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All Journal BAHASANTODEA Statistika Jurnal Statistika Universitas Muhammadiyah Semarang Jurnal Mechanical BAREKENG: Jurnal Ilmu Matematika dan Terapan SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan IJoASER (International Journal on Advanced Science, Education, and Religion) Jurnal Aplikasi Statistika & Komputasi Statistik Jurnal Ilmiah Maju Jurnal Ilmiah Matematika dan Pendidikan Matematika (JMP) MOTIVECTION : Journal of Mechanical, Electrical and Industrial Engineering Ihtiyath : Jurnal Manajemen Keuangan Syariah Indomera : Jurnal Magister Manajemen Journal of Mathematics Education and Science International Journal of Educational Research and Social Sciences (IJERSC) Jurnal Ilmu Sosial dan Ilmu Politik Malikussaleh (JSPM) Proceeding International Seminar of Islamic Studies Al-Mizan: Jurnal Hukum Islam dan Ekonomi Syariah Jurnal Al-Qiyam Jurnal Tana Mana Seminar Nasional Pengabdian Kepada Masyarakat Jurnal Ekonomi dan Pembangunan Journal of Research Applications in Community Services International Journal of Science and Environment Jurnal Statistika dan Komputasi (STATKOM) Basis : Jurnal Ilmiah Matematika Sora Journal of Mathematics Education Eksponensial JMT (Jurnal Matematika dan Terapan) Jurnal Penelitian Multidisiplin Bangsa Ekonomika : Jurnal Ekonomi dan Pembangunan Singkite Journal Indonesian Journal of Islamic Jurisprudence, Economic and Legal Theory

Syaripuddin Syaripuddin

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Author-ID : 399502

Religion Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Physics Public Health Social Sciences Transportation Other

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Analisis Cluster Single Linkage Berdasarkan Potensi Desa Di Kabupaten Kutai KartanegaraTahun 2019 Suyanto, Suyanto; Syaripuddin, Syaripuddin; Wasono, Wasono
EKSPONENSIAL Vol. 12 No. 1 (2021)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Data mining is a step in the process of Knowledge Discovery in Database (KDD) which consists of the application of data analysis and the discovery of algorithms that produce certain enumerations of patterns in the data,Cluster Analysis is one of the methods in multivariate statistical analysis that is used to group objects into groups based on their characteristics, so the objects in one group have more homogeneous characteristics compared to objects in other groups. Single Linkage is a clustering process based on the closest distance between objects. If two objects are separated by a short distance, then the two objects will merge into one cluster. This study aims to obtain a cluster of village potential in Kutai Kartanegara Regency in 2019, based on the variable availability of educational facilities, the availability of health facilities, the availability of health workers, the availability of coin / card public telephones, the existence of lodging, the existence of market buildings, the existence of supermarkets, the existence of banks, the population obtaining credit facilities, the existence of other Non KUD cooperatives., Based on the results of the analysis, it can be seen that, Clusters formed in the grouping of potential villages / villages in Kutai Kartanegara Regency using a single linkage method are as many as 2 clusters.

Penyelesaian Masalah Pemrograman Kuadratik Menggunakan Metode Beale Erlina, Erlina; Syaripuddin, Syaripuddin; Amijaya, Fidia Deny Tisna
EKSPONENSIAL Vol. 13 No. 1 (2022)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30872/eksponensial.v13i1.889

Quadratic programming is a special form of nonlinear programming which has the general form of the objective function in the form of a quadratic functions and the constraints in the form of linear functions. One of the methods used to solve the quadratic programming model is Beale’s method. This method is a modification of the simplex method for linear programming problems. This study aims to determine the optmal results of paddy production data in Balikpapan city using Beale’s method. The quadratic programming model was formed using the least squares method with the objective functions by selecting two types of plants,namely lowland paddy and upland paddy. Furthermore, the quadratic programming model formed that is formed is solved using Beale’s method. The data used is data on the paddy production of balikpapan city in 2005-2019. Based on the calculatios, the objective function is with the constraint functions and . After calculating using Beale’s method, the optimal result for the maximum yield of lowland paddy and upland paddy is quintals with a harvested area of hectares of lowland paddy and a harvested paddy of hectares of upland paddy.

Penerapan Metode Klasifikasi Multinomial Naive Bayes: (Studi Kasus: PT Prudential Life Samarinda Tahun 2019) Rinaldi, Rival; Goejantoro, Rito; Syaripuddin, Syaripuddin
EKSPONENSIAL Vol. 12 No. 2 (2021)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Life insurance is a risk management service provide payment to policyholders in the event of a disaster that has been stipulated in the agreement. A classification system needs to be done to facilitate the company in making decisions to provide policies to customers. One system that can be used is multinomial Naive Bayes. Multinomial Naive Bayes is a simple probabilistic classification that has more than two groups or categories. An algorithm using Bayes theorem assumes all independent variables. The aim of this study is to obtain an accuracy level of 5 different proportions with the Naive Bayes multinomial method used in insurance customer payment status data. The data used is the customer data of PT. Prudential Life Samarinda in 2019 with the status of current premium payment, substandard and non-current and using 5 independent variables, namely income, age, amount of premium payment, sex and employment. The results of the measurement of classification accuracy using APER status premium payment on insurance customer data of PT. Prudential Life 2019 Naive Bayes multinomial method showed 22,96% misclassification at 50:50 proportion, at the proportion of 60:40 there were 21,43% misclassification, at the proportion of 70:30 there were 19,05% misclassified, at proportions 80:20 had a misclassification of 14,29%, and a proportion of 90:10 has a misclassification of 7,14%.

Pengelompokan Kabupaten/Kota Di Pulau Kalimantan Dengan Fuzzy C-Means Berdasarkan Indikator Kemiskinan Ningtyas, Retno Ayu; Nasution, Yuki Novia; Syaripuddin, Syaripuddin
EKSPONENSIAL Vol. 13 No. 2 (2022)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Cluster analysis is a branch of statistical science that is used to grouping data that have similar characteristics between each other. The grouping method used in this research is Fuzzy C-Means. Fuzzy C-Means method is one of the grouping methods developed from the C-Means method by applying the properties of fuzzy sets. With the existence of each data is determined by the degree of membership. This method is applied to data from 56 districts/cities on Borneo based on poverty indicators with variables namely the percentage of average length of schooling, life expectancy, percentage of the poor, percentage of open unemployment rate, percentage of households with proper sanitation, and percentage of households with proper drinking water. This study aims to obtain the results of grouping districts/cities on Borneo based on poverty indicators and to obtain optimal cluster results based on three validity indices, namely Connectivity, Dunn, and Silhoutte values. Based on the results of the study, it was found that there were 2 optimal clusters, namely the first cluster consisted of 36 regencies/cities while the second cluster consisted of 20 regencies/cities.

Pengelompokan Data Kategorik Dengan Algoritma Robust Clustering Using Links: Studi Kasus: PT. Prudential Life Jalan MT. Haryono Samarinda Dewi, Isma; Syaripuddin, Syaripuddin; Hayati, Memi Nor
EKSPONENSIAL Vol. 11 No. 2 (2020)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Cluster analysis is a technique of data mining that is used to group data based on the similarity of attributes of data objects. The problem that is often encountered in cluster analysis is the data on a categorical scale. Categorical scale data grouping can be done using the ROCK (RObust Clustering using linKs) algorithm. The ROCK algorithm is included in the of agglomerative hierarchical clustering algorithms in cluster analysis. This algorithm introduces a concept called neighbors and links in grouping data. Categorical data grouping with ROCK algorithm is done in three steps. The first step is counting similarities. The second step is determining the neighbors and the last is calculating the links between the observation objects. The value of the link is affected by θ. The optimum number of clusters in the ROCK algorithm is selected using a minimum ratio value of . The purpose of this study is to group 100 data of insurance customers of PT. Prudential Life Samarinda in 2018. Based on the analysis results, obtained that the optimum group is at θ = 0.1 with a ratio value of is 0.1371. The optimum number of groups formed is 2 clusters. The first group consisted of 42 customers and the second group consisted of 58 customers.

Analisis Cluster Pada Produk Mie Instan Berdasarkan Komposisi Yang Terkandung Dengan Menggunakan Metode Ward Sam, Faza Syahrudin; Syaripuddin, Syaripuddin; Wasono, Wasono
EKSPONENSIAL Vol. 12 No. 1 (2021)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Cluster analysis is a grouping of data (objects) based on only the information found in the data that describes the object and the relationships between data. The variance method commonly used is the Ward method where the average for each cluster is calculated. At each stage, the two clusters that have the smallest increase in sum of squares in the cluster are combined.. Some compositions of ingredients in noodles, for example, fat, protein, carbohydrates, food fiber, sugar and sodium. The composition of the noodles that are dangerous one of which is Monosodium Glutamate (MSG). The purpose of this research is to find out how many clusters are formed based on the composition of the content of instant noodle products. Based on the results of cluster research formed based on the composition of the contents of 43 instant noodle samples are 9 clusters where the first cluster consists of 2 members, the second cluster consists of 7 members, the third cluster consists of 5 members, the fourth cluster consists of 7 members, the fifth cluster consists of 6 members, the sixth cluster consists of 4 members, the seventh cluster consists of 4 members, the cluster the eighth consists of 1 member and the ninth cluster consists of 7 members.

Mengatasi Multikoliniearitas Dalam Regresi Linier Berganda Menggunakan Principal Component Analysis Chairunnisa, Niken Harel; Darnah, Darnah; Syaripuddin, Syaripuddin
EKSPONENSIAL Vol. 16 No. 1 (2025): Jurnal Eksponensial
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30872/eksponensial.v16i1.1155

Multiple linear regression analysis has assumptions that must be met, one of which is multicollinearity. Multicollinearity occurs when the independent variables correlate with each other, resulting in the regression coefficient produced by multiple linear regression analysis being very weak or unable to provide analysis results that represent the nature or influence of the independent variable concerned. The detection of multicollinearity can be known through the VIF value. In this study, human development index data on Kalimantan Island in 2019 detected multicollinearity because some independent variables have a VIF value of more than 10 so that the method used to overcome multicollinearity in this study is Principal Component Analysis (PCA). Based on the results of research using the Principal Component Regression method, There are five independent variables that influence the IPM that is Percentage of Poor Population, Number of Health Workers, Number of Workforce, Number of High Schools, and Number of High School Teachers.

Co-Authors A'yun, Qonita Qurrota Abdi Wijaya, Abdi Abdul Haris Abidah, Abidah Adawiyah, Rabbiatul Adhitya Ronnie Effendie, Adhitya Ronnie Akhmad Syahroni Ali Murtadho Emzaed Alima, Isna Aminah, Esse Andi Wawan Mulyawan, Andi Wawan Anggraini, Dewi Susi Ansori, Fuad Arifin Arifin Aryo Hartanto Aribowo Asmaidi Asmaidi Auliya Rahman A’yun, Qonita Qurrota Cahyadi, Aldy Fradana Mahaputra Chairunnisa, Niken Harel Dala, Maria Alensia Deltin Dani, Andrea Tri Rian Darnah, Darnah Desy Arum Sunarta Dewi, Isma Dimas Raditya Elvita, Melati Erlina Erlina Fachry Abda El Rahman Fahrezi, Korompot Naufal Fakhrurazi, Fakhrurazi Farha, Izzaty Fatmawati, Fatmawati Fauzi, Andri Azmul Ferry Budhi Susetyo Ferry Budhi Susetyo Fidia Deny Tisna Amijaya Gunardi Gunardi Gusti Ketut Alit Suputra Hardina Sandariria Hasbi, Muhammad Yunan Ika Purnamasari indarsih, Indarsih Khaeriyah, Hamzah Khoirunnisa, Kori Lubi, Ahmad Manggiri, Itsar Mashuri, Arif Memi Nor Hayati Moh. Nurul Huda, Moh. Nurul Mohammad WIJAYA Muhammad Jamil Barambangi Muhammad Wiharto Mulyadi, Taqriri Kamal Munawarah Munawarah, Munawarah Munfaati, Rafika Husnia Mushalifah, Mushalifah Mustika, Anggi Winda Nana Nirwana Nanda Arista Rizki Ningtyas, Retno Ayu Nofendri, Yos Oktavia, Vira Permatasari, Welly Dona Pridiptama, Raka Putra Purnamasari Putra, Fachrian Bimantoro Putri, Annisa Amalia Putri, Desi Febriani Rahma Wati Rahmat, Mustiwal Ramadhan, Rizal Furqan Ramadhanty, Husna Novia Raming, Indriasri Rinaldi, Rival Rito Goejantoro, Rito Saderisa, Saderisa Sahputra, Dimas Raditya Said Said, Said Saifannur, Saifannur Sam, Faza Syahrudin Saputri, Nola Febriana Sifriyani, Sifriyani Simahatie, Mai Sitti Harisah Solikhatun, Solikhatun Sopiyan, Sopiyan Sri Wahyuni Sri Wigantono Suciati, Rara SUHERI, EDI Sulaiman Hamzani Sumantri Mangkuwinata, Denny Suyanto Suyanto Syamsuir, Syamsuir Tengku Riza Zarzani N Tulzahrah, Shanaz Tumilaar, Rinancy Uha Isnaini Wahyujati, Mohamad Fahruli Wasono, Wasono Wulandari Wulandari Yuki Novia Nasution, Yuki Novia Yumna, Munadya Yusak, Monica Yeyen Zainuddin Iba

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