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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 ESTIMASI: Journal of Statistics and Its Application Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika 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
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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Peramalan Dengan Menggunakan Metode Double Exponential Smoothing Dari Brown Etri Pujiati; Desi Yuniarti; Rito Goejantoro
EKSPONENSIAL Vol 7 No 1 (2016)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (223.992 KB)

Abstract

Consumer Price Index (CPI) is one of the economic indicator that givethe information about the price of goods andservices which paid by consumer. CPI in Samarinda City increases so long which the pattern of the data is indicating a trend pattern. Time series forecasting designed to handle the trend of data which used a double exponential smoothing method. The purpose of this study is to determine the using of the parameters α and the forecasting amount of CPI in Samarinda City for three months that use double exponential smoothing method. The best parameter α which use to forecast CPI in Samarinda City is (0,61). To forecast CPI in Samarinda City is using double exponential smoothing method obtained F72+m=119,83+1,62 m. The forecasting result of CPI in Samarinda City from January to March 2015 are 121,44, 123,06, and 124,68.
Optimasi Fuzzy C-Means Menggunakan Particle Swarm Optimization Untuk Pengelompokan Kabupaten/Kota Di Pulau Kalimantan (Studi Kasus: Data Indikator Kesejahteraan Rakyat Tahun 2020) Deviyana Nurmin; Memi Nor Hayati; Rito Goejantoro
EKSPONENSIAL Vol 14 No 1 (2023): Jurnal Eksponensial
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (948.946 KB) | DOI: 10.30872/eksponensial.v14i1.1002

Abstract

Clustering is a method of grouping data into several clusters or groups so that data in one cluster has a high level of similarity and data between clusters has a low level of similarity. The clustering method used in this research is Fuzzy C-Means (FCM). FCM is a data grouping technique in which the existence of each data point in a cluster is determined by the degree of membership. To optimize the grouping results, it is necessary to validate the number of clusters using Partition Coefficient (PC). The purpose of this study is to obtain optimal grouping results from the FCM method using the PC validity indices from the people's welfare indicator data in 56 regencies/cities on the island of Kalimantan in 2020. Based on the results of the analysis, the conclusion is that the optimal number of clusters is three clusters. The first cluster consists of 24 regencies/cities on the island of Kalimantan, the second cluster consists of 17 regencies/cities on the island of Kalimantan, and the third cluster consists of 15 regencies/cities on the island of Kalimantan.
Penerapan Statistika Nonparametrik dengan Metode Brown-Mood pada Regresi Linier Berganda Ni Wayan Rica A; Darnah Andi Nohe; Rito Goejantoro
EKSPONENSIAL Vol 7 No 1 (2016)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

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Abstract

Brown-Mood is a method first developed by GW brown 1950 and AM mood in 1951 with the purpose of the parameters of the multiple linear regression model of the linear regression model of the equation of the median small sample size. This study discusse the application of the method of brown-mood on multiple linear regression with the open unemployment rate (X1), and growth rate of gross regional domestic product at constant prices (X2) to the number of poor population (Y) Province of east Kalimantan. If the method ordinary least square in a multiple linear regression is a statistical parametric aims to minimize the average (mean) error, the brown-mood methods as a nonparametric statistical method chose a multiple linear regression model by minimising the median and average weighted. The results of this research to get a linear regression model using the method of brown-mood is Ŷ=-31.11+1.74 X1 + 1.44 X2 from the multiple linear regression model obtained are percentage distribution of gross regional domestic product at current prices [without oil, gas and its products] and growth rate of gross regional domestic product at constant prices affect to the number of poor population.
Penerapan Metode If-Then dari Rough Set Theory dalam Menangani Kecelakaan Lalu Lintas di Kota Samarinda Tahun 2016 Martua Tri Januar Sinaga; Rito Goejantoro; Fidia Deny Tisna Amijaya
EKSPONENSIAL Vol 8 No 2 (2017)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

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Abstract

Traffic accidents have caused many victims and lost materials, so itbecomes one of casesneed special attention every year. Therefore, it required a serious treatment to avoid the incidence of traffic accidents, so it can reduce the number of victimsbe inflicted. The aim ofthis study to determine the greatest factor/conditioncausing the fatality rate of traffic accidents and to determine the rules of decision rules from data that has been collected. The data used was secondary data taken from the report of traffic accidents recapitulation at Laka Lantas Unit, Satlantas Samarinda City. The analytical methods used to analyze the data are descriptive statistics analysis and Rough Set Theory. Based on the result, it can be seen the largest frequency of the victim who died is in traffic accidents that occur in sunny conditions. Moreover it is obtained 53 decision rules from the fatalities of victims by the traffic accidents in Samarinda City. The most powerful rule is "if a male student involved in a traffic accide nt at residential area and the road condition feasible passed by vehicles then the victim is likely to get serious injuries" with weight of 0.80.
Perbandingan Peta Pengendali Rata-rata Bergerak Dengan Peta Pengendali Rata-rata Bergerak Geometrik Nurdayanti Nurdayanti; Darnah Andi Nohe; Rito Goejantoro
EKSPONENSIAL Vol 7 No 2 (2016)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

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Abstract

The Moving Average Control Chart is a control chart of data observation for small average shift process. The Geometric Moving Average Control Chart is a control chart of specific weight, making it more effective in detecting the smallest change in process. The purpose of this study is to determine whether the wood width which produced by Suryadi Moulding are controlled by Moving Average and Geometric Moving Average Control Chart, and between the two control chart the research want to know which is the best chart.Based on the results of research in the wood width data obtained that the Moving Average and Geometric Moving Average Control Chart there are no points on the outside of the control limits so that it can be concluded that the wood width which produced by Suryadi Moulding Samarinda on the under controlled conditions. If viewed from the width limit controller chart because of the wide limit on the Geometric Moving Average Control Chart is better than the Moving Average Control Chart because the wide limit on the Geometric Moving Average Control Chart is narrower so the result of this control chart is more accurate.
Pemodelan Geographically Weighted Regression (Gwr) Dengan Fungsi Pembobot Adaptive Kernel Bisquare Untuk Angka Kesakitan Demam Berdarah di Kalimantan Timur Tahun 2015 Aditiya Risky Tizona; Rito Goejantoro; Wasono Wasono
EKSPONENSIAL Vol 8 No 1 (2017)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

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Abstract

Dengue Fever in East Borneo is thought to be a spatial problem that affected by geographic factor and linear regression analysis that is often can not describe with Good Relations pattern. The solution for this problem can be solved using Geographic Weighted Regression Method (GWR) to review and Troubleshooting geographic factor. This research Model proposed to consider GWR model with geography factor or location as the weight to estimate the model parameters, the weight type that used for this research is Adaptive Bisquare. Based on the analysis, this research revealed different model to every observations and different indicators. The eight locations are Paser, Kutai Kartanegara, West Kutai, East Kutai, Berau, Balikpapan, Samarinda dan Bontang. Those locations have variable that affected the morbidity number of dengue fever equally specifically house, elementary school facilities and public place that do not meet the requirements of health, and also waste transported while for the observation location of Penajam Paser Utara has the affected variable of dengue fever morbidity number equally which are house, waste transported, elementary school facilities and public place that do not meet the requirements of health, and also the citizen that do not have the healthy and hygienic lifestyle pattern.
Literasi Dasar Melalui Numerasi dan Keuangan Rito Goejantoro; Ika Purnamasari; Memi Nor Hayati; Meiliyani Siringoringo; Darnah Andi Nohe; Muhammad Fathurahman; Surya Prangga; Khairun Nida; Sekar Nur Utami; Dini Elizabeth
Jurnal Kreativitas Pengabdian Kepada Masyarakat (PKM) Vol 6, No 12 (2023): Volume 6 No 12 2023
Publisher : Universitas Malahayati Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33024/jkpm.v6i12.12705

Abstract

ABSTRAK Gerakan Literasi Nasional (GLN) merupakan kegiatan yang saat ini diserukan sebagai bentuk penerapan dari peraturan KEMENDIKBUD untuk menumbuhkan budi pekerti masyarakat. Numerasi dan literasi keuangan merupakan dua jenis literasi yang saling terkait. Salah satu dimensi dari literasi keuangan yaitu keterampilan menghitung. Keterampilan ini terkait pemahaman numerik, lambang bilangan dan analisa kuantitatif yang berkenaan dengan statistika dasar dalam dimensi numerasi. Kegiatan ini memiliki tujuan yaitu memberikan informasi dan pengetahuan numerasi dan keuangan kepada peserta dengan cara sederhana, menyenangkan, dan mudah dipahami berdasarkan tema lingkungan sekitar. Hasil penilaian sebelum dan sesudah kegiatan, menunjukkan bahwa adanya peningkatan kemampuan dan pemahaman peserta terkait numerasi dan keuangan, yang terlihat dari kenaikan nilai rata-rata pada saat evaluasi. Untuk kegiatan literasi selanjutnya, materi yang disampaikan dapat ditingkatkan ke jenjang materi lanjutan, serta dapat mengkombinasikan antara numerasi, literasi keuangan, dan digital untuk lebih menarik. Kata Kunci: GLN, KEMENDIKBUD, Literasi, Numerasi, Literasi Keuangan ABSTRACT The National Literacy Movement (GLN) is an activity that is currently called for as a form of application of the regulation of KEMENDIKBUD to foster community ethics. Numeracy and financial literacy are two types of literacy that are interrelated. One dimension of financial literacy is counting skills. This skill is related to numerical understanding, number symbols and quantitative analysis related to basic statistics in the numeracy dimension. This activity has the following objectives is to provide numeracy and financial information and knowledge to participants in a simple, fun, and easy-to-understand way based on the theme of the surrounding environment. The results of the assessment before and after the activity showed an increase in the abilities of participants and understanding related to numeracy and finance, which can be seen through the increase in the average scores at the time of evaluation. For further literacy activities, the material delivered can be upgraded to an advanced level of material, and can combine numeracy, financial literacy, and digital to be more attractive. Keywords: GLN, KEMENDIKBUD, Literacy, Numerasi, Financial Literacy.
PENGELOMPOKAN DESA ATAU KELURAHAN DI KUTAI KARTANEGARA MENGGUNAKAN ALGORITMA DIVISIVE ANALYSIS Ilham Adnan Kasoqi; Memi Nor Hayati; Rito Goejantoro
Jurnal Statistika Universitas Muhammadiyah Semarang Vol 9, No 2 (2021): Jurnal Statistika Universitas Muhammadiyah Semarang
Publisher : Department Statistics, Faculty Mathematics and Natural Science, UNIMUS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/jsunimus.9.2.2021.101-108

Abstract

Potential Villages (PODES) provide data on the existence, availability and development of the potential of each government administrative area. In order to make it easier for governments to make policies for a region, it is necessary to group the village and sub-districts. Cluster analysis is an analysis that aims to group objects based on the information that found in the data. One of the cluster analysis methods is the divisive analysis, which is a hierarchical grouping method with a top-down approach, where all objects are placed in one cluster and then sequentially divided into separate groups. This research aim to group villages or sub-districts in Kutai Kartanegara based on the determinants of village backwardness and obtaining the silhouette coefficient value from the optimal cluster analysis using the divisive analysis algorithm. The data used is the 2018 PODES data in Kutai Kartanegara and used 15 variables from natural and environmental factors, facilities infrastructure and access factors as well as socio-economic factors of the population. The results of the optimal cluster formed in the grouping of villages or sub-districts in Kutai Kartanegara using the divisive analysis method are 2 clusters. Cluster 1 consisting of 230 villages or sub-districts and cluster 2 consisting of 2 sub-districts. Silhouette coefficient value for data validation from clustering village or sub-districts in Kutai Kartanegara using the divisive analysis method produces 2 clusters is 0,744 which states that the cluster structure formed in this grouping is a strong structure.
K-MEDOIDS ALGORITHM CLUSTERING WITH PRINCIPAL COMPONENT ANALYSIS (PCA) (CASE STUDY: DISTRICTS/CITIES ON THE BORNEO ISLAND BASED ON POVERTY INDICATORS IN 2021) Muhammad Yafi; Rito Goejantoro; Andrea Tri Rian Dani
Jurnal Statistika Universitas Muhammadiyah Semarang Vol 11, No 2 (2023): Jurnal Statistika Universitas Muhammadiyah Semarang
Publisher : Department Statistics, Faculty Mathematics and Natural Science, UNIMUS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/jsunimus.11.2.2023.31-43

Abstract

Cluster analysis is a technique in data mining that aims to group data (object) based on the information in the data. This research is used a non-hierarchical grouping named K-Medoids algorithm to group districts/cities in Borneo island based on poverty indicators and Principal Component Analysis (PCA) method to reduce research variable. This research is also do a cluster validity test to see how many cluster there are has the best grouping result using Silhouette Coefficient (SC) method. Based on the results of the analysis there is 3 optimal Principal Component (PC) were obtained with eigen value criteria of greater than or equal to 1. Furthermore, districts/cities on Borneo island were grouped based on the PC that formed and obtained 2 optimal clusters with an SC value of 0.61. The K-Medoids algorithm obtain 2 cluster, cluster 1 consisting of 49 districts/cities and cluster 2 consisting of 7 cities.
PERBANDINGAN AKURASI KLASIFIKASI MENGGUNAKAN ALGORITMA QUEST PADA PADA SKENARIO DATA KODIFIKASI DAN NON-KODIFIKASI Surya Prangga; Rito Goejantoro; Memi Nor Hayati; Siti Mahmuda; Dwi Husnul Mubiin
Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Vol. 5 No. 1 (2024): Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistik
Publisher : LPPM Universitas Bina Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46306/lb.v5i1.525

Abstract

Traffic accidents are difficult to predict in terms of when and where will occur. The number of traffic accident cases in Indonesia is relatively high. Regarding on data from the Central Statistics Agency (Badan Pusat Statistik) from 2020 until 2021, the average number of traffic accidents reaches one hundred thousand cases every year. Especially, in the Samarinda City, which is the capital of East Kalimantan Province, it ranked the highest in 2020 compared to several other regencies and cities within East Kalimantan Province. Considering these facts, traffic accident cases need to be addressed to minimize accident-related casualties. One data mining technique used to analyze traffic accident patterns is the decision tree-based classification method. One of the decision tree-based classification methods is QUEST algorithm. The QUEST algorithm (Quick, Unbiased, Efficient, and Statistical Tree) can be used to classify the status of traffic accident victims. Based on data analysis, the best accuracy to classify the status of traffic accident victims was obtained using second scenario data with 80:20 data split, with an accuracy of 66,10% and an F1-Score of 62,96%.
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 Candra, Yossy Christyadi, Santo Dani, Andrea Tri Rian Darnah Darnah Andi Nohe Darnah, Darnah Desi Yuniarti Deviyana Nurmin Devy Sintya Putri Dewi Wulan Sari 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 Gerald Claudio Messakh 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 Mochammad Imron Awalludin Muhammad Rahmad Fadli Muhammad Rais Muhammad Yafi Mulyta Anggraini Murdani, Endah Mulia Ni Wayan Rica A 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 Sri Wahyuningsih Suerni, Widya - Surya Prangga Suyitno Suyitno Suyitno Suyitno Syafitri, Febriana 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