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Peramalan Menggunakan Metode Fuzzy Time Series Cheng Sumartini Sumartini; Memi Nor Hayati; Sri Wahyuningsih
EKSPONENSIAL Vol 8 No 1 (2017)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

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Abstract

Forecasting process play an important role in time series data as required for decision-making process. Fuzzy Time Series (FTS) is a concept known as artificial intelligence which use to predict a problem where the actual data was formed in the values ​​of linguistic. This study discusses the FTS method developed by Cheng to forecast the Composite Stock Price Index (CSPI) in October 2016. Within FTS, long intervals determined in beginning process. Based on FTS Cheng method with interval determination using frequency distribution, forecasting stock index based on data from January 2011-September 2016 result forecast for the month of October 2016 was 5.367.98 points. Based on calculation of MAPE, CSPI data from January 2011-September 2016 had an error value as big as 2.56% and has an accuracy of forecasting results amounted to 97.44%. Forecasting use the FTS Cheng has a great performance because it has MAPE value below 10%.
Pemodelan Faktor-Faktor yang Berpengaruh Terhadap Indeks Pembangunan Manusia (IPM) di Kalimantan dengan Geographically Weighted Logistic Regression (GWLR) Lili Widyastuti; Desi Yuniarti; Memi Nor Hayati
EKSPONENSIAL Vol 9 No 1 (2018)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

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Abstract

Human Development Index (HDI) is an indicator to measure the success in building the quality of human life (community/population) and HDI can be used to see the results of the development. The average of Kalimantan HDI in 2016 has low HDI value however there is also high HDI value. Be observed from the score of those HDI, Kalimantan only has two categories those are medium and high. The statistical method used for determining the IPM model is the Geographically Weighted Logistic Regression (GWLR) method. GWLR is a local form of logistic regression in which geographic factors are considered and it is assumed that the data distributed Bernoulli are used to analyzing spatial data. This research was conducted to know the model of HDI and the factors that influence HDI in Kalimantan with GWLR using Adaptive Bisquare Kernel. The results showed that by using Adaptive Bisquare Kernel there are 56 different models for each district/city with the factors that affect the HDI in Kalimantan in 2016 vary by district/city as follows; the percentage of the poor population, the percentage of open unemployment, the percentage of the population graduated from college.
Peramalan dengan Metode Seasonal Autoregressive Integrated Moving Average (SARIMA) di Bidang Ekonomi Verawaty Bettyani Sitorus; Sri Wahyuningsih; Memi Nor Hayati
EKSPONENSIAL Vol 8 No 1 (2017)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

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Abstract

A present event is probably a reiteration from a past event. The reiteration of an event every particular time period indicates seasonal pattern. Seasonal Autoregressive Integrated Moving Average (SARIMA) is one of the methods that is used for data forecasting which has seasonal pattern. The purposes of this research are finding out the best SARIMA model and forecasting the inflation in Indonesia for period January 2016 until December 2016 using the best SARIMA model. Sample of this research is 96 Indonesia inflation data (mtm) for period January 2008 until December 2015. The technique of this research is purposive sampling. There are five steps of SARIMA method, those are model identification, model estimating, diagnostic checking, selecting the best model, and forecasting. Based on the analysis, the best SARIMA model is SARIMA (1,0,0)(0,1,0)12. The forecasting of Indonesia inflation 2016 has similar pattern with the previous time. The inflation increases in January 2016 and decreases in February 2016 until April 2016. The inflation increases again in Mey 2016 until August 2016 and decreases in September 2016 until November 2016. At last, the inflation increases in December 2016.
Penerapan Analisis Joint-Space dan Analisis Faktor dalam Persepsi Mahasiswa FMIPA UNMUL terhadap Penggunaan Aplikasi Messenger pada Smartphone Emi Harmianti; Ika Purnamasari; Memi Nor Hayati
EKSPONENSIAL Vol 7 No 1 (2016)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

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Abstract

Multidimensional Scaling Analysis (MDS) is a technique that can be used to determine the relative views of respondents to an object which is then represented in a multidimensional map. Joint-Space Analysis is a type of MDS that aims to determine the coordinates of the position of each object and variable pictured together on a map perception (perceptual map). While the factor analysis is a branch of multivariate analysis to determine the factors of concern to respondents. This study aims to determine the position of messenger applications on smartphones based on attributes that are owned, as well as to identify factors that concern respondents in choosing the messenger application based on attributes of the messenger application by the respondents are students FMIPA UNMUL. The data used in this research is primary data from research by spreading the questionnaire with the number of respondents (students FMIPA UNMUL) as many as 100 people. Results from this study indicate that the BlackBerry Messenger application, LINE, WhatsApp best position with all superior attributes that exist within the application.While the application KakaoTalk third place with some excellent attributes of the display, application updates, promotions, connection, performance applications, contacts and groups, stickers and emoticons, as well as account settings. Meanwhile, the Yahoo Messenger application and WeChat is the weakest of applications in a variety of attributes that exist in the messenger application. From the results of the factor analysis, found that there are two factors that concern the consumer in choosing a smartphone messenger app that attribute connections and promotion.
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

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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.
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

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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%.
Pengelompokan Puskesmas Berdasarkan Kasus Balita Stunting di Kabupaten Paser Menggunakan Metode K-Medoids Puspita, Ika; Hayati, Memi Nor; Nohe, Darnah Andi
EKSPONENSIAL Vol. 14 No. 1 (2023)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30872/eksponensial.v14i1.1089

Abstract

The number of cases of stunting toddler in Paser Regency increased by 6.66% from 2018 to 2019%. The increased in the number of stunting toddler in Paser Regency shows that the efforts made by the Paser Regency Government have not been effective in reducing the prevalence of stunting toddler because the stunting toddler rate in Paser Regency is still above the threshold set by the World Health Organization (WHO), which is a maximum of 20%. Therefore, an appropriate strategy is needed to find out which areas receive special attention and treatment, one of method to be used is cluster analysis. Cluster analysis is divided into two methods, namely the hierarchical method and the non-hierarchical method. The non-hierarchical method begins by establishing the number of groups. One of the methods included in the non-hierarchical method is K-medoids. In this study, clustering will be carried out in cases of stunting toddlers in Paser Regency using the K-medoids method. This study aims to determine the optimal cluster formed by selecting the smallest Davies Buoldin Index (DBI) value from the 2019 Community Health Center grouping in Paser Regency. The clusters formed for the K-medoids method in this study were 2 clusters, 3 clusters, and 4 clusters. Based on the results of the analysis, the K-medoids method for 2 clusters, 3 clusters and 4 clusters was based on the DBI values ​​of 0.977, 1.470, and 1.670, respectively. The optimal group for classifying stunting toddler cases in Paser Regency in 2019 is 2 cluster using K-medoids method.
Analisis Diagram Kontrol Fuzzy U: Studi Kasus: Kecacatan Produk Kayu Lapis (Plywood) di PT. Segara Timber Mangkujenang, Samarinda Provinsi Kalimantan Timur Tahun 2018 Fauzia, Rina; Yuniarti, Desi; Hayati, Memi Nor
EKSPONENSIAL Vol. 11 No. 1 (2020)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (854.197 KB) | DOI: 10.30872/eksponensial.v11i1.647

Abstract

Fuzzy in general means that an element can be classified into two sets simultaneously. Fuzzy control diagrams are very suitable to be used for observations that produce information (data) that is uncertain, unclear and based on one's subjectivity. This study was applied to data on plywood products in PT. Segara Timber, Samarinda, East Kalimantan Province in 2018. The purpose of this study is to get the results of the decision fuzzy u control diagram. Based on the results of the use of the fuzzy control diagram u produce the most found decisions are rather in control that is equal to 26 observations, while the second most is rather out of control that is equal to 22 observations, and out of control that is equal to 14 and in control of 5 out of 67 observation.
Penerapan Metode K-Means Dalam Pengelompokan Kabupaten/Kota Di Kalimantan Berdasarkan Indikator Pendidikan Messakh, Gerald Claudio; Hayati, Memi Nor; Sifriyani, Sifriyani
EKSPONENSIAL Vol. 14 No. 2 (2023)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30872/eksponensial.v14i2.1103

Abstract

Cluster analysis is an analysis that aims to classify data based on the similarity of spesific characteristics. Based on the structure, cluster analysis is divided into two, namely hierarchical and non-hierarchical methods. One of the non-hierarchical methods used in this study is K-Means. K-Means is a partition-based non-hierarchical data grouping method. This purpose of this study is to obtain the best results of grouping regencies/cities on the island of Kalimantan based on education indicators using the K-Means method based on the smallest ratio of standard deviation. Based on the results of the analysis, it can be concluded that the best grouping results based on the smallest ratio of standard deviation is 0.6052 which produces optimal clusters of 2 clusters with the first cluster consisting of 14 Regencies/Cities while the second cluster consists of 42 Regencies/Cities on Kalimantan Island
Pengklasifikasian Status Gizi Balita di Puskesmas Sempaja Samarinda menggunakan Probabilistic Neural Network (PNN) Tahun 2019 Lestari, Putri Ayu Dwi; Hayati, Memi Nor; Nasution, Yuki Novia
EKSPONENSIAL Vol. 12 No. 2 (2021)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1059.709 KB) | DOI: 10.30872/eksponensial.v12i2.812

Abstract

Probabilistic Neural Network (PNN) is a model in Artificial Neural Networks (ANN) that is used for classification. PNN depends on the smoothing parameter (α). PNN has the advantage of being able to value of problems that previously existed in the back propagation method of ANN. The PNN method in this study was applied to the nutritional status of toddlers. Assessment of the nutritional status of toddlers can be determined through measurements of the human body known as anthropometry. Parameters for determining nutritional status based on anthropometry are age, weight and height. Therefore, in this study, a classification of the nutritional status of children under five is carried out to determine whether the toddler is experiencing good nutrition or poor nutrition. It was found that PNN with the best classification accuracy rate on the nutritional status of toddlers, namely the proportion of training data and testing data of 50%: 50% with α = 1, with accuracy results between training data and training data of 85% and accuracy results between data testing of the training data by 70%.
Co-Authors - Purhadi Abda Abda Alifta Ainurrochmah Amanah Saeroni Anak Agung Gede Sugianthara Andi M. Ade Satriya Anjani Anjani Annabaa Aulia, Muzizah Asnita, Asnita Astuti, Putri Sri Cahyaningsih, Ariyanti Candra Dewi, Ni Luh Ayu Casuarina, Indah Putri Damayanti, Elok Dani, Andrea Tri Rian Darnah Darnah Darnah, Darnah Desi Yuniarti Deviyana Nurmin Dewi, Isma Diani, Milda Alfitri Dini Elizabeth Dwi Husnul Mubiin Edy Fahrin Emi Harmianti Eric Sapto Raharjo Fatma wati Fauzia, Rina Fauziyah, Meirinda Fidia Deny Tisna Amijaya Goenjatoro, Rito Hadisti, Zahrah Dhafina Hadistii, Zahrah Dhafiinia Hidayatullah, Aji Syarif Hisintus Suban Hurint Ibrahim, Rizky Nur Iim Masfian Nur Ika Purnamasari Ika Purnamasari Ika Puspita, Ika Ineu Sintia Julia Julia Julnita Bidangan Karima, Nabila Al Kartika Ramadani Khairun Nida Khasanah, Lisa Dwi Nurul Krisna Rendi Awalludin Lestari, Nur Aini Ayu Lili Widyastuti Lupinda, Indah Cahyani M. Fathurahman Mahmuda, Siti Marsandy, Aldwin Falah Hasan Masrawanti Masrawanti Meiliyani Siringoringo Messakh, Gerald Claudio Mochammad Imron Awalludin Muhammad Jainudin Nabilla, Maghrisa Ayu Nana Nirwana Nanda Arista Rizki Nida, Khairun Ningsih, Eva Lestari Nohe, Darnah Andi Nur - Azizah Nur Annisa Fitri Nur Azizah Nur Fajar Apriyani Nurmalia Purwita Yuriantari Nurmin, Deviyana Nurul Hidayah Oroh, Chiko Zet Paradilla, Yunda Sasha Pratama Yuly Nugraha Pratiwi, Reni Purhadi - Putri Ayu Dwi Lestari, Putri Ayu Dwi Putri, Nurlia Sucianti Rahmah, Putri Aulia Rahmaulidyah, Fatihah Noor Ramadani, Kartika Riska Veronika Rito Goejantoro, Rito Ronald Tediwibawa Safitri, Ranita Nur Sari, Devi Nur Endah Sa’diyah, Lita Vindiyatus Sekar Nur Utami Sembiring, Rinawati Sifriyani, Sifriyani Sinaga, Julia Oriana Siringoringo, Meiliyani Siti Mahmuda Siti Rahmah Binaiya Soraya, Raihana Sri Wahyuningsih Sri Wahyuningsih Sri Wahyuningsih Suerni, Widya - Sumartini Sumartini Surya Prangga Suyitno Suyitno Suyitno Suyitno Suyitno Suyitno Suyitno Suyono, Ari Krisna Syamsiar, Syamsiar Syaripuddin Syaripuddin Tiara Nur Hikmaulida Tiara Nurul Ma’ala Utami, Riska Putri Verawaty Bettyani Sitorus Wahyuni, Nanda Anggun Yuki Novia Nasution, Yuki Novia Yuniarti, Desi