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All Journal HAYATI Journal of Biosciences Jurnal Pengolahan Hasil Perikanan Indonesia FORUM STATISTIKA DAN KOMPUTASI Media Statistika JURNAL KIMIA SAINS DAN APLIKASI Jurnal Manajemen Teknologi CAUCHY: Jurnal Matematika Murni dan Aplikasi Jurnal Ilmu Komputer dan Agri-Informatika The Journal of Pure and Applied Chemistry Research JUITA : Jurnal Informatika Jurnal Aplikasi Bisnis dan Manajemen (JABM) E-Journal Knowledge Engineering and Data Science Jurnal Matematika Sains dan Teknologi Syntax Literate: Jurnal Ilmiah Indonesia Indonesian Journal of Artificial Intelligence and Data Mining BAREKENG: Jurnal Ilmu Matematika dan Terapan Indonesian Journal of Chemistry JTAM (Jurnal Teori dan Aplikasi Matematika) Limits: Journal of Mathematics and Its Applications Martabat: Jurnal Perempuan dan Anak MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Zero : Jurnal Sains, Matematika, dan Terapan Jurnal Ilmiah Ecosystem Jambura Journal of Mathematics Jurnal Samudra Ekonomi dan Bisnis Al-Khwarizmi: Jurnal Pendidikan Matematika dan Ilmu Pengetahuan Alam Inferensi InPrime: Indonesian Journal Of Pure And Applied Mathematics Jurnal Statistika dan Aplikasinya Xplore: Journal of Statistics Molekul: Jurnal Ilmiah Kimia Indonesian Journal of Jamu Indonesian Journal of Statistics and Its Applications Journal on Mathematics Education Limits: Journal of Mathematics and Its Applications

Utami Dyah Syafitri

Department Of Statistics, Faculty Of Mathematics And Natural Sciences, IPB University, Jl. Meranti Kampus IPB Dramaga, Bogor 16680, Indonesia

Author-ID : 398549

Agriculture, Biological Sciences & Forestry Humanities 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 Earth & Planetary Sciences Economics, Econometrics & Finance Education Energy Engineering Environmental Science Health Professions Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Physics Social Sciences Transportation Other

Published : 67 Documents Claim Missing Document

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Identifikasi Cepat Segmentasi Konsumen Susu Cair dalam Kemasan Fadhila Hijryani; Bagus Sartono; Utami Dyah Syafitri
Xplore: Journal of Statistics Vol. 7 No. 3 (2018): 31 Desember 2018
Publisher : Department of Statistics, IPB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/xplore.v7i3.128

Consumer segmentation is the process of grouping customers into some segments based on some shared similar characteristics. Consumer segmentation allows companies to understand the customer's characteristics in each segment, thus make them easier to establish suitable marketing strategies for each segment's characteristics.Companies tend to use marketing strategies with demographical and consumer behavioural based scheme of consumer segmentation therefore make them easier to identify customer as the characteristics are easily measured. This research uses k-means method for segmenting 419 customers of packaged liquid milk. The life style pattern of the customers are used as the basis of the segmentation. Furthermore, this research uses decision tree algorithm to classify characteristics of the new customer. According to Hartigan index alteration (26.2433), ideal number of segments is 4. After tree pruning step, classification modelling with CART method yielded 54.61% accuracy.

Penerapan SMOTE dalam Pemodelan CHAID pada Data Keberhasilan Mahasiswa PPKU IPB Ririn Fara Afriani; Mohammad Masjkur; Utami Dyah Syafitri
Xplore: Journal of Statistics Vol. 8 No. 1 (2019): 30 April 2019
Publisher : Department of Statistics, IPB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/xplore.v8i1.154

Bogor Agricultural University (IPB) as the third rank of Indonesian non polytechnic universities in 2017 requires new students to join the General Competency Education Program (PPKU) for two semesters to improve the quality of human resources. Student achievement success can be determine from the student's academic status, where the student's academic status is divided into two, which are Drop Out (DO) and not DO. Only 1% of PPKU students who are drop out.. This means there is a data imbalance. One of the method used to handled that is Synthetic Minority Oversampling Technique (SMOTE) method. Classification analysis used is the Chi-Square Automatic Interaction Detection (CHAID) method to identify the factors that influence the success of PPKU students. The application of SMOTE to the 2016/2017 PPKU student data was able to improve the ability of classiï¬cation trees with the average values â€‹â€‹of accuracy, sensitivity, and specificity to 0.718, 0.575, and 0.72. The factors that influence the success of IPB's PPKU students are the entry point, gender, and regional origin.

Evaluasi Produk Multivitamin Baru Berdasarkan Penilaian Responden Noer Endah Islami; Utami Dyah Syafitri; Cici Suhaeni
Xplore: Journal of Statistics Vol. 10 No. 2 (2021)
Publisher : Department of Statistics, IPB

In order to lead in the market, companies should have an innovation product. Before the innovation product lauch to the market, the marketing research should be done. The goal of the reasearch is to determine whether the new product is accepted or rejected in the market. This study was to identify the characteristics of the new product based on organoleptic point of view and performance the three type of new multivitamin products based on location and social economic classes (SEC) of respondents. MANOVA and biplot analysis were used in this research. Based on MANOVA, there were differences on the organoleptic point of view of respondents among three type of new multivitamin products. The three products had differences on the assessment of aroma, sour taste, and sour after taste. In addtion with biplot analysis, it was concluded that each product had different location for sale and the target of respondents based on sosial economic classes. According to respondents, product A was too sweet taste and too sour after taste in the mouth compared to others. This product was preferred by respondents who reside in South Jakarta with social economic classes (SEC) A2 and C1. Unlike product A, product B was too hard with a bit of bitter after taste in the mouth. This product was relatively preferred by respondents in various residential with social economic classes (SEC) B. Product C was strong aroma with smooth texture and more bitter taste than others. This product was preferred by respondents who reside in North Jakarta and Depok with social economic classes (SEC) A1. Overall, product B was preferred by respondents compared to other products.

Metode SVM untuk Klasifikasi Enam Tumbuhan Zingiberaceae Menggunakan Variabel Terpilih Hasil Algoritma Genetika Triyani Oktaria; Utami Dyah Syafitri; Mohamad Rafi; Farit M Afendi
Xplore: Journal of Statistics Vol. 10 No. 2 (2021)
Publisher : Department of Statistics, IPB

Ginger, red ginger, emprit ginger, elephant ginger, red galangal and white galangal are known to have similar shapes and uses, especially those that are packaged in powder form. In this study, UV-Vis spectrum 200nm-700nm were used as a source of data from chemical compound contain in those plants for classification of the six plants. In this research, the support vector machine (SVM) classification method was used to classify the six plants. Another goal of this study was to identify the wavelengths which give more information about the chemical compound of the plants. The preprocessing procedure was implemented by construction of a genetic algorithm. There were four parameters in the genetic algorithm were set namely population size, crossover probability, mutation, and generation probability. The mutation and the population size influenced significantly the results of SVM. The best result was given by probability of mutation was 10 and population size was 30. The SVM model was better than the SVM model without preprocessing procedure.

Penggerombolan Sekolah pada Penerimaan Mahasiswa Baru Jalur SNMPTN di IPB Menggunakan Metode Two-Step Cluster Ni Kadek Manik Dewantari; Utami Dyah Syafitri; Aam Alamudi
Xplore: Journal of Statistics Vol. 10 No. 3 (2021)
Publisher : Department of Statistics, IPB

New student admissions are opened in three pathways including SNMPTN, SBMPTN, and Seleksi Mandiri. In order to improve the SNMPTN selection system at IPB, a study was conducted on the quality of SMA/MA which registered to IPB through school clustering. In general, cluster analysis cannot handle large and mixed-type data, so this school clustering used the Two-Step Cluster method with two alternatives, namely without handling outliers and handling 5 percent outliers. Both of these alternatives produced an average Silhouette coefficient value of 0.2 and 0.3 respectively, which was still under the good category. However, clustering without handling outliers resulted in more detailed cluster criteria with 4 optimal clusters. The criteria for these four clusters include, Cluster 1 is a category of Low Commitment, Low Quality, and Low Consistency schools, Cluster 2 and 3 are categories of schools that have special criteria in certain categories, and Cluster 4 is a category of High Commitment, High Quality, and High Consistency.

Faktor-Faktor yang Memengaruhi Keberhasilan Studi Mahasiswa IPB Jalur Ketua OSIS dengan Metode Pohon Regresi Novia Yustika Tri Lestari. YR; Utami Dyah Syafitri; Mulianto Raharjo
Xplore: Journal of Statistics Vol. 11 No. 2 (2022):
Publisher : Department of Statistics, IPB

The success of IPB student's study can be seen from the achievement index obtained at the end of each semester. Meanwhile, the success rate of one's study is generally influenced by two factors, internal factors and external factors. Internal factors consist of intelligence (intellectual), physical, attitudes, interests, talents, and motivations, while external factors consist of family circumstances, school conditions, and the community environment. Therefore, this study uses the analysis method of classification and regression trees (CART) to find out what factors influenced the success of the Student Council (OSIS) university students. Regression tree it is one of the methods of classification and regression trees (CART) to perform classification analysis on both categorical and continuous response variables. Continuous response variables will produce a regression tree or hierarchical data group that starts at the root and ends with a relatively homogeneous small group. The response variable used in this study is the Achievement Index of first semester students. The results obtained from the analysis showed that there are several different variables in each class in influencing the success of the student council (OSIS) university students, but if we look further, there are two variables that are the same in influencing the success of the student council (OSIS) university students, which are variables from high school province and student study programs. This study uses secondary data from 493 IPB students track the chairman of the student council of the year 2018-2020 which is still active until now. Furthermore, the analysis of the regression tree is performed against four different models, for each of the force and the overall force by adjusting the variables available. The formation of tree regression performed 10 repetitions and the results of regression trees is taken from a tree which has the approximate value of the smallest risk. Then, the final results obtained from the analysis showed that there are several different variables in each class in influencing the success of the student council (OSIS) university students, but if we look further, there are two variables that are the same in influencing the success of the student council (OSIS) university students, which are variables from high school province and student study programs.

Analisis Regresi Logistik dan Cart untuk Credit Scoring dengan Penanganan Kelas Tak Seimbang Siwi Haryu Pramesti; Indahwati Indahwati; Utami Dyah Syafitri
Xplore: Journal of Statistics Vol. 11 No. 3 (2022): Vol. 11 No. 3 (2022)
Publisher : Department of Statistics, IPB

The absence of collateral for a type of credit will increase the bank's credit risk (failed to pay). Banks apply the precautionary principle by managing their credit portfolios so that potential hazards that occur can be measured and controlled in a model. Credit scoring describes how likely a debtor will fail with payments. This study aimed to compare logistic regression analysis and Classification and Regression Trees (CART) in classifying debtors to evaluate credit policies. One of the problems in classification is unbalanced data. Synthetic Minority Oversampling Technique (SMOTE) is a technique to handle the unbalanced problem in classification. The results show that the logistic regression model with SMOTE has higher sensitivity than the CART model, and there was no difference in Area Under Curve (AUC). The variables that have significant effects on the classification of debtors (good, bad) are level of education, homeownership status, and income.

Klasifikasi Sekolah dalam Penerimaan Mahasiswa Baru Vokasi IPB Jalur USMI Menggunakan Metode CART Erlinda Widya Widjanarko; Utami Dyah Syafitri; Aam Alamudi
Xplore: Journal of Statistics Vol. 11 No. 3 (2022): Vol. 11 No. 3 (2022)
Publisher : Department of Statistics, IPB

The selection of new student admissions for the IPB vocational school consists of several routes, one of which is the USMI route. To improve its performance, it is necessary to evaluate the USMI new student admission system. Previously, research with the same objective had been carried out using the clustering method. The study resulted in three clusters in which schools were differentiated based on commitment and quality. This study aim to create a classification model of the clusters obtained using the CART method. Classification and Regression Tree (CART) is a nonparametric classification technique that produces a single decision tree. The CART method can involve mixed-type data. The classification model generated from the 2019 data yields an accuracy of 98.52%. However, the results of the 2019 model evaluation with the 2020 data are still not good enough to predict with an accuracy of 57.22%, so the 2020 data is re-clustered and produces three clusters. Furthermore, the classification model was remade with 2020 data, resulting in an accuracy of 97.47%. However, the results of the 2020 model evaluation with the 2021 data are still not good enough to predict with an accuracy of 44.34%, so the clustering in the previous year cannot be used for predictions of the following year's data. The grouping of schools for USMI applicants needs to be done by grouping schools every year.

Klasifikasi Kadar Glukosa Darah Keluaran Alat Non-invasif Menggunakan Regresi Logistik Ordinal dengan Peringkasan Luas Yuniar Istiqomah; Erfiani Erfiani; Utami Dyah Syafitri
Xplore: Journal of Statistics Vol. 12 No. 1 (2023): Vol. 12 No. 1 (2023)
Publisher : Department of Statistics, IPB

Diabetes Mellitus (DM) is the silent killer because its symptoms tend to go unnoticed. The IPB Non-Invasive Biomarking Team developed a non-invasive monitoring device to check blood. The tool uses the spectroscopy principle and produces an output in the form of a residual value of light intensity. A method is needed to predict the category of blood glucose levels based on the measurement results of non-invasive tools. Classification modeling is one of the methods that can be used to analyze the relationship between the blood glucose level class of invasive measurement results and the residual value of the intensity of non-invasive measurement results. One of the commonly used classification methods is ordinal logistic regression. Light spectrum-based data used as predictor X changes often provide changes that correlate with each other. The principal component analysis reduces its dimensions to become a new set of changes that do not correlate. Graph area summation in the period is the best summarization method because it can take advantage of the general data information. This study uses the ordinal logistic regression method as a modeling method by applying principal component analysis and graph area summation applied to 2017 data and 2019 data. Classification modeling in the 2017 data had a balanced accuracy value of 64,64%. Classification modeling in the 2019 data produced a balanced accuracy value of 57,57%. The design used in the 2017 tool and the 2019 tool is different, causing the residual intensity graph of the non-invasive measurement results to be read differently. The 2017 data model is better applied to homogeneous data and the 2019 data model is better applied to heterogeneous data.

The Role of Human Resource Risk on Employee Performance in The Hybrid Workforce Era Thasya Putri; Utami Dyah Syafitri; Anggraini Sukmawati
Jurnal Aplikasi Bisnis dan Manajemen (JABM) Vol. 9 No. 2 (2023): JABM Vol. 9 No. 2, Mei 2023
Publisher : School of Business, Bogor Agricultural University (SB-IPB)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17358/jabm.9.2.386

The COVID-19 pandemic has brought about significant changes, particularly in work systems and patterns. The adoption of a hybrid work model allows employees to work remotely based on individually or collectively negotiated work arrangements. However, implementing a hybrid workforce presents several challenges, such as communication issues, varying levels of technological proficiency among employees, irregular working hours, and the potential for internal team problems. By implementing a hybrid work system in Pegadaian Co., employees are exposed to risks from both financial and non-financial aspects. This study aims to identify employee characteristics and analyze the impact of the hybrid workforce era and human resource risks on employee performance. The research uses the descriptive analysis method and SEM-PLS. The results show that the hybrid workforce era has a positive effect on employee performance, demonstrating that employees feel more productive when working in the office. These findings suggest that Pegadaian Co. should provide a comfortable and practical office environment to facilitate employee performance. Conversely, the study finds that human resource risks do not significantly influence employee performance. The selection process is identified as a minor factor within the HR risk variable. The company's selection process prioritizes effectiveness and efficiency by focusing on recruitment needs and objectives. Keywords: flexible working arrangement, hybrid workforce, working from office, Pegadaian, employee performance

Co-Authors Aam Alamudi Abdul Rohman Abdul Rohman Agus Mohamad Soleh Agustin Faradila Aidi, Muhammad Nur Aji Hamim Wigena Akbar Rizki Alfi Hudatul Karomah ALIU, MUFTIH ALWI Anang Kurnia Andreas Nicholas Gandaputra Simbolon Andrew Donda Munthe Anggrahini, Ervina Dwi Anggraini Sukmawati Anik Djuraidah Anissa Permatasari Antonio Kautsar ASEP SAEFUDDIN Auliya Ilmiawati Aziza, Vivin Nur Azkiya, Azka Al Baehera, Seta Bagus Sartono Bambang - Riyanto Bambang Prajogo Eko Wardoyo Bambang Riyanto Bartho Sihombing Bayu Pranata, Bayu Budi Susetyo Christin Halim Cici Suhaeni Dea Amelia, Dea Dwi Agustin Nuriani Sirodj Dwi Putri Kurniasari Eka Dewi Pertiwi Eka Winarni Sapitri Eminita, Viarti Endina Fatihah Yasmin Erfiani Erfiani Erfiani, Erfiani Erlinda Widya Widjanarko Ernawati, Fitrah Eti Rohaeti Evita Choiriyah Fadhila Hijryani FAHREZAL ZUBEDI Farit M Afendi Fatimah, Zahra Nurul Fitrianto, Anwar Gusti Tasya Meilania Hari Wijayanto I Made Sumertajaya Idqan Fahmi Immatul Ulya Indahwati Indonesian Journal of Statistics and Its Applications IJSA Intan Lukiswati Irmanida Batubara Irzaman, Irzaman Isti Rochayati Izzati, Mumpuni Nur Joko Santoso Jumansyah, L. M. Risman Dwi Khairil Anwar Notodiputro Kusman Sadik Laradea Marifni Lidiasari, Melisa Lismayani Usman M. Iqbal M. Rafi Meilania, Gusti Tasya Mohamad Rafi Mohamad Rafi Mohamad Rafi Mohammad Masjkur Muhamad Insanu Muhammad Bachri Amran Muhammad Nur Aidi Muhammad Nursid Mulianto Raharjo Muslim, Muhammad Irfai Muthahari, Wadudi Nanik Siti Aminah Nariswari Karina Dewi Ni Kadek Manik Dewantari Noer Endah Islami Nofrida Elly Zendrato Novia Yustika Tri Lestari. YR Nur Aidi, Muhammad Nurhajawarsi Nurhajawarsi Nursifa Mawadah R, Arifuddin Rifki Husnul Khuluk Ririn Fara Afriani Riswan Riswan Sanusi, Ratna Nur Mustika Sari, Mutia Dwi Permata Septaningsih, Dewi Anggraini Setyowati, Silfiana Lis Sifa Awalul Fikriah Siwi Haryu Pramesti Soleh, Agus M Soni Yadi Mulyadi Sony Hartono Wijaya Sri Sulastri Sri Wahyuningsih Syam, Ummul Auliyah Syifa Muflihah Tania Amalia Darsono Thasya Putri Topan . Ruspayandi Triyani Oktaria Vega, Iliana Patricia Vivin Nur Aziza Weisha, Ghea Wini - Trilaksani Wulan Tri Wahyuni Yenni Angraini Yuan Millafanti Yuni Suci Kurniawati Yuniar Istiqomah

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