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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 CAUCHY: Jurnal Matematika Murni dan Aplikasi 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 Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) 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) 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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Factors Influencing Informal Workers’ Registration for Social Security: A Comparative Analysis Between Indonesia and Taiwan Rhesa Adisty, Mohamad; Mintarto Mundandar, Jono; Sumertajaya, I Made
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.9.2.523

Abstract

Social security should be mandatory for all members of society to protect them from social risks, including the informal workers who are particularly vulnerable to such risks. However, the coverage of social security for informal workers in Indonesia remains very low. Therefore, the study aims to identify the factors that drive informal workers' desire to enroll in social security programs. The Theory of Planned Behavior will be utilized as a tool to uncover these factors. The study will compare the findings with the policies implemented in Indonesia and Taiwan as a comparison for countries with extensive social security coverage. The research sample is determined by using purposive sampling method with 100 respondents participated in this study. Data are examined by using structural equation model - partial least square (SEM-PLS). The results show that Attitude Toward Behavior and Perceived Behavioral Control have a significant impact on the intention of informal workers to join social security programs, while subjective norms have not been proven to have a significant impact. In conclusion, Indonesia needs to review its current policies, which primarily focus on subjective norms, and learn from Taiwan's successful implementation of broad social security coverage. Transforming informal labor into formal employment can be an effective strategy for achieving this goal. Keywords: social security, informal worker, sem-pls, theory of planned behavior
Voters’ Perceptions of Mayoral Candidates’ Personal Characteristics in the 2024 Bogor Mayoral Election Aini, Febri Nur; Munanda, Jono Mintarto; Sumertajaya, I Made
Asian Journal of Social and Humanities Vol. 4 No. 2 (2025): Asian Journal of Social and Humanities
Publisher : Pelopor Publikasi Akademika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59888/wb5d0657

Abstract

  This study examines voters’ perceptions of the personal characteristics of mayoral candidates in the 2024 Bogor mayoral election. Using survey data collected from voters, the analysis focuses on fifteen character attributes, including sociability, communication skills, decisiveness, trustworthiness, responsibility, integrity, and competence. Descriptive analysis was employed to compare positive and negative perceptions across five candidates. The results indicate that all candidates were perceived very positively across most attributes. Characteristics related to leadership and integrity—such as decisiveness, honesty, responsibility, intelligence, and consistency—received exceptionally high positive evaluations, reaching 100 percent for several candidates. Candidates with larger numbers of respondents exhibited more consistent and stable positive perceptions across all indicators. In contrast, candidates with fewer respondents showed relatively higher negative perceptions, particularly in communication-related attributes, suggesting variability in public image formation. Overall, the findings highlight the importance of personal character dimensions in shaping voter perceptions in local elections. Voters tend to favor candidates perceived as credible, competent, and emotionally stable, underscoring the role of character-based evaluations in influencing electoral preferences in the 2024 Bogor mayoral election.
Comparison of ARIMA, LSTM, and Ensemble Averaging Models for Short-Term and Long- Term Forecasting of Non-Stationary Time Series Data Pratiwi, Windy Ayu; Sumertajaya, I Made; Notodiputro, Khairil Anwar
Inferensi Vol 8, No 3 (2025)
Publisher : Department of Statistics ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j27213862.v8i3.22643

Abstract

This study aims to forecast the highest weekly selling rate of the Indonesian Rupiah (IDR) against the US Dollar (USD) and identify the most accurate model among ARIMA, LSTM, and Ensemble Averaging. The evaluation results indicate that ARIMA achieves an accuracy of 97.75%, demonstrating strong performance in short-term forecasting, while LSTM achieves 99.98% accuracy, excelling in capturing complex and dynamic patterns in long-term predictions. The Ensemble Averaging approach attains the highest accuracy of 99.99%, proving to be the optimal solution by combining ARIMA’s stability with LSTM’s adaptability, resulting in more precise and stable predictions. The findings of this study highlight that the ensemble approach is more effective than individual models, as it balances accuracy and prediction stability across various forecasting scenarios. This method serves as a reliable tool for addressing market volatility and contributes significantly to the advancement of financial and economic forecasting techniques that are more adaptive and accurate.
Support vector machine performance: simulation and rice phenology application Muradi, Hengki; Saefuddin, Asep; Sumertajaya, I Made; Soleh, Agus Mohamad; Domiri, Dede Dirgahayu
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 14, No 6: December 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v14.i6.pp4878-4890

Abstract

In the case of classification, model accuracy is expected to result in correct predictions. This study aims to analyze the performance of two kinds of support vector machine (SVM) methods: the support vector machine one versus one (SVM OvO) method and the generalized multiclass support vector machine (GenSVM) method. This method will compare to the generalized linear model, namely the multinomial logistic regression (MLR) method. Simulations were conducted using SVM OvO and GenSVM methods to get an overview of the parameters affecting both methods' performance. Furthermore, the three classification methods are implemented in the case of modelling the rice phenology and tested for performance. Simulation results show that, however, the SVM OvO and GenSVM machine learning methods are sensitive to the choice of model parameters. The empirical study results show that the SVM OvO and GenSVM methods can produce satisfactory model accuracy and are comparable to the MLR method. The best rice phenology model accuracy was obtained from the SVM OvO model, where 79.20 ± 0.21 overall accuracy and 70.69 ± 0.29 kappa were obtained. This research can be continued by handling samples, especially when class members are a minority, and can also add random effects to the SVM model.
Dampak Gig Economy terhadap Kinerja Sosial dan Lingkungan pada Sektor Transportasi Daring: Perbandingan Perspektif Perusahaan Platform dan Mitra Driver Yoga, Ibnu Abi; Maarif, Mohamad Syamsul; I Made Sumertajaya
Jurnal Ilmiah Global Education Vol. 6 No. 4 (2025): JURNAL ILMIAH GLOBAL EDUCATION
Publisher : LPPM Institut Pendidikan Nusantara Global

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55681/jige.v6i4.4527

Abstract

This study aims to analyze the impact of the gig economy on social and environmental performance in the online transportation platform sector in the Greater Jakarta area by comparing the perspectives of platform companies and gig workers (driver partners). This study uses a case study design with a mixed method combining Likert scale questionnaires and in-depth interviews. The respondents consist of 183 platform company employees and 101 driver partners from various online transportation companies. Data analysis was conducted using descriptive statistical approaches and Structural Equation Modeling–Partial Least Squares (SEM–PLS). The results indicate that the gig economy significantly impacts social and environmental performance from both perspectives, though with differing levels of perception. Driver partners tend to experience stronger positive impacts regarding work flexibility, income opportunities, and involvement in environmental efforts, yet they still face challenges such as income instability, limited job protection, and unequal access to social programs. Platform companies acknowledge the gig economy's contribution to social and environmental aspects, though with a more moderate assessment. These findings underscore the importance of integrating social and environmental dimensions into core business strategies, as well as the need to incorporate driver partners' input to strengthen the sustainability and inclusivity of the gig economy ecosystem in the future.
Spatiotemporal Clustering of Key Food Commodity Prices Using Multivariate Time Series Tsabitah, Dhiya Ulayya; Angraini, Yenni; Sumertajaya, I Made
International Journal of Advances in Data and Information Systems Vol. 6 No. 3 (2025): December 2025 - International Journal of Advances in Data and Information Syste
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59395/ijadis.v6i3.1422

Abstract

Food price stabilization remains a critical challenge in economic development planning and food security, particularly in developing countries like Indonesia, which exhibit high spatial and temporal diversity. To develop an efficient and adaptive predictive approach for understanding food commodity price dynamics, this study integrates multivariate time series clustering using a Dynamic Time Warping-based K-Means algorithm with a hybrid forecasting model that combines Vector Error Correction Model with Exogenous Variables and Long Short-Term Memory. The clustering evaluation results indicate reasonably cohesive group structures, with a silhouette score of 0.45 and a Davies-Bouldin Index of 0.67. Each cluster profile reveals significant differences in price trends, volatility, and anomaly patterns. Model validation using the Wilcoxon signed-rank test shows that the differences between cluster-level forecasts and individual-level actual values are generally statistically insignificant. These findings suggest that the proposed integrative approach can accurately capture regional price patterns and serve as a foundation for more data-driven and responsive policymaking in food price stabilization efforts. The 30-period forecasts for rice, eggs, and red onions reflected dynamic variations aligned with spatial characteristics: rice shows relatively stable behavior, eggs exhibit strong seasonal patterns, and red onions display the highest price volatility.
Pemetaan Penelitian Resiliensi Organisasi pada Pendidikan Tinggi: Sebuah Analisis Bibliometrik Mulya, Diki Akhwan; Sumertajaya, I Made; Sukmawati, Anggraini
Jurnal Manajemen dan Organisasi Vol. 16 No. 3 (2025): Jurnal Manajemen dan Organisasi
Publisher : IPB University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/jmo.v16i3.67868

Abstract

Organizations are confronted with multiple uncertainties and unexpected changes, requiring them to survive and adapt in order to achieve long-term success. One strategic approach that has increasingly attracted scholarly attention is the strengthening of organizational resilienceNevertheless, academic studies on organizational resilience within the higher education sector continue to exhibit diverse developmental patterns and therefore require comprehensive mapping. This study adopts a bibliometric approach using data retrieved from the Scopus database. Articles were collected using the keyword string “organizational_resilience_AND_higher_education” within the subject areas of business, management, and accounting. All data were analyzed using VOSviewer software to map publication trends, author networks, institutional affiliations, and keyword interrelationships. The results reveal that the highest number of publications occurred in 2021, with a total of 50 articles. The most productive institutional affiliation was Technische Universität Dresden, with five publications. Furthermore, keywords with the highest total link strength included industry, COVID, organizational resilience, and technology. Author network analysis identified 14 interconnected authors within collaborative research clusters. These findings indicate a growing academic focus on organizational resilience in the higher education sector, particularly in response to global challenges such as the COVID-19 pandemic and technological transformation.
Perbandingan Metode GWR, MGWR, dan MGWR-SAR pada Data Persentase Penduduk Miskin di Pulau Jawa Andina Fahriya; Budi Susetyo; I Made Sumertajaya
Limits: Journal of Mathematics and Its Applications Vol. 22 No. 2 (2025): Limits: Journal of Mathematics and Its Applications Volume 22 Nomor 2 Edisi Ju
Publisher : Pusat Publikasi Ilmiah LPPM Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/limits.v22i2.3057

Abstract

The primary goal of Sustainable Development Goals (SDGs) is to end poverty everywhere in all its forms. Poverty is defined as the inability to meet basic needs, such as food, clothing, shelter, education, and healthcare. In Indonesia, the poor population has reached 26.36 million people, with half of them residing on Java Island. Extensive research has been conducted on poverty, particularly using a spatial approach. Spatial regression is a statistical method that explicitly incorporates geographical aspects into a model framework. In spatial regression, two main challenges arise: spatial dependence and heterogeneity. These two effects are inherently interconnected and must be considered simultaneously. Mixed Geographically Weighted Regression with Spatial Autoregressive (MGWR-SAR) is a combination of Mixed Geographically Weighted Regression (MGWR) and Spatial Autoregressive (SAR). MGWR-SAR effectively addresses both spatial dependence and spatial heterogeneity simultaneously. This study aims to determine the best method for modeling the percentage of poor population on Java. The variables used included PPM, BPJSPBI, PPKM, PLSMP, PPTB, BPNT, NCPR, and IPM. The kernel function was selected based on the smallest cross-validation (CV) value, which was a Fixed Gaussian with a CV of 603.8268. Based on the GWR model, the global variables identified were PPTB, BPNT, and IPM, whereas the remaining variables were local. The MGWR-SAR method was found to be the best model for predicting the percentage of poor population, with an AIC = 448.9645, RMSE = 1.9075, and  = 75.23%.
Evaluasi Kinerja Spectral Biclustering dalam Identifikasi Potensi Produksi Komoditas Hortikultura di Indonesia Merryanty Lestari P; I Made Sumertajaya; Erfiani
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

Biclustering merupakan metode penggerombolan dua arah untuk menemukan subset baris dan kolom dari suatu matriks data. Spectral biclustering merupakan salah satu algoritma dari biclustering. Algoritma spectral mempunyai tiga metode normalisasi matriks antara lain independent rescaling of rows and columns , bistochastization , dan log . Penerapan spectral biclustering bertujuan untuk mengidentifikasi potensi produksi komoditas hortikultura jenis sayuran di Indonesia. Metode normalisasi bistochastization menghasilkan bicluster optimal dengan nilai rataan mean squared residue terkecil sebesar 0,079593. Bicluster yang dihasilkan sebanyak 5 bicluster. Bicluster 1 dan 2 terdiri dari wilayah Papua dan Sulawesi Tenggara memiliki potensi produksi jenis tanaman sayuran mayoritas kategori rendah di antaranya kentang, bawang merah, bawang putih, dan bawang daun. Bicluster 3 dan 4 terdiri dari sebagian besar wilayah Kalimantan, Riau, Sumatera Selatan, Nusa Tenggara Timur, dan Maluku dengan potensi produksi mayoritas terkategori sedang di antaranya cabai rawit, tomat, buncis, labu siam, dan melinjo. Bicluster 5 merupakan wilayah Jawa, Bali, Nusa Tenggara Barat, sebagian besar wilayah Sumatera dan Sulawesi, serta Kalimantan Selatan. Bicluster 5 memiliki potensi produksi terkategori tinggi pada jenis sayuran sawi, kacang panjang, terung, ketimun, dan jengkol.
Evaluation of Imputation Methods for Clustering Categorical Time Series on Financial Sector Stock Data Rita Rahmawati; I Made Sumertajaya; Asep Saefuddin; Kusman Sadik
Journal of Mathematics, Computations and Statistics Vol. 9 No. 2 (2026): Volume 09 Issue 02 (June 2026)
Publisher : Jurusan Matematika FMIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/Jmathcos12460

Abstract

Missing values in financial time series data can affect the information structure of the data and impact the clustering results obtained. This research aims to evaluate the performance of several time series data imputation methods on the quality of categorical time series clustering on financial sector stock data on the Indonesia Stock Exchange. The imputation methods compared include linear interpolation, spline interpolation, and Kalman smoothing. The research data is in the form of daily closing prices of 92 financial sector stocks for the period 2 January 2023 to 31 October 2025. Numerical clustering was carried out using K-Means Time Series based on Dynamic Time Warping (DTW), while categorical clustering was carried out using K-Medoids with the Gower distance measure in two categorization schemes, namely five and seven categories. Evaluation of suitability between numerical and categorical clustering was carried out using the Rand Index (RI), Fowlkes–Mallows Index (FMI), and Jaccard Index. The research results show that the imputation method produces different clustering qualities. Linear interpolation provides the best and most consistent performance compared to other methods, especially in the seven-category scheme with an RI value of 0.6417, FMI of 0.4338, and Jaccard Index of 0.3256. These results show that linear interpolation is better able to maintain the information structure of the data in the categorical time series clustering process compared to spline interpolation or Kalman smoothing.
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 Andina Fahriya 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 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 Erwina Evita Choiriyah Fadilah, Anggita Rizky FAHREZAL ZUBEDI Faqih Udin dan Jono M. Munandar Meivita Amelia Farit M Afendi Farit Mochamad Afendi Fitria Hasanah Fitrianto, Anwar Gerry Alfa Dito 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 Indah Ratih Anggriyani 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 Luh Putu Widya Adnyani 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 Rita Rahmawati 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 Windy Ayu Pratiwi Wiwik Andriyani Lestari Ningsih Yani Prihantini Hiola Yenni Angraini Yoga, Ibnu Abi Zulkarnain, Rizky