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All Journal Jurnal Sains Matematika dan Statistika Indonesian Journal of Applied Statistics Jurnal Pengabdian Masyarakat MIPA dan Pendidikan MIPA ESTIMASI: Journal of Statistics and Its Application Jurnal Pengabdian kepada Masyarakat Nusantara JAMBURA JOURNAL OF PROBABILITY AND STATISTICS Jurnal AbdiMas Nusa Mandiri
Brilliant, Indira Ihnu
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Agriculture, Biological Sciences & Forestry Computer Science & IT Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Energy Environmental Science Mathematics Physics Social Sciences Other

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Workshop on Visual Data Analysis with R Program Wutsqa, Dhoriva Urwatul; Kismiantini, Kismiantini; Kusumawati, Rosita; Subekti, Retno; Setiawan, Ezra Putranda; Isnaini, Bayutama; Brilliant, Indira Ihnu
Jurnal Pengabdian Masyarakat MIPA dan Pendidikan MIPA Vol. 8 No. 2 (2024): Vol 8, No 2 (2024)
Publisher : Yogyakarta State University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/jpmmp.v8i2.71583

Abstract

Statistics data analysis generally focuses more on mathematical procedures than visual. Visual analysis is very useful for research and this is still very limited to study at Universitas Mercu Buana Yogyakarta, so the UNY Statistics lecturer's service activity is holding visual data analysis workshop with the R program, where this program is open source and is complete for visual analysis. The material for this activity is about procedures and uses for visual data analysis, introduction to the R program, data management with the R program, visual data analysis for group descriptions and comparisons, and visual data analysis for relationships between variables. Evaluation of participants' ability to understand the material is measured through 14 questions with four Likert Scale responses. Based on 40 questionnaires, 27,86% answered "Strongly Agree", 71,96% "Agree", and 0,18% "Disagree" regarding understanding and applying visual data analysis techniques with the R program. Therefore, it can be concluded that the majority of participants could understand the workshop material and follow the training well.
Faktor-Faktor Penentu Prevalensi Stunting di Nusa Tenggara Barat: Analisis Spasial dengan Modifikasi Ketetanggaan Nastiti, Kartika Tri; Luthfi, Zalfa Jihan; Ummah, Karimatul; Brilliant, Indira Ihnu; Setiawan, Ezra Putranda
Jambura Journal of Probability and Statistics Vol 6, No 1 (2025): Jambura Journal of Probability and Statistics
Publisher : Department of Mathematics, Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/jjps.v6i1.24714

Abstract

Stunting is one of the problems faced by the Indonesian population. In 2022, its prevalence in West Nusa Tenggara reached 18.5% and became the fourth highest in Indonesia. This study was conducted to identify the factors that can be used to explain the prevalence of stunting in West Nusa Tenggara using the spatial regression method.  Considering that this province consists of two separate islands, Queen's contiguity matrix was modified to consider the connections between the islands.  Based on the AIC values, the Spatial Durbin Model (SDM) becomes the best model for stunting prevalence. The research results show that the variables Human Development Index (HDI), ADHK Gross Regional Domestic Product, and the number of community health centers have a significant effect on the prevalence of stunting in West Nusa Tenggara. Of these three variables, the HDI variable has the greatest influence on reducing the prevalence of stunting in West Nusa Tenggara. The significance of the Spatial Durbin model shows that there is a spatial effect on the dependent and independent variables. 
Analisis Spasial Kualitas Air Sungai Winongo menggunakan Metode Universal Kriging Annindiya, Harsyta; ‘Ibad, Muhammad Irsyadul; Nashirah, Najla; Brilliant, Indira Ihnu; Setiawan, Ezra Putranda
Jurnal Sains Matematika dan Statistika Vol 11, No 2 (2025): JSMS Juli 2025
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/jsms.v11i2.29193

Abstract

Yogyakarta merupakan salah satu kota di Jawa yang dialiri oleh dua sungai, yakni Sungai Code dan Sungai Winongo. Penelitian ini bertujuan menerapkan universal kriging guna memetakan dan menganalisis kualitas air di Sungai Winongo dengan parameter fisis berupa Total Dissolve Solid, serta parameter biokimia berupa Bakteri Coliform dan Biological Oxygen Demand. Sampel diambil pada bulan Desember 2021 di lima titik pantau yaitu Bener, Peta, Serangan, Taman Sari, dan Prapanca. Metode Universal Kriging digunakan dalam penelitian ini karena adanya trend pada data parameter yang digunakan dan tidak memenuhi asumsi stasioner. Hasil yang diperoleh adalah sungai yang memiliki Biological Oxygen Demand paling tinggi adalah di sekitar titik pantau Peta, tercemar Total Dissolve Solid paling tinggi di sekitar titik pantau Prapanca serta tercemar Bakteri Coliform paling tinggi di sekitar titik pantau Prapanca dan Taman Sari.
Workshop Inferensi Statistik dengan Pendekatan Berbasis Simulasi Kismiantini, Kismiantini; Subekti, Retno; Brilliant, Indira Ihnu; Ratnasari, Andika Putri
Jurnal Pengabdian Masyarakat MIPA dan Pendidikan MIPA Vol. 9 No. 2 (2025): Jurnal Pengabdian Masyarakat MIPA dan Pendidikan MIPA
Publisher : Yogyakarta State University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/jpmmp.v9i2.83414

Abstract

Mata kuliah Statistika umumnya lebih fokus pada prosedur inferensi bagi parameter secara teoritis dan belum memperhatikan pendekatan berbasis simulasi. Pendekatan berbasis simulasi memiliki kelebihan tanpa adanya pemenuhan asumsi klasik. Di Program Studi Matematika Universitas Nusa Cendana, materi inferensi statistik dengan pendekatan berbasis simulasi masih belum diterapkan secara optimal sehingga kelompok dosen Statistika Universitas Negeri Yogyakarta melaksanakan kegiatan workshop inferensi statistik dengan pendekatan berbasis simulasi. Evaluasi kemampuan peserta dalam memahami dan menerapkan materi yang disampaikan diukur melalui 15 butir pernyataan dengan empat respons skala Likert (sangat setuju, setuju, tidak setuju, sangat tidak setuju). Berdasarkan kuesioner hari pertama (39 peserta memberikan respons lengkap), diperoleh rata-rata 38,10% peserta menjawab "˜sangat setuju', 61,54% "˜setuju', dan 0,37% "˜tidak setuju'. Kemudian kuesioner hari kedua (20 peserta memberikan respons lengkap), diperoleh hasil rata-rata 39,38% peserta menjawab "˜sangat setuju', 58,75% "˜setuju', dan 1,88% "˜tidak setuju'. Oleh karena itu, dapat disimpulkan bahwa mayoritas peserta dapat memahami materi workshop dan mengikuti pelatihan dengan baik.
Peningkatan Literasi Statistik Melalui Workshop Analisis Regresi Linier Menggunakan Software JASP Subekti, Retno; Kismiantini; Brilliant, Indira Ihnu; Ratnasari, Andika Putri; Atikah, Farahhuda
Jurnal Pengabdian kepada Masyarakat Nusantara Vol. 7 No. 1 (2026): Edisi Januari - April
Publisher : Lembaga Dongan Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Kegiatan pengabdian kepada masyarakat ini bertujuan untuk meningkatkan literasi statistik bagi dosen dan mahasiswa melalui pelatihan analisis regresi linier menggunakan software statistik yang gratis yaitu JASP. Kegiatan dilaksanakan pada tanggal 7–8 Oktober 2025 di Program Studi Demografi dan Pencatatan Sipil UNS secara luring dan daring.  Metode pelaksanaan mencakup ceramah, demonstrasi, dan praktik langsung dengan studi kasus. Hasil evaluasi menunjukkan bahwa seluruh peserta mengalami peningkatan pemahaman, dengan 42,33% peserta menyatakan sangat setuju dan 57,77% menyatakan setuju bahwa peserta memahami materi analisis regresi linier sederhana dan berganda menggunakan JASP. Kegiatan ini memberikan kontribusi positif terhadap peningkatan kemampuan analisis data berbasis software statistik bebas lisensi
SOSIALISASI JASP: PELATIHAN ANALISIS DATA STATISTIK BAGI AKADEMISI MAKASAR Subekti, Retno; Insani, Nur; Brilliant, Indira Ihnu; Sari, Eminugroho Ratna; Saptaningtyas, Fitriana Yuli; Bayyinah, Nurul
Jurnal AbdiMas Nusa Mandiri Vol. 8 No. 2 (2026): Periode April 2026
Publisher : LPPM Universitas Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/abdimas.v8i2.7813

Abstract

Limited access to licensed statistical software is one of the obstacles in strengthening data analysis competencies at the Makassar Ujung Pandang Education Foundation (YPUP) College of Teacher Training and Education (STKIP). The introduction of free and open-source statistical software such as Jeffreys's Amazing Statistics Program (JASP) has encouraged the implementation of this service activity. The activity aims to increase literacy and readiness to use legal and easily accessible alternative statistical software. The workshop was held online on July 11–12, 2025 with a participatory training approach that included presentation of educational research design, demonstration of the use of JASP, as well as descriptive, parametric, and non-parametric statistical analysis practices. There were 37 participants including lecturers and students, with 33 participants filling out the evaluation instruments. The evaluation was carried out descriptively through a self-assessment questionnaire to measure the level of understanding of participants after the training. The results showed that 32.73% of participants strongly agreed and 67.27% agreed that they had understood the use of JASP. These findings indicate an increase in initial literacy and readiness for the adoption of open-source-based statistical software. Although the objective measurement of the improvement of analytical skills through pre-test and post-test has not been carried out, this activity opens opportunities for the integration of JASP in learning and research and becomes the basis for planning further assistance as a form of program sustainability.
Identifikasi Prediktor Jumlah Kasus Baru Tuberkolosis di Jawa Barat: Perbandingan Regresi Poisson, Binomial Negatif, dan Poisson terbobot Geografis Khalishah, Athayya Putri; Advani, Nadjma Maulidya; Syahputra, Fathur Rahman; Brilliant, Indira Ihnu; Setiawan, Ezra Putranda
ESTIMASI: Journal of Statistics and Its Application Vol. 7, No. 1, Januari, 2026 : Estimasi
Publisher : Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/ejsa.v7i1.34314

Abstract

Tuberculosis (TB) is still a serious problem for the world, including Indonesia as the third largest contributor of TB cases in the world. This study aims to analyze the factors that affect the number of new TB cases in West Java Province as the province with the most TB cases in Indonesia in 2022. The response variable used is the number of new TB cases in West Java Province in 2022, while the predictor variables used are population density, number of AIDS cases, poverty, and sanitation. Since the dependent variable comes from counting procedure, we conducted the analysis through three models, namely Poisson regression, negative binomial regression, and Geographically Weighted Poisson Regression (GWPR). We find that in the negative binomial method there was only one insignificant predictor variable, namely population density. Based on influential predictor variables, GWPR models in districts / cities in West Java can be separated into four groups. The best model to analyze the factors affecting new TB cases is the negative binomial regression model with an AIC of 487.76.
Penerapan Metode Fuzzy Time Series (FTS) Cheng dan Markov-Chain untuk Peramalan Indonesia Crude Oil Price (ICP) Fakhriyana, Deby; Brilliant, Indira Ihnu
Indonesian Journal of Applied Statistics Vol 6, No 1 (2023)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13057/ijas.v6i1.79907

Abstract

In Indonesia, crude oil plays a significant role in the country’s economy as it serves as a source of income and meets the country's energy needs. Therefore, fluctuations in crude oil prices have a significant impact on the economic activities of the society. Forecasting the price of Indonesian crude oil is thus crucial. The international price of crude oil in Indonesia is known as the Indonesian Crude Oil Price (ICP). One commonly used statistical method for forecasting is the ARIMA method. However, the ARIMA method has certain assumptions that need to be fulfil, and many real-world data cannot meet these assumptions. Hence, forecasting using the Fuzzy Time Series (FTS) method, which does not rely on assumptions, is employed. Some popular FTS methods include the Cheng FTS method and the Markov Chain FTS method. This study implements the Cheng FTS and Markov Chain FTS methods on the ICP data from May 2018 to June 2023 to determine the most appropriate method for forecasting. The analysis results using the Cheng FTS method on the testing data yield a Mean Absolute Percentage Error (MAPE) value of 4,083%, while the Markov Chain FTS method has MAPE value of 4,585%. The Cheng FTS method selected as the appropriate model for forecasting the ICP data since it has a smaller MAPE value. Using the Cheng FTS method, the predicted ICP value for July 2023 is US$72,907 per barrel.Keywords: ICP; FTS Cheng; FTS Markov Chain; MAPE
Co-Authors Advani, Nadjma Maulidya Annindiya, Harsyta Atikah, Farahhuda Bayyinah, Nurul Deby Fakhriyana, Deby Dhoriva Urwatul Wutsqa Eminugroho Ratna Sari Ezra Putranda Setiawan Fitriana Yuli Saptaningtyas Isnaini, Bayutama Khalishah, Athayya Putri Kismiantini Kismiantini Luthfi, Zalfa Jihan Nashirah, Najla Nastiti, Kartika Tri Nur Insani Ratnasari, Andika Putri Retno Subekti Rosita Kusumawati Syahputra, Fathur Rahman Ummah, Karimatul ‘Ibad, Muhammad Irsyadul