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All Journal Jurnal Ilmu Pertanian Indonesia Jurnal Manajemen dan Agribisnis FORUM STATISTIKA DAN KOMPUTASI Jurnal Ekonomi Pembangunan Indonesian Journal of Geography IJCCS (Indonesian Journal of Computing and Cybernetics Systems) ETIKONOMI EKSAKTA: Journal of Sciences and Data Analysis MATRIK: JURNAL MANAJEMEN, STRATEGI BISNIS, DAN KEWIRAUSAHAAN Media Statistika Sosiohumaniora Statistika Techno.Com: Jurnal Teknologi Informasi CAUCHY: Jurnal Matematika Murni dan Aplikasi TELKOMNIKA (Telecommunication Computing Electronics and Control) Indonesian Journal of Business and Entrepreneurship (IJBE) Jurnal Berkala Ilmu Perpustakaan dan Informasi Jurnal Teknologi Informasi dan Ilmu Komputer JUITA : Jurnal Informatika Jurnal Aplikasi Bisnis dan Manajemen (JABM) E-Journal Scientific Journal of Informatics Journal of Consumer Science CESS (Journal of Computer Engineering, System and Science) Jurnal Ilmiah Arena Tekstil MIX : Jurnal Ilmiah Manajemen JOIN (Jurnal Online Informatika) Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) International Journal of Artificial Intelligence Research Asia-Pacific Management and Business Application Knowledge Engineering and Data Science MAJALAH ILMIAH GLOBE Matra Pembaruan: Jurnal Inovasi Kebijakan Seminar Nasional Variansi (Venue Artikulasi-Riset, Inovasi, Resonansi-Teori, dan Aplikasi Statistika) Informatika Pertanian CogITo Smart Journal Inovasi : Jurnal Ekonomi, Keuangan, dan Manajemen Indonesian Journal of Artificial Intelligence and Data Mining JEPA (Jurnal Ekonomi Pertanian dan Agribisnis) Albacore : Jurnal Penelitian Perikanan Laut BAREKENG: Jurnal Ilmu Matematika dan Terapan Jurnal Organisasi Dan Manajemen JOURNAL OF APPLIED INFORMATICS AND COMPUTING JTAM (Jurnal Teori dan Aplikasi Matematika) Jambura Journal of Mathematics Journal of Humanities and Social Studies International Journal of Remote Sensing and Earth Sciences (IJReSES) Aptisi Transactions on Technopreneurship (ATT) STI Policy and Management Journal Jurnal Aplikasi Statistika & Komputasi Statistik TELKA - Telekomunikasi, Elektronika, Komputasi dan Kontrol Jurnal Administrasi dan Manajemen Jurnal Matematika UNAND Variance : Journal of Statistics and Its Applications Ecces: Economics, Social, and Development Studies International Journal of Zakat (IJAZ) Indonesian Journal of Electrical Engineering and Computer Science Inferensi InPrime: Indonesian Journal Of Pure And Applied Mathematics International Journal of Science, Engineering and Information Technology Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Jurnal Statistika dan Aplikasinya Dinasti International Journal of Economics, Finance & Accounting (DIJEFA) Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi SRIWIJAYA JOURNAL OF ENVIRONMENT Jurnal Natural Xplore: Journal of Statistics STATISTIKA Jurnal Informatika: Jurnal Pengembangan IT PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON DATA SCIENCE AND OFFICIAL STATISTICS Jurnal Ekonomi dan Pembangunan Indonesia The Indonesian Journal of Computer Science Journal of Mathematics, Computation and Statistics (JMATHCOS) Journal of International Accounting, Taxation and Information Systems Indonesian Journal of Statistics and Its Applications Diophantine Journal of Mathematics and Its Applications Khazanah Informatika : Jurnal Ilmu Komputer dan Informatika Warta Penelitian Perhubungan The International Journal of Remote Sensing and Earth Sciences (IJReSES) Teknobuga : Jurnal Teknologi Busana dan Boga Scientific Contributions Oil and Gas
Bagus Sartono
Departmen Statistika Institut Pertanian Bogor Gedung IPB Dramaga, Jl. Meranti Wing 22 Lantai 2 Kampus IPB Darmaga Bogor (16680) Indonesia Phone: +62-811-118-508
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Making Sense of Fashion Feedback : Comparing Two Popular Text Analysis Tools Muhammad Syafiq; Wawan Saputra; Carlya Agmis Aimandiga; Cici Suhaeni; Bagus Sartono; Gerry Alfa Dito
TEKNOBUGA: Jurnal Teknologi Busana dan Boga Vol. 13 No. 1 (2025)
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/teknobuga.v13i1.25930

Abstract

The rapid expansion of the fashion industry, propelled by digital technology and e-commerce, has resulted in a significant volume of customer-generated reviews. These reviews serve as a valuable source for understanding customer satisfaction and behavior. This study aims to (1) analyze customer sentiment, (2) predict product recommendations, and (3) examine the relationship between sentiment classification and recommendation decisions using text embeddings from Word2Vec and GloVe. The research utilized over 23,000 fashion product reviews sourced from Kaggle. Text data were preprocessed and vectorized using Word2Vec and GloVe, followed by classification and prediction tasks using six machine learning models: Random Forest, SVM, Naïve Bayes, LSTM, Logistic Regression, and Gradient Boosting. The results revealed that Word2Vec consistently outperformed GloVe across all models and tasks, with the Word2Vec-LSTM combination achieving the highest accuracy of 87.35% and F1 score of 92.35% in imbalanced data scenarios. Correlation analysis also confirmed a strong and statistically significant relationship between sentiment and recommendation labels, with Spearman’s Rho of 0.8340 and Kendall’s Tau of 0.8120. These findings suggest that high-quality sentiment representation can effectively support product recommendation systems. This study contributes to the understanding of embedding effectiveness in fashion-related text analysis and opens avenues for hybrid and transformer-based representations in future research.
Strategy Formulation of Natural Gas Continuity Supply (Case Study PT ABC) Dhanu Saptowulan; Idqan Fahmi; Bagus Sartono
Scientific Contributions Oil and Gas Vol 45 No 1 (2022)
Publisher : Testing Center for Oil and Gas LEMIGAS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29017/SCOG.45.1.921

Abstract

This study aims to formulate a strategy for PT ABC in maintaining the continuity of natural gas supply. Feasibility analysis and decision tree method are used to determine the chosen strategy in maintaining the continuity of natural gas supply. Internal and external analysis are used to identify the key success factors of the company in implementing the chosen strategy and then summarized and evaluated using IFE and EFE matrix. To formulate implementation strategies by aligning key internal and external factors, IE and SWOT matrix are used. QSPM matrix is used to determine the priority of the implementation strategy. The results show IFE and EFE score are 2.55 and 2.76 respectively, so that PT ABC has suffi cient internal resources to maintain the continuity of natural gas supply and able to respond well to opportunities and threats. This condition can be managed best with hold and maintain strategies which are market penetration and product development. QSPM Matrix analysis show that product development group strategy has the highest Total Attractiveness Score (TAS) thus become priority to be executed and then market penetration strategy.
Examining the Influence of Women's Leadership and Flexible Working Arrangements on Employee Performance Across Generations in Startups Desi Prabandari Kusuma Ningtyas; Sukmawati, Anggraini; Sartono, Bagus
APMBA (Asia Pacific Management and Business Application) Vol. 14 No. 2 (2025)
Publisher : Department of Management, Faculty of Economics and Business, Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.apmba.2025.014.02.1

Abstract

Startups, as rapidly growing and dynamic organizations, face unique challenges in managing human resources, especially regarding generational diversity and the need for work flexibility. In this regard, the adoption of flexible working arrangements and women’s leadership are crucial elements thought to enhance employee performance. This study collected data through a questionnaire with 140 respondents. A quantitative method with descriptive analysis was used to depict the questionnaire data filled out by respondents and Structural Equation Modelling (SEM-PLS) was applied to analyse the relationships among the variables studied. This research examines the influence of women’s leadership and flexible working arrangements on employee performance while positioning a multigenerational workforce as a moderating factor within the proposed relationships. The results demonstrate that both women’s leadership and flexible working arrangements (FWA) each exert a positive influence on employee performance. Multigenerational does not moderate the relationship between women’s leadership and performance, indicating that leadership qualities such as inclusiveness, empathy and collaboration are broadly valued across generations. In contrast, multigenerational moderates flexible working arrangements on employee performance, highlighting the role of work flexibility in accommodating differing expectations and work preferences among employees from various generational backgrounds.
Integrating Support Vector Regression and Kriging in Spatial Interpolation of Statistical Seismicity Parameters Sirodj, Dwi Agustin Nuriani; Aidi, Muhammad Nur; Sartono, Bagus; Syafitri, Utami Dyah; Pranata, Bayu
Indonesian Journal of Geography Vol 57, No 3 (2025): Indonesian Journal of Geography
Publisher : Faculty of Geography, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijg.102153

Abstract

Spatial interpolation methods, such as Inverse Distance Weighting (IDW) and kriging, are commonly used in various fields. In Kriging method, semivariogram fitting is an important step, where empirical data are used to derive a theoretical model. However, when the known theoretical semivariogram model does not provide a satisfactory fit, the bias in the estimated values is increased. To address this limitation, Support Vector Regression (SVR) can be used to model the empirical semivariogram with a machine-learning method. This method has been applied in ordinary kriging interpolation for semivariogram fitting to estimate parameters related to the potential occurrence of earthquake. Specifically, the calculated parameters, based on the Gutenberg-Richter law, include the seismic activity (a-value) and rock fragility (b-value) in the Sumatera region. The results showed that SVR can model the empirical semivariogram better than the theoretical. The integration of SVR-Ordinary Kriging provides the best performance compared to other methods, such as IDW, with the smallest RMSEP values for both the b-value and a-value measuring 0.1378 and 0.7423, respectively. Aceh and Mentawai Islands tend to show low a and b values, suggesting that these areas are more vulnerable to earthquake with large magnitudes.
Sustainability Strategy of PT XYZ in Entering the Blue Ammonia Industry in Indonesia Zulmi, Muhammad Indra; Zulbainarni, Nimmi; Sartono, Bagus
Journal of International Accounting, Taxation and Information Systems Vol. 2 No. 4 (2025): November
Publisher : CV. Proaksara Global Transeduka

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70865/jiatis.v2i4.142

Abstract

Blue ammonia is emerging as a critical transitional solution in the global energy transition, with market volumes projected to grow from 1.1 million tons in 2023 to 9.2 million tons by 2028, and Indonesia has positioned it as a key pillar of its net-zero strategy by 2060. This article analyses the sustainability strategy of PT XYZ, an Indonesian integrated energy and chemical company, in entering the blue ammonia industry. Produced from natural gas with carbon capture and storage (CCS), blue ammonia offers a decarbonisation pathway for hard-to-abate sectors. PT XYZ is converting an existing ammonia plant but faces challenges including CCS costs, gas-price volatility, financing needs, and stringent international standards. The study aims to (1) map external opportunities and threats, (2) assess PT XYZ's internal resources and capabilities, and (3) formulate sustainability-oriented strategic alternatives. A mixed-method approach combines PESTLE and Porter's Five Forces analyses with Resource-Based View and VRIO assessment, followed by SWOT and TOWS synthesis using document review, interviews, focus groups, and expert questionnaires. Findings shed light that PT XYZ operates in a supportive yet demanding environment, possessing strengths in HSE culture, gas procurement, CCS design, MRV readiness, and contract management, alongside gaps in equity gas, CCS agreements, blended finance, and anchor contracts. The resulting SO, WO, ST, and WT strategies provide a roadmap for de-risking investment, securing premium markets, and aligning with long-term decarbonisation goals.
Analysis of Household Risk Factors Associated with Food Anxiety Using Boosting-Based Machine Learning Methods Nisa Nur Aisyah; Rupmana Br Butar; Mega Ramatika Putri; Lisa Amelia; Bagus Sartono; Aulia Rizki Firdawanti
Journal of Mathematics, Computations and Statistics Vol. 9 No. 1 (2026): Volume 09 Issue 01 (March 2026)
Publisher : Jurusan Matematika FMIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/nz9epj83

Abstract

Food anxiety represents an early psychological indicator of household food insecurity and is influenced by economic vulnerability, household characteristics, and unstable access to food. West Java, as Indonesia’s most populous province, faces substantial socio-economic disparities that heighten the risk of food insecurity. Using SUSENAS 2024 data, this study aims to classify household food anxiety and evaluate the predictive performance of three boosting algorithms XGBoost, LightGBM, and CatBoost. The dataset exhibits a strong class imbalance, with only 19.1% of households categorized as food anxious, prompting the application of SMOTE and Winsorization during preprocessing. SMOTE considerably improved model performance, particularly in balanced accuracy. For XGBoost, balanced accuracy increased sharply from 0.5199 to 0.8738, while LightGBM experienced a similar improvement from 0.5261 to 0.8736. Winsorization produced only marginal additional effects. Across all scenarios, XGBoost demonstrated the highest overall performance, followed closely by LightGBM, whereas CatBoost showed limited ability to detect minority-class households. These findings underscore the effectiveness of boosting algorithms especially XGBoost enhanced by SMOTE in identifying food-anxious households and supporting data-driven, targeted food security interventions in West Java.
Evaluation of Tree-Based Models for Predicting Social Assistance Recipient Status Based on National Socio-Economic Survey (SUSENAS) 2024 Yani Prihantini Hiola; Zulhijrah; I Gusti Ngurah Sentana Putra; Syella Zignora Limba; Bagus Sartono; Aulia Rizki Firdawanti; Budi Susetyo; Gerry Alfa Dito
Journal of Mathematics, Computations and Statistics Vol. 9 No. 1 (2026): Volume 09 Issue 01 (March 2026)
Publisher : Jurusan Matematika FMIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/xyyv0f37

Abstract

Abstract. Poverty is a major socioeconomic challenge in Indonesia that affects the effectiveness of social protection programs. In response to this challenge, the government has created social assistance programs to improve the welfare of the people. However, the distribution of social assistance is often considered to be inaccurate, resulting in households that are deemed eligible for social assistance not being identified as recipients. One solution to improve the accuracy of distribution is the application of machine learning in the context of classification. Several tree-based models, such as LightGBM, Random Forest, and XGBoost, were selected because of their superior capabilities compared to classical models such as logistic regression, especially in handling complex data and fulfilling model assumptions. This study compares the performance of these three models in predicting social assistance recipient status using data from the 2024 West Java Provincial National Socioeconomic Survey (SUSENAS). Model evaluation was conducted on several data pre-processing scenarios involving outlier handling, class balancing, and feature engineering. The results show that LightGBM consistently outperforms the other models on six metrics, namely Accuracy, Balanced Accuracy, F1-Score, ROC-AUC, PR-AUC, and Brier Score, out of a total of eight evaluation metrics used. SHAP analysis identifies Social Assistance History and Asset Score as the most influential features for model prediction. Friedman and Nemenyi nonparametric tests confirmed significant performance differences between LightGBM and other models based on the F1-Score, PR-AUC, and Brier Score metrics. These findings indicate that tree-based models, particularly LightGBM, can support the development of a more targeted and data-driven social assistance targeting system. Keywords: Social Assistance; Tree-Based; SHAP; SUSENAS; Hybrid Bayesian Optimization
Technical Analysis of the Indonesian Stock Market with Gated Recurrent Unit and Temporal Convolutional Network Siti Aisyah; Yenni Angraini; Kusman Sadik; Bagus Sartono; Gerry Alfa Dito
JUITA: Jurnal Informatika JUITA Vol. 12 No. 2, November 2024
Publisher : Department of Informatics Engineering, Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30595/juita.v12i2.23464

Abstract

Big data is essential in the age of 4.0 industry as it becomes the basis of decision making. Deep learning research in the last few years has been proven effective in understanding complex big data patterns, especially in the finance sector. The rapid growth of the Indonesian stock market in the last 20 years, which was driven by globalization, prompted fluctuation in the Bursa Efek Jakarta (JKSE) which was influenced by stock prices, commodity prices, and exchange rate. This study identifies the main indicators of Indonesian stock market crisis, applies and compares deep learning models, particularly Gated Recurrent Unit (GRU) and Temporal Convolutional Network (TCN), in predicting stock prices. This study identified 20 JKSE crisis points between the 2002-2023 period with average return value at around -6%. All variables correlated positively with JKSE, with SET.BK as the highest correlated variable in lag 0. The American and European stock market, commodity price, and exchange rate tend to show a pattern opposite to the JKSE crisis. Predictor variables such as STI, HIS, KLSE, KS11, SET.BK, PSEI.PS, RUT, and USDIDR are chosen based on significant cross correlation and average return plot. Hyperparameter tuning and cross validation within a 3 years window concluded that the GRU model is accurate and efficient, with RMSE value at 43.35568 and MAE value at 33.66909 in the validation data.
Enhancing Employee Innovation Through Digital Talent Development: The Mediation of Digital Competency, Leadership and Culture in the Telecom Industry Fauziah, Nadira Aribah; Sukmawati, Anggraini; Sartono, Bagus
Dinasti International Journal of Economics, Finance & Accounting Vol. 7 No. 1 (2026): Dinasti International Journal of Economics, Finance & Accounting (March-April 2
Publisher : Dinasti Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38035/dijefa.v7i1.6448

Abstract

In the digital economy, innovation is a strategic imperative for sustaining organizational competitiveness, with employees’ innovative work behavior serving as a crucial micro-level foundation. Accelerated technological change and skill disruption have intensified the need for systematic digital talent development. Despite increasing scholarly attention to digital talent management, empirical research remains limited in explaining how digital talent development interacts with digital leadership, digital competence, and digital culture to shape innovative work behavior. This study addresses this gap by examining the structural relationships among these digital enablers within the context of digital transformation in the telecommunications industry. This study adopts a quantitative approach using survey data collected from 189 certified digital talents across PT Telkom Indonesia. Structural Equation Modeling–Partial Least Squares was employed to test the hypothesized relationships and mediating mechanisms. The results demonstrate that digital talent development influences innovative work behavior through an integrated mediating mechanism involving digital leadership, digital competence, and digital culture. This study advances the digital transformation literature by clarifying the systemic role of organizational enablers in translating digital talent investments into employee-level innovation. It emphasizes the necessity of aligning talent development with leadership capability, competency, and cultural reinforcement to support sustainable innovation in digitally transforming organizations.
Identifying the Types of Future Skills Needed in The Manufacturing Industry: A Systematic Literature Review Kharismatul Zaenab Akhilla; Anggraini Sukmawati; Bagus Sartono
Jurnal Aplikasi Bisnis dan Manajemen Vol. 11 No. 3 (2025): JABM Vol. 11 No. 3, September 2025
Publisher : School of Business, Bogor Agricultural University (SB-IPB)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17358/jabm.11.3.1099

Abstract

Background: The advent of Industrial Revolution 4.0 has led to the need to redesign the jobs and skills required across various industries and markets. As the manufacturing industry has the most significant contribution to GDP, it has not escaped the impact of this revolution. The dynamics of industrial growth, which tend to fluctuate from year to year, are also significant indicators of the need for strategic efforts to enhance the sector's resilience and competitiveness. One step that can be taken is to identify the types of future skills required and relevant to the manufacturing industry to adapt to a changing environment. Purpose: This study aims to identify the types of future skills needed by the manufacturing industry through a systematic literature review approach in order to obtain a comprehensive overview of relevant and strategic skill trends. Design/methodology/approach: This research employed the Systematic Literature Review (SLR) method, adhering to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. SLR serves as a systematic approach to identifying, evaluating, and synthesizing relevant previous research results, thereby obtaining a comprehensive understanding of the future skills required in the manufacturing industry. In addition, thematic analysis was used to identify and interpret patterns or themes within a dataset, as well as to develop a conceptual model of the study's results. Findings/Results: 63 types of future skills were categorized into eight categories. The classification of future skills in this study consists of: 1) Interpersonal Skills, 2) Leadership and Management, 3) adaptive and resilient mindsets, 4) Higher-Order Thinking Skills, 5) Entrepreneurial and Business Skills, 6) Learning and Development; Social and Ethical Responsibility; and 8) Personal Effectiveness. Conclusion: This research highlights the importance of the manufacturing industry in adapting to the changing demands brought about by Industrial Revolution 4.0 through the development of future skills. This study identified 63 types of future skills. It classifies them into eight main categories, considering the similarity of concepts, interrelationships in their application in the workplace, and the role of each skill in supporting individual readiness to face future challenges. Originality/value: This study has substantial originality value because it fills a significant research gap related to future skills in the manufacturing industry context. The lack of previous studies that specifically address future skill needs in this sector indicates the need for further exploration to strengthen the scientific foundation while making practical contributions. Therefore, this study is the first step in identifying the types of future skills that are relevant and potentially applicable to the manufacturing industry in Indonesia. Keywords: future skills, manufacturing industry, soft skills, systematic literature review, thematic analysis
Co-Authors -, Salsabila Aam Alamudi Abdul Aziz Nurussadad Achmad Fauzan Achmad Fauzan, Achmad Achsani, Noer Azham Ade Agusti Alwinie Adi Hadianto, Adi Adinna Astrianti Afendi, Farit M Agus M Soleh Agus M Soleh Agus M. Sholeh Agus Mohamad Soleh Agusta, Madania Tetiani Agwil, Winalia Ain Fitri Basri Aji Hamim Wigena Akbar Rizki Alfa Nugraha Pradana Alfian Futuhul Hadi Alifviansyah, Kevin Alona Dwinata Alwinie, Ade Agusti Amanda, Nabila Tri Amatullah, Fida Fariha Amin, Toufiq Al Amir Abduljabbar Dalimunthe Anang Kurnia Andi Susanto Andrie Agustino Anggraini Sukmawati Ani Safitri Anik Djuraidah Anisa Nurizki Annisa Permata Sari Annissa Nur Fitria Fathina Anton Ferdiansyah Ardhani, Rizky Ardiansyah, Muhlis Arie Wahyu Wijayanto Arief Daryanto Arief Daryanto Arief Gusnanto Arif Imam Suroso Aris Yaman Aris Yaman Aristawidya, Rafika Aruddy Aruddy Asep Rusyana ASEP SAEFUDDIN Asfar Asrirawan, Asrirawan Aulia Rizki Firdawanti Aulia Rizki Firdawanti Aunuddin Aunuddin Auzi Asfarian Ayu Sofia Azlam Nas Bagus Randhyartha Gumilar Bariq, Muhammad Shidqi Abdul Barokaturrizkia Ameliani Bayu Indrayana Bayu Pranata Bayu Pranata, Bayu Bayu Suseno Beny Mulyana Sukandar Billy Bimandra Adiputra Djaafara Bonar Marulitua Sinaga Budi Susetyo Bukhari, Ari Shobri Cahya, Septa Dwi Carlya Agmis Aimandiga Cici Suhaeni Cici Suhaeni Cici Suhaeni Cintari, Nanda Putri Claudian Tikulimbong Tangdilomban Dani Al Mahkya Dede Dirgahayu Dede Dirgahayu Defri Ramadhan Ismana Deiby T Salaki Dela Gustiara Denanda Aufadlan Tsaqif Deni Achmad Soeboer Deri Siswara Desi Prabandari Kusuma Ningtyas Desi Prabandari Kusuma Ningtyas Dessy Rotua Natalina Siahaan Desy Endriani Dewi Margareth Lumbantoruan Dhanu Dhanu Saptowulan Dian Ayuningtyas Dian Handayani Dian Kusumaningrum Dito, Gerry Alfa Dwi Agustin Nuriani Sirodj Dwi Agustin Nuriani Sirodj Dwi Erzalianti Dwi Wahyu Triscowati Dyah Setyo Rini Eko Ruddy Cahyadi Embay Rohaeti Erfiani Erfiani Erliza Noor Erwan Setiawan, Erwan Etis Sunandi EVI RAMADHANI Evita Purnaningrum Fachry Abda El Rahman Fadhila Hijryani FAHREZAL ZUBEDI Farit M. Afendi Farit Mochamad Afendi Fatiya Hanifah Fauzi, Fatkhurokhman Fauziah, Nadira Aribah Ferdiansyah, Anton Ferdiansyah, Anton Fitri Mudia Sari Fitrianto, Anwar Frisca Rizki Ananda Galih Hedy Saputra Gerry Alfa Dito Ghiffary, Ghardapaty Ghaly Ginting, Victor Gumilar, Bagus Randhyartha Gusti Arviana Rahman Hanum Rachmawati Nur Hari Wijayanto Harianto Harianto Hartoyo Hartoyo Hartoyo Hazan Azhari Zainuddin Hazelita Dwi Rahmasari Hendri Wijaya Hendria, Muhammad Herlin Fransiska Herlina Herlina Hidayat, Agus Sofian Eka Hidayat, Muhammad Hilman Dwi Anggana I Gusti Ngurah Sentana Putra I Made Sumertajaya I Wayan Mangku Idqan Fahmi Ilma, Hafizah Ilma, Meisyatul Ilmani, Erdanisa Aghnia Iman, Mutiara Nurul INA YATUL ULYA Indahwati Indonesian Journal of Statistics and Its Applications IJSA Ines Riantika Irene Muflikh Nadhiroh Irfan Syauqi Beik Ismah, Ismah Itasia Dina Sulvianti Iwan Kurniawan Jaelani, Raditya Joice Junansi Tandirerung Kamila, Sabrina Adnin Kenny Masbagusdanta Khairil Anwar Notodiputro Khairunnajah Khairunnajah Khairunnisa, Adlina Kharismatul Zaenab Akhilla Khikmah, Khusnia Nurul Kinanti Rizky Pangestutik Kudang Boro Seminar Kusman Sadik Kusnaeni Kusnaeni, Kusnaeni La Surimi La Surimi, La Laode Ahmad Sabil Leni Anggraini Susanti Lilik Noor Yuliati Linda Karlina Sari Lisa Amelia Luh Putu Widya Adnyani Luky Adrianto Lukytawati Anggraeni M. Yunus Magfirrah, Indah Mardatunnisa Isnaini Matualage, Dariani Mega Maulina Mega Ramatika Putri Megawati - Megawati Simanjuntak Meri Hari Yanni Meylisah, Eni Mohamad Agus Setiawan Muh. Sunan Muhammad Hendria Muhammad Ilham Abidin Muhammad Irfan Hanifiandi Kurnia Muhammad Nur Aidi Muhammad Rizal Muhammad Subianto Muhammad Syafiq Muhammad Yusran Mukhamad Najib Murpraptomo, Saka Haditya MY, Hadyanti Utami Nimmi Zulbainarni Nisa Nur Aisyah Nofrida Elly Zendrato Novian Tamara Nugraha, Adhiyatma Nur Aulia NUR HASANAH NURADILLA, SITI Nurfadilah, Khalilah Oktaviani, Rina Pardomuan Robinson Sihombing Pika Silvianti Popong Nurhayati Pratiwi, Windy Ayu Purwanto, Arie Puspita, Novi Qalbi, Asyifah Rachma Fitriati Rahardi, Naufal Rahardiantoro, Septian Rahma Anisa Rahma Anisa Rahma Dany Asyifa Rahman, Gusti Arviana Rahmatulloh, Febriandi Rais Rere Kautsar Rhendy K P Widiyanto Rina Oktaviani Riska Yulianti, Riska Riza Indriani Rakhmalia Rizal Bakri Rizka Rahmaida Rizqi Annafi Muhadi Rizqi, Tasya Anisah ROCHYATI ROCHYATI Roy Sembel Rupmana Br Butar Sachnaz Desta Oktarina Saka Haditya Murpraptomo salsa bila Saptowulan Sarah Putri Sari, Jefita Resti Sentana Putra, I Gusti Ngurah Seta Baehera Setiadi Djohar Setyowati, Silfiana Lis Shalshabilla Shafa Sholeh, Agus M. Siregar, Indra Rivaldi Siskarossa Ika Oktora Siti Aisyah Suantari, Ni Gusti Ayu Putu Puteri Suhaeni, Cici Sukarna Sukarna Suprayogi, Muhammad Azis Susanto, Andi Suseno Bayu Syaifullah Yusuf Ramdhan Syam, Ummul Auliyah Syarip, Dodi Irawan Syella Zignora Limba Totong Martono Toufiq Al Amin Toufiq Al Amin Triscowati, Dwi Wahyu Tsabitah, Dhiya Ulayya Ujang Sumarwan Ulfia, Ratu Risha Unique Desyrre A. Resiloy Utami Dyah Syafitri Valentika, Nina Vera Maya Santi Wahida Ainun Mumtaza Wahyudi Setyo Wahyuni, Silvia Tri Waliulu, Megawati Zein Wawan Saputra Widiyanto, Rhendy K P Windi Pangesti Yani Prihantini Hiola Yanuari, Eka Dicky Darmawan Yenni Angraini Yoga Primanda Yopi Ariesia Ulfa Yudhianto, Rachmat Bintang Zahra, Latifah Zaima Nurrusydah Zulhijrah Zulmi, Muhammad Indra