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All Journal JURNAL MATEMATIKA STATISTIKA DAN KOMPUTASI Jurnal Statistika Universitas Muhammadiyah Semarang Informatika Mulawarman: Jurnal Ilmiah Ilmu Komputer BAREKENG: Jurnal Ilmu Matematika dan Terapan Jurnal Kreativitas PKM Jambura Journal of Mathematics Variance : Journal of Statistics and Its Applications Mandalika Mathematics and Educations Journal ESTIMASI: Journal of Statistics and Its Application Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Journal of Mathematics Education and Science Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi VARIANSI: Journal of Statistics and Its Application on Teaching and Research Jurnal Statistika dan Komputasi (STATKOM) Eksponensial

Rito Goejantoro, Rito

Statistics Study Program, Department Of Mathematics, Faculty Of Mathematics And Natural Sciences, Mulawarman University, Samarinda

Author-ID : 2469461

Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Energy Engineering Health Professions Industrial & Manufacturing Engineering Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Physics Public Health Social Sciences Transportation Other

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Klasifikasi Rumah Tangga Miskin Di Kecamatan Kaubun Tahun 2020 Dengan Menggunakan Metode Improved Chi-Square Automatic Interaction Detection Yuliasari, Pratiwi Dwi; Goejantoro, Rito; Amijaya, Fidia Deny Tisna
EKSPONENSIAL Vol. 12 No. 1 (2021)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Classification was grouping samples based on similarities and differences by using categorical variables. The classification method used in this study was the Improved Chi-square Automatic Interaction Detection (I-CHAID) which was an improvement from the CHAID method. This research aims to provide an overview of poor households and classify poor households, and to compare the accuracy of the classification results for each data proportion. The data used is household data in Kaubun District in 2020 with poor and non-poor status. The results of this study indicate that there were 10 households with poor status, and households were classified as poor if the frequency of eating is less than 3 times a day, and the best classification accuracy results use the proportion of training data of 60% and testing data of 40%.

Analisis Regresi Logistik Multinomial Bayes untuk Pemodelan Minat Peserta Didik MAN 2 Samarinda Tahun Ajaran 2018/2019 Cahyani, Era Tri; Goejantoro, Rito; Siringoringo, Meiliyani
EKSPONENSIAL Vol. 13 No. 1 (2022)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Currently, Senior High School and Madrasah Aliyah have implemented student specialization. The specialization includes Natural Science, Social Science and Language. There are several criteria for determining interest in Senior High School and Madrasah Aliyah which include academic scores, student interests and IQ. The multinomial logistic regression model is used to examine these factors because the dependent variable has more than 2 categories. Bayes method is used to estimate the parameters of the multinomial logistic regression. The Bayesian method is a parameter estimation technique that combines the likelihood and prior distribution function. The estimation with the Bayesian method was solved using Markov Chain Monte Carlo simulation (MCMC) with the Gibbs Sampler algorithm. The data used were new students at MAN 2 Samarinda on 2018/2019 with the results of interest namely Natural Science, Social Science and Language. Independent variables were used, namely the score of the Junior High School in subjects Natural Science, Social Science, Language and the rate of National Test. The results of modeling and analysis showed that the factors that significantly influenced were the score of the junior high school in the subject of Natural Science and the rate of National Test. The classification accuracy of the model was 63,10%.

Perbandingan Algoritma C4.5 Dan Naïve Bayes Untuk Prediksi Ketepatan Waktu Studi Mahasiswa: Studi Kasus: Program Studi Statistika Universitas Mulawarman Permana, Jordan Nata; Goejantoro, Rito; Prangga, Surya
EKSPONENSIAL Vol. 13 No. 2 (2022)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Classification is a statistical technique that aims to classify data into classes that already have labels by building a model based on training data. There are many methods that can be used in the classification including Naïve Bayes and C4.5. The C4.5 algorithm is an algorithm used to form a decision tree while Naïve Bayes is a classification based on probability. This study aims to determine the results of the classification of C4.5 and Naïve Bayes and to determine the classification accuracy of the two methods. The variables used in this study were graduation status , entrance , gender , regional origin , GPA , and UKT group . After the analysis, the results showed that the average accuracy level of the C4.5 algorithm was 61.99% and the Naïve Bayes accuracy level was 69.97%. So it can be said that the Naïve Bayes method is a better method in classifying student status compared to the C4.5 . method.

Optimalisasi K-Means Cluster dengan Principal Component Analysis pada Pengelompokan Kabupaten/Kota di Pulau Kalimantan Berdasarkan Indikator Tingkat Pengangguran Terbuka Rais, Muhammad; Goejantoro, Rito; Prangga, Surya
EKSPONENSIAL Vol. 12 No. 2 (2021)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Data mining or often also called knowledge discovery in databases is an activity that includes collecting, using historical data to find regularity, patterns, or relationships in large data sets resulting in useful new information. Cluster analysis is an analysis that aims to group data based on its likeness. This research uses the K-Means method combined with PCA. The K-Means method groups data in the form of one or more clusters that share the same characteristics. While the PCA method was used to reduce research variables. This grouping method was applied to the data indicator of the unemployment rate of districts/cities in Kalimantan Island in 2018. The cluster validation used in this study was the Davies-Bouldin Index (DBI). Based on the results of the analysis, it was concluded that the number of principal components formed was as many as 2 principal components. The most optimal grouping of districts/cities in Kalimantan island in 2018 was to use 2 clusters with a DBI value of 0,507. The grouping of districts/cities in Kalimantan Island in 2018 produced 2 clusters, cluster 1 consisting of 51 districts/cities and clusters of 2 consisting of 5 districts/cities. Cluster 1 was a cluster that has the highest percentage of the poor population and the highest labor force participation rate when compared to cluster 2. While cluster 2 was a cluster that has an index value of human development, population, number of the labor force, number of unemployed, population density, and the minimum wage of district/city was high compared to cluster 1.

Analisis Distribusi Frekuensi dan Periode Ulang Hujan: Studi Kasus: Curah Hujan Kecamatan Long Iram Kabupaten Kutai Barat Tahun 2013-2017 Widyawati, Widyawati; Yuniarti, Desi; Goejantoro, Rito
EKSPONENSIAL Vol. 11 No. 1 (2020)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Increasing water demand for various needs can be a complex problem so it is necessary to manage water resources. Analysis of hydrological data is very necessary to get information about water resources where the information can be used as a benchmark for planning a water resources builder. One of hydrological analysis is the analysis of rainfall data where this analysis uses frequency distribution analysis and rain return periods. There are four types of distribution used, namely normal distribution, normal log distribution, Gumbel distribution and type III log Pearson distribution. The goodness of fit test uses the Kolmogorov-Smirnov method, Chi-Square and Anderson-Darling. Rainfall return calculation is calculated when it is known the type of distribution of the data studied. This research uses rainfall data of Long Iram Sub-Distric, West Kutai Distric in 2013 to 2017 obtained from the Meteorology, Climatology and Geophysics Agency (BMKG) of Samarinda City. The results from research showed that the Gumbel distribution was the right distribution or distribution that was the best with the results of the return period of rain for the return period of 2 years obtained by rainfall of 519 mm, 5-year return period of 796 mm, 10-year return period of 980 mm, return period 20 years of 1.154 mm, a 50 year return period of 1.348 mm and in a 100 year return period of 1.752 mm.

Penaksiran Kandungan Klorida di Sungai Mahakam Wilayah Samarinda Tahun 2017 dengan Metode Cokriging Putra, Eko Prasatyo; Goejantoro, Rito; Suyitno, Suyitno
EKSPONENSIAL Vol. 11 No. 2 (2020)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Cokriging is the interpolation method of value of an unsampled data by minimizing the variance of the estimation error by utilizing cross correlations between the main variable and the additional variable. This study aims to estimate the chloride content in the Mahakam River in Samarinda by using the cokriging method. The data of this study are spatial data that consists of the main variable data is chloride content and additional variable data is the pH of the water, as well as the coordinates of the observation location. Semivariogram (matrix covariance) is determined based on the best model, namely theoretical semivariogram. The best theoretical semivariogram model for cross variables is the exponential model, while the best theoretical semivariogram model for the main variable and additional variables are the spherical model. The selected theoretical semivariogram model was used to determine the semivariogram matrix in estimating chloride content in IPA Bantuas and Teluk Lerong. The results of estimation of chloride content in IPA Bantuas and Teluk Lerong are 1.91 mg/l and 1.64 mg/l. Based on the estimated chloride content in IPA Bantuas and in Teluk Lerong, it shows that the chloride content is still below the maximum threshold and meets the water chloride content standard for consumption by the Ministry of Health of the Republic of Indonesia, which is a maximum of 250 mg/l.

Pengelompokan Provinsi Berdasarkan Indikator Ekonomi, Pendidikan, Kesehatan, dan Kriminalitas di Indonesia Menggunakan Algoritma Centroid Linkage Candra, Yossy; Goejantoro, Rito; Dani, Andrea Tri Rian
Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi EULER: Volume 12 Issue 1 June 2024
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/euler.v12i1.24887

With its rich cultural diversity and abundant natural resource potential, Indonesia still faces various social science problems. Economic inequality, low quality of education, limited access to health, and high crime rates are social problems that hit various provinces in Indonesia. This research was conducted to group provinces in Indonesia based on social indicators, which include economy, education, health, and crime. This research uses cluster analysis with the Centroid Linkage algorithm to group provinces in Indonesia. The Centroid Linkage algorithm was chosen because of its advantages in producing optimal grouping. Test cluster validity using the Silhouette Coefficient (SC). The case studies used are variables that are thought to be related to economic, health, education, and crime problems in 34 provinces in Indonesia in 2021. Based on the analysis, the grouping results using the Centroid Linkage algorithm show that the optimal number of clusters is 2, with an SC value of 0.538. Cluster 1 consists of 33 provinces, and Cluster 2 consists of only one province, DKI Jakarta.

Penerapan Automatic Clustering pada Fuzzy Time series pada Data Wisatawan Mancanegara Kalimantan Timur Juliartha, Made Angga; Purnamasari, Ika; Goejantoro, Rito
EKSPONENSIAL Vol. 15 No. 2 (2024): Jurnal Eksponensial
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30872/eksponensial.v15i2.1326

Tourism played a significant role in national foreign exchange earnings and Regional Original Revenue (PAD), therefore accurate statistical analysis was needed as a preventive measure. Forecasting was one of the accurate statistical analyses that could assist the government in determining more effective policies in the future. The method used was the Automatic Clustering Fuzzy Logical Relationship (ACFLR) for time series data. Automatic Clustering was used to determine the length of data intervals, while the Fuzzy Logical Relationship was used to obtain forecasting results. The research objective was to forecast the number of foreign tourist visits for the next period using data on the number of foreign tourist visits to East Kalimantan from January 2023 to March 2024. The accuracy of the forecast was measured using the Mean Absolute Percentage Error (MAPE). The research findings indicated that the forecast for April 2024 was 261 visits with a MAPE value of 7.72%, indicating a very good level of accuracy. The conclusion of this research showed that the ACFLR method was effective in forecasting the number of foreign tourists, thus it could be used as a decision-making tool by local governments.

Clustering Titik Panas Bumi Pada Potensi Kebakaran Hutan Menggunakan K-Affinity Propagation Primantoro, Sudhan; Goejantoro, Rito; Prangga, Surya
EKSPONENSIAL Vol. 15 No. 2 (2024): Jurnal Eksponensial
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30872/eksponensial.v15i2.1299

K-Affinity Propagation is a development of affinity propagation from Brendan J. Frey and Delbert Dueck. The purpose of this research is to cluster geothermal hotspots on potential forest fires in Indonesia using K-Affinity Propagation for the period July 2022 and obtain optimal cluster results using standard deviation with ratio calculations. The optimal cluster results are 4 clusters, with the number of members in cluster 1 being 12 members with copies in West Sumatera Province, the number of members in cluster 2 being 12 members with copies in Southeast Sulawesi Province, the number of members in cluster 3 being 4 members with copies in Central Sulawesi Province, the number of members in cluster 4 being 1 member with copies in North Sulawesi Province. The optimal cluster results using standard deviation with the smallest ratio value is cluster 4 with a ratio value of 0.057.

Pengelompokan Kabupaten/Kota di Kalimantan Berdasarkan Indikator Pendidikan Menggunakan Metode K-Means dengan Optimasi Principal Component Analysis Putri, Nurlia Sucianti; Hayati, Memi Nor; Goejantoro, Rito
EKSPONENSIAL Vol. 15 No. 2 (2024): Jurnal Eksponensial
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30872/eksponensial.v15i2.1373

Cluster analysis is used to group several objects based on similarities within the group. There are many methods included in cluster analysis, including k-means. K-means is a non-hierarchical cluster analysis method. The assumption that needs to be considered in cluster analysis is that there is no strong correlation between research variables. An alternative that can be done to deal with variables that are strongly correlated is to use Principal Component Analysis (PCA). This research aims to group districts/cities in Kalimantan based on education indicators in 2022 using k-means with PCA optimization, as well as finding out the optimal cluster based on the smallest Davies Bouldin Index (DBI) value. Based on the results of the analysis, from 11 research variables two main components were formed. From these two main components, new data transformations are produced which are then used in grouping districts/cities in Kalimantan based on education indicators using the k-means methods. The analysis results, it was found that the optimal cluster with k-means grouping was 5 clusters with a DBI value of 0.835. Cluster 1 has 8 regencies/cities, cluster 2 has 16 regencies/cities, cluster 6 has 5 regencies/cities, cluster 4 has 21 regencies/cities, and cluster 5 has 5 regencies/cities.

Co-Authors Abidin, Ahmad Aliful Aditiya Risky Tizona Amanah Saeroni Andrea Tri Rian Dani Annabaa Aulia, Muzizah Ardyanti, Hesti Ariessela, Syeli Astuti, Putri Sri Athifaturrofifah Athifaturrofifah Cahyani, Era Tri Cahyono, Budi Cahyono Candra, Yossy Christyadi, Santo Dani, Andrea Tri Rian Darnah Darnah Andi Nohe Darnah, Darnah Desi Yuniarti Deviyana Nurmin Devy Sintya Putri Dewi Wulan Sari Diani, Milda Alfitri Dini Elizabeth Dwi Agoes Setiawan Dwi Husnul Mubiin Dwi Indra Yunistya Dyah Arumatica Novilla Etri Pujiati Fatmi’aturro’isah, Nurul Febriyanti, Nur Afifah Fidia Deny Tisna Amijaya Hairi Septiyanor Hidayatullah, Aji Syarif Ika Purnamasari Ika Purnamasari Ilham Adnan Kasoqi Irene Lishania Irfan Fadil Isgiarahmah, Afryda Juliartha, Made Angga Katianda, Kristin Rulin Khairun Nida Khoiril Anwar Lupinda, Indah Cahyani M. Fathurahman Mahmudi Mahmudi Martua Tri Januar Sinaga Meiliyani Siringoringo Memi Nor Hayati Memi Nor Hayati Memi Nor Hayati Memi Nor Hayati Messakh, Gerald Claudio Mochammad Imron Awalludin Muhammad Rahmad Fadli Muhammad Rais Muhammad Yafi Mulyta Anggraini Murdani, Endah Mulia Ni Wayan Rica A Nida, Khairun Novalia, Viona Nur Annisa Fitri Nur Azizah Nurdayanti Nurdayanti Nurhasanah Nurhasanah Nurmin, Deviyana Nurul Rahmahani Oktri Mayasari Permana, Jordan Nata Primantoro, Sudhan Putra, Eko Prasatyo Putri, Nurlia Sucianti Rachman, Dezty Adhe Chajannah Rahmaulidyah, Fatihah Noor Rinaldi, Rival Satriya, Andi M Ade Sekar Nur Utami Septilasse, Rebeka Norcaline Sifriyani, Sifriyani Siringoringo, Meiliyani Siti Mahmuda Soraya, Raihana Sri Wahyuningsih Sri Wahyuningsih Sri Wahyuningsih Sri Wahyuningsih Suerni, Widya - Surya Prangga Suyitno Suyitno Suyitno Suyitno Syafitri, Febriana Syamsiar, Syamsiar Syaripuddin Syaripuddin Syaripuddin Syaripuddin Wasono Wasono Wasono, Wasono Widyawati Widyawati Yenni Safitri Yudha Muhammad Faishol Yuki Novia Nasution Yuki Novia Nasution, Yuki Novia Yuliasari, Pratiwi Dwi Yuniarti, Desi

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