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All Journal JURNAL EKONOMI DAN KEBIJAKAN PEMBANGUNAN Jurnal Manajemen dan Organisasi MANAJEMEN IKM: Jurnal Manajemen Pengembangan Industri Kecil Menengah FORUM STATISTIKA DAN KOMPUTASI Forum Pasca Sarjana Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Jurnal Agro Ekonomi Analisis Kebijakan Pertanian Indonesian Journal of Business and Entrepreneurship (IJBE) Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan (Journal of Natural Resources and Environmental Management) Jurnal Ilmu Keluarga dan Konsumen Informatika Pertanian BAREKENG: Jurnal Ilmu Matematika dan Terapan JTAM (Jurnal Teori dan Aplikasi Matematika) IJID (International Journal on Informatics for Development) Jambura Journal of Mathematics Jurnal Kesehatan Ibu dan Anak Jurnal Matematika UNAND Jurnal Agro Ekonomi Analisis Kebijakan Pertanian International Journal of Advances in Data and Information Systems ARRUS Journal of Mathematics and Applied Science Makara Journal of Technology Prosiding Seminar Nasional Official Statistics Scientific Journal of Informatics Indonesian Journal of Jamu Indonesian Journal of Statistics and Its Applications

Hari Wijayanto

Departemen Statistik, FMIPA Institut Pertanian Bogor

Author-ID : 275693

Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Physics Public Health Social Sciences Transportation Other

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Comparison of Extremely Randomized Survival Trees and Random Survival Forests: A Simulation Study Zaenal, Mohamad Solehudin; Fitrianto, Anwar; Wijayanto, Hari
Scientific Journal of Informatics Vol. 11 No. 3: August 2024
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v11i3.8464

Abstract. Purpose: This simulation study investigates the Extremely Randomized Survival Trees (EST) model, a machine learning technique expected to handle survival analysis, particularly in large survival datasets, effectively. The study compares the performance of the EST model with that of the Random Survival Forest (RSF) model, focusing on the C-index value to determine which model performs better. Methods: The analysis begins with the generation of 540 simulated datasets, created by combining three levels of sample sizes, two levels of censoring proportions, three types of hazard functions, and 30 repetitions for each scenario. The simulation data were split into 80% training and 20% testing data. The training data were used to build the EST and RSF models, while the test data were used to evaluate their performance. The model with the highest C-index value was deemed the best performer, as a higher C-index indicates superior model performance. Result: The results indicate that the sample size, type of hazard function, and the method used influence that model performance. The EST model significantly outperformed the RSF model when the sample size was large, though no significant difference was observed when the sample size was small or medium. Additionally, the EST model consistently demonstrated faster computation times across all simulation scenarios. Novelty: This study provides a pioneering exploration into applying decision tree algorithms, specifically EST and RSF, in survival analysis. While these methods have been extensively studied in regression and classification contexts, their application in survival analysis remains relatively unexplored.

Prediksi Senyawa Aktif Pada Tanaman Obat Berdasarkan Kemiripan Struktur Kimiawi untuk Penyakit Diabetes Tipe II Bakri, Rizal; Wijayanto, Hari; Afendi, Farit Mochamad
Jurnal Jamu Indonesia Vol. 1 No. 3 (2016): Jurnal Jamu Indonesia
Publisher : Tropical Biopharmaca Research Center, IPB University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/jji.v1i3.18

Diabetes melitus merupakan penyakit metabolik yang dicirikan oleh tingginya kadar glukosa dalam darah. Di Indonesia jumlah penderita diabetes menempati urutan keempat di dunia setelah Amerika Serikat, India, dan Cina dengan jumlah penderita mencapai lebih dari 12 juta jiwa. Salah satu upaya yang dilakukan untuk mengatasi diabetes adalah mengkonsumsi obat herbal berupa jamu sebagai alternatif obat sintetik. Pusat Studi Biofarmaka Bogor sedang mengembangkan ramuan jamu untuk penyakit Diabetes Melitus Tipe II yang terdiri dari empat tanaman obat yaitu pare (Momordica charantia), sembung (Blumea balsamifera), bratawali (Tinospora crispa), dan jahe (Zingiber officinale). Kandungan senyawa keempat tanaman diduga memiliki aktivitas biologis yang mirip dengan senyawa sintetik. Pada prinsipnya, diasumsikan bahwa senyawa yang struktur kimiawinya mirip memiliki sifat biologis yang mirip. Kemiripan senyawa diukur menggunakan koefisien Modifikasi Tanimoto dengan sidik jari molekuler KR. Hasil penelitian menunjukkan bahwa tanaman Bratawali merupakan tanaman utama pada ramuan jamu untuk penyakit diabetes berdasarkan jumlah kandungan senyawa yang dominan mirip dengan senyawa sintetik yaitu senyawa N-trans-feruloyltyramine (B015) dan N-formylanonaine (B018). Selanjutnya, Senyawa-senyawa yang memiliki nilai kemiripan tinggi dengan senyawa sintetik diperoleh pula pada senyawa karaviloside I (P195) dari tanaman pare, senyawa xanthoxylin (S002) dari tanaman sembung, senyawa borneol (J207) dan (-)- isoborneol (J226) dari tanaman Jahe.

Komparasi Sistem Remunerasi Pada Tiga Perguruan Tinggi Negeri Badan Hukum (PTNbh) Astridina, Astridina; Maarif, M. Syamsul; Wijayanto, Hari
Jurnal Manajemen dan Organisasi Vol. 8 No. 3 (2017): Jurnal Manajemen dan Organisasi
Publisher : IPB University

ABSTRACTThe research objective is to analyze the suitability of the design of the remuneration system in three PTNbh with preparation stages and principles of remuneration and evaluate the system of socialization and information systems used in the application of the remuneration of the three PTNbh. This research was conducted in three PTNbh located in Jakarta (PTNbh X), West Java (PTNbh Y) and East Java (PTNbh Z) using primary data obtained from in-depth interviews and secondary data derived from the literature, previous research, laws and regulations, government regulations and decrees that are relevant to the implementation of the remuneration of PTNbh. This study used a descriptive approach qualitative analysis benchmarking method. In the preparation of the remuneration system, which first assigned PTNbh not follow the stages of preparation with good remuneration, whereas previously PTNbh derived from State BLU more likely to obey the principle and the preparation of their remuneration has been prepared in detail based on the principles of remuneration and government regulations.ABSTRAKPenelitian ini bertujuan untuk menganalisis kesesuaian rancangan sistem remunerasi di tiga PTNbh dengan tahapan dan prinsip penyusunan remunerasi dan mengevaluasi sistem sosialisasi serta sistem informasi yang digunakan dalam penerapan remunerasi pada tiga PTNbh. Penelitian ini dilakukan di tiga PTNbh yang berada di DKI Jakarta (PTNbh X), Jawa Barat (PTNbh Y) dan Jawa Timur (PTNbh Z) dengan menggunakan data primer yang diperoleh dari wawancara mendalam serta data sekunder yang berasal dari studi pustaka, penelitian terdahulu, peraturan pemerintah yang berlaku dan surat keputusan yang relevan dengan penerapan remunerasi pada PTNbh. Penelitian ini menggunakan pendekatan deskriptif kualitatif dengan metode analisis patok duga. Dalam penyusunan sistem remunerasi, PTNbh yang lebih dulu ditetapkan belum mengikuti tahapan penyusunan remunerasi dengan baik, sedangkan PTNbh yang sebelumnya berasal dari PTN BLU cenderung lebih taat azas dan penyusunan remunerasinya sudah disusun dengan detil berdasarkan prinsip-prinsip remunerasi dan peraturan pemerintah.

PATIENT EMPOWERMENT INDEX OF DIABETES MELLITUS PATIENTS Darjono, Agus Heru; Sumarwan, Ujang; Yuliati, Lilik Noor; Wijayanto, Hari
Jurnal Ilmu Keluarga dan Konsumen Vol. 12 No. 3 (2019): JURNAL ILMU KELUARGA DAN KONSUMEN
Publisher : Department of Family and Consumer Sciences, Faculty of Human Ecology, IPB University

The measurement of patient empowerment is important in the health care of chronic diseases, especially diabetes mellitus. The purpose of the study was to develop the patient empowerment index (‘IKP’/Indeks Keberdayaan Pasien) and its dimensions (patient knowledge, patient control, and patient participation) in patients with diabetes mellitus. The research utilized factor analysis in developing patient empowerment index for data analysis. Purposive sampling has been conductedwith 330respondents of diabetes mellitus patients from 26 hospitals in Jabotabek (Jakarta, Bogor, Tangerang, and Bekasi). The variables measured using the Likert scale with a scale of 1 to 5, in which 1 indicates the level of strongly disagree and 5 indicates the level of strongly agree. The collected data were analysed with factor analysis.The results showed that the patient empowerment index consisted of 25.84 percent of knowledge dimensions, 33.44 percent of control dimensions and40.76 percent of participation dimensions. The total score of patient empowerment index value is 68.84 that is in the critical category, which means that consumers have control for the management of their disease conditions in their daily lives. The managerial implication based on the result was the emerging issues of the government to develop an empowerment index for each province in Indonesia that can be used as a benchmark and key performance indicator (KPI) to measure the governance of health programs so the patient empowerment can be increased.

CLUSTER ANALYSIS OF MULTIVARIATE PANEL DATA ON DATA CONTAINING OUTLIERS Kapiluka, Kristuisno Martsuyanto; Wijayanto, Hari; Fitrianto, Anwar
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 20 No 1 (2026): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol20iss1pp0439-0452

One clustering method for panel data is K-Means Longitudinal (KML), which considers only a single trajectory per subject over time. To address this limitation, KML was extended into K-Means Longitudinal 3D (KML3D), which enables clustering of joint or multivariate longitudinal data by considering multiple trajectories measured simultaneously for each subject. Both KML and KML3D provide new insights into clustering panel data using a non-hierarchical K-means approach. Hereinafter, this method is referred to as KML3D K-Means. KML3D K-Means implements the K-Means algorithm, specifically designed to cluster trajectories in panel data, and uses the mean as the clustering centroid. In practice, the K-Means algorithm is less effective in clustering data with outliers. This issue can be overcome by KML3D K-Medoids, a method based on KML3D that uses the median as the centroid. This study aims to determine cluster analysis for multivariate panel data on data containing outliers with KML3D K-Means and KML3D K-Medoids. Both methods are applied to panel data of social and welfare statistical data from 34 provinces observed for 8 years (2016 – 2023). The comparison of methods is based on the Calinski–Harabasz index. The results of the study show that KML3D K-Medoids has a Calinski-Harabasz index that is higher than KML3D K-Means in clustering multivariate panel data with outliers. The analysis identified three optimal clusters (k = 3) based on the Calinski–Harabasz (CH) index, which can be categorized as the “more prosperous”, “moderately prosperous”, and “less prosperous” groups. The growth rate analysis reveals disparities in development trajectories across clusters, with cluster 3 showing the most consistent improvements, cluster 1 moderate progress, and cluster 2 lagging in key social and welfare indicators.

Sentiment Analysis of Tokopedia Customer Reviews Using BiLSTM and IndoBERT with Comparative Analysis of Preprocessing and Labeling Methods Anadra, Rahmi; Wijayanto, Hari; Sadik, Kusman
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.v6i3.1458

This study addresses key challenges in Indonesian sentiment analysis related to preprocessing, labeling strategies, and class imbalance. It compares the performance of BiLSTM and IndoBERT using user reviews collected from Tokopedia. The dataset was manually and automatically labeled, then processed under three preprocessing schemes. Both models were trained with tuned hyperparameters and imbalance-handling techniques and evaluated through twenty rounds of stratified five-fold cross-validation. Performance was assessed using balanced accuracy and F1-score. IndoBERT achieved the highest results, with balanced accuracy up to 0.85 and F1-scores up to 0.83, while BiLSTM reached balanced accuracy up to 0.78 and F1-scores up to 0.76. Applying class weight and focal loss improved model performance by approximately 2% to 11% over the baseline. BiLSTM demonstrated greater training efficiency, requiring only 1 to 2.5 minutes per epoch, compared with IndoBERT’s 2.6 to 3.6 minutes. Although manual labeling remained superior in capturing contextual nuance and emotional cues, GPT-based labeling showed strong agreement with the human annotations. A four-way ANOVA revealed that all main factors and several interactions significantly influenced classification outcomes. Overall, BiLSTM provides faster training efficiency, whereas IndoBERT delivers higher predictive accuracy.

Co-Authors . Aunuddin . Barizi . Gunawan Aan Kardiana Afnan, Irsyifa Mayzela Agus Mohamad Soleh Aji Hamim Wigena Akhmad Fauzi Aldi Cahyanugroho Anadra, Rahmi Anang Kurnia Andres Purmalino Anggraini Sukmawati Aqmar, Nurzatil Arief Hendarto Arif Handoyo Marsuhandi Aruddy Aruddy ASEP SAEFUDDIN Astridina, Astridina Aunuddin Aunuddin Baba Barus Bagus Sartono Bambang Hendro Trisasongko Barizi . Basita G. Sugihen Bertho Tantular Boedi Tjahjono Budi Susetyo Cici Suhaeni Cut Zaraswati DAHRUL SYAH Darjono, Agus Heru Dede Dirgahayu Domiri Dedi Budiman Hakim Dyah R Panuju Dyah R. Panuju Dyah R. Panuju Edi Abdurrachman Eko S. Pribadi Erfiani Erfiani Erliza Noor Fachry Abda El Rahman Farit Mochamad Afendi Farly Shabahul Khairi fatimah Fatimah Fitria Hasanah Fitrianto, Anwar H S, Rahmat Hikmah, Zetil I K Marla Lusda I Made Sumertajaya Ilma, Meisyatul Ina Widayanty Indahwati Irzaman, Irzaman Istiqlaliyah Muflikhati Jajah K. Wagiono Jayawarsa, A.A. Ketut Kapiluka, Kristuisno Martsuyanto Khairil Anwar Notodiputro Kurnia Suci Indraningsih Kusman Sadik La Ode Abdul Rahman Leny Maryesa Lilik Noor Yuliati Luvy Mayanda M. Syamsul Maarif Mahmud A. Raimadoya Mahmud A. Raimadoya Mualifah, Laily Nissa Atul Muhammad Nur Aidi Musa Hubeis Nunung Nurjanah Nurrahman, Fathu Panca Wiputra Pang S. Asngari Pannu, Abdullah Prabowo Tjitrpranoto Riana Riskinandini Rizal Bakri Rizky Nurkhaerani Rysda Rysda Sachnaz Desta Oktarina Siti Hafsah Suhaeni, Cici Ujang Sumarwan Utami Dyah Syafitri Yarah, Helena Ramadhini Yenni Angraini Yuni Suci Kurniawati Zaenal, Mohamad Solehudin

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