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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Jurnal Manajemen dan Organisasi FORUM STATISTIKA DAN KOMPUTASI Pythagoras: Jurnal Matematika dan Pendidikan Matematika Media Statistika Jurnal Ilmu Dasar Jurnal Manajemen Teknologi Jurnal Agro Ekonomi JAM : Jurnal Aplikasi Manajemen Indonesian Journal of Business and Entrepreneurship (IJBE) JUITA : Jurnal Informatika Indonesian Journal of Biotechnology Jurnal Aplikasi Bisnis dan Manajemen (JABM) E-Journal Jurnal Manajemen. AL ISHLAH Jurnal Pendidikan International Research Journal of Business Studies (E-Journal) Jurnal Penelitian Pertanian Tanaman Pangan BAREKENG: Jurnal Ilmu Matematika dan Terapan Jurnal Ekonomi Integra JTAM (Jurnal Teori dan Aplikasi Matematika) Limits: Journal of Mathematics and Its Applications JURNAL AGRONIDA Saintifik : Jurnal Matematika, Sains, dan Pembelajarannya ComTech: Computer, Mathematics and Engineering Applications Jurnal Manajemen Inferensi Jurnal Agro Ekonomi International Journal of Advances in Data and Information Systems Journal of Data Science and Its Applications Jurnal Teknik Informatika (JUTIF) JURNAL ILMIAH GLOBAL EDUCATION Xplore: Journal of Statistics STATISTIKA Asian Journal of Social and Humanities Scientific Journal of Informatics Journal of Mathematics, Computation and Statistics (JMATHCOS) International Research Journal of Business Studies Indonesian Journal of Statistics and Its Applications Limits: Journal of Mathematics and Its Applications
I Made Sumertajaya
Departemen Statistika, Fakultas Matematika Dan Ilmu Pengetahuan Alam, Institut Pertanian Bogor Kampus Darmaga, Bogor 16680
Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Immunology & microbiology Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Social Sciences Transportation Other

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Peran Mediasi Budaya Organisasi dalam Memperkuat Resiliensi Manajemen Perguruan Tinggi Diki Akhwan Mulya; I Made Sumertajaya; Anggraini Sukmawati
Jurnal Manajemen dan Organisasi Vol. 14 No. 2 (2023): Jurnal Manajemen dan Organisasi
Publisher : IPB University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/jmo.v14i2.42332

Abstract

Resilience is the ability to survive, adapt, rise, and recover from unexpected conditions. The Covid-19 pandemic is unpredictable for almost all organizations, including Bogor Agricultural University (IPB), one of the state universities in Indonesia with legal status (PTN-BH). The study analyzes the effect of strategic human resource management (SHRM) on the resilience of university management in facing the COVID-19 pandemic, mediated by organizational culture. Respondents in this study were lecturers and education personnel at Bogor Agricultural University (IPB). The sampling technique used a stratified random sampling technique, obtaining 358 respondents. The research data were obtained by survey method using an online questionnaire. Data were analyzed using the Structural Equation Modeling-Partial Least Square (SEM-PLS) method. The results showed that organizational culture successfully mediated the effect of SHRM on organizational resilience positively and significantly. Strategic HRM latent variables have a positive and significant impact on organizational culture, and organizational culture has a positive and significant impact on organizational resilience. The direct effect of SHRM on organizational resilience is positive and effective according to lecturers but not substantial according to education employees. This result means that the strategic HR policies implemented can support lecturers in adapting to changing conditions to continue to carry out their duties and achieve their performance targets. Meanwhile, for education employees, existing policies that have yet to help tend to contribute significantly to efforts to achieve organizational resilience. Education employees requires strategic HRM policy support that is different from lecturers to be able to contribute significantly to the achievement of organizational resilience.
Analisis Clustering Time Series untuk Pengelompokan Provinsi di Indonesia Berdasarkan Indeks Pembangunan Manusia Jenis Kelamin Perempuan Dwi Agustin Nuriani Sirodj; I Made Sumertajaya; Anang Kurnia
Statistika Vol. 23 No. 1 (2023): Statistika
Publisher : Department of Statistics, Faculty of Mathematics and Natural Sciences, Universitas Islam Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29313/statistika.v23i1.2181

Abstract

ABSTRAK Indeks Pembangunan Manusia (IPM) mencerminkan bagaimana kualitas dari pembangunan suatu wilayah tertentu. Selain adanya ketimpangan nilai IPM antar wilayah provinsi di Indonesia, jika dilihat dari sudut pandang gender, maka kesenjangan IPM laki-laki dan perempuan pun tidak bisa dihindari. Peningkatan pertumbuhan pembangunan di setiap wilayah tentu harus mendorong peningkatan kesetaraan gender pula, dalam hal ini kesenjangan pembangunan antara laki-laki dan perempuan harus mampu diminimalisir sehingga penting untuk melihat bagaimana kondisi IPM perempuan perwilayah provinsi di Indonesia agar dapat dilakukan langkah-langkah intervensi untuk meminimalisir isu ketimpangan yang harapannya dapat mendorong indeks pembangunan di wilayah tersebut. Metode analisis yang digunakan untuk mengelompokkan daerah berdasarkan nilai IPM perempuan adalah Clustering time series. Hasil analisis memperlihatkan metode clustering time series dengan menggunakan jarak dynamic time-warping (DTW) menghasilkan dua kelompok yaitu kelompok 1 (daerah dengan IPM perempuan rendah): daerah Papua dan kelompok 2 (daerah dengan IPM perempuan tinggi): daerah lain selain Papua. Pengelompokan yang dibentuk menghasilkan nilai koefisien Silhouette sebesar 0,74. Nilai tersebut menandakan bahwa kelompok yang dibentuk berada dalam kategori kuat dalam artian bahwa dua kelompok tersebut mempunyai karakteristik yang jelas berbeda sehingga metode pengelompokan dengan jarak DTW dapat digunakan dalam pengelompokan provinsi-provinsi di Indonesia berdasarkan nilai IPM Perempuan. ABSTRACT The Human Development Index (HDI) reflects the quality of development in a particular region. In addition to the inequality of HDI values between provinces in Indonesia, when viewed from a gender perspective, the gap between the HDI of men and women is inevitable. Increased development growth in each region must certainly encourage an increase in gender equality as well; in this case, the development gap between men and women must be able to be minimized, so it is important to see how the condition of the women's HDI per region in Indonesia so that intervention steps can be taken to minimize the issue of inequality. The analysis method used in this paper is Time Series Clustering. The analysis results show that the time series clustering method using dynamic time-warping (DTW) distance produces two groups: group 1 (regions with low female HDI): Papua region and group (2 regions with high female HDI): all provinces except Papua. The grouping formed produced a Silhouette coefficient value of 0.74. This value indicates that the groups formed are in a strong category, so the clustering method with DTW distance can be used in grouping provinces in Indonesia based on the value of Women's HDI.
Bicluster Analysis of Cheng and Church's Algorithm to Identify Patterns of People's Welfare in Indonesia Laradea Marifni; I Made Sumertajaya; Utami Dyah Syafitri
JUITA: Jurnal Informatika JUITA Vol. 11 No. 2, November 2023
Publisher : Department of Informatics Engineering, Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30595/juita.v11i2.17446

Abstract

Biclustering is a method of grouping numerical data where rows and columns are grouped simultaneously. The Cheng and Church (CC) algorithm is one of the bi-clustering algorithms that try to find the maximum bi-cluster with a high similarity value, called MSR (Mean Square Residue). The association of rows and columns is called a bi-cluster if the MSR is lower than a predetermined threshold value (delta). Detection of people's welfare in Indonesia using Bi-Clustering is essential to get an overview of the characteristics of people's interest in each province in Indonesia. Bi-Clustering using the CC algorithm requires a threshold value (delta) determined by finding the MSR value of the actual data. The threshold value (delta) must be smaller than the MSR of the actual data. This study's threshold values are 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, and 0.8. After evaluating the optimum delta by considering the MSR value and the bi-cluster formed, the optimum delta is obtained as 0.1, with the number of bi-cluster included as 4.
Comparison of the Symmetric and Asymmetric Generalized Autoregressive Conditional Heteroscedasticity (GARCH) Models in Forecasting the 2018-2023 Jakarta Composite Index Yenni Angraini; Adelia Putri Pangestika; I Made Sumertajaya
ComTech: Computer, Mathematics and Engineering Applications Vol. 15 No. 1 (2024): ComTech
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/comtech.v15i1.10610

Abstract

The Autoregressive Integrated Moving Average with Exogenous Variables (ARIMAX) method assumes a homogeneous residual variance, but data with high volatility can cause violations of this assumption. Hence, it is interesting to compare the forecasting accuracy of symmetric and asymmetric Autoregressive Conditional Heteroskedasticity (ARCH) models in various data conditions. The research aimed to compare the accuracy of the symmetric ARCH/ Generalized Autoregressive Conditional Heteroscedasticity (GARCH) and asymmetric TGARCH models in forecasting weekly Jakarta Composite Index (JCI) data on January 1st, 2018, to April 24th, 2023, by involving the influence of COVID-19 as a covariate variable and applying several validation scenario models to training and testing data. Based on the best-selected model, forecasting was carried out from May 1st, 2023, to July 3rd, 2023. The data used were weekly JCI opening data from January 1st, 2018, to April 24th, 2023, with the COVID-19 period as a covariate variable. The analysis results show that symmetric and asymmetric methods can handle violations of the heteroscedasticity assumption in the ARIMAX model. The best model produced based on four data validation scenarios is the asymmetric ARIMAX(3,1,3)-TGARCH(1,2) model with an average MAPE value of 3.158%. In this model, the COVID-19 variable significantly influences the JCI movement. Forecasting is done with forecasting results that are stable with confidence intervals that widen in each period.
ANALISIS INTERAKSI GENOTIP x LINGKUNGAN MENGGUNAKAN STRUCTURAL EQUATION MODELING Sumertajaya, I Made; Matjjik, Ahmad Ansori; Mindra Jaya, I Gede Nyoman
PYTHAGORAS Jurnal Matematika dan Pendidikan Matematika Vol. 4 No. 1: Juni 2008
Publisher : Department of Mathematics Education, Faculty of Mathematics and Natural Sciences, UNY

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (688.75 KB) | DOI: 10.21831/pg.v4i1.684

Abstract

Additive Main Effect and Multiplicative Model (AMMI Model) nowadays is used to asses in plant breeding, especially to asses the Genotype í— Environment Interaction (GEI) on multi-environment trial. The presence of genotype í— environment interaction (GEI) creates difficulties in modeling complex trait that involve sequence biological process. Coupling Structural equation modeling with AMMI was developed to analyzed genotype í— environment interaction (GEI). Structural equation modeling allows us to account for underlying sequential process in plant development by incorporating intermediate variables associated with those processes in the model. With this method we can incorporating genotypic and environmental covariate in the model and explain how those covariates influence grain yield. SEM-AMMI useful when both environments and genotype are fixed and the purpose of the multi-environment trials (MET) is to assess the combined effect genotypic and environmental covariate on yield and yield components  Keywords : AMMI Model, Structural equation modeling 
Faktor-Faktor yang Mempengaruhi Risiko Saham dengan Menggunakan Regresi Logistik Ordinal Valentika, Nina; Sumertajaya, I Made; Azis, Irfani; Nunung Kusdaniyama
Journal of Mathematics, Computations and Statistics Vol. 7 No. 1 (2024): Volume 07 Nomor 01 (April 2024)
Publisher : Jurusan Matematika FMIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/jmathcos.v7i1.1962

Abstract

Abstrak. Tujuan dalam penelitian ini adalah untuk mengetahui kategori risiko pada saham dengan menggunakan beta saham, serta membandingkan model regresi logistik ordinal tanpa efek interaksi dan dengan efek interaksi untuk mengetahui faktor-faktor yang mempengaruhi risiko saham. Hasil penelitian yang diperoleh adalah model terbaik yang diperoleh adalah Untuk rendah|sama Untuk sama|tinggi Ukuran dari koefisien determinasi (R-Square) yang digunakan dalam pengujian kebaikan model adalah Negelkerke yaitu sebesar 66,80%. Variabel yang berpengaruh terhadap risiko saham adalah return pada taraf nyata 10%.
Penentuan Faktor Kemiskinan Indonesia Menggunakan Regresi Logistik Azis, Irfani; Sumertajaya, I Made; Purwaningsih, Siti Samsiyah; Tjahjawati, Sri Surjani
Journal of Mathematics, Computations and Statistics Vol. 6 No. 1 (2023): Volume 06 Nomor 01 (April 2023)
Publisher : Jurusan Matematika FMIPA UNM

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

Abstract

Poverty is a global problem faced by various countries, including Indonesia. This study aims to determine the factors that influence the level of poverty in Indonesia by looking at the poverty classification itself. The data used is data on the website of the Central Statistics Agency and Bappenas in 2021 with the model used is an ordinal logistic regression model. The backward elimination method isused to select the best model with the lowest information criterion akaike value. The results of this study are that the gross domestic product factor and the unemployment rate have a significant positive effect, while population size and the provincial minimum wage have a significant negative effect on the poverty rate in Indonesia.
Perbandingan Regresi Data Panel Variabel Perdagangan berdasarkan Periode Data Selama Pandemi Covid-19 Valentika, Nina; Sumertajaya, I Made; Kusdaniyama, Nunung; Sunardi
Journal of Mathematics, Computations and Statistics Vol. 6 No. 1 (2023): Volume 06 Nomor 01 (April 2023)
Publisher : Jurusan Matematika FMIPA UNM

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

Abstract

The purpose of this study is to model the effect of returns and trading volume on the bid-ask spread using monthly and annual data during the Covid-19 Pandemic, as well as compare the panel data regression model to see the effect of returns and trading volume on the bid-ask spread based on monthly data periods and annually during the Covid-19 Pandemic. The results showed that the best model for monthly and annual data during the Covid-19 Pandemic was a random effect data model with individual effects or cross sections. In the random effect data model with individual effects or cross-section for monthly data, it is found that volume has a significant effect on the bid-ask spread at a significant level of 5%. Meanwhile, for annual data, it is found that returns have a significant effect on the bid-ask spread at a significant level of 5%. The best model based on monthly and annual data periods is the random effects data model with individual effects or cross sections using annual data.
Factors Affecting Employee Performance during Work from Home Aropah, Vina Da’watul; Sarma, Ma’mun; Sumertajaya, I Made
International Research Journal of Business Studies Vol. 13 No. 2 (2020): August-November 2020
Publisher : Universitas Prasetiya Mulya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21632/irjbs.13.2.201-214

Abstract

The Corona Virus Disease (Covid-19) pandemic in Indonesia began with the discovery of Covid-19 sufferers on March 2, 2020. Coronavirus is a group of viruses that can cause disease in animals or humans. To respond the conditions of the Covid-19 outbreak, NPPA issued a regulation concerning adjustments to the work system of the government employee in efforts to prevent the spread of Covid-19. This study uses census sampling, where all members of the population used as samples. The total responden of the Government Employee in NPPA is 128 employees, who are works mostly at home during the pandemic. The research data used primary and secondary data. Comparison using PLS-SEM as analyzing the data. The result of the research showed that leadership and work environment have impact on employee performance, whereas organizational support has no impact on employee performance.
Effectiveness of GPCA in Reducing Data Dimensions and its Application to Human Development Dimension Indicators Data Zubedi, Fahrezal; Sumertajaya, I Made; Notodiputro, Khairil Anwar; Syafitri, Utami Dyah
Inferensi Vol 7, No 3 (2024)
Publisher : Department of Statistics ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j27213862.v7i3.21506

Abstract

Analysis of human development growth at the regency/city level is challenging because the data is high-dimensional, indicators are correlated, and the regencies/cities are correlated. In this study, we propose a Generalized Principal Component Analysis to analyze human development growth by reducing the dimensions of regency/city and indicator. Thus, human development growth at the regency/city level is analyzed using the GPCA results in Biplot to describe each regency/city and its indicators. This study aims to evaluate GPCA in reducing the dimensionality of data whose observations are correlated, and indicators are correlated through simulation and empirical study; to analyze the growth of human development at the regency/city level based on the results of GPCA-Biplot. This research shows that GPCA works well in reducing data dimensions from correlated observations and correlated variables. Based on the results of the GPCA-Biplot visualization, the growth of human development in the Nduga regency from 2019 to 2022 showed significant fluctuations. Although some indicators show progress, especially in 2021, significant challenges remain. In the same way, the growth of human development in each regency/city can be analyzed. Thus, government policy focuses on real problems in the field.
Co-Authors A Kurnia A. A. Mattjik AA Mattjik Abd. Rasyid Syamsuri Abdu Alifah Abdul Aziz Nurussadad Ade Gusalinda Adelia Putri Pangestika Agus Mohamad Soleh Agustin Faradila Ahmad Anshori Mattjik Ahmad Ansori Matjjik Ahmad Ansori Mattjik Ahmad Ansori Mattjik Aidi, Muhammad N Aini, Febri Nur Aji Hamim Wigena Akbar Rizki Alfian Futuhul Hadi Alwani, Nadira Nisa Amanda Permata Dewi Anang Kurnia Andi Setiawan Andrew Donda Munthe Anggraini Sukmawati Anik Djuraidah Arina, Faula Aropah, Vina Da'watul Aropah, Vina Da’watul ASEP SAEFUDDIN Astari, Reka Agustia Azagi, Ilham Alifa Azis, Irfani Bagus Sartono Budi Susetyo Budi Susetyo Choirun Nisa Chrisinta, Debora Cici Suhaeni Cynthia Wulandari Dede Dirgahayu Domiri Dede Dirgahayu Domiri, Dede Dirgahayu Dian Kusumaningrum Dian Kusumaningrum Diki Akhwan Mulya Doni Suhartono Dwi Agustin Nuriani Sirodj Dwi Yulianti Embay Rohaeti Emeylia Safitri Erfiani Erfiani Erfiani Erfiani, Erfiani Erwina Erwina Evita Choiriyah Fadilah, Anggita Rizky FAHREZAL ZUBEDI Fahriya, Andina Faqih Udin dan Jono M. Munandar Meivita Amelia Farit M Afendi Farit Mochamad Afendi Fitria Hasanah Fitrianto, Anwar Gusti Tasya Meilania Halimatus Sa'diyah Hari Wijayanto Haryastuti, Rizqi Hengki Muradi Hidayat, Agus Sofian Eka Hilda Zaikarina Huda, Usep Firdaus I Gede Nyoman Mindra Jaya Ilma Nabila Ilmani, Erdanisa Aghnia Imam Adiyana Indahwati Indonesian Journal of Statistics and Its Applications IJSA Iqbal, Teuku Achmad Irfani Azis Irfani Azis Ismah, Ismah Isti Rochayati Itasia Dina Sulvianti Jamaluddin Rabbani Harahap Jasiulewicz, Anna Khairil Anwar Notodiputro Kurnia, A Kusdaniyama, Nunung Kusman Sadik Laradea Marifni Lestari P, Merryanty Linda Sakinah M. Syamsul Maarif Ma'mun Sarma Manuel Leonard Sirait Manuel Leonard Sirait Manuel Leonard Sirait Mattjik, AA Maulida, Annisaturrahmah Mega Pradita Pangestika Meilania, Gusti Tasya Merryanty Lestari P Mintarto Mundandar, Jono Muhamad Nur Aidi Muhammad Amirullah Yusuf Albasia Muhammad N Aidi Muhammad Nur Aidi Muhammad Ulinnuha Mulianto Raharjo Munanda, Jono Mintarto Muradi, Hengki Newton Newton Nina Valentika Ningsih, Wiwik Andriyani Lestari Noercahyo, Unggul Sentanu Novi Hidayat Pusponegoro Nunung Kusdaniyama Nunung Kusdaniyama Nur Hikmah Nurlia Eka Damayanti Nurus Sabani Pasaribu, Sahat M. Pepi Novianti Pika Silvianti Pratiwi, Windy Ayu Pratiwi, Windy Ayu Pudji Muljono Purwaningsih, Siti Samsiyah Puspasari, Novia Rahardiantoro, Septian Rahma Anisa Rahma Anisa Rhesa Adisty, Mohamad Risnawati, I'lmisukma Rizqi Haryastuti Sahat M. Pasaribu Sarah Fadhlia Sarma, Ma’mun Satria Yudha Herawan SATRIYAS ILYAS Setyono Setyono Setyono Sirait, Manuel Leonard Siti Samsiyah Purwaningsih Sri Surjani Tjahjawati Sunardi Sunardi Sunardi Suruddin, Adzkar Adlu Hasyr Sutomo, Valantino A Syafitri, Utami Syella Sumampouw Tsabitah, Dhiya Tsabitah, Dhiya Ulayya Ulfah Sulistyowati Utami Dyah Syafitri Valantino A Sutomo Valentika, Nina Wibowo, Dwi Yoga Ari Winda Nurpadilah Windi D.Y Putri Wiwik Andriyani Lestari Ningsih Yenni Angraini Yoga, Ibnu Abi Zulkarnain, Rizky