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All Journal Science and Technology Indonesia SWARNA Jurnal Pengabdian Masyarakat Tapis Berseri Abdi Akommedia : Jurnal Pengabdian Masyarakat Sciencestatistics: Journal of Statistics, Probability, and Its Application Integra: Journal of Integrated Mathematics and Computer Science INTENS Jurnal Inovasi Sains Teknologi dan Bisnis Nemui Nyimah
Widiarti
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Modeling and Analysis Data Production of Oil, and Oil and Gas in Indonesia by Using Threshold Vector Error Correction Model Widiarti; Usman, Mustofa; Putri, Almira Rizka; Russel, Edwin
Science and Technology Indonesia Vol. 9 No. 1 (2024): January
Publisher : Research Center of Inorganic Materials and Coordination Complexes, FMIPA Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26554/sti.2024.9.1.189-197

Abstract

Data in the fields of finance, business, economics, agriculture, the environment and weather are commonly in the form of time series data. To analyze time series data that involves more than one variable (multivariate), vector autoregressive (VAR) models, vector autoregressive moving average (VARMA) models are generally used. If the variables discussed have cointegration, then the VAR model is modified into a vector error correction model (VECM). The relationship between short-term dynamics and deviation in the VECM model is assumed to be linear. If there is a nonlinear relationship between short-term dynamics and deviation, then a threshold vector error correction model (TVECM) can be used. The variables used in this research consist of oil production and Indonesian oil and gas production from January 2019 to March 2021. The research results show that the best model for data on oil production and oil and gas production is the TVECM 2 Regime model. Based on the TVECM 2 Regime model, further analysis, namely Granger causality and Impulse Response Function are discussed.
Penerapan Metode Geographically Weighted Panel Regression Pada Indeks Pembangunan Manusia di Indonesia Tahun 2017-2022 Deta Erviana; Mustofa Usman; Widiarti; Khoirin Nisa
Sciencestatistics: Journal of Statistics, Probability, and Its Application Vol. 2 No. 1 (2024): JANUARY
Publisher : Universitas Muhammadiyah Metro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24127/sciencestatistics.v2i1.5669

Abstract

Regresi linier merupakan metode statistik untuk memeriksa hubungan antara variabel respons dan satu atau lebih variabel prediktor. Dalam sebuah penelitian, satu unit observasi harus diteliti selama beberapa periode waktu, karena mempelajari satu unit dalam satu periode waktu tidaklah cukup. Oleh karena itu, sebuah pendekatan statistik yang disebut analisis regresi panel diciptakan untuk mengintegrasikan data cross-section dan data time series. Namun pada kenyataannya, perbedaan kondisi antar lokasi dipengaruhi oleh efek spasial yang menyebabkan terjadinya heterogenitas spasial. Dikembangkanlah metode Geographically Weighted Regression (GWR) untuk mengatasi masalah heterogenitas spasial. Berdasarkan kelebihan kedua metode tersebut maka berkembanglah suatu metode yang menggabungkan antara regresi data panel dan GWR yaitu Geographically Weighted Panel Regression (GWPR). Tujuan dari penelitian ini adalah untuk mengetahui faktor-faktor yang mempengaruhi indeks pembangunan manusia (IPM) di Indonesia tahun 2017-2022 dan menentukan model terbaik dengan membandingkan model regresi global dan GWPR. Model GWPR dengan pembobot adaptive bisquare merupakan model terbaik dengan nilai AIC terkecil dan R^2 terbesar. Secara keseluruhan semua variabel prediktor yang digunakan dalam penelitian berpengaruh signifikan terhadap IPM pada taraf signifikansi α=0,05. Persamaan model dan variabel yang berpengaruh signifikan yang dihasilkan dalam pemodelan GWPR berbeda untuk setiap provinsi. Berdasarkan kesamaan variabel yang mempengaruhi IPM di provinsi yang letaknya berdekatan membentuk 8 kelompok.
Workshop Pembuatan Media Pembelajaran dan Pengolahan Nilai bagi Guru SMK Nurul Huda Pringsewu Widiarti; Asmiati; Kurniasari, Dian; Notiragayu; Warsono; Okzarima, Wenty; Suciati, Indah
SWARNA: Jurnal Pengabdian Kepada Masyarakat Vol. 3 No. 6 (2024): SWARNA: Jurnal Pengabdian Kepada Masyarakat, Juni 2024
Publisher : LPPM Sekolah Tinggi Ilmu Ekonomi 45 Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55681/swarna.v3i6.1315

Abstract

Sekolah Menengah Kejuruan (SMK) Swasta Nurul Huda Pringsewu memiliki empat jurusan, yaitu Asisten Perawat, Farmasi, Multimedia, dan Teknik Kendaraan Ringan dengan jumlah peserta didik sebanyak 205 Siswa dan guru sebanyak 30 orang. Berdasarkan data yang diperoleh hanya sekitar  28% lulusan SMKS Nurul Huda Pringsewu yang melanjutkan pendidikannya ke PT. Dengan demikian diperlukan adanya pembinaan terintegrasi untuk meningkatkan keinginan para siswa melanjutkan pendidikan ke PT.  Pengabdian ini menitik beratkan pada pembinaan komprehensif guru. Pembinaan guru meliputi pelatihan pembuatan media pembelajaran menggunakan Canva dan pengolahan nilai menggunakan Microsoft Excel. Kegiatan pengabdian ini mendapat sambutan  dan hasil yang baik dari para guru di SMK Swasta Nurul Huda Pringsewu. Berdasarkan hasil analisis statistik dengan menggunakan Uji T (T Test) menggunakan R Studio diperoleh bahwa nilai pre-test sebelum dilakukan workshop berbeda sangat signifikan dengan nilai post-test setelah dilakukan workshop.
Konservasi Anggrek Dan Peningkatan Peringkat Greenmetric Melalui Kegiatan Penanaman Anggrek Di Kampus Widiarti; Usman, Mustofa; Wamiliana; Nurcahyani, Nuning; Master, Jani
Jurnal Pengabdian Masyarakat Tapis Berseri (JPMTB) Vol. 2 No. 1 (2023): Jurnal Pengabdian Masyarakat Tapis Berseri (JPMTB) (Edisi April)
Publisher : Pusat Studi Teknologi Informasi Fakultas Ilmu Komputer Universitas Bandar Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36448/jpmtb.v2i1.39

Abstract

Upaya pelestarian anggrek, khususnya anggrek spesies merupakan salah satu kegiatan konservasi lingkungan hidup. Dalam rangka pelestarian lingkungan, lingkungan kampus sudah dipenuhi berbagai pohon-pohon rindang dan tinggi, yang sangat sesuai untuk habitat anggrek hutan. Adanya tanaman-tanaman ini merupakan salah satu upaya konservasi lingkungan, keindahan, dan pengurangan gas CO2. Untuk menambah keindahannya, pohon-pohon besar yang ada di lingkungan taman kampus dapat ditempel berbagai jenis anggrek yang sesuai dengan habitatnya seperti amabilis, retusa, bulbophyllum, aphyllum, dan dendrobium. Anggrek, selain indah dan cantik, juga akan mengurangi kadar CO2 di udara sehingga penanaman anggrek di lingkungan kampus akan berdampak baik terhadap peringkat greenmetric. Tujuan kegiatan pengabdian ini adalah untuk: (1) melestarikan anggrek spesies khususnya amabilis yang merupakan spesies asli Lampung, (2) mengurangi CO2 dan meningkatkan peringkat greenmetric. Kegiatan ini melibatkan tim dosen, mahasiswa, dan staff untuk membantu merawat tanaman anggrek. Tingkat keberhasilan hidup anggrek untuk beradaptasi di lingkungan kampus sangat baik (lebih dari 95%). Partisipasi dan antusiasme masyarakat dan civitas akademika di lingkungan kampus juga sangat baik. Hal ini ditandai dengan pertumbuhan anggrek yang baik dan masih utuhnya plant anggrek yang ditanam.
Modeling Vector Error Correction with Exogeneous (VECMX) Variable for Analyzing Nonstationary Variable Energy Used and Gross Domestic Product (GDP) Usman, Mustofa; Wamiliana; Russel, Edwin; Kurniasari, Dian; Widiarti; Elfaki, Faiz A.M
Science and Technology Indonesia Vol. 10 No. 1 (2025): January
Publisher : Research Center of Inorganic Materials and Coordination Complexes, FMIPA Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26554/sti.2025.10.1.283-293

Abstract

Analysis of energy used, GDP and population has been carried out in many countries and has become a topic of interest for many researchers and governments. This is because energy used is an important factor for society and industry in a country. In this study, the modeling of the relationship between energy used, GDP and population as an exogenous variable for the cases of Indonesia from 1967-2023 will be discussed. The energy used and GDP data are nonstationary with order one, I(1), and there is cointegration between energy used and GDP. Therefore, the model which will be used is the Vector Error Correction Model with Exogenous variable (VECMX) with population as the exogenous variable. From the results of analysis, the best model is VECMX(3,1) with cointegration rank R=1. Based on this model, the pattern of the relationship among the three variables, Granger-causality between energy used and GDP, exogenous impact on energy used and GDP, and forecasting for the next 10 years will be discussed.
Pelatihan Pembuatan Infografis Desa dalam Rangka Mendukung Program Desa Cantik Widiarti; Kurniasari, Dian; Wamiliana; Asmiati
Jurnal Pengabdian Masyarakat Tapis Berseri (JPMTB) Vol. 4 No. 1 (2025): Jurnal Pengabdian Masyarakat Tapis Berseri (JPMTB) (Edisi April)
Publisher : Pusat Studi Teknologi Informasi Fakultas Ilmu Komputer Universitas Bandar Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36448/jpmtb.v4i1.129

Abstract

The Desa Cantik program is one of the Central Statistics Agency (BPS) programs to realize sectoral statistical development at the village level in a sustainable and comprehensive manner. BPS Tanggamus Regency is one of the BPS that participates in developing Desa Cantik. In 2024, BPS Tanggamus will develop 4 villages spread across Tanggamus Regency. The four villages are Kampung Baru, Kagungan, Purwodadi and Banding Agung. The purpose of this development is to increase the capacity of the village or the ease in identifying data needs and potential owned by the village in order to eradicate poverty and increase statistical literacy in the village. In line with the responsibility carried out by BPS regarding this Desa Cantik program, the development is also a challenge for the staff of the Mathematics Department FMIPA Unila to participate in transferring knowledge and skills, especially related to Statistical Techniques. Through this program, human resources in the village are trained to process village monographic data and present it in the form of infographics with the help of the Tableu and Canva applications. The results of this training activity showed that 71% of participants had actively participated in preparing infographics.
Workshop Pelatihan Pemahaman Konsep Aritmatika Sosial untuk Siswa SMKS Nurul Huda Pringsewu Kurniasari, Dian; Asmiati; Widiarti; Sawitri, Riza
ABDI AKOMMEDIA : JURNAL PENGABDIAN MASYARAKAT Vol. 3 No. 3 (2025)
Publisher : ABDI AKOMMEDIA : JURNAL PENGABDIAN MASYARAKAT

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

Abstract

Aritmatika sosial salah satu aspek penting dalam numerasi dasar dan memiliki manfaat praktis yang relevan dengan dunia kerja dan kehidupan sehari-hari. Rendahnya pemahaman siswa SMKS Nurul Huda terhadap konsep matematika yang kontekstual, khususnya pada materi aritmatika sosial, sehingga diperlukan pelatihan pemahaman konsep aritmatika sosial. Kegiatan ini bertujuan untuk memberikan pemahaman konsep aritmatika sosial secara aplikatif serta memotivasi siswa untuk belajar secara mandiri dan berkelanjutan. Workshop ini dilakukan dalam bentuk ceramah interaktif, diskusi, dan simulasi perhitungan kontekstual agar siswa lebih mudah memahami konsep matematika yang diajarkan. Keberhasilan kegiatan workshop dievaluasi melalui pre-test dan post-test. Berdasarkan nilai pre-test dan post-test, diperoleh rata-rata selisih perbedaan nilai post-test dan pre-test sebesar 33,08. Pengujian selisih beda dua rata-rata dengan menggunakan uji t memberikan hasil bahwa secara statistik nilai post-test lebih besar dibandingkan dengan nilai pre-test. Hasil ini menunjukkan bahwa para peserta memahami apa yang disampaikan oleh narasumber dan membuka wawasan mereka tentang artimatika sosial dalam kehidupan sehari-hari.
Robust Panel Data Regression Analysis using the Least Trimmed Squares (LTS) Estimator on Poverty Line Data in Lampung Province Lestari, Windi; Widiarti; Utami, Bernadhita Herindri Samodera; Usman, Mustofa; Handayani, Vitri Aprilla
Integra: Journal of Integrated Mathematics and Computer Science Vol. 1 No. 2 (2024): July
Publisher : Magister Program of Mathematics, Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26554/integrajimcs.20241210

Abstract

Robust regression is an alternative method in regression analysis designed to produce stable parameter estimates, even when the data contain outliers or deviate from classical assumptions. One of its estimation techniques, the Least Trimmed Square (LTS),works by minimizing the smallest squared residuals, thereby assigning smaller weights to extreme data points. This method serves as a solution when classical approaches, such as Ordinary Least Squares (OLS), fail to meet the assumptions, especially in socio-economic data that are often complex and prone to outliers. This study employs robust regression with the LTS estimator on panel data to examine the impact of population size , population density , and registered job vacancies on poverty lines in Lampung Province. The data cover 15 districts and cities from 2019 to 2023. The analysis results show that the model obtained has a coefficient of determination of R2=0.8909. This means that the three predictor variables can explain 89.09% of the variation in the poverty line.
Comparison of Naïve Bayes and Random Forest Models in Predicting Undergraduate Study Duration Classification at the University of Lampung Hestina P., Shelvira; Widiarti; Nuryaman, Aang; Usman, Mustofa
Integra: Journal of Integrated Mathematics and Computer Science Vol. 1 No. 3 (2024): November
Publisher : Magister Program of Mathematics, Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26554/integrajimcs.20241317

Abstract

This study aims to compare the performance of the Naïve Bayes and Random Forest classification algorithms in predicting the study duration of undergraduate students in the Mathematics Study Program at the University of Lampung. The dataset consists of 537 graduation records from 2020–2024. The research steps include data preprocessing, data partitioning (train-test split and k-fold cross validation), model building, and evaluation using a confusion matrix. The results show that the Random Forest algorithm achieved the highest accuracy of 94.44%, outperforming Naïve Bayes which reached a maximum accuracy of 92.59%. These findings suggest that Random Forest is more effective for classifying student study durations. These findings suggest that Random Forest is more effective for classifying student study durations.
Georaphically Weighted Ridge Regression Modelling on 2023 Poverty Indicators Data in the Provinces of West Kalimantan and Central Kalimantan Anjani, Syarli Dita; Widiarti; Utami, Bernadhita Herindri Samodera; Usman, Mustofa; Handayani, Vitri Aprilla
Integra: Journal of Integrated Mathematics and Computer Science Vol. 1 No. 3 (2024): November
Publisher : Magister Program of Mathematics, Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26554/integrajimcs.20241320

Abstract

Regression analysis is a method to explain the relations between independent variables and a dependent variable. Linear regression analysis relies on certain assumptions, one of the assumption is homogeneity. However, there is a situation when the variance at each observation differs or called spatial heterogeneity.This issue can be solved using Geographically Weighted Regression (GWR), a statistical method that can be fixed spatial heterogeneity by adding a local weighted matrix, the result in GWR model is a local model for each observation point. However, GWR has a limitation, it cannot handle multicollinearity. Ridge regression is a method used to solved multicollinearity by adding a bias constant (λ). A GWR model that contains multicollinearity and fixed using ridge regression is known as Geographically Weighted Ridge Regression (GWRR).
Co-Authors Aang Nuryaman Anjani, Syarli Dita Ardillawati Fadlia Asmiati Daoud, Jamal I. Deta Erviana Dian Kurniasari Dina Eka Nurvazly, Dina Eka Elfaki, Faiz A.M Elfaki, Faiz AM Eristiani Fadlia, Ardillawati Fitriani, Linda Handayani, Vitri Aprilla Herman, Andi Akbar Hestina P., Shelvira Ilma, Nur Jani Master, Jani Khoirin Nisa Lestari, Windi Loves, Luvita Mustofa Usman Mustofa Usman Nashar, Fitri Nirwana, Saina Notiragayu Nuning Nurcahyani Nurekawati Okzarima, Wenty Putri, Almira Rizka Reski, Nur Awalia Reski, Nurawalia Russel, Edwin Saina Nirwana Sari, Dede Ratna Sawitri, Riza Siti Laelatul Chasanah, Siti Laelatul Suciati, Indah Utami, Bernadhita Herindri Samodera Wamiliana Warsono Yoka, Ranara Athalla