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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) Cetta: Jurnal Ilmu Pendidikan 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 Enthusiastic : International Journal of Applied Statistics and Data Science 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
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The Role of Employee Engagement in Increasing Talent Retention at A Crude Palm Oil Company Amelia, Dea; Sukmawati, Anggraini; Syafitri, Utami Dyah
Jurnal Samudra Ekonomi dan Bisnis Vol 16 No 3 (2025): JSEB
Publisher : Fakultas Ekonomi dan Bisnis Universitas Samudra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33059/jseb.v16i3.12768

Abstract

This study examines the effect of employee engagement on talent retention at PT. Wilmar Nabati Indonesia, Dumai, with reward system as a mediating variable. Data were collected from 177 employees through an online questionnaire and analyzed using SEM-PLS with SmartPLS 3.0. Respondents were classified by age, tenure, and educational background. The results show that employee engagement has a positive and significant effect on talent retention. Furthermore, reward system mediates the relationship between employee engagement and talent retention. These findings emphasize the importance of fostering employee engagement and developing effective reward systems to retain critical talent in the crude palm oil industry. The study contributes to the literature by positioning reward system as a mediator, a perspective that has received limited attention in previous research. HR managers should focus on appreciation and clear promotion paths to improve retention.
Effectiveness of Machine Learning Models with Bayesian Optimization-Based Method to Identify Important Variables that Affect GPA R, Arifuddin; Syafitri, Utami Dyah; Erfiani, Erfiani
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 8, No 3 (2024): July
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v8i3.21711

Abstract

To produce superior human resources, the SPs-IPB Master Program must consider the factors influencing the GPA in the student selection process. The method that can be used to identify these factors is a machine learning algorithm. This paper applies the random forest and XGBoost algorithms to identify significant variables that affect GPA. In the evaluation process, the default model will be compared with the model resulting from Bayesian and random search optimization. Bayesian optimization is a method for optimizing hyperparameters that combines information from previous iterations to improve estimates. It is highly efficient in terms of computing time. Based on a balanced accuracy and sensitivity metrics average, Bayesian optimization produces a model superior to the default model and more time-efficient than random search optimization. XGBoost sensitivity metric is 25% better than random forest. However, random forest is 19% better in accuracy and 30% in specificity. Important variables are obtained from the information gain value when splitting the tree nodes formed. According to the best random forest and XGBoost model, variables that have the most influence on students' GPA are Undergraduate University Status (X8) and Undergraduate University (X6). Meanwhile, the variables with the smallest influence are Gender (X4) and Enrollment (X9).
The Impact of Using A Linear Model for the Ordinal Response of Mixture Experiments Syafitri, Utami Dyah; Erfiani, Erfiani; Soleh, Agus M; Wigena, Aji Hamim
ZERO: Jurnal Sains, Matematika dan Terapan Vol 9, No 2 (2025): Zero: Jurnal Sains Matematika dan Terapan
Publisher : UIN Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30829/zero.v9i2.25760

Abstract

In a sensory test, the response is a Likert scale, which belongs to the ordinal scale. The ordinal response can be analyzed using a linear model approach; however, this approach can be misleading.  This research aims to compare three different methods for ordinal response: the average score, the second-order Scheffe model, and the ordinal logistic model. The case study focused on the response to the taste of cookies resulting from the mixture experiment. The mixture experiment is one type of experimental design which is commonly used for product formulation.  The research involved three ingredients with different lower bonds.  The D-optimal design which also the {3,2} simplex-lattice design was chosen for the experiment. The three methods were conducted, and they all yielded the same results for the optimum composition; however, the ordinal model provided more information about the data's characteristics. The optimal formulation of each ingredient was 10%, 20%, 70%. 
Perbandingan Metode Regresi Multilevel dan Beta Generalized Linear Mixed Models pada Data Longitudinal Capaian IPK Mahasiswa Gusti Tasya Meilania; Utami Dyah Syafitri; I Made Sumertajaya
Limits: Journal of Mathematics and Its Applications Vol. 21 No. 3 (2024): Limits: Journal of Mathematics and Its Applications Volume 21 Nomor 3 Edisi No
Publisher : Pusat Publikasi Ilmiah LPPM Institut Teknologi Sepuluh Nopember

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

Abstract

Penelitian ini membandingkan kinerja model Beta Generalized Linear Mixed Model (Beta GLMM) dengan Regresi Multilevel pada data Indeks Prestasi Kumulatif (IPK) mahasiswa. Data IPK yang digunakan dalam penelitian ini terlihat miring ke sisi kiri atau memiliki ekor kiri yang lebih panjang yang mencerminkan kecenderungan mahasiswa memperoleh nilai yang lebih besar daripada rata-rata IPK keseluruhan. Hal ini mengindikasikan bahwa data tidak berdistribusi normal, melainkan diduga berdistribusi Beta. Tujuan dari penelitian ini adalah melakukan perbandingan terhadap metode regresi multilevel dan Beta Generalized Linear Mixed Model (GLMM) untuk melihat faktor-faktor yang memengaruhi IPK mahasiswa setiap semester. Data yang digunakan adalah data longitudinal dimana setiap mahasiswa diamati IPK per semester serta beberapa peubah penjelas lainnya. Pendekatan Beta GLMM digunakan karena Beta GLMM menggabungkan antara pendekatan Linear Mixed Model (LMM) dengan Generalized Linear Model (GLM)Berdasarkan analisis yang dilakukan, diperoleh hasil bahwa metode Beta GLMM memiliki nilai Akaike Information Criterion (AIC) yang lebih rendah dibandingkan metode regresi multilevel. Adapun faktor-faktor yang mempengaruhi capaian IPK mahasiswa berdasarkan analisis Beta GLMM diantaranya semester mahasiswa, SKS mahasiswa setiap semester, status perkawinan, jalur masuk kuliah, sumber biaya pendidikan (beasiswa), interaksi semester dengan status perkawinan, interaksi antara semester dengan jalur masuk kuliah, dan interaksi antara semester dengan beasiswa. Selain itu, diketahui bahwa proporsi keragaman IPK yang dapat dijelaskan oleh perbedaan antar mahasiswa adalah sebesar 0.837. Hal ini menunjukkan bahwa 83.7% dari total variasi IPK dapat dijelaskan oleh perbedaan antar mahasiswa (Level 2), sedangkan sisanya 16.3% dijelaskan oleh variasi pada setiap mahasiswa disetiap semester (Level 1).
Optimizing Currency Circulation Forecasts in Indonesia: A Hybrid Prophet- Long Short Term Memory Model with Hyperparameter Tuning Aziza, Vivin Nur; Syafitri, Utami Dyah; Fitrianto, Anwar
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 24 No. 1 (2024)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v24i1.4052

Abstract

The core problem for decision-makers lies in selecting an effective forecasting method, particularly when faced with the challenges of nonlinearity and nonstationarity in time series data. To address this, hybrid models are increasingly employed to enhance forecasting accuracy. In Indonesia and other Muslim countries, monthly economic and business time series data often include trends, seasonality, and calendar variations. This study compares the performance of the hybrid Prophet-Long Short-Term Memory (LSTM) model with their individual counterparts to forecast such patterned time series. The aim is to identify the best model through a hybrid approach for forecasting time series data exhibitingtrend, seasonality, and calendar variations, using the real-life case of currency circulation in South Sulawesi. The goodness of the models is evaluated using the smallest Mean Absolute Percentage Error (MAPE) and Root Mean Square Error (RMSE) values. The results indicate that the hybrid Prophet- LSTM model demonstrates superior accuracy, especially for predicting currency outflow, with lower MAPE and RMSE values than standalone models. The LSTM model shows excellent performance for currency inflow, while the Prophet model lags in inflow and outflow accuracy. This insight is valuable for Bank Indonesia’s strategic planning, aiding in better cash flow prediction and currency stock management.
K-Means Clustering Application of Open ‎Unemployment in 2020 Caused by COVID-19 in West Java Province Ardiansyah, M. Ficky Haris; Amany, Nurfatimah; Anugrah, Cahya Ireno; Syafitri, Utami Dyah
Enthusiastic : International Journal of Applied Statistics and Data Science Volume 4 Issue 1, April 2024
Publisher : Universitas Islam Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/enthusiastic.vol4.iss1.art1

Abstract

West Java was the province with the highest unemployed rate during the COVID-19 pandemic. Significant increase of open ‎unemployment rate in West Java negatively impacts the national income. This study aims to apply the ‎clustering method using the k-means algorithm to determine priority clusters in West Java ‎Province by looking at the number of clusters in West Java’s city and the main characteristic of ‎each cluster. The clustering was conducted utilizing a k-means clustering algorithm which is grouping data based on similar ‎characteristics. The clustering results were evaluated using silhouette method. The results indicated that ‎two clusters were optimal. The clustering process using the k-means method showed that there were three clusters distinguishing the open unemployment rate during the pandemic in West Java Province in 2020. Cluster 1 ‎had a fairly low open unemployment rate due to the stalled service sector and low minimum city wage. ‎Cluster 2 had a high open unemployment rate due to the service sector and high minimum city wage. ‎Cluster 3 had medium open unemployment rate due to the service sector and also medium minimum city ‎wage. It suggests that cluster 2 is a priority cluster in dealing with the open unemployment rate.‎
Strategi Pengembangan Yayasan Seri Amal Pasca Pandemi Covid-19 : Studi Kasus SMA Cahaya Medan dan SMA ST. Petrus Sidikalang Gandaputra Simbolon, Andreas Nicholas; Fahmi, Idqan; Syafitri, Utami Dyah
Cetta: Jurnal Ilmu Pendidikan Vol 7 No 1 (2024)
Publisher : Jayapangus Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37329/cetta.v7i1.2932

Abstract

The COVID-19 pandemic has necessitated profound changes in the field of education, triggering a shift from conventional to online learning. This research delves into the impact of the implementation of online learning systems on students' academic performance in two high schools, namely SMA Putri Cahaya Medan and SMA Santo Petrus Sidikalang, under the auspices of the Yayasan Seri Amal. Through biplot analysis and the Analytical Hierarchy Process (AHP) approach, this study identifies patterns of changes in student grades and develops strategic school development strategies. The findings indicate that although there have been no significant changes in student grades, development strategies focused on staff training, improvement of facilities and technology, and external collaborations—especially with alumni and relevant institutions—are key to maintaining competitiveness and enhancing the quality of education. The conclusions and recommendations of this research provide guidance for school management and stakeholders to design adaptive strategic measures amid the evolving dynamics of education.
Strategi Pengembangan Yayasan Seri Amal Pasca Pandemi COVID-19 Studi Kasus: SMA Cahaya Medan & SMA St. Petrus Sidikalang Simbolon, Andreas Nicholas Gandaputra; Fahmi, Idqan; Syafitri, Utami Dyah
Syntax Literate Jurnal Ilmiah Indonesia
Publisher : Syntax Corporation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36418/syntax-literate.v9i8.15879

Abstract

Penelitian ini bertujuan untuk: (1) Menganalisis faktor lingkungan internal dan eksternal yang berpengaruh pada SMA Cahaya Medan dan SMA St. Petrus Sidikalang, (2) Merumuskan alternatif strategi pengembangan yang dapat dipakai oleh kedua sekolah, dan (3) Menentukan serta merekomendasikan strategi bisnis yang tepat bagi Yayasan Seri Amal dalam menghadapi persaingan. Metode yang digunakan adalah analisis faktor lingkungan internal (IFE) dan eksternal (EFE) serta Analytical Hierarchy Process (AHP). Hasil penelitian menunjukkan bahwa faktor dominan yang mempengaruhi SMA Cahaya Medan dari faktor internal adalah kurangnya SDM, sedangkan faktor eksternal adalah regenerasi sekolah dan potensi pangsa pasar lebih besar ke luar kota. Untuk SMA St. Petrus Sidikalang, faktor internal yang paling berpengaruh adalah akreditasi A dan penggunaan LMS, sementara faktor eksternal adalah minimnya kompetitor SMA swasta di daerah tersebut. Strategi pengembangan yang direkomendasikan untuk SMA Cahaya Medan meliputi pelatihan SDM, peningkatan kerjasama dengan berbagai pihak, dan penggabungan pembelajaran daring dengan luring. Untuk SMA St. Petrus Sidikalang, strategi meliputi meningkatkan kerjasama dengan instansi di bidang olahraga dan seni, pembangunan fasilitas pendukung, serta pengembangan desain pembelajaran yang unggul dan terukur. Prioritas strategi pengembangan untuk SMA Cahaya Medan adalah pelatihan SDM dan penggabungan pembelajaran daring dengan luring, sedangkan untuk SMA St. Petrus Sidikalang adalah kerjasama dengan instansi dalam pengembangan kurikulum serta prestasi akademik dan non-akademik. Penelitian ini memberikan rekomendasi strategis yang dapat meningkatkan daya saing dan kualitas pendidikan di kedua sekolah tersebut.
The Role of Human Resource Risk on Employee Performance in The Hybrid Workforce Era Putri, Thasya; Syafitri, Utami Dyah; Sukmawati, Anggraini
Jurnal Aplikasi Bisnis dan Manajemen 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

Abstract

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
Multilevel Regression Analysis on Graduate Student Grade Point Average Riswan, Riswan; Dyah Syafitri, Utami; Nur Aidi, Muhammad
Al-Khwarizmi : Jurnal Pendidikan Matematika dan Ilmu Pengetahuan Alam Vol. 12 No. 1 (2024): Al-Khwarizmi : Jurnal Pendidikan Matematika dan Ilmu Pengetahuan Alam
Publisher : Prodi Pendidikan Matematika FTIK IAIN Palopo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24256/jpmipa.v12i1.3969

Abstract

Abstract:Multilevel regression is one of the methods used to analyze hierarchical data structures. One case of data with a hierarchical structure is the cumulative grade point average (GPA) data for students each semester (level one) which is nested within students (level two), and nested within faculties (level three). This study produced the three best three-level regression models: the multilevel regression model, the multilevel regression model with natural logarithmic transformation, and the multilevel binary logistic regression model. The multilevel regression model and the multilevel regression model with natural logarithmic transformation at a significant level of 5%, have the same variables that affect student GPA scores, including semesters, credits, gender, scholarships, and marital status with the same interaction effect, namely semester interactions with scholarships. In addition, the ICC values by the two models are also the same which explains that 91% of the total diversity of student GPA comes from the student level and 8% comes from the faculty level. For the multilevel binary logistic regression model, all explanatory variables affect GPA without involving interaction between levels. Abstrak:Regresi multilevel merupakan salah satu metode yang digunakan untuk menganalisis struktur data hirarkhi. Salah satu kasus data dengan struktur hirarki adalah data indeks prestasi kumulatif (IPK) mahasiswa tiap semester (level satu) yang tersarang dalam mahasiswa (level dua), tersarang dalam fakultas (level tiga). Dalam penelitian ini menghasilkan tiga model regresi tiga level terbaik yaitu model regresi multilevel, model regresi multilevel dengan transformasi logaritma natural, dan model regresi logistik biner multlevel. Model regresi multilevel dan model regresi multilevel dengan transformasi logaritma natural pada taraf nyata 5%, memiliki peubah sama yang berpengaruh terhadap nilai IPK mahasiswa antara lain semester, SKS, jenis kelamin, beasiswa, dan status nikah dengan pengaruh interaksi yang sama yaitu interaksi semester dengan beasiswa. Selain itu, nilai ICC oleh kedua model tersebut juga sama yang menjelaskan bahwa 91% total keragaman IPK mahasiswa berasal dari level mahasiswa dan 8% berasal dari level fakultas.  Untuk model regresi logistik biner multilevel semua peubah penjelas berpengaruh terhadap IPK tetapi tanpa melibatkan interaksi antar level.
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 Amany, Nurfatimah Anang Kurnia Andrew Donda Munthe Anggrahini, Ervina Dwi Anggraini Sukmawati Anik Djuraidah Anissa Permatasari Antonio Kautsar Anugrah, Cahya Ireno Ardiansyah, M. Ficky Haris 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 Fachry Abda El Rahman Fadhila Hijryani FAHREZAL ZUBEDI Farit M Afendi Fatimah, Zahra Nurul Fitrianto, Anwar Gandaputra Simbolon, Andreas Nicholas Gusti Tasya Meilania Hari Wijayanto I Made Sumertajaya Idqan Fahmi Immatul Ulya Indahwati Indonesian Journal of Statistics and Its Applications IJSA Indradewa, Rhian 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 Putri, Thasya 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 Simbolon, Andreas Nicholas Gandaputra Siwi Haryu Pramesti Soleh, Agus M Soni Yadi Mulyadi Sony Hartono Wijaya Sri Sulastri Syam, Ummul Auliyah Syifa Muflihah Tania Amalia Darsono 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