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Penentuan Cadangan Premi Asuransi Jiwa Dengan Metode Fackler Faturachman, Faturachman; Suyitno, Suyitno; Rizki, Nanda Arista
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.v13i1.876

Abstract

Insurance is an agreement between two parties, where one party is obliged to pay and the other party has the obligation to provide compensation to the premium payer if something happens to the party in accordance with the agreement that has been made. The main problem faced by insurance companies is that the fees paid through premiums are not sufficient to finance compensation payments at the beginning of the policys, To overcome the shortage of costs the insurance company must have a reserve fund called a premium reserve. The purpose of this study was to determine the reserve for term, endowment and whole life insurance premiums using the Fackler method. The variables used in this study are the customer's age, gender, payment term, interest rate and the sum insured. In this study, premium reserves were calculated for participants aged 30 years, men and women, with a payment term of 30 years, an interest rate of 6.75%, and an insurance value of Rp. 100,000,000. Based on the calculation results, the reserve value of term life insurance premium for customers with 30 years of age and the insurance period of 30 years increases at the beginning of the year to the 21st year, after which it decreases until the reserve at the end of the 30th year, the value of the lifetime insurance premium reserve. life for customers with 30 years of age always increases from the beginning of the year to the last year where the payment for male customers is Rp. 93,176,962 and women in the amount of Rp. 93,296,217,156250. The reserve value of dual-purpose life insurance premiums for customers with 30 years of age and insurance period of 30 years always increases from the beginning of the year to the end of the year of payment of Rp. 100,000,000. The large difference in premium reserves for men and women is due to the higher chance of life for women than men.
Model Geographically Weighted Univariat Weibull Regression pada Data Indikator Pencemaran Air Dissolve Oxygen di Daerah Aliran Sungai Mahakam Kalimantan Timur Tahun 2018 Sugiarto, Sugiarto; Suyitno, Suyitno; Rizki, Nanda Arista
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 (1241.218 KB) | DOI: 10.30872/eksponensial.v12i2.813

Abstract

Geographically Weighted Univariat Weibull Regression (GWUWR) model is a regression model applied to spatial data. Parameter estimation of GWUWR model is performed at every observation location using spatial weighting. The purpose of this study is to determine the GWUWR model at the water pollution indicator data namely dissolved oxygen (DO) at Mahakam river in East Kalimantan and to find out the factors that influence DO in Mahakam river. The research data are secondary from the environmental services East Borneo. The research response variable was DO, meanwhile the predictor variables were pH, Total Dissolve Solid, Total Suspended Solid, Nitrate and Amonia. Parameter estimation method is Maximum Likelihood Estimation (MLE). Spatial weighting was determined using the Adaptive Gaussian weighting function and optimum bandwidth determination criteria used Generalized Cross-Validation (GCV). Based on the result of the parameter testing of GWUWR model it was concluded the factors influencing DO locally were pH, Total Dissolve Solid and ammonia concentrations, while the factors influencing globally were Total Dissolve Solid and ammonia concentration
Metode Hierarchical Density-Based Spatial Clustering of Application with Noise (HDBSCAN) Pada Wilayah Desa/Kelurahan Tertinggal di Kabupaten Kutai Kartanegara: (Studi Kasus : Data Hasil Pendataan Potensi Desa (PODES) Tahun 2018) Wahyuni, Nanda Anggun; Hayati, Memi Nor; Rizki, Nanda Arista
EKSPONENSIAL Vol. 12 No. 1 (2021)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (778.141 KB) | DOI: 10.30872/eksponensial.v12i1.758

Abstract

The underdeveloped areas are generally the districts which are relatively underdeveloped compared to other regions on a national scale. Determination of underdeveloped villages is often done in order to determine the distribution of government assistance so that assistance can be distributed appropriately. The identification is based on facilities, infrastructure, access, social, population and economy provided in the Village Potential data (PODES). The concept of grouping based on regional or spatial is done to find out certain characteristics in an area. HDBSCAN is a grouping concept with a parameter called Mpts. The purpose of this study is to know the number of clusters formed in the grouping of underdeveloped villages / urban areas in Kutai Kartanegara Regency using the HDBSCAN method. The Mpts parameters that is used in this study is from 2 to 6. Based on the results of the analysis, the clusters formed in the grouping of underdeveloped villages / urban areas in Kutai Kartanegara Regency using the HDBSCAN method, were 3 clusters. Cluster 0 consists of 19 villages / urban areas , cluster 1 consists of 4 villages / urban areas and cluster 2 consists of 61 villages / urban areas. Based on the analysis, villages / urban areas included in cluster 1 could be the main target of the government in providing assistance and development of regional facilities / infrastructure.
Pengelompokkan Data Runtun Waktu menggunakan Analisis Cluster: Studi Kasus: Nilai Ekspor Komoditi Migas dan Nonmigas Provinsi Kalimantan Timur Periode Januari 2000-Desember 2016 Dani, Andrea Tri Rian; Wahyuningsih, Sri; Rizki, Nanda Arista
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 (673.538 KB) | DOI: 10.30872/eksponensial.v11i1.642

Abstract

The export value of East Kalimantan Province has big data conditions with time series and multivariable data types. Cluster analysis can be applied to time series data, where there are different procedures and grouping algorithms compared to grouping cross section data. Algorithms and procedures in the cluster formation process are done differently, because time series data is a series of observational data that occur based on a time index in sequence with a fixed time interval. The purpose of this research is to obtain the best similarity measurement using the cophenetic correlation coefficient and get the optimal c-value using the silhouete coefficient. In this study, the grouping algorithm used is a single linkage with four measurements of similarity, namely the Pearson correlation distance, euclidean, dynamic time warping and autocorrelation based distance. The sample in this study is the data on the export value of oil and non-oil commodities in East Kalimantan Province from January 2000 to December 2016 consisting of 10 variables. Based on the results of the analysis, the distance of the best similarity measurement in clustering the export value of oil and non-oil commodities in East Kalimantan Province is the dynamic time warping distance with the optimal c-value of 3 clusters.
Kemampuan kognitif Siswa kelas homogen saat mengerjakan soal TIMSS materi bilangan Aras, Silvia; Rusdiana, Rusdiana; Rizki, Nanda Arista
Primatika : Jurnal Pendidikan Matematika Vol. 13 No. 1 (2024)
Publisher : Program Studi Pendidikan Matematika, Fakultas Keguruan dan Ilmu Pendidikan, Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30872/primatika.v13i1.3732

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Matematika merupakan mata pelajaran yang memiliki peran penting dalam kehidupan sehari hari sehingga perlu untuk diajarkan sedari kecil. Penilaian kemampuan matematika dapat dilakukan dengan berbagai cara, salah satunya adalah dengan menggunakan Trend in Intenational Mathematic Science Study (TIMSS). Penelitian ini bertujuan untuk mengetahui kemampuan kognitif matematika Siswa kelas homogen di SMP Negeri 3 Tanjung Redeb saat mengerjakan soal TIMSS materi bilangan. Penelitian ini menggunakan metode penelitian kuantitatif deskriptif. Populasi dalam penelitian ini adalah Siswa kelas VIII homogen di SMP Negeri 3 Tanjung Redeb, sedangkan sampel penelitian menggunakan teknik cluster random sampling. Teknik pengumpulan data yang digunakan adalah tes tertulis berupa 20 soal TIMSS uraian. Teknik analisis data yang digunakan adalah statistic deskriptif kuantitatif. Hasil penelitian ini menunjukkan bahwa kemampuan Siswa menjawab benar yaitu untuk kognitif pengetahuan dengan persentase 58%, kognitif penerapan dengan persentase 43% dan kognitif penalaran dengan persentase 20%. Berdasarkan hasil data tes tertulis dapat disimpulkan bahwa untuk kemampuan Siswa dominan tinggi pada kognitif pengetahuan sedangkan kemampuan Siswa dominan rendah pada kognitif penalaran.
Implementasi Algoritma K-Means Untuk Mengelompokkan Mahasiswa Program Studi Pendidikan Matematika Berdasarkan Sumber Belajarnya Rizki, Nanda Arista; Kurniawan, Kurniawan; Hasan, Isran K.; Sampe, Nofia
METIK JURNAL Vol 7 No 2 (2023): METIK Jurnal
Publisher : LPPM Universitas Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47002/metik.v7i2.584

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Students must be able to utilize learning resources properly to improve academic achievement. Students can be grouped based on the learning resources they use frequently. Grouping results are helpful for lecturers in designing, evaluating, and analyzing learning in the classroom. This research aimed to implement the K-Means algorithm to classify student learning resources and determine which learning resources determine which groups. The population of this research were students of the Mathematics Education study program at Mulawarman University who are still taking courses. At the same time, the sample were active students from classes 2019, 2020, 2021, and 2022 of the Mathematics Education Study Program at Universitas Mulawarman who were still taking courses and were willing to fill out the questionnaire, namely as many as 111 Students. The data analysis used was clustering analysis using the K-Means algorithm with the Elbow method. New dummy data was formed from learning resource data because it was multiple choice. Based on the results, three main groups were obtained according to the use of learning resources. The learning resources that determine the distribution of groups were electronic books and journals. The first group used electronic books and journals, while the third group did not use either. While the second group only used electronic books. The Silhouette value for this cluster model was 0.615. The classification was classified as good.
LINEAR ALGEBRA APPLICATIONS TO DETECT THE EXISTENCE OF PLAGIARISM AND IN SEARCH ENGINE METHODOLOGY Nainggolan, Sahat Pandapotan; Solikhin, Mukhammad; Anwar, Andi Muhammad; Rizki, Nanda Arista
Jurnal Kajian Matematika dan Aplikasinya (JKMA) Vol 4, No 1 (2023): JANUARY
Publisher : UNIVERSITAS NEGERI MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17977/um055v4i12023p1-5

Abstract

The theory of algebra is highly beneficial and used in daily life. Identifying plagiarism is one of many activities that can be solved with the concept of linear algebra. Even today, plagiarism is still a crucial issue to discuss, preferably in academic scope, both in assignment papers and academic theses. Identifying plagiarism aims to provide a document as a vector. Even the basic concept of linear algebra can be applied in plagiarism detection applications. This paper proposed a modeling example of plagiarism checking on a document with a matrix representation and the calculation of angles among subspaces of each compared document. Finally, the results can be used as one of the considerations to determine the similarity index.Keywords: plagiarism, linear algebra, vector, matrix representation
REGRESI LOGISTIK BINER UNTUK MENGKLASIFIKASIKAN CARA BELAJAR MAHASISWA MENURUT SUMBER BELAJARNYA Rizki, Nanda Arista; Mumtaza, Mutiara; Dewi, Carolina Fadia; Syahlafandi, Dhira
Scientific Timeline Vol. 4 No. 1 (2024)
Publisher : UNU Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Penelitian ini bertujuan untuk membuat model regresi logistik biner yang dapat mengklasifikasikan cara belajar Mahasiswa berdasarkan sumber belajarnya. Data diambil dari 111 Mahasiswa program studi pendidikan matematika Universitas Mulawarman. Sumber belajar yang menjadi variabel prediktor merupakan pilihan ganda majemuk. Hasil penelitian menunjukkan bahwa Mahasiswa yang menjadikan YouTube sebagai sumber belajarnya berpeluang untuk belajar secara mandiri sebesar 2,232 kali lebih besar dari pada belajar matematika berkelompok. Sementara Mahasiswa yang menjadikan buku cetak sebagai sumber belajarnya berpeluang untuk belajar secara kelompok sebesar 1,968 kali lebih besar dari pada belajar matematika mandiri. Nilai skor F1 tertinggi terletak pada pembagian data 90:10 yaitu sebesar 0,643. Skor AUC untuk model regresi logistik biner yang digunakan adalah sebesar 0,611.
Pengaruh kecerdasan emosional dan aktivitas belajar terhadap hasil belajar matematika siswa kelas VII SMP Barung, Thesalonica Graina; Rizki, Nanda Arista; Asyril, Asyril; Fendiyanto, Petrus
Primatika : Jurnal Pendidikan Matematika Vol. 13 No. 2 (2024)
Publisher : Program Studi Pendidikan Matematika, Fakultas Keguruan dan Ilmu Pendidikan, Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30872/primatika.v13i2.4525

Abstract

Tujuan dari dilakukannya penelitian ini yaitu dalam rangka mengidentifikasi pengaruh yang diberikan kecerdasan emosional dan aktivitas belajar pada hasil belajar matematika siswa kelas VII di SMPN 7 Samarinda. Penelitian yang berjenis ex post facto menggunakan sejumlah 149 siswa dari 6 kelas sebagai sampelnya yang ditentukan melalui cluster random sebagai teknik samplingnya. Analisis data penelitian dilakukan secara statistik deskriptif dan statistik inferensial dengan regresi linear berganda berdasarkan taraf signifikan (α) sebesar 0.05. Adapun hasil analisis deskriptif yaitu, nilai rata-rata atas hasil penelitian kecerdasan emosional senilai 54.10, dari aktivitas belajar senilai 57.22, dan dari hasil belajar matematika siswa adalah senilai 58.50. Ketiga variabel berada dalam kategori cukup. Hasil analisis statistik inferensial, didapatkan persamaan regresi dugaan, yakni Y̅=-3.788+0.606X1+0.151X2. Didapati adanya pengaruh yang diberikan oleh kecerdasan emosional pada hasil belajar matematika dan ada pengaruh yang diberikan aktvitas belajar pada hasil belajar matematika. Koefisien determinasi (R2) sebesar 0.152. Sehingga disimpulkan bahwa ditemukan sebesar 15.2% pengaruh yang diberikan kecerdasan emosional dan aktivitas belajar pada hasil belajar matematika siswa kelas VII di SMPN 7 Samarinda.
Penerapan Pohon Keputusan untuk Memetakan Gaya Kognitif Berdasarkan Kesalahan Siswa dalam Berpikir Aljabar Menurut Teori Newman Mumtaza, Mutiara; Rizki, Nanda Arista
Jurnal Pendidikan Matematika : Judika Education Vol 7 No 2 (2024): Jurnal Pendidikan Matematika:Judika Education
Publisher : Institut Penelitian Matematika, Komputer, Keperawatan, Pendidikan dan Ekonomi (IPM2KPE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31539/judika.v7i2.12903

Abstract

An understanding of Field Independent (FI) and Field Dependent (FD) cognitive styles is important for teachers because these two styles affect the way students understand and process information, which ultimately has an impact on the effectiveness of learning. This study aimed to build a decision tree model to map the cognitive style of students based on errors that students make in solving algebra problems according to Newman's error theory. The method used in this study was a quantitative approach with the ID3 algorithm in decision tree modeling. The instruments used include the GEFT test to identify students' cognitive style and the basic algebra ability test containing 6 aspects of algebra ability according to Lew, i.e. generalization, abstraction, analytical thinking, dynamic thinking, modeling, and organization. The decision tree model was built based on the errors made by students according to Newman's error theory. The results showed that the decision tree generated from algebra problems in the generalization aspect had an accuracy of 82.5%. This decision tree has a main attribute in the form of process skill errors, which can map the cognitive style of students as FI or FD. This decision tree formed three implication rules, which became the basis for classifying the cognitive style of students. This finding was expected to be a guide for teachers in designing a more adaptive and efficient learning strategy with an approach that is on the cognitive style of students to improve students' algebraic thinking ability. Keywords: Cognitive Style, Algebraic Thinking Ability, Decision Tree, Newman's Error Theory