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All Journal Jurnal Pilar Sains Jurnal Online Mahasiswa (JOM) Bidang Matematika dan Ilmu Pengetahuan Alam Jurnal Sains Matematika dan Statistika Science and Technology Indonesia Sinkron : Jurnal dan Penelitian Teknik Informatika Seminar Nasional Teknologi Informasi Komunikasi dan Industri Indonesian Journal of Chemistry Instructional Development Journal Jurnal Keluarga Berencana Abdi: Jurnal Pengabdian dan Pemberdayaan Masyarakat KAIBON ABHINAYA : JURNAL PENGABDIAN MASYARAKAT Journal of Applied Engineering and Technological Science (JAETS) Al-Muqayyad Indonesian Journal of Electrical Engineering and Computer Science Jurnal Statistika dan Aplikasinya Jambura Journal of Mathematics Education Unri Conference Series: Community Engagement Jurnal Ketenagakerjaan Edumatica: Jurnal Pendidikan Matematika J-ABDIPAMAS (Jurnal Pengabdian Kepada Masyarakat) Indonesian Journal of Advanced Social Works (DARMA) Journal of Mathematics, Computation and Statistics (JMATHCOS)
Arisman Adnan
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Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Medicine & Pharmacology Physics Public Health Social Sciences Other

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Penguatan Kapasitas Komunitas Statistika Bantar dalam Tata Kelola Data Desa untuk Pembangunan Berkelanjutan Adnan, Arisman; Yolanda, Anne Mudya; Erda, Gustriza; Syamsudhuha, Syamsudhuha; Indra, Zul; Solfitri, Titi; T, Masrina Munawarah
Unri Conference Series: Community Engagement Vol 6 (2024): Seminar Nasional Pemberdayaan Masyarakat
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31258/unricsce.6.640-645

Abstract

This activity aims to strengthen the capacity of the statistical community in Bantar Village in supporting the transformation and management of data for sustainable development. The program focuses on assisting village officials in effectively managing data at the village level, in line with the Desa Cantik initiative and Indonesia One Data (SDI) program. The goal is to improve data accuracy and the effectiveness of village development planning. As a result, the statistical community, which also includes village officials, has shown increased capabilities in managing sectoral statistics and digitalizing data integrated with the Desa Cantik program. The village officials actively participated in this assistance, supported by the provincial and district BPS, who acted as facilitators. BPS provided training, monitoring, evaluation, and assistance in the preparation of program materials and outputs. One of the key outputs of this program is the creation of an infographic summarizing the statistics and potential of Bantar Village, covering demographic profiles, population density, and key commodities. This infographic serves as a visual communication tool that supports data-driven development planning. The program successfully established a strong foundation for better data management, supporting sustainable village development.
Analysis of Labor Force Participation Rate in Riau Province: A Spatial Autoregressive Approach Adnan, Arisman; Erda, Gustriza; Sirait, Tesa Theresia
Jurnal Ketenagakerjaan Vol 19 No 3 (2024)
Publisher : Pusat Pengembangan Kebijakan Ketenagakerjaan Kementerian Ketenagakerjaan Republik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47198/jnaker.v19i3.345

Abstract

The labor force participation rate (LFPR) is one of the important indicators for measuring the participation of the labor force involved in economic activities. In Riau Province, LFPR has exceeded half the population, resulting in increasingly tight job competition. This research aims to model the factors influencing LFPR in Riau Province in 2021 using the Spatial Autoregressive Model (SAR). Based on the Moran Index, there is positive spatial autocorrelation in LFPR, while based on the Lagrange Multiplier test, the SAR model is appropriate to use because of the lag dependence on the dependent variable. SAR analysis shows that the non-labor force variables (????1), poverty line (????2), productive age population (15-64 years) (????3), and population growth rate (????4) have a significant positive influence on LFPR. In contrast, the type ratio variable gender (????5) has a negative influence. Apart from that, a lag coefficient of 0.4935 was obtained, which means that if the value of the LFPR figure in a region increases by 1 unit, it will increase by 0.4935 times the average LFPR in neighboring areas of the region. This highlights the need for policies aimed at increasing the LFPR to account for regional coordination, as changes in one area's LFPR can influence adjacent regions. Consequently, the Riau Provincial Government should promote collaboration among districts and cities to formulate a cohesive strategy, while each district should design policies that align with their unique local characteristics and the spatial dynamics of surrounding areas.
Robust Method with Cross-Validation in Partial Least Square Regression Sibuea, Nuraini; Syamsudhuha, Syamsudhuha; Adnan, Arisman; Silalahi, Divo Dharma
Journal of Mathematics, Computations and Statistics Vol. 8 No. 1 (2025): Volume 08 Nomor 01 (April 2025)
Publisher : Jurusan Matematika FMIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/jmathcos.v8i1.4766

Abstract

Partial Least Squares Regression (PLSR) is a multivariate analysis technique used to handle data with highly correlated predictor variables or when the number of predictor variables exceeds the number of samples. PLSR is not robust to outliers, which can disrupt the stability and accuracy of the model. Cross-validation is an important approach to improve model reliability, particularly in data that contains outliers. This study aims to evaluate the effectiveness of K-fold cross-validation and nested cross-validation in a PLSR model using NIRS data from oil palm plantation soil that contains outliers. The methods used in this study include outlier identification using RBF kernel PCA, followed by the application of K-fold cross-validation and nested cross-validation in the PLSR model. The evaluation is based on the Root Mean Square Error (RMSE) and the Coefficient of Determination (R²). The results show that nested cross-validation performs better than K-fold cross-validation. Nested cross-validation results in lower RMSE and higher R², both with and without outliers. K-fold cross-validation is more susceptible to overfitting, whereas nested cross-validation is more effective in mitigating the impact of outliers and improving model accuracy. The conclusion of this study is that nested cross-validation outperforms K-fold cross-validation in improving prediction accuracy and the stability of the PLSR model, especially in data containing outliers. It is recommended to use nested cross-
Interactive Geographic Visualization and Unsupervised Learning for Optimal Assignment of Preachers to Appropriate Congregations Rahmad Kurniawan; Ibnu Daqiqil ID; Abdul Somad Batubara; Fitra Lestari; Arisman Adnan; Fatayat Fatayat; Ilyas Husti
Journal of Applied Engineering and Technological Science (JAETS) Vol. 6 No. 1 (2024): Journal of Applied Engineering and Technological Science (JAETS)
Publisher : Yayasan Riset dan Pengembangan Intelektual (YRPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37385/jaets.v6i1.5760

Abstract

Riau Province has a population of 6,642,874 and a diverse geography, which poses significant challenges in optimizing Islamic preaching activities. Traditional assignment methods often lead to inefficiencies due to misalignment between the preacher’s expertise and congregational needs, as well as logistical issues. This study integrates K-Means clustering and DBSCAN algorithms with interactive geographic visualization to optimize the assignment of preachers to mosques. We collected 435 data points, including 185 mosques and 250 preachers. K-Means was evaluated using the Elbow Method and Silhouette Score, identifying 10 clusters as optimal with a Silhouette Score of 0.435654. However, K-Means does not handle outliers effectively, as indicated by zero outliers in all configurations. DBSCAN was tested with various epsilon (eps) and minimum sample values. The optimal configuration with eps of 1.5 and 5 minimum samples resulted in 10 clusters with a Silhouette Score of 0.381108 and 60 outliers. DBSCAN effectively manages outliers and varying densities. Although K-Means is advantageous for its simplicity and higher Silhouette Scores, it is unable to handle outliers effectively. DBSCAN provides robust clustering for noisy data. Therefore, it can be concluded that hybridizing unsupervised learning algorithms with geographic visualization can potentially improve the effectiveness of preaching activities in Riau Province and enhance preacher assignment.
Evaluating Statistical Power in t-Test and Welch’s Test Using Monte Carlo Simulation Approach Tengku Irfan Wira Buana; Arisman Adnan
Journal of Mathematics, Computations and Statistics Vol. 8 No. 2 (2025): Volume 08 Nomor 02 (Oktober 2025)
Publisher : Jurusan Matematika FMIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/jmathcos.v8i2.7407

Abstract

Statistical hypothesis testing is a key method in inferential statistics for assessing whether group differences are simply due to chance or amount to actual effect. One of the central concepts in hypothesis testing is statistical power. Statistical power is the probability of correctly rejecting the null hypothesis when the alternative hypothesis is true. Low statistical power increases the risk of Type II errors, leading to misleading conclusions. This study explores the key factors influencing statistical power, including sample size, effect size, variance, and significance level. Monte Carlo simulation method was utilized in this study to examine the statistical power associated with the two-sample t-test across various combinations of sample size, effect size (mean difference), and population variance. Simulations were conducted by generating random samples, performing variance tests, and applying either the Student’s t-test or Welch’s t-test based on variance equality. The results confirmed that statistical power increases with larger sample sizes and greater effect sizes, while higher variance and stricter significance levels reduce power. Welch’s t-test was found to be more reliable than the standard t-test in cases of unequal variances, reinforcing its importance in real-world data analysis. These findings show the importance of careful study design in hypothesis testing. Researchers must consider and plan the study so that there is enough power to detect meaningful effects. Future studies should examine different statistical methods of power, and potentially extend the simulation to different non-normal distributions for hypothesis testing.
Dynamic Modeling of Energy Data: World Crude Oil and Coal Prices 2017-2023 (A State-Space Model Analysis of Multivariate Time Series) Russel, Edwin; Wamiliana; Usman, Mustofa; Elfaki, Faiz AM; Adnan, Arisman; Lindrianasari
Science and Technology Indonesia Vol. 10 No. 4 (2025): October
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.2025.10.4.1301-1311

Abstract

The analysis of global crude oil and coal prices has attracted considerable research interest, as these prices significantly affect both society and industry, making the topic highly relevant for governments and policy makers. This study examines the correlation between global coal and crude oil prices from 2017 to 2023. It analyzes the behavior of these price series using a unit root test and develops an optimal model for conducting a Granger-causality analysis. To forecast crude oil and coal prices for the next 30 periods, a state-space modeling approach is applied. The unit root test results reveal that these prices are non-stationary, suggesting that any shocks to prices will have persistent effects. The best-fitting model for the association between coal and crude oil prices is a vector autoregressive model of order two (VAR(2)). The Granger-causality results reveal that current crude oil prices are influenced by both their own past values and previous coal prices, and vice versa. Forecasts using the state-space model suggest a modest upward trend for crude oil prices over the next 30 periods, while coal prices are projected to rise more strongly.
Pendampingan Pada Aparat dan UMKM Desa untuk Peningkatan Ekonomi Simpang Petai-Kampar Putra, Agus Ika; Yuniarto, Enno; Siswanto, S.; Nugroho, Soewignjo Agus; Satibi, Syawal; Khairat, K; Herman, Syamsu; Saeri, Muhammad; Adnan, Arisman
J-ABDIPAMAS (Jurnal Pengabdian Kepada Masyarakat) Vol. 8 No. 1 (2024): April 2024
Publisher : IKIP PGRI Bojonegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30734/j-abdipamas.v8i1.2812

Abstract

Simpang Petai village was formed due to the expansion of the village in 2008.  As a new village, Simpang Petai lacks facilities to face the challenges of implementing village development. The level of understanding and skills of the village officials for planning system is still very low.  The participation of UMKM in the implementation of village development needs to be carried out and strengthened as one of the bases of village stability and the driving force for improving the village economy.  The PkM Team of the Riau University Village Development Program, as Technical Assistance, helped solve village problems.  Inventarisasi PkM team, compile activities systematically and continuously, to improve the understanding and skills of officials and village communities in the process of preparing and implementing participatory village development planning. The forming of active participation of young people, as drivers of village UMKM, in development as the basis for the resilience of rural communities and the driving force of the village economy.  The activities of Advanced Welding Skills Practice, which with Product orientation, and Management Activities website Desa as the basis for village planning for Community Services and Marketing of Local Products succeeded in improving the economy of UMKM ABSTRAKDesa Simpang Petai terbentuk karena pemekaran desa tahun 2008. Sebagai desa baru, Simpang Petai minim fasilitas menghadapi tantangan melaksanakan pembangunan desa. Tingkat pemahaman dan keterampilan Aparat desa menyusun sistem perencanaan desa masih sangat rendah. Partisipasi UMKM dalam pelaksanaan pembangunan desa perlu dijalankan serta diperkuat sebagai salah satu basis stabilitas desa dan motor penggerak peningkatan Perekonomian desa. Tim Kegiatan Pengabdian Masyarakat Program Bina Desa Universitas Riau, sebagai Technical Assistance, membantu menyelesaikan permasalahan desa. Inventarisasi tim PkM, menyusun kegiatan secara sistematis dan berkesinambungan, yaitu untuk meningkatkan pemahaman dan keterampilan Aparat dan masyarakat desa pada proses penyusunan dan implementasi perencanaan pembangunan desa yang partisipatif. Terbentuknya partisipasi aktif para pemuda, sebagai penggerak UMKM desa, dalam pembangunan sebagai basis ketahanan masyarakat desa dan motor penggerak Perekonomian desa. Kegiatan Praktik Keterampilan Pengelasan Lanjut, yang dengan orientasi Produk, dan Kegiatan Pengelolaan website Desa sebagai basis perencanaan desa untuk Pelayanan Masyarakat dan Pemasaran Produk Lokal berhasil meningkatkan ekonomi UMKM.
Creating a Digital Thematic Map Based on Spatial Data in Alahair Village Using the QGIS 3.22.4 Application Arisman Adnan; Sul Kantri Rahma Wanti; Windy Lasma Sari Purba; Rahwana Saputra; Fikri Marwansyah; Defrinaldi Absari; Kesi Marseliani; Nabilah Fitriyyah Delfira; Sillaturahim; Sukma Novia Syafitri; Wirda Hia
Indonesian Journal of Advanced Social Works Vol. 2 No. 5 (2023): October 2023
Publisher : PT FORMOSA CENDEKIA GLOBAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55927/darma.v2i5.6283

Abstract

Located in the Meranti Islands Regency of Riau Province, Alahair Village is a part of the Tebing Tinggi subdistrict. Alahair Village faces a number of data-related issues, such as data that isn't validated according to the field, unstructured data, and the need to find data quickly; requests from agencies at the sub-district, district, and provincial levels for data from the village; and the fact that when staff changes occur in the village, the data stored in the soft file is lost. Soil types, political boundaries, roads, irrigation zones, altitude, weather, and population can all be stored and managed with the help of spatial and non-spatial data. QGIS 3.22.4 is one such GIS-based program, and it can be used to make maps. Service to the community is accomplished through the following procedures: obtaining a statement of willingness to collaborate and partner; identifying village data needs; collecting village data; processing village data; creating thematic maps; discussing the results of thematic maps; holding workshops to discuss thematic map findings. Lecturers, students, and partners involved in mentoring in the field carry out this community service activity, producing a thematic map with generational, occupational, and educational classifications. Making a thematic map is the presentation of village data in the form of a map which contains village data which will later be easily accessed as a basis for information for the spatial needs of the village's sustainable development plan.
Enhancing Mathematical Problem-Solving and Teamwork Skills For Junior High Schools Student Through Project-Based Learning Roza, Yenita; Murni, Atma; Gumanti; Adnan, Arisman; Alawiyah, Tuti
Edumatica : Jurnal Pendidikan Matematika Vol 15 No 3 (2025): Edumatica: Jurnal Pendidikan matematika (Desember 2025)
Publisher : Department of Mathematics Education, Faculty of Teacher Training and Education, Universitas Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22437/edumatica.v15i3.43491

Abstract

Problem-solving skills are not only correlated to academic success but also to increased competitiveness in a professional environment. However, many junior high school students have both weak mathematical problem-solving and teamwork skills. This study aims to describe the improvement of mathematical problem-solving and teamwork skills of students using the Project Based Learning (PjBL) model and scientific learning. This study is a quantitative study with a quasi-experimental method, using Pretest-Posttest Control Group Design. The population in this study consisted of 186 junior high school students in Bengkalis Regency. Data collection techniques were carried out through mathematical problem-solving ability tests and teamwork questionnaires. Data analysis was carried out using normalized gain (N-Gain) and one-way ANOVA. Based on the results of the data analysis, the results obtained were that students in the PjBL group showed a higher increase in problem-solving and teamwork skills with N-gains of 0.48 and 0.42, respectively, compared to the control class which obtained N-gains of 0.21 and 0.09, respectively. Teamwork skills consistently improved across all grades, while improvement in problem-solving skills varied according to students' initial abilities. This study supports existing research by integrating cognitive and affective aspects of problem-solving and financial literacy skills into everyday life.
Co-Authors ', Firdaus Abdul Somad Batubara Afrianto Daud Agus Ika Putra Agus Kurniawati Ahmad Fadli Ahmad Jamaan Amun Amri Anne Mudya Yolanda Asri Elvita Atma Murni Ayu Agustiani Azhari Setiawan Azra Aulia Dwiputri Bustami Bustami Defrinaldi Absari Deni Rizaldi Devri Maulana Ecelly Indriani Putri Elfaki, Faiz AM Endah Dwi Jayanti Enno Yuniarto Fatayat Feblil Huda Febrianti, Lusi Ferdian Fadly Fikri Marwansyah Firdaus ' Fitra Lestari Goldameir, Noor Ell Gumanti Gustriza Erda Haposan Sirait Haposan Sirait Harison ' Harison Harison Heru Angrianto Ibnu Daqiqil ID Icha Yulia Ilyas Husti Indra, Zul Irfansyah Irfansyah Isnaini ' Isti Yuliani Iswadi HR Iwantono Iwan Barnawi Jusman, Yessi K Khairat Kesi Marseliani Khairat, K Khairunnisa, Siska Khairunnissa, Khairunnissa Khusnal Marzuqo Lindrianasari Liza Yarmanita Mardiyah Muhgni Maria Erna Mayangsari Mayangsari Mirza Hardian Mohammad Saeri Muhammad Saeri, Muhammad Mustofa Usman Nabilah Fitriyyah Delfira Nike Syelfina Noor Ell Goldameir Nurhayati, Nurhayati Nurqolbi, Leliyana Ody Azis Saputra Okta Bella Syuhada Putri Sion Cahayana Putri Susanti Rahmad Kurniawan Rahmad Ramadhan Laska Rahwana Saputra Raudatul Yusra Ridho Tri Mulya Riko Febrian Rini, Ari Sulistyo Riski Rahmadani Rosma, Iswadi Hasyim Russel, Edwin Rustam Efendi Rustam Efendi S. Siswanto S. Siswanto Satibi, Syawal Sehatta Saragih Sibuea, Nuraini Sigit Sugiarto Silalahi, Divo Dharma Sillaturahim Sirait, Tesa Theresia Siska Yuliati Soewignjo Agus Nugroho Sukma Novia Syafitri Sukoco Sukoco Sul Kantri Rahma Wanti Sunarno Syamsu Herman Syamsu Herman Syamsudhuha Syamsudhuha T, Masrina Munawarah Tengku Irfan Wira Buana Tira Mei Darnis Titi Solfitri Tuti Alawiyah Wamiliana Windy Lasma Sari Purba Windy Maya Sari Wirda Hia Yenita Roza Yennita Y Zul Indra