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All Journal Jurnal Gaussian Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal BPPK : Badan Pendidikan dan Pelatihan Keuangan Jurnal Kreativitas PKM Sulolipu: Media Komunikasi Sivitas Akademika dan Masyarakat Jurnal Informatika dan Rekayasa Elektronik Unri Conference Series: Community Engagement Jurnal Ketenagakerjaan Parameter: Journal of Statistics Journal of Community Engagement Research for Sustainability Jurnal Ilmiah Pengabdian Masyarakat Bidang Kesehatan Sulolipu: Media Komunikasi Sivitas Akademika dan Masyarakat Journal of Mathematics, Computation and Statistics (JMATHCOS)
Gustriza Erda
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Humanities Computer Science & IT Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Electrical & Electronics Engineering Energy Environmental Science Health Professions Immunology & microbiology Law, Crime, Criminology & Criminal Justice Mathematics Medicine & Pharmacology Nursing Public Health Social Sciences Other

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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.
Classifiying The Factors Influencing The Human Development Index in Riau Province using Principal Component Analysis Erda, Gustriza; Mega Aulia, Sartika; Erda, Zulya
Parameter: Journal of Statistics Vol. 2 No. 3 (2022)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22487/27765660.2022.v2.i3.16203

Abstract

The Human Development Index is a critical indicator of economic growth. Several factors, including average length of schooling (X1), expected length of schooling (X2), life expectancy at birth (X3), number of health workers (X4), number of health facilities (X5), spending per capita (X6), open unemployment rate (X7), number of poor people (X8), percentage of households with proper drinking water sources (X9), and GRDP growth rate (X10), can influence the Human Development Index. The purpose of this research was to simplify the factors that influence the human development index in Riau Province in 2021. Data analysis used R-Studio software by applying descriptive statistical analysis, Principal Component analysis, and Biplot analysis. The analysis revealed that the ten variables that influence human development index in Riau in 2021 can be divided into three categories: community service quality, health facilities, access, and economic conditions. These three factors can describe up to 80% of the diversity of the data.
GROUPING OF POVERTY IN INDONESIA USING K-MEANS WITH SILHOUETTE COEFFICIENT Erda, Gustriza; Gunawan , Chairani; Erda, Zulya
Parameter: Journal of Statistics Vol. 3 No. 1 (2023)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22487/27765660.2023.v3.i1.16435

Abstract

Poverty is an enormous problem in numerous nations including Indonesia. Poverty can be measured using several indicators, including the unemployment rate, the percentage of poor people, expenditures per capita, and the poverty line. The purpose of this study is to categorize Indonesian provinces based on poverty indicators in 2021 using K-Means with the Silhouette Coefficient approach. Based on the silhouette coefficient approach, there are two clusters that are created. The first cluster is a high-poverty-rate regional group that includes the provinces of Aceh, Bengkulu, West Nusa Tenggara, East Nusa Tenggara, Central Sulawesi, Gorontalo, Maluku, West Papua, and Papua. On the other hand, the second cluster is an association of regions with a low poverty rate, and it includes 25 provinces. The greater number of provinces in the low poverty rate cluster implies that the poverty rate in Indonesia in 2021 is included in the low category
IMPLEMENTATION OF THE K-MEDOIDS METHOD IN CLUSTERING HUMAN DEVELOPMENT INDEXES IN INDONESIA Erda, Gustriza; Usdika, Radhiatul Khaira; Pitri, Rizka; Erda, Zulya
Parameter: Journal of Statistics Vol. 3 No. 2 (2023)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22487/27765660.2023.v3.i2.16906

Abstract

The Human Development Index (HDI), which takes into account three fundamental aspects of human existence, a long and healthy life, knowledge, and a reasonable level of living, is one tool used to assess the effectiveness of human progress. Clustering provinces based on the human development index is important so that development disparities can be identified and help identify provinces with high, medium or low levels of development. The purpose of this study was to use the k-medoids approach to perform a cluster analysis of HDI in Indonesia based on life expectancy, average years of schooling, expected years of schooling, and expenditure per capita adjusted for 2022. The analysis indicate that two clusters were created: cluster 1 had a high human development index, while cluster 2 had a low human development index. More provinces belonged to cluster 1 than cluster 2 suggesting that human development index in Indonesia in 2022 was largely in the high category
APPLICATION OF THE LIGHTGBM ALGORITHM IN THE CLASSIFICATION OF GREENHOUSE GAS EMISSIONS Rini Latifah; Gustriza Erda
Parameter: Journal of Statistics Vol. 4 No. 1 (2024)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22487/27765660.2024.v4.i1.17055

Abstract

Ada banyak dampak negatif yang dapat ditimbulkan oleh peningkatan emisi gas rumah kaca. Oleh karena itu, penting untuk mengetahui tingkat emisi gas rumah kaca di masa depan dengan membuat prediksi sehingga kita dapat merencanakan kebijakan untuk memitigasi dampaknya. Pada penelitian ini, klasifikasi tingkat emisi gas rumah kaca dilakukan dengan menggunakan metode lightGBM. Tujuannya untuk melihat kinerja metode light GBM dalam melakukan klasifikasi emisi rumah kaca. Hasil yang diperoleh dari penelitian ini adalah akurasi sebesar 96,26%, sensitivitas sebesar 97,62%, spesifisitas sebesar 93,97%, dan MAE sebesar 0,0374.
Forecasting International Tourist Arrivals to Indonesia Using LSTM: Post-Pandemic Analysis for 2024-2025 Ayu Sofia; Dien, Zulfanita; Erda, Gustriza
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.v8i2.7309

Abstract

As Indonesia's main foreign exchange contributor, the tourism sector experienced significant dynamics after the COVID-19 pandemic, characterized by a sharp decline in the number of foreign tourists during the pandemic and consistent recovery in the post-pandemic period. This study aims to predict the number of foreign tourists to Indonesia from September 2024 to August 2025 using the Long Short-Term Memory (LSTM) method. The LSTM model is optimized with an 80:20 data split for training testing and uses optimal parameters, namely Learning Rate 0.005, Batch Size 64, Optimizer Adam, and Epoch 200. The prediction results show an increase in the number of tourists to a peak of 1,390,564 in November 2024, followed by a gradual decline to 987,970 in August 2025, with an accuracy level indicated by a MAPE value of 14.39%
Counseling on Early Stunting Prevention Efforts with Riau University KKN Students in Munsalo Kopah Village Erda, Gustriza; Siregar, Nurainun; Ramadhani, Fitri; Efendi, MHD; Mistika, Lensi; Ferdinan, Tri Agus; Jannah, Miftahul; Anisa, Rahmatul; Putri, Nelsa; Mariza; Al Baihaqi, Habib
Jurnal Ilmiah Pengabdian Masyarakat Bidang Kesehatan (Abdigermas) Vol. 1 No. 3 (2023): Jurnal Ilmiah Pengabdian Masyarakat Bidang Kesehatan (Abdigermas)
Publisher : CV Media Inti Teknologi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58723/abdigermas.v1i3.91

Abstract

Stunting is a condition of chronic malnutrition that can cause children to experience health problems such as susceptibility to disease and a decrease in productivity levels. Factors that can cause stunting include insufficient food sources, parenting, and economic conditions. This work program aims to increase public knowledge about stunting in children from an early age. As well as educating parents about foods that can prevent stunting in children. Socialization is carried out in the form of delivering material related to counseling on what stunting is, its characteristics, the impact of stunting, and prevention of stunting. The low knowledge of mothers about stunting in Munsaloh Village encouraged Riau University KKN students to invite the community to participate in counseling efforts to prevent stunting from an early age. Understanding about stunting counseling efforts is expected to help the community increase knowledge about fulfilling balanced nutrition, exclusive breastfeeding, and complementary foods (MPASI) as a form of prevention against stunting.
Pengembangan Desa Cinta Statistik Sebagai Upaya Percepatan Penguatan Statistik Sektoral di Desa Selatbaru SITI SUHAILA; Anne Mudya Yolanda; Rustam Efendi; Sukamto; Musraini M; Syamsudhuha; Gustriza Erda; Yenita Roza; Gumanti; M. SYIFA RAMADHAN; Althoff Hibban; Dimas Abyan Fatkhin Al-Aswad; Fandi Gusriyanda; Sarasmita Apriyenti; Adia Syaputri; Nusantri Purba; Nurhaliza; Okta Bella Syuhada
Journal of Community Engagement Research for Sustainability Vol. 4 No. 1 (2024): Januari
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31258/cers.4.1.32-44

Abstract

The Desa Cinta Statistik (Cantik) program aims to improve the quality of statistical data produced by increasing literacy, awareness and the active role of village officials and the village statistical community. This program is also a form of the Statistics Study Program's participation in the implementation of community service and is a collaboration between the Statistics Study Program (lecturers and students of Real Work Lectures) with BPS and Villages. The activities carried out in the form of assisting village officials in improving sectoral data and village-specific data are expected to suffice the availability of data for village development as one of the efforts to make One Data Indonesia successful. This program will be implemented in Selat Baru Village, Bengkalis Regency. Based on the data that has been collected, there are several work programs carried out by the Selatbaru Integrated Community Service Program (Cinta Statistik) Selatbaru Team in 2022. Village officials as non-productive partners have improved their sectoral data management capabilities. The outputs of the activity are the publication of Selatbaru Village statistics, Selatbaru Village Profiles and Statistics, Infographics, Monographs, and Videographics.
Optimalkan Layanan Posyandu Siklus Hidup melalui Pemberdayaan Kader dengan Edukasi Kesehatan Cegah Anemia pada Remaja Tampubolon, Nurhannifah Rizky; Erda, Gustriza; Yolanda, Anne Mudya; Finda, Ingla; Tata, Tata
Jurnal Kreativitas Pengabdian Kepada Masyarakat (PKM) Vol 7, No 11 (2024): Volume 7 No 11 (2024)
Publisher : Universitas Malahayati Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33024/jkpm.v7i11.17574

Abstract

ABSTRAK Remaja merupakan kelompok usia yang rentan mengalami anemia karena memiliki gaya hidup sedentary dan pola konsumsi yang tidak sehat. Walaupun upaya pencegahan anemia telah dilakukan melalui pemberian tablet tambah darah di sekolah, peran posyandu perlu dioptimalkan untuk mencegah kejadian anemia pada remaja. Kegiatan pengabdian ini adalah untuk meningkatkan pengetahuan tentang pencegahan anemia pada remaja dan mengoptimalkan layanan posyandu siklus hidup. Pengabdian kepada masyarakat dilakukan melalui kegiatan edukasi pada kader kesehatan dan ibu yang memiliki remaja yang berjumlah 20 orang. Terjadi peningkatan pengetahuan dari hasil pre test dengan tingkat pengetahuan cukup (60%), menjadi baik (80%). Layanan posyandu siklus hidup dapat dioptimalkan melalui edukasi kesehatan pada kader. Kader yang telah mengikuti kegiatan diharapkan dapat menyebarkan informasi pencegahan anemia pada remaja untuk keluarga-keluarga yang memiliki anak remaja. Kata Kunci: Anemia, Posyandu Siklus Hidup, Remaja  ABSTRACT Adolescents are an age group that is vulnerable to anemia because they have a sedentary lifestyle and unhealthy consumption patterns. Although efforts to prevent anemia have been made by providing blood supplement tablets at schools, the role of posyandu needs to be optimized to prevent the incidence of anemia in adolescents. This service activity is to increase knowledge about preventing anemia in adolescents and optimizing life cycle posyandu services. Community service is carried out through educational activities for health cadres and mothers who have 20 teenagers. There was an increase in knowledge from the pre-test results from a sufficient level of knowledge (60%), to good (80%). The life cycle of posyandu services can be optimized through health education for cadres. Cadres who have taken part in the activity are expected to be able to disseminate information on preventing anemia in teenagers to families with teenage children. Keywords: Anemia, Life Cycle Posyandu, Teenagers
PERBANDINGAN KINERJA MACHINE LEARNING DALAM KLASIFIKASI MINAT MBKM MAHASISWA UNRI Erda, Gustriza; Siti Farika Sari; Syaftiani Dwi Astuti; Thearas, Lia; Yolanda, Anne Mudya
Jurnal Informatika dan Rekayasa Elektronik Vol. 8 No. 2 (2025): JIRE November 2025
Publisher : LPPM STMIK Lombok

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36595/jire.v8i2.1217

Abstract

Program Merdeka Belajar Kampus Merdeka (MBKM) merupakan program yang bertujuan meningkatkan potensi dan keterampilan mahasiswa untuk menghadapi tantangan dunia kerja. Namun, minat mahasiswa Universitas Riau (UNRI) dalam mengikuti program ini masih rendah sehingga perlu penelitian lebih lanjut untuk meningkatkan minat mahasiswa UNRI dalam mengikuti MBKM. Penelitian ini bertujuan membandingkan kinerja bebrapa algoritma machine learning seperti Random Forest, Logistic Regression, Decision Tree, dan Gradient Boost Machine (GBM), serta mengidentifikasi faktor penting yang memengaruhi minat mahasiswa UNRI terhadap MBKM. Data dikumpulkan melalui kuisioner yang disebarkan kepada 396 mahasiswa aktif S1-UNRI angkatan 2019-2023 yang dipilih menggunakan teknik stratified random sampling. Dengan 12 variabel independen yang digunakan, diperoleh bahwa model GBM memiliki kinerja terbaik dengan akurasi uji 91,25% dan recall 98,63%, mengungguli model lainnya. Faktor yang paling berpengaruh terhadap minat mahasiswa adalah keyakinan diri dan dukungan keluarga. Temuan ini menunjukkan bahwa faktor-faktor tersebut dapat menjadi fokus dalam evaluasi dan pengembangan program MBKM di masa depan.
Co-Authors Adia Syaputri Al Baihaqi, Habib Althoff Hibban Anisa, Rahmatul Anne Mudya Yolanda Arisman Adnan Ayu Sofia Dien, Zulfanita Dimas Abyan Fatkhin Al-Aswad Efendi, MHD Erie Sadewo Fandi Gusriyanda Ferdinan, Tri Agus Finda, Ingla Fitri Ramadhani Goldameir, Noor Ell Gumanti Gunawan , Chairani Indra, Zul Kholilah Samosir Kurnia Ramadani Lafina, Melanie Maria M. SYIFA RAMADHAN Mariza Mega Aulia, Sartika Miftahul Jannah Mistika, Lensi Musraini M Nurhaliza Nurhannifah Rizky Tampubolon Nusantri Purba Okta Bella Syuhada Pitri, Rizka Putri, Nelsa Rahmi, Afrilia Ramadani, Kurnia Rezzy Eko Caraka Rini Latifah Riris Putri Kinanti Rustam Efendi Safitri, Nuraini Sarasmita Apriyenti Simbolon, Veronika Amelia Sirait, Tesa Theresia Siregar, Nurainun Siti Farika Sari SITI SUHAILA Sukamto Syaftiani Dwi Astuti Syamsudhuha Syamsudhuha Syamsudhuha T, Masrina Munawarah T, Nurhannifah Rizky Tata, Tata Tatik Widiharih Thearas, Lia Titi Solfitri Usdika, Radhiatul Khaira Wawan Sugiyarto Yenita Roza Yuciana Wilandari Zahra, Lathifah Zulya Erda