGN's stock price for the period January 1, 2019, to December 31, 2023, totalling 1,231 data. The results of the optimal stock performance analysis show that PGN's stock performance is declared optimal with an intrinsic value of 3,149.18, which is greater than the current stock price (undervalued). The results of stock price forecasting show that the forecasting results follow the actual data pattern, with an accuracy value using MAPE (mean absolute percentage error ) of 10.9%, it is stated that the forecasting performance has performed well.
Co-Authors Aeni, Kurnia' Agisti, Gitsa Laili Aji Hamim Wigena Amar Sumarsa Andriyati, Ani Ani Andriyati Anzari, Bandar ASEP SAEFUDDIN Bagus Sartono Dion, Shelly Selgiant Else As Syavira Fernanda Caesa Putri Fitriyani, Fijriyah Hagni Wijayanti I Made Sumertajaya Isti Kamila Kusman Sadik Luthfi, Alaika Maya Widyastiti Maya Widyastiti, Maya Miasih, Sekar Mulyati , Ningsih, Wiwik Andriyani Lestari Oktaviani, Nita Prilia Ditasari Rafli, Muhammad Sekar Miasih Sri Yuningsih Sungkar, Adisty Triyanto, Muhammad Virgantari, Fitria Widiastuti, Qori Fadilah Yasmin Eka Faridhan