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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) International Journal of Advances in Applied Sciences Jurnal Ilmu Komputer dan Informasi Jurnal Presipitasi : Media Komunikasi dan Pengembangan Teknik Lingkungan Jurnal Kesehatan Lingkungan indonesia Media Statistika JURNAL SISTEM INFORMASI BISNIS Jurnal Gaussian Jurnal Statistika Universitas Muhammadiyah Semarang Jurnal Sains dan Teknologi Jurnal Simetris TELKOMNIKA (Telecommunication Computing Electronics and Control) Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) CommIT (Communication & Information Technology) Jurnal Ilmiah Kursor Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Transformatika JUITA : Jurnal Informatika WARTA Register: Jurnal Ilmiah Teknologi Sistem Informasi E-Dimas: Jurnal Pengabdian kepada Masyarakat Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) International Journal of Artificial Intelligence Research Jurnal Informatika INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi Seminar Nasional Variansi (Venue Artikulasi-Riset, Inovasi, Resonansi-Teori, dan Aplikasi Statistika) InComTech: Jurnal Telekomunikasi dan Komputer ILKOM Jurnal Ilmiah KOMPUTIKA - Jurnal Sistem Komputer JTP - Jurnal Teknologi Pendidikan Indonesian Journal of Community Services Journal of Information Systems and Informatics Jurnal Pustaka Ilmiah Indonesian Journal of Electrical Engineering and Computer Science Journal of Applied Data Sciences Jurnal Riset Teknologi Pencegahan Pencemaran Industri Indonesian Journal of Librarianship Media Pustakawan STATISTIKA PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON DATA SCIENCE AND OFFICIAL STATISTICS Journal of Bioresources and Environmental Sciences Scientific Journal of Informatics Jurnal Ragam Pengabdian Jurnal Informatika IJoICT (International Journal on Information and Communication Technology)
Budi Warsito
Departemen Statistika, Fakultas Sains Dan Matematika, Universitas Diponegoro
Agriculture, Biological Sciences & Forestry Humanities Chemical Engineering, Chemistry & Bioengineering Chemistry 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 Library & Information Science Materials Science & Nanotechnology Mathematics Physics Public Health Social Sciences Other

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Klasifikasi Citra Sentinel melalui Google Earth Engine dengan menggunakan algoritma Machine Learning XGBoost Gregorius Anung Hanindito; Adi Wibowo; Budi Warsito
InComTech : Jurnal Telekomunikasi dan Komputer Vol. 16 No. 1 (2026)
Publisher : Department of Electrical Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/incomtech.v16i1.31354

Abstract

Remote sensing technology and Geographic Information Systems (GIS) have rapidly evolved to provide extensive data and information on land cover. This study aims to monitor land cover in Tanjung Keluang Nature Tourism Park (TWA) and its surroundings using Sentinel satellite imagery on the Google Earth Engine (GEE) platform, employing the XGBoost machine learning algorithm. The methods involved acquiring Sentinel satellite imagery, pre-processing for geometric correction, developing training and testing datasets, as well as performing classification and accuracy evaluation. The results indicate that the XGBoost algorithm can classify land cover into several categories with an accuracy of up to 98%. The classified land cover includes water bodies (23,346 Ha), open land (9,680.54 Ha), sand mining areas (931.15 Ha), and vegetation (16,596.84 Ha). This study contributes positively to the management of conservation areas, particularly in supporting decision-making for TWA Tanjung Keluang in the future.
LATENT DIRICHLET ALLOCATION DALAM IDENTIFIKASI RESPON MASYARAKAT INDONESIA TERHADAP PROFESI PEGAWAI NEGERI SIPIL Nurul Fajrin Aghentika; Sugito Sugito; Budi Warsito
Jurnal Gaussian Vol 15, No 1 (2026): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/j.gauss.15.1.57-66

Abstract

Data on social media comments can be extracted to produce hidden information that is useful as a guide for evaluation and decision making. YouTube has a comments feature as a forum for expressing opinions, experiences and questions. Civil Servants are known as one of the job choices of Indonesian people, the government announced that there were resignations of Civil Servant Candidates in 2022. Responses written in the comment column are difficult to understand, topic modeling can be applied as a text analysis process to find descriptions from unstructured data. Latent Dirichlet Allocation method is able to find out hidden topics in a document as well as the words that make up a topic so that the application of this method will help in identifying responses discussed by the audience. The data used is textual data in the form of comments from YouTube scrapping during 2022. The results of topic modeling form eight topics, namely retirement life, parents hopes, dream jobs, civil servants, job differences, characteristics of generation Z, salary and benefits, and reasons for resignation. The RStudio GUI program can make it easier for users to analyze topic modeling with similar methods.
A BIMAS-Based Assessment Framework of Digital Readiness: Evidence and Institutional Patterns Agus Pamuji; Aries Susanty; Budi Warsito
IJoICT (International Journal on Information and Communication Technology) Vol. 12 No. 1 (2026): Vol.12 No.1 Jun 2026
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21108/ijoict.v12i1.10521

Abstract

This study examines the digital readiness of Islamic higher education institutions (IHEIs) in Indonesia in response to the intensifying demands of digital transformation, which have increasingly exposed structural constraints related to limited investment capacity, persistently low levels of digital equity, and the absence of consistent and comparable empirical evidence. Although digitalization has been widely promoted across higher education, existing assessments remain fragmented and insufficiently contextualized, thereby creating a research gap concerning how institutional readiness can be systematically evaluated within value-based educational systems. To address this gap, the study adopts the BIMAS framework as a comprehensive analytical model and applies a cross-sectional research design using a survey-based data collection approach. Methodologically, digital readiness is measured through the calculation of the Digital Readiness Index (DRI), the aggregation of the Net Promoter Score (NPS), and the qualitative evaluation of readiness levels across BIMAS dimensions. The findings, which are interpreted across seven distinct readiness levels, reveal that the Business Model, Infrastructure and Technology, and Audit and Quality Control dimensions demonstrate relatively significant developmental progress, particularly where technological adoption and procedural formalization have been prioritized.
Pengukuran Indeks Pembangunan Literasi Masyarakat (IPLM) Kota Salatiga sebagai Dasar Penyusunan Program Pengembangan dan Pembinaan Perpustakaan Warsito, Budi; Rachman Hakim, Arief; Fatmawati, Endang
Jurnal Pustaka Ilmiah Vol 9, No 2 (2023): Jurnal Pustaka Ilmiah
Publisher : Universitas Sebelas Maret Library

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/jpi.v9i2.75337

Abstract

The development of public literacy in Indonesia is very dependent on several aspects of people’s reading skills. In determining program development policies and indicators of success, periodic reviews and benchmarks are required. The formulation of the Community Literacy Development Index measurement needs to be done in Salatiga City. The CLDI research aims to determine the value of CLDI in Salatiga City, such as the condition of all types of libraries, both from the aspect of library distribution, collections, library staff, to users in Salatiga City. CLDI measurements were carried out using a census approach. From the results of the research, the score for the Salatiga City CLDI in 2023 was 81.21%. It can be concluded that the score of 81.21% is in the interval between 80 and 90 so the CLDI of Salatiga City in 2023 is included in the high level.
The physiological and ecological characteristics of some phytoremediation plants for wastewater treatment: a review Sri Sumiyati; Anik Sarminingsih; Budi Warsito
International Journal of Advances in Applied Sciences Vol 15, No 2: June 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijaas.v15.i2.pp705-717

Abstract

Phytoremediation has emerged as an effective method for mitigating heavy metal contamination in waterways. This study synthesizes literature to assess the physiological and ecological characteristics enhancing the efficiency of five plant species traditionally recognized for their phytoremediation potential: Napier grass (Pennisetum purpureum), Phragmites australis, Typha spp., Pistia stratiotes, and Eichhornia crassipes. A systematic review methodology was utilized, focusing on data from Proquest, EBSCO, and Scopus, prioritizing studies based on pollutant absorption capacities, publication quality, and recency. Key parameters examined include the identification of plant species, growth conditions, pollutant absorption efficiency, ecological roles, and physiological characteristics. Phragmites australis is noted for its nutrient uptake and sediment stabilization, while Eichhornia crassipes demonstrates high heavy metal absorption and rapid growth. Pistia stratiotes effectively removes heavy metals and enhances water quality, and Typha spp. aids in nutrient removal while providing habitat. Napier grass contributes to biomass production and soil stabilization. The integration of these species into wastewater treatment systems not only improves water quality but also fosters sustainability and ecological health. This study emphasizes the potential utility of these plants in environmental management initiatives, highlighting the necessity for careful monitoring to mitigate associated ecological risks.
Development of Customer Loyalty Measurement Application Using R Shiny with Structural Equation Model Partial Least Square Method, Customer Satisfaction Index, and Customer Loyalty Index Cintika Oktavia; Budi Warsito; Vincensius Gunawan Slamet Kadarrisman
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol. 9 No. 4 (2023): December
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v9i4.26649

Abstract

One of Indonesia's well-known e-commerce platforms, Shopee, relies on information technology to run its business. The information technology used by Shopee is considered unable to meet customer satisfaction. Customer reviews are dissatisfied with the facilities provided by Shopee, and some customers compare Shopee with other e-commerce sites. The research contribution is the understanding that the proper use of information technology can positively impact customer experience, improve operational efficiency, and support business growth in the e-commerce industry. Research with a quantitative approach will build a website-based application as a statistical tool for data processing using R shiny so that the application results have high interactivity, dynamic visualization, and better explanation. The research will collect 100 data provided to customers who have transacted at Shopee and distributed through the telegram application, which is distributed to particular groups and channels for Shopee users. Data processing for this study will use the  Structural Equation Model Partial Least Square, Customer Satisfaction Index, Net Promoter Score, and Customer Loyalty Index. The study results show that electronic service quality and security seals positively and significantly affect customer satisfaction. Electronic service quality has a moderate effect on customer satisfaction, while electronic security seals have a slightly lower effect on customer satisfaction (t=5.584, p<0.001). Additionally, a significant correlation between customer loyalty and satisfaction was discovered (t=14.764, p=0.001). Research proves the need to improve service quality and security aspects to increase customer satisfaction on e-commerce platforms and the importance of maintaining customer satisfaction as a strategy to increase customer loyalty.
Digital Readiness Assessment in Islamic Higher Education Institutions with Operationalized BIMAS Framework Agus Pamuji; Aries Susanty; Budi Warsito; Tonni Agustiono Kurniawan
INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi Vol 10 No 1 (2026)
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/intensif.v10i1.28120

Abstract

Background: Digital readiness (DR) has become a critical prerequisite for effective digital transformation (DT), particularly as institutions face increasing demands for digital governance, quality assurance, and institutional resilience. These challenges are especially evident in Islamic Higher Education Institutions (IHEIs), where digital transformation must align with regulatory and value-based frameworks. Objective: The purpose of this research is to construct and operationalize the BIMAS framework, comprising Business Model, Infrastructure and Technology, Management and Organization, Audit and Quality Control, and Sustainability and Environment, as an integrated reference for assessing institutional digital readiness. Methods: A Digital Readiness Index (DRI) is developed using a seven-level continuum to classify readiness across BIMAS dimensions and institutional levels. Structural Equation Modeling (SEM) is employed to analyze the causal relationships among the dimensions, complemented by Importance–Performance Map Analysis (IPMA) to identify priority areas for strategic improvement. Results: The findings indicate that Management and Organization (β = 0.378, p < 0.05) and Sustainability and Environment (β = 0,352, p < 0.05) have positive and statistically significant effects on digital readiness, confirming the validity of the BIMAS framework and the proposed DRI. Conclusion: The findings reveal that Management and Organization and Sustainability and Environment exert positive and statistically significant effects on DR; moreover, confirming the validity of the BIMAS framework and the proposed DRI, offering a reliable foundation for guiding DT in IHEIs.
A hybrid divisive K-means framework for big data–driven poverty analysis in Central Java Province Bowo Winarno; Budi Warsito; Bayu Surarso
Indonesian Journal of Electrical Engineering and Computer Science Vol 41, No 1: January 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v41.i1.pp258-269

Abstract

Clustering is essential in big data analytics, especially for partitioning high dimensional socioeconomic datasets to support interpretation and policy decisions. While K-Means is widely used for its simplicity and scalability, its strong sensitivity to initial centroid selection often leads to unstable results and slower convergence. Previous hybrid approaches, such as Agglomerative–K-Means, attempted to address this issue by using hierarchical clustering for centroid initialization; however, these methods rely on bottom-up merging, which can produce suboptimal initial partitions and increase computational overhead for larger datasets. To overcome these limitations, this study proposes a hybrid divisive–K-Means (DHC) model that employs top-down hierarchical splitting to generate more coherent initial centroids before refinement with K-Means. Using a multidimensional poverty dataset from Central Java Province provided by the Indonesian Central Bureau of Statistics (BPS), the performance of DHC was evaluated against standard K-Means and Agglomerative–K-Means. The assessment included execution time, convergence iterations, and cluster validity indices (Silhouette, Davies–Bouldin, and Calinski–Harabasz). Experimental results demonstrate that DHC reduces execution time by up to 97% and requires 40% fewer iterations than standard K-Means, while achieving comparable or improved cluster quality (e.g., CH Index increasing from 14.3 to 15.8). These findings indicate that the DHC model offers a more efficient and stable clustering solution, addressing the shortcomings of previous standard K-Means methods and improving performance for large-scale socioeconomic data analysis.
IMPLEMENTASI ALGORITMA FUZZY K-NEAREST NEIGHBOR UNTUK KLASIFIKASI PENYAKIT DIARE Nur Dihyah; Budi Warsito; Iut Tri Utami
Jurnal Gaussian Vol 15, No 1 (2026): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/j.gauss.15.1.255-263

Abstract

Diarrhea is digestive disruption retrieved by defecation that become more fluid and occur over three times a day. The prevalence of diarrhea in Indonesia is public health problem with high cases. Diarrhea management is carried out with rehydration efforts by administering oral rehydration salts at puskesmas. Diarrhea is classified into 2 types, namely acute diarrhea (mild) and chronic diarrhea (severe). Puskesmas only handles mild diarrhea so that a method is needed to classify diagnosis of diarrhea that occurs at puskesmas appropriately so that diagnosis of acute diarrhea is not misclassified into chronic diarrhea. This research implements Fuzzy K-Nearest Neighbor procedure for Diarrhea Classification. Fuzzy K-Nearest Neighbor incorporates fuzzy logic and K-Nearest Neighbor in the classification practice. The advantage of Fuzzy K-Nearest Neighbor is data will have membership value in each data class so that it further strengthens reason for data to enter predicted class. Data is processed by applying Shiny Package in Rstudio to create Graphical User Interface (GUI-R) so that it makes it easier for researchers to process data. The results obtained highest classification accuracy at K = 3 with accuracy of 80.19% and specificity of 85.45% so that Fuzzy K-Nearest Neighbor was able to classify diarrhea well.
An Explainable PCA-XGBoost Model for Predicting Bloodstream Infection in Hemodialysis Patients Rani Zulaikha; Budi Warsito; Aris Sugiharto
Journal of Information System and Informatics Vol 8 No 4 (2026): August
Publisher : Asosiasi Doktor Sistem Informasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63158/journalisi.v8i4.1694

Abstract

Bloodstream infection (BSI) is a life-threatening complication in hemodialysis (HD) patients with catheter-based vascular access, carrying mortality rates of 15–50%, yet early detection remains challenging due to high-dimensional clinical data with significant multicollinearity. This study develops a BSI prediction model integrating Principal Component Analysis (PCA), XGBoost, Synthetic Minority Oversampling Technique (SMOTE), and dual Explainable AI (XAI) methods to improve predictive performance and clinical transparency. A dataset of 391 HD patients (18.9% BSI-positive) was preprocessed with encoding, standardization, and median imputation. PCA reduced 37 features to 29 components retaining 95.0% variance; SMOTE was applied inside each cross-validation fold to prevent leakage; and hyperparameters were optimized via RandomizedSearchCV. The proposed model achieved 83.5% accuracy, 33.3% recall, 43.5% F1-score, 85.5% AUC-ROC, and 0.643 PR-AUC, outperforming the baseline (81.0% accuracy, 0.0% recall, 0.190 PR-AUC). Bootstrap 95% confidence intervals and Brier score calibration are reported; results require cautious interpretation given the small positive test set (n=15). SHAP and LIME identified PC1 (hematological parameters) and PC2 (inflammatory markers) as dominant predictors. This study explores PCA, XGBoost, and dual XAI integration for BSI prediction in HD patients, an approach not extensively examined in this context. External multicenter prospective validation is required before clinical deployment.
Co-Authors . Widayat Abdul Hoyyi Adi Waridi Basyirudin Arifin Adi Wibowo Adi Wibowo Adi Wibowo Agus Pamuji Agus Pamuji Agus Pamuji Agus Rusgiyono Ahmad Lubis Ghozali Ahmed, Kamil Alan Prahutama Anik Sarminingsih Anindita Nur Safira Arafa Rahman Aziz Arbella Maharani Putri Arief Rachman Hakim Arief Rachman Hakim Arief Rachman Hakim Aries Susanty Aries Susanty Aris Sugiharto Arsyil Hendra Saputra Atmaja, Dinul Darma Atur Ekharisma Dewi Aurum Anisa Salsabela Azizah Bagus Dwi Saputra Bayastura, Shahnilna Fitrasha Bayu Surarso Bayu Surarso Bimastyaji Surya Ramadhan Bowo Winarno Budiyono Budiyono Calvin, Esagu John Catur Edi Widodo Chrisna Suhendi Cintika Oktavia Di Asih I Maruddani Di Mokhammad Hakim Ilmawan Dian Mariana L Manullang Dinar Mutiara Kusumo Nugraheni Dwi Ispriyanti Dyna Marisa Khairina Eka Rahmawati eka rahmawati Ekky Rosita Singgih Wigati Endang Fatmawati Endang Fatmawati Fachry Abda El Rahman Fadhilah, Husni Fadli Dony Pradana Faisal Fikri Utama Faliha Muthmainah Faridah, Hasna Fath Ezzati Kavabilla Fatiya Nur Umma Ferry Hermawan Fiqria Devi Ariyani Firdonsyah, Arizona Gayuh Kresnawati Gertrude, Akello Ghifar Rahman Gregorius Anung Hanindito Handayani, Sri Hanif Kusumasasmita Haritsa, Rifda Tsaqifarani Harjum Muharam Hasbi Yasin Hendri Setyawan Henny Widayanti, Henny Heriyanto Hizkia Christian Putra Setiadi Indra Jaya Infan Nur Kharismawan Intan Monica Hanmastiana Iut Tri Utami Jafron Wasiq Hidayat Jumi Juwanda, Farikhin Kadarrisman, Vincensius Gunawan Slamet Kiswanto Kiswanto M. Afif Amirillah M. Andang Novianta Maharani, Chintya Ayu Mahrus Ali Maori, Nadia Annisa Maryono Maryono Maryono Maryono Masruroh, Fitriana Maulida Najwa, Maulida Mifta Ardianti Moch. Abdul Mukid Mochamad Arief Budihardjo Moh Ali Fikri mohamad jamil Muhammad Shodiq Muliyadi Muliyadi Munji Hanafi Mustafid Mustafid Mustaqim Mustaqim, Mustaqim Nisa Afida Izati Noor Azizah Nur Dihyah Nur Fitriyah Nur Rochman Nurcahyanti, Tri Meida Nurul Fajrin Aghentika Nurul Hidayati Oktavia, Cintika Oky Dwi Nurhayati Pandu Anggara Paul, Gudoyi M Perdana, Ery Purwanto Purwanto Puspita Kartikasari Putri, Nitami Lestari R Rizal Isnanto R. Rizal Isnanto RACHMAN HAKIM, ARIEF Rachmat Gernowo Rachmat Gernowo Rahmat Gernowo Rahmat Gernowo Rahmatul Akbar Rani Zulaikha Ratna Kencana Putri Rini Nuraini Rita Rahmawati Rita Rahmawati Riva Amrulloh Riza Rizqi Robbi Arisandi Royani, Noorhanida Rukun Santoso Rully Rahadian Safitri, Adila Salma Farah Aliyah Sang Nur Cahya Widiutama Sari, Juwita Dwinda Silvia Elsa Suryana Siti Fadhilla Femadiyanti Sri Endah Moelya Artha Sri Sumiyati Sri Sumiyati Sudarno Sudarno Sudarno Sudarno Sudarno utomo Sugito Sugito Sulardjaka Sulardjaka Suparti Suparti Syafrudin Syafrudin Tarno Tarno Tarno Tarno Tatik Widiharih Tatik Widiharih Ta’fif Lukman Afandi Tonni Agustiono Kurniawan Tri Yani Elisabeth Nababan Ummayah, Putri Qodar Vincensius Gunawan Slamet Kadarrisman Wahyul Amien Syafei Whisnumurti Adhiwibowo Wibowo, Catur Edi Winahyu Handayani Yanuar Yoga Prasetyawan Yundari, Yundari