Article Per Year (5 Year)
p-Index From 2021 - 2026
5.38
P-Index
This Author published in this journals
All Journal Jurnal Matematika dan Statistika serta Aplikasinya (Jurnal MSA) JURNAL PENDIDIKAN TAMBUSAI Pelita Eksakta Suluah Bendang: Jurnal Ilmiah Pengabdian Kepada Masyarakat Rangkiang Mathematics Journal UNP Journal of Statistics and Data Science Mathematical Journal of Modelling and Forecasting Indonesian Journal of Statistics and Its Applications
Dodi Vionanda
Unknown Affiliation
Humanities Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Environmental Science Mathematics Medicine & Pharmacology Physics Social Sciences Other

Published : 43 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 43 Documents
Search

 1   2   3   4   5 
Classification of Poor Households in West Sumatra Province using Decision Tree Algorithm C4.5 Dinda Fitriza; Atus Amadi Putra; Dodi Vionanda; Zilrahmi
UNP Journal of Statistics and Data Science Vol. 2 No. 2 (2024): UNP Journal of Statistics and Data Science
Publisher : Departemen Statistika Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/ujsds/vol2-iss2/157

Abstract

The significant and increasingly complex issue of poverty poses a considerable challenge to Indonesia's development, including West Sumatra Province, with a poverty rate was 5.92% in 2022. The government has initiated programs to address poverty by focusing on the criteria of impoverished households. Data on impoverished households can be obtained through the National Socio-Economic Survey (Susenas). One method that can classify impoverished households is the decision tree. Decision tree is a flowchart that resembles a tree. The C4.5 algorithm used in this research has the ability handle discrete and continuous data, manage variables with missing values, and prune decision tree branches. The result of the analysis shows that the variables affecting the classification of poor households are the number of household members, then the age of the household head, type of house floor, type of house wall, source of drinking water, and cooking fuel. The accuracy of the test data using a confusion matrix is 69.89%, sensitivity of 71.15% for classifying regular households, and specificity of 68.72% for classifying impoverished households.
Impelementation of Subtractive Fuzzy C-Means Method in Clustering Provinces in Indonesia Based on Factors Causing Stunting in Toddlers Hariati Ainun Nisa; Admi Salma; Dodi Vionanda; Tessy Octavia Mukhti
UNP Journal of Statistics and Data Science Vol. 2 No. 2 (2024): UNP Journal of Statistics and Data Science
Publisher : Departemen Statistika Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/ujsds/vol2-iss2/164

Abstract

Indonesia in 2022 has a stunting rate that is still relatively high at 21.6%. For this reason, it is necessary to make various efforts to reduce the stunting rate. One of the efforts that can be made is to understand the characteristics of each province in Indonesia with cluster analysis. This study aims to cluster provinces in Indonesia based on factors that cause stunting in children under five. The method used is Subtractive Fuzzy C-Means which has advantages in terms of speed, iteration, thus producing more stable and accurate results. The results of the validity test with Silhouette Coefficient Index, the optimum number of clusters is 8 clusters with a radius (r) of 0.70. There are 8 provinces that have provided maximum handling and efforts in reducing stunting rates, namely the provinces of Bangka Belitung Islands, Riau Islands, DKI Jakarta, DI Yogyakarta, Bali, East Kalimantan, South Kalimantan, and South Sulawesi. Meanwhile, 7 provinces namely East Nusa Tenggara, South Kalimantan, Central Sulawesi, West Sulawesi, Maluku, North Maluku, and West Papua, still need special attention from the government in reducing stunting rates based on the factors that cause stunting discussed in this study.
K-Modes Analysis with Validation of the DBI in Grouping Provinces in Indonesia based on Indicators of Poor Households Syifa Azahra; Zilrahmi; Dodi Vionanda; Fadhilah Fitri
UNP Journal of Statistics and Data Science Vol. 2 No. 2 (2024): UNP Journal of Statistics and Data Science
Publisher : Departemen Statistika Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/ujsds/vol2-iss2/165

Abstract

Poverty is the most pressing social problem in Indonesia. Efforts to alleviate poverty are to group provinces in Indonesia based on indicators of poor households using the K-modes algorithm. The data used is data from the 2017 Indonesian Demographic and Health Survey (IDHS) on the Household List. The analysis includes data noise detection, data clustering using K-Modes algorithm, and cluster validation with Davies Bouildin Index (DBI). Based on the clustering that has been done, two clusters are obtained, where cluster 1 consists of 26 provinces and cluster 2 consists of 8 provinces. cluster 1 is a cluster that fulfills 9 indicators of poor households and cluster 2 only a few indicators of poor households. So that the government can prioritize these 8 provinces to overcome poverty in Indonesia. For the DBI value obtained is 1.89 which means that 2 clusters are already well used in the algorithm.
Artificial Neural Networks to Forecasting the Retail Price of Beras Solok in Padang City using Backpropagation Algorithm Putri Rivani; Tessy Octavia Mukhti; Dodi Vionanda; Dina Fitria
UNP Journal of Statistics and Data Science Vol. 2 No. 2 (2024): UNP Journal of Statistics and Data Science
Publisher : Departemen Statistika Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/ujsds/vol2-iss2/168

Abstract

Strengthening rice production is an important step as the population continues to grow. Padang City is only able to meet 30% of the community's needs, so to fulfill the community's needs, rice is also imported from Solok. Forecasting can be done especially in order to see the movement of the average retail price of Anak Daro Solok Rice in Padang City which has decreased and increased in rice prices due to the lack of rice availability in Padang City. In this research, the forecasting method that will be used is the Artificial Neural Network Backpropogation Algorithm. Artificial Neural Networks are widely used for forecasting nonlinear time series data. Based on the results of the research that has been done, forecasting the average retail price of Anak Daro Solok Rice in Padang City using the Backpropagation Algorithm Artificial Neural Network obtained the optimal network architecture has the best model, namely BP (1,6,1) which model produces a MAPE of 0.03121%, indicating that the network performance of the model that has been formed shows very good results because it manages to achieve an accuracy rate (MAPE) of less than 10%. Artificial Neural Network Model based on Backpropagation Algorithm can be applied to predict the average retail price of Anak Daro Solok Rice in Padang City. Comparison of the results of forecasting the average retail price of Anak Daro Solok Rice in Padang City for the next 12 months period, namely an increase from the previous 12 months period.
Sentiment Analysis of Twitter User Government Official of Indonesia Vacancy in 2024 Using Naive Bayes Classification Larissa, Dwika; Vionanda, Dodi
Jurnal Pendidikan Tambusai Vol. 9 No. 1 (2025)
Publisher : LPPM Universitas Pahlawan Tuanku Tambusai, Riau, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jptam.v9i1.25497

Abstract

Pengumuman seleksi CPNS merupakan momen penting yang selalu ditunggu-tunggu oleh masyarakat Indonesia setiap tahunnya. Hal ini tidak terlepas dari tingginya animo masyarakat untuk menjadi bagian dari Aparatur Sipil Negara. Penelitian ini menganalisis sentimen masyarakat terhadap pengumuman seleksi CPNS tahun 2024 dengan menggunakan metode klasifikasi Naive Bayes. Data dikumpulkan dari 2001 tweet di Twitter yang berkaitan dengan Lowongan CPNS 2024, dan dilakukan preprocessing sebelum dilakukan analisis sentimen. Hasil penelitian menunjukkan bahwa mayoritas respon masyarakat adalah netral dengan 1788 tweet, sedangkan 94 tweet positif, dan 10 tweet negatif. Ketidakpastian mengenai jumlah formasi, proses seleksi, persyaratan, dan kebijakan lainnya menjadi faktor utama yang membuat sebagian besar masyarakat cenderung netral. Hasil analisis juga menunjukkan bahwa model klasifikasi Naive Bayes memiliki akurasi sebesar 92%, menunjukkan kemampuan yang baik dalam mengkategorikan data sentimen. Penelitian ini memberikan masukan yang berharga bagi pemerintah dan lembaga terkait dalam merancang kebijakan yang lebih transparan dan jelas untuk meningkatkan dukungan masyarakat terhadap pembukaan lowongan CPNS di masa mendatang.
Comparison of the Fuzzy Time Series Chen Model and the Heuristic Model in Forecasting the Number of International Tourists in West Sumatra Rizki Akbar; Fitri, Fadhilah; Vionanda, Dodi; Mukhti, Tessy Octavia
Mathematical Journal of Modelling and Forecasting Vol. 2 No. 1 (2024): June 2024
Publisher : Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/mjmf.v2i1.20

Abstract

The Fuzzy Time Series Chen and Heuristic are two forecasting methods based on fuzzy logic used to predict values in time series. The FTS Chen and Heuristic models have almost identical forecasting processes, but the main difference lies in how they develop fuzzy logical relationships. The FTS Chen model uses Fuzzy Logical Relationship Groups obtained from the results of Fuzzy Logical Relationships for the forecasting process. On the other hand, the FTS Heuristic model uses Fuzzy Logical Relationships directly in the forecasting process. Fuzzy Logical Relationships are a collection of fuzzy logical relationships used to connect values in time series. By using Fuzzy Logical Relationships, the Heuristic model can predict values in time series more accurately and effectively. The forecasting is done to plan the development of tourism infrastructure, determine service needs, and optimize tourism promotion. The data shows that the number of foreign tourists visiting West Sumatra has continued to grow from 2006 to 2023. The comparison of the accuracy of the forecasting results of FTS Chen and Heuristic models for foreign tourists in West Sumatra yielded a MAPE of 0.241% for FTS model Chen and 0.194% for FTS model Heuristic. This indicates that the best forecasting model for foreign tourists is the Heuristic model due to its lower MAPE value.
Nagari Tanjung Balik Menuju Digitalisasi Data Syafriandi, Syafriandi; Amalita, Nonong; Vionanda, Dodi; Fitria, Dina; Zilrahmi, Zilrahmi; Yarman, Yarman
Suluah Bendang: Jurnal Ilmiah Pengabdian Kepada Masyarakat Vol 22, No 3 (2022): Suluah Bendang: Jurnal Ilmiah Pengabdian kepada Masyarakat
Publisher : Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/sb.03280

Abstract

Kegiatan pembangunan hendaknya dilaksanakan dengan menggunakan perencanaan yang tepat. Perencanaan ini memerlukan informasi yang diperoleh dengan adanya data.  Nagari Tanjung Balik Kecamatan X Koto Singkarak merupakan salah satu nagari yang termasuk dalam Kecamatan X Koto Singakarak, Kabupaten Solok. Untuk perencanaan pembangunan, nagari ini memerlukan adanya informasi dan data. Namun, nagari ini tidak memiliki akses ke data sektoral yang terhimpun di BPS. Di sisi lain, nagari ini juga dihadapkan pada keterbatasan sumber daya yang memiliki pengetahuan tentang Statistika. Oleh karena itu, tim pengabdi melaksanakan Kegiatan Pengabdian kepada Masyarakat di Nagari Tanjung Balik untuk membantu mengatasi kedua masalah di atas.  Dari kegiatan pengabdian ini, pemerintah Nagari Tanjung Balik memiliki database yang terbaru, akurat, dan mudah diakses yang bisa digunakan untuk mengetahui informasi yang detail tentang masyarakat nagari ataupun untuk memetakan potensi dan masalah di nagari. Begitu pula, dari kegiatan ini,  pemerintah nagari telah memiliki kader yang bisa melakukan pengumpulan data di waktu yang akan datang dengan menggunakan aplikasi RSN dan mengelola database yang telah dibangun.
Do Prestigious Schools Still Exist in Padang? An Exploratory Study on State Junior High School Admission 2025 in Padang Vionanda, Dodi; Wood, Raihan Attaya; Susrifalah, Amelia
Rangkiang Mathematics Journal Vol. 4 No. 2 (2025): Rangkiang Mathematics Journal
Publisher : Department of Mathematics, Universitas Negeri Padang (UNP)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/rmj.v4i2.106

Abstract

In this study, we perform an exploratory study of New Student Admission datasets for public Junior High School in Padang in 2025. We utilized tables, barplots, and boxplots to present information contained in datasets and we carried out cluster analysis using HDBSCAN algorithm. For this study we made use of admitted students’ datasets for each admission pathway of all state Junior High Schools in Padang in 2025. We carried out this study to investigate the emergence of prestigious schools among public Junior High School in Padang amid the implementation on zoning system. Our study reveals the presence of group of prestigious schools along with group of schools that admitted students mostly live nearby the schools. Hence, it is recommended for Padang Municipal government to improve the quality of schools that are not considered as prestigious schools since there are many schools that admitted students mostly live nearby the school.
Handling Unbalanced Data with SMOTE Algorithm for Unemployment Classification in Lima Puluh Kota Regency Using CART Method Aldwi Riandhoko; Amalita, Nonong; Vionanda, Dodi; Salma, Admi
Indonesian Journal of Statistics and Applications Vol 8 No 2 (2024)
Publisher : Statistics and Data Science Program Study, SSMI, IPB University, in collaboration with the Forum Pendidikan Tinggi Statistika Indonesia (FORSTAT) and the Ikatan Statistisi Indonesia (ISI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/ijsa.v8i2p166-177

Abstract

Unemployment is a problem that occurs in the labor force, where high unemployment is caused by the low ability of the labor force. A region that is still experiencing unemployment problems in West Sumatera is Lima Puluh Kota Regency. Unemployment in Lima Puluh Kota Regency is caused by the low competence of human resources to fulfill employment market requirements. Based on the results of the Sakernas survey in August 2023, Lima Puluh Kota Regency has more employed labor force than unemployed labor force, so this results in unbalanced data. A method that can overcome unbalanced data is Synthetic Minority Oversampling Technique (SMOTE). SMOTE is a technique with addition of synthetic data in minority class so that the proportion is balanced. Data imbalance conditions need to be handled so as to improve the performance of the classification model. Classification and Regression Trees (CART) is a classification technique with a decision tree method that can obtain the characteristics of a classification. The purpose of this research is to compare the CART model before and after applying SMOTE which can be measured by comparing the highest Area Under Curve (AUC) value. The AUC value in the CART method before SMOTE applied has a value of 62.1% while the AUC value in the CART method after SMOTE applied has a value of 70.2%. Therefore, it can be concluded that the CART classification analysis after SMOTE applied is able to provide better performance compared to the CART classification analysis before SMOTE applied.
Implementation of Fuzzy C-Means Algorithm for Clustering Provinces in Indonesia Based on Micro and Small Industry Ratio in Village Areas Rahmanesta, Frandito; Martha, Zamahsary; Vionanda, Dodi; Zilrahmi, Zilrahmi
Indonesian Journal of Statistics and Applications Vol 8 No 2 (2024)
Publisher : Statistics and Data Science Program Study, SSMI, IPB University, in collaboration with the Forum Pendidikan Tinggi Statistika Indonesia (FORSTAT) and the Ikatan Statistisi Indonesia (ISI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/ijsa.v8i2p178-190

Abstract

Post-economic crisis, the micro and small industries contribute the most labor compared to other industries. Regional development sourced from small micro industries is a strategic force in developing a country because the development of small micro industries leads to realizing equitable welfare to reduce income inequality. Development in village areas is an important factor for regional development, reducing inequality between regions, and alleviating poverty. However, based on the 2018 PODES survey, there are regional imbalances in Indonesia in the small micro industry which is centralized on Java Island. Therefore, clustering and characteristics of the province were carried out based on the PODES survey of the small micro industry sector. This research uses the Fuzzy C-Means algorithm to cluster 34 provinces in Indonesia based on the ratio of small micro industries in village areas in 2021, to see how the development of small micro industries in village areas in each province in Indonesia. Fuzzy C-Means is one of the data clustering techniques that uses a fuzzy clustering model, where cluster formation is based on a membership degree value that varies between 0 and 1. The Fuzzy C-Means algorithm generates 4 clusters, cluster 1 and 2 represents provinces with high and very high micro and small industry development in village areas and cluster 3 and 4 represents provinces with medium and low micro and small industry development in village areas. The Fuzzy C-Means algorithm produces a good cluster structure with a silhouette coefficient value of 0,6406.
Co-Authors Afdhal Rezeki Afdhal Alandra, Cindy Resha Aldwi Riandhoko Andini Yulianti Aprilla Suhada Atus Amadi Putra Bahri Annur Sinaga defal aditya defran Dina Fitria Dina Fitria Dina Fitria, Dina Dinda Fitriza Dony Permana Dwi Sulistiowati, Dwi Fadhilah Fitri Fadhillah Fitri Fashihullisan Fayza Annisa Febrianti FAZHIRA ANISHA Febri Ramayanti Findri Wara Putri Fitri, Fadhilah Fitria Panca Ramadhani Hariati Ainun Nisa Ichlas Djuazva Ihsanul Fikri Isra Miraltamirus Jimmi Darma putra Khairisa Putri, Nadya Larissa, Dwika Lifia Zullani Mardhiatul Azmi Muhammad Tibri Syofyan nabillah putri Nazifatul Azizah Nindi Syahfitrri Nonong Amalita Nurul Afifah Permana, Dony Putri Rivani Rahmanesta, Frandito rama novialdi Rizki Akbar Robiati, Silfi Salma, Admi Seif Adil El-Muslih Shavira Asysyifa S Sherly Amora Jofipasi Silvia Agustina Susrifalah, Amelia Syafriandi Syafriandi Syafriandi Syifa Azahra Tessy Octavia Mukhti Tessy Octavia Mukhti Wood, Raihan Attaya Yarman Yarman, Yarman Yenni Kurniawati Yunistika Ilanda Zamahsary Martha Zilrahmi, Zilrahmi