Article Per Year (5 Year)
p-Index From 2020 - 2025
1.503
P-Index
This Author published in this journals
All Journal MAGISTRA Electro Luceat Jurnal Ilmiah Matematika dan Pendidikan Matematika (JMP) JURNAL PENGABDIAN PENDIDIKAN MASYARAKAT (JPPM) Jurnal Sistem Informasi dan Ilmu Komputer International Journal of Technology and Education Research PESHUM
Agustini Tripena
Unknown Affiliation
Religion Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Library & Information Science Mathematics Public Health Social Sciences Other

Published : 9 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 9 Documents
Search

 1 
PERAMALAN INDEKS HARGA KONSUMEN DAN INFLASI INDONESIA DENGAN METODE ARIMA BOX-JENKINS Tripena, Agustini
MAGISTRA Vol 23, No 75 (2011): Magistra Edisi Maret
Publisher : MAGISTRA

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (13.153 KB)

Abstract

In this paper, forecasting the consumer price index data and inflation. The method used Box-JenkinsARIMA. For data that belongs there more than one model that can be used the method of ARIMA (1, 1, 0),ARIMA (0, 1, 1), and ARIMA (1, 1, 1). Thus the value of AIC, ARIMA (1, 1, 1) is the best method for data andconsumer price index inflationThe results showed that the forecast value of the consumer price index based on the model ARIMA (1, 1,1) is for May 2009 was 175.82, in June 2009 was 176.63, and in July 2009 was 177, 65 While the forecastinflation for the month May 2009 is -0.05, June 2009  4105 ??? , and July 2009  4105,5 ??? .Keywords : CPI, inflation, time series, forecasting, ARIMA, AIC
ESTIMATOR DERET FOURIER UNTUK ESTIMASI KURVA REGRESI NONPARAMETRIK BIRESPON Tripena, Agustini
MAGISTRA Vol 25, No 84 (2013): Magistra Edisi Juni
Publisher : MAGISTRA

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (13.153 KB)

Abstract

In the last decade Fourier series estimator in nonparametric regression (one response) a lot of attention from researchers because of its flexibility. In this paper will be developed in Fourier series estimator in nonparametric regression of two responses (Birespon). Data are given in pairs (t1j, y1j), j = 1, 2, ... n1 and (t2j, y2j), j = 1, 2, ... n2,. The relationship between t1j, t2j, y1j and y2j following nonparametric regression model Birespon: y1j = f1 (t1j) +  1j and y2j = f2 (t2j) +  2j Form of regression curves f1 and f2 are unknown and assumed to be contained within the space of continuous functions (0,  ). Random error  1j mutually independent with mean zero and variance 2 1 , and  1j also mutually independent with mean zero and variance 2 2 . Random error  1j and  2j are correlated with the Cor(  1j,  2j) = r. Regression curve f1(t) and f2(t) respectively were approached by a continuous and differentiable function: 1 1( )jd t = 1 1 01 1 1 1 1 cos 2 K j k j k t kt       , And 2 2( )jd t = 2 2 02 2 2 1 1 cos 2 K j k j k t kt       ,  1  ,  2  , 01  , 02  , 1k  , k = 1, 2, ..., n1, 2k  , k = 1, 2, ..., n2 are parameters that are unknown in the Fourier series model. Estimated nonparametric regression curve Birespon f1(t) and f2(t) obtained from the complete optimization Penalized Weighted Least Square (PLST):              0 0 2 2 2221 2 111 2 2 2 1 1 dttfdttfywy ]([ ]([ ))(,,()( n (n "" 21 Completion of this form of optimization PLST Fourier series estimator that can be presented in the form: 1 2 11 1 2 22 ˆ ( )ˆ ( ) ( , ) ˆ ( ) yf t f t B yf t                       . Fourier series estimator in nonparametric regression Birespon is biased to nonparametric regression curve 1 1 2 2 ( ) ( ) ( ) f t f t f t        Although biased, but this estimator is a linear estimator, which is very supportive in building statistical inference for nonparametric regression curve Birespon... Key words: Fourier series estimator, Nonparametric Regression Birespon, Penalized Weighted Least Square
PENGGUNAAN ALAT PERAGA PAPAN ALJABAR DALAM PENJUMLAHAN DAN PENGURANGAN BILANGAN BULAT UNTUK SISWA PKBM BUDI LUHUR Triyani Triyani; Niken Larasati; Ari Wardayani; Agustini Tripena; Slamet Riyadi
Jurnal Pengabdian Pendidikan Masyarakat (JPPM) Vol 3 No 2 (2022): Jurnal Pengabdian Pendidikan Masyarakat (JPPM) Volume 3, No 2 Oktober 2022
Publisher : LP3M STKIP MUHAMMADIYAH MUARA BUNGO

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (333.389 KB) | DOI: 10.52060/jppm.v3i2.967

Abstract

This Community Service activity aims to improve the quality and motivation of mathematics learning, especially the addition and subtraction of integers for PKBM Budi Luhur Pekaja Banyumas students. This learning activity is carried out offline at the beginning of the odd semester of the 2022/2023 academic year by involving 7 (seven) graders. The learning method used is lectures and demonstrations of the use of teaching aids called 'algebra boards'. Algebra board teaching aids are concrete teaching aids resulting from the development of semi-concrete teaching aids, namely the number line that is used to explain the addition and subtraction of integers. The evaluation of the success of the learning activity results is based on the pre-test and post-test scores given to students before and after using the algebra board props. The results of the evaluation showed that the average score of students increased by 64.7% for the material of adding integers and 39.1% for the material of subtracting integers.
ANALISIS FAKTOR-FAKTOR YANG MEMPENGARUHI KEMISKINAN RUMAH TANGGA DI DESA KOTAYASA MELALUI PENDEKATAN REGRESI LOGISTIK BINER Agustini Tripena; Yosita Lianawati; Antonius Ary Setyawan
Electro Luceat Vol 9 No 2 (2023): Elektro Luceat (JEC)-November 2023
Publisher : LPPM Poltek ST Paul

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32531/jelekn.v9i2.708

Abstract

Kotayasa Village is a village that has the highest number of poor households in Banyumas Regency with 1,662 poor households (78%). This study aims to determine which factors have a significant effect and interpret the binary logistic regression model for poor households in Kotayasa Village. The data used in this research is secondary data from the Office of Social and Community and Village Empowerment in Banyumas Regency. The results showed that the factors that had a significant effect on poor households in Kotayasa Village were electricity, gold savings and livestock. Meanwhile, factors that have no significant effect are sources of drinking water and private vehicles. The results of the analysis obtained the odds ratio values, namely electric power of 3,999, gold deposits of 7,963, and livestock of 1,497. The electric power variable shows that households with electric power less than equal to 900 have a greater chance of being included in poor households of 3,999. The gold savings variable is that households that do not have gold savings have a greater chance of being included in poor households of 7,963. The livestock variable shows that households that do not have livestock have a greater chance of being included in poor households of 1,497. Keywords: Odds ratio, binary logistic regression, poor household.
PENENTUAN UKURAN SAMPEL MENGGUNAKAN RUMUS BERNOULLI DAN SLOVIN: KONSEP DAN APLIKASINYA Majdina, Nadhilah Idzni; Pratikno, Budi; Tripena, Agustini
Jurnal Ilmiah Matematika dan Pendidikan Matematika Vol 16 No 1 (2024): Jurnal Ilmiah Matematika dan Pendidikan Matematika (JMP)
Publisher : Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20884/1.jmp.2024.16.1.11230

Abstract

ABSTRACT. The research discussed a sample survey to draw the population inference based on the sample from that population. There are several techniques to take a sample size, but here we focused to use the Bernoulli’s and Slovin’s formula. This study aims to: (1) reconstruct the Bernoulli’s and Slovin’s formula and (2) examine the conditions (properties) in using the Bernoulli’s and Slovin’s formula. Here, we used a simple random sampling (SRM). Furthermore, both the reconstruction of Bernoulli's and Slovin's formula used the SRM as a sampling technique. This is due to the simple random sampling is a sampling technique that does not try to reduce the effect of variation or variance of data (on estimation errors). The results showed that the Bernoulli’s formula is used to determine sample size which estimates the infinite population proportion. Here, the assumption of the level of confidence is any values and the variance of the population is given as with p is any real value of the proportion between 0 and 1. Meanwhile, the Slovin’s formula is used to determine the sample size which estimates the finite population proportion with the confidence levels from 87%<=1-\alpha<=99%, where p is better to be 0.5. This is due to it will produce the maximum samples.Keywords: Bernoulli’s Formula, Solvin’s Formula, sample size, and survey sample. ABSTRAK. Riset ini membahas survei sampel dalam upayanya menarik kesimpulan populasi berdasarkan informasi yang diperoleh dari sampel dalam populasi. Beberapa teknik sampling untuk menentukan ukuran sampel relatif banyak sehingga riset ini difokuskan untuk menggunakan ukuran sampel berdasarkan metode (rumus) Bernoulli dan Slovin. Selanjutnya, riset ini dilakukan untuk: (1) merekonstruksi rumus Bernoulli dan rumus Slovin dan (2) mengkaji ketentuan penggunaan (properties) dari kedua metode (rumus) tersebut, Bernoulli dan Slovin. Pada riset ini, metode pengambilan sampel yang digunakan adalah simple random sampling (SRM), yang mana model ini digunakan sebagai teknik sampling yang mendasari rekonstruksi rumus Bernoulli dan rumus Slovin. Hal ini, karena SRM merupakan salah satu teknik sampling yang tidak mengurangi pengaruh variansi atau keragaman data pada kesalahan estimasi. Hasil penelitian referensi menunjukan bahwa metode Benoulli dipakai estimasi ukuran sampel infinite population proportion. Pada konsep ini, asumsi keragaman populasi yang dimasukkan dalam perhitungan adalah pq/n dengan nilai p diambil sembarang, dan error ditentukan peneliti. Sedangkan metode Slovin dipakai untuk menentukan estimasi ukuran sampel finite population proportion, dengan tingkat kepercayaan adalah 87%<=1-\alpha<=99%, dimana nilai tidak boleh mendekati 0 atau 1, tetapia mendekati 0,5 merupakan pilihan terbaik yang menghasilkan sampel terbanyak.Kata Kunci: Metode Bernoulli, rumus Slovin, survey sampel, dan ukuran sampel
Regresi Nonparametrik Spline Truncated Tripena, Agustini; Yosita Lianawati
Jurnal Sistem Informasi dan Ilmu Komputer Vol. 1 No. 3 (2023): Agustus: Jurnal Sistem Informasi dan Ilmu Komputer
Publisher : Universitas Katolik Widya Karya Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59581/jusiik-widyakarya.v1i3.1160

Abstract

Nonparametric regression is used to determine the relationship between the response variable and the predictor variable whose shape of the regression curve is not known. This study examines the factors that affect the number of tuberculosis cases in Central Java in 2021. The number of berculosis cases in Central Java reached 117 cases per 115,000 residents with a mean of 110,35 and a variance of 1360.74. Tuberculosis case rates and their affecting factors are modeled using a spline truncated nonparametric regression method. The relationship between tuberculosis case rates in Central Java and the factors that are thought to affect it does not form a specific plot. . Based on the research results, the best model of the minimum Mean Square Error (MSE) value is obtained at the knot point combination (1, 3, 2, 3, 3), with a MSE value of 0.57. The model, it is known that all factors have a significant effect on tuberculosis cases in Central Java, with a coefficient of determination of 93.41%. That is, the model can explain the diversity of tuberculosis cases in Central Java by 93.41%.
Fourier Series Estimator For Estimation of Birespon Nonparametric Regression Curves Agustini Tripena; Niken Larasati; Agus Sugandha; Putri Raffikah
International Journal of Technology and Education Research Vol. 2 No. 03 (2024): July - September, International Journal of Technology and Education Research (
Publisher : International journal of technology and education research

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63922/ijeter.v2i03.1320

Abstract

In the last decade the Fourier Series estimator in nonparametric regression (one response) has received a lot of attention from researchers because of its flexibility. In this case, the Derer Fourier estimator will be developed in two response nonparametric regression (Birespon). The shape of the regression curve is unknown and is assumed to be contained in a continuous function space . Random errors are mutually independent with zero mean and variance , and are also mutually independent with zero mean and variance . Errors are random and correlated with each other .
Poverty Mapping of District/City in Central Java Province in 2023 Using Biplot Analysis Abdiyansah, Muhamad Nur; Tripena, Agustini; Estri, Mutia Nur
PESHUM : Jurnal Pendidikan, Sosial dan Humaniora Vol. 4 No. 3: April 2025
Publisher : CV. Ulil Albab Corp

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56799/peshum.v4i3.8739

Abstract

Kemiskinan merupakan salah satu permasalahan yang dihadapi Indonesia. Kemiskinan di Indonesia harus diatasi untuk mencapai salah satu tujuan bangsa, yaitu memajukan kesejahteraan umum sebagaimana tercantum dalam pembukaan Undang-Undang Dasar 1945. Jawa Tengah merupakan salah satu provinsi di Indonesia dengan jumlah penduduk miskin per Maret 2023 sebanyak 3.791.500 jiwa. Kabupaten Brebes memiliki jumlah penduduk miskin tertinggi yaitu 286.140 jiwa, sedangkan jumlah penduduk miskin terendah terdapat di Kota Magelang yaitu 7.450 jiwa. Hal ini menunjukkan adanya perbedaan distribusi penduduk yang cukup signifikan di Provinsi Jawa Tengah, sehingga diperlukan pemetaan kemiskinan pada 35 kabupaten/kota di Jawa Tengah berdasarkan variabel kemiskinan. Salah satu metode yang dapat digunakan adalah analisis biplot. Variabel yang digunakan meliputi garis kemiskinan, jumlah penduduk miskin, indeks kedalaman kemiskinan, indeks keparahan kemiskinan, tingkat pengangguran terbuka, kepadatan penduduk, dan indeks pembangunan manusia. Grafik biplot menghasilkan 5 kelompok pemetaan dengan nilai kelayakan biplot sebesar 79,17%, artinya grafik biplot menjelaskan 79,17% informasi yang terkandung dalam data.
Rainfall Forecasting Using Seasonal Autoregressive Integrated Moving Average Method And Decomposition Method in Pangkalan Bun Grisella Estefania R; Agustini Tripena; Triyani, Triyani
PESHUM : Jurnal Pendidikan, Sosial dan Humaniora Vol. 4 No. 4: Juni 2025
Publisher : CV. Ulil Albab Corp

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56799/peshum.v4i4.9431

Abstract

Flash floods and droughts that often occur in Pangkalan Bun, Central Kalimantan are clear evidence of the impact of climate change. Global climate change has caused an increase in the frequency and intensity of extreme weather, including significant fluctuations in rainfall. The purpose of this study is to create the best model for predicting rainfall using the SARIMA method and the Decomposition method in the case of data in Pangkalan Bun. The data used are rainfall data in Pangkalan Bun as many as 180 observations (January 2009 - December 2023). Rainfall data is divided into training data and testing data. Training data is used to determine the forecasting model using the SARIMA method and the Decomposition method. The results, the SARIMA (1,0,1) (1,0,1)12 model gives the lowest MAPE value compared to other decomposition models, namely a MAPE value of 26.05%. The MAPE value indicates that the SARIMA (1,0,1) (1,0,1)12 model is suitable for use in predicting future data. The forecast results show that the highest rainfall will occur in November 2024 at 263.97 mm and the lowest in August 2024 at 106.26 mm.
Co-Authors Abdiyansah, Muhamad Nur Agus Sugandha Ari Wardayani Budi Pratikno, Budi Esa Anugrah Salsabila Grisella Estefania R Majdina, Nadhilah Idzni Mutia Nur Estri, Mutia Nur Niken Larasati Putri Raffikah Setyawan, Antonius Ary Slamet Riyadi Triyani Triyani Triyani Triyani Yosita Lianawati