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All Journal TEKNIK INFORMATIKA Dinamik SEGMEN Jurnal Manajemen dan Bisnis GEMA TEKNOLOGI Techno.Com: Jurnal Teknologi Informasi Jurnal Simetris Syntax Jurnal Informatika Elkom: Jurnal Elektronika dan Komputer Jurnal Ilmiah Mahasiswa FEB Prosiding SNATIF Jurnal Ketahanan Nasional Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Berkala Epidemiologi Seminar Nasional Informatika (SEMNASIF) CESS (Journal of Computer Engineering, System and Science) E-Dimas: Jurnal Pengabdian kepada Masyarakat JOIN (Jurnal Online Informatika) Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) SISFOTENIKA Journal of Information Technology and Computer Science (JOINTECS) JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Jurnal Ilmiah FIFO Jurnal Pilar Nusa Mandiri InComTech: Jurnal Telekomunikasi dan Komputer Prosiding Seminar Nasional Teknoka JRST (Jurnal Riset Sains dan Teknologi) JOURNAL OF APPLIED INFORMATICS AND COMPUTING SINTECH (Science and Information Technology) Journal JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Jurnal Sisfokom (Sistem Informasi dan Komputer) JURNAL EDUCATION AND DEVELOPMENT Jiko (Jurnal Informatika dan komputer) JSiI (Jurnal Sistem Informasi) Explore IT : Jurnal Keilmuan dan Aplikasi Teknik Informatika JURIKOM (Jurnal Riset Komputer) Jurnal Telematika JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) STRING (Satuan Tulisan Riset dan Inovasi Teknologi) CCIT (Creative Communication and Innovative Technology) Journal Journal of Information System, Applied, Management, Accounting and Research Jurnal Ilmiah Ilmu Komputer Fakultas Ilmu Komputer Universitas Al Asyariah Mandar Journal of Electronics, Electromedical Engineering, and Medical Informatics Jurnal Ilmu Komputer dan Bisnis Syntax Idea Techno Xplore : Jurnal Ilmu Komputer dan Teknologi Informasi Jurnal Informatika dan Rekayasa Perangkat Lunak Jurnal Mnemonic Jurnal Asiimetrik: Jurnal Ilmiah Rekayasa Dan Inovasi International Journal of Advances in Data and Information Systems Journal of Computer Science and Engineering (JCSE) SKANIKA: Sistem Komputer dan Teknik Informatika Jurnal Teknik Informatika (JUTIF) Jurnal Pewarta Indonesia JURNAL KOMUNIKASI DAN BISNIS Ascarya: Journal of Islamic Science, Culture and Social Studies Jurnal PkM (Pengabdian kepada Masyarakat) Humantech : Jurnal Ilmiah Multidisiplin Indonesia Media Publikasi Promosi Kesehatan Indonesia (MPPKI) Bit (Fakultas Teknologi Informasi Universitas Budi Luhur) Journal Of Human And Education (JAHE) Prosiding Seminar Nasional Sisfotek (Sistem Informasi dan Teknologi Informasi) Economic Reviews Journal Jurnal Algoritma Jurnal Ticom: Technology of Information and Communication Berita Kedokteran Masyarakat Jurnal Hasil Pengabdian Masyarakat (JURIBMAS) Journal of Systems Engineering and Information Technology J-Icon : Jurnal Komputer dan Informatika Jurnal Teknik Indonesia Research Horizon IIJSE Jurnal Relawan dan Pengabdian Masyarakat REDI Jurnal Pengabdian Masyarakat Nasional Health Dynamics Jurnal Ticom: Technology of Information and Communication The Indonesian Journal of Computer Science Seminar Nasional Riset dan Teknologi (SEMNAS RISTEK) Prosiding SeNTIK STI&K Journal of Medical and Health Science Jurnal Ilmu Kesehatan Immanuel Jurnal Ekonomi, Manajemen, Akuntansi dan Keuangan
Arief Wibowo
Universitas Budi Luhur
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Comparison of Individual Algorithms (Decision Tree, Naïve Bayes, and Support Vector Machine) and Ensemble Voting in Predicting Students’ On-Time Graduation Based on Course Grades Ferdian, Sevtian; Miechael, Miechael; Wibowo, Arief
Jurnal Informatika dan Rekayasa Perangkat Lunak Vol. 8 No. 1 (2026): Maret
Publisher : Universitas Wahid Hasyim

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

Abstract

Education plays an important role in improving the quality of human resources and supporting a country’s progress toward becoming a developed nation. Higher education institutions serve as one of the providers of formal education, where the quality of these institutions is measured through accreditation. One of the key indicators influencing accreditation is the outcomes and achievements of the Tri Dharma of higher education, which include the timeliness of student graduation. This study aims to compare models for predicting on-time student graduation using three machine learning algorithms, namely Decision Tree, Naïve Bayes, and Support Vector Machine (SVM), as well as their combination through the Ensemble Voting method. The prediction is based on historical grade data from courses taken during semesters one to four. The research methodology adopts the Cross-Industry Standard Process for Data Mining (CRISP-DM), which consists of six stages: business understanding, data understanding, data preparation, modeling, evaluation, and deployment. The dataset used in this study consists of 2,471 records with 11 attributes. Data preprocessing was conducted through data cleaning and class balancing using under sampling techniques. The results indicate that the Ensemble Voting model using the Soft Voting method achieves the best performance, with an accuracy of 91.80%, precision of 91.87%, and recall of 91.80%, outperforming the individual models of Decision Tree, Naïve Bayes, and SVM. The implementation of this model can be utilized to predict students’ on-time graduation based on course grade inputs. Therefore, this research can serve as a supporting tool for early detection of potential delays in student graduation.
Explainable Ensemble Learning for Urban Flood Risk Mapping in Jakarta Using Multi-Source Geospatial and Hydrometeorological Data Wibowo, Arief; Achadi, Abdul Haris
JURNAL TEKNIK INFORMATIKA Vol. 19 No. 1: JURNAL TEKNIK INFORMATIKA
Publisher : Department of Informatics, Universitas Islam Negeri Syarif Hidayatullah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/jti.v19i1.49010

Abstract

Urban flooding is a frequent hydrometeorological hazard in Indonesia, particularly in Jakarta, driven by rapid urbanization, limited drainage capacity, land cover change, and extreme rainfall. This study develops an explainable ensemble learning framework for urban flood risk mapping in Jakarta using multi-source geospatial and hydrometeorological data, including satellite-based rainfall, topography, land use/land cover, NDVI, and IoT-based river water level observations from 2023–2025. Flood occurrence labels were constructed by integrating municipal flood records with satellite-based inundation data. The framework integrates Random Forest, Gradient Boosting, and XGBoost models, with SHAP applied for interpretability and identification of dominant flood drivers. Model evaluation using ROC-AUC and RMSE indicates that XGBoost achieved the highest performance (AUC = 0.91, RMSE = 0.184), outperforming Random Forest (AUC = 0.87, RMSE = 0.221) and Gradient Boosting (AUC = 0.89, RMSE = 0.203). SHAP analysis identifies rainfall intensity, elevation, proximity to river channels, and built-up area percentage as the most influential factors. Despite uncertainties in flood labeling and the lack of high-resolution drainage data, the results demonstrate the potential of explainable ensemble learning for urban flood risk assessment and resilience planning. 
Pengaruh Penggunaan Lease Management System, Kualitas Sistem, Dan Kualitas Informasi Terhadap Produktivitas Karyawan Pada Digital Procurement, Dengan Corporate Support Sebagai Variabel Moderasi Rachman, Abdul; Wibowo, Arief
Indonesian Interdisciplinary Journal of Sharia Economics (IIJSE) Vol 9 No 2 (2026): Sharia Economics
Publisher : Universitas KH. Abdul Chalim Mojokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31538/iijse.v9i2.10072

Abstract

This study examines the effects of Lease Management System (LeMS) Usage, System Quality, and Information Quality on Employee Productivity, with Corporate Support as a moderating variable in a post-merger telecommunications company. The research employs an explanatory quantitative approach using a survey method involving a total of 109 respondents, consisting of internal employees and external partners engaged in lease asset management processes. Data analysis was conducted using PLS-SEM, encompassing evaluation of the outer model (validity and reliability) and the inner model (R-square, f-square, and path testing through bootstrapping). The results indicate that Information Quality has a significant effect on Employee Productivity, whereas LeMS Usage and System Quality do not show significant effects. In addition, Corporate Support is not proven to moderate the relationships between the three independent variables and Employee Productivity. These findings suggest that during the post-merger transition phase, administrative-process productivity is more sensitive to the accuracy, completeness and timeliness of information than to system usage intensity or technical system quality. The practical implications of this study emphasize the importance of strengthening data governance to maintain the quality of information generated by LeMS, which should be supported by hands-on training to enhance user adoption, as well as policy and SOP updates to ensure more consistent utilization of LeMS in administrative processes, thereby improving employee productivity.
Improving Students' Artificial Intelligence Literacy through Hybrid Training in Supporting the Competency of the Society 5.0 Era Supiyandi, Supiyandi; Rizal, Chairul; Efendi, Irman; Siregar, Muhammad Noor Hasan; Wibowo, Arief
JURIBMAS : Jurnal Hasil Pengabdian Masyarakat Vol 5 No 1 (2026): Juli 2026
Publisher : LKP KARYA PRIMA KURSUS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62712/juribmas.v5i1.1038

Abstract

This community service program aimed to improve university students’ Artificial Intelligence (AI) literacy through hybrid training that supports the competencies required in the Society 5.0 era. The rapid advancement of digital technology has increased the need for students to understand, utilize, and critically evaluate AI technologies in academic and professional contexts. The program was implemented using a hybrid learning approach that combined face-to-face and online learning activities through educational counseling, workshops, interactive discussions, and practical simulations of AI applications. The participants were university students who received training in basic AI concepts, ethical use of AI, digital literacy, and the implementation of AI technologies to support academic activities and twenty-first-century competencies. The instruments used in this activity included training modules, digital presentation media, observation sheets, and pre-test and post-test evaluations to assess participants’ understanding before and after the training sessions. The findings indicated that the hybrid training successfully improved students’ understanding of Artificial Intelligence, enhanced their ability to use AI technologies in academic activities, and increased their awareness of ethical and responsible AI use. Furthermore, the hybrid learning model provided flexible, interactive learning experiences that promoted active participation and strengthened students’ adaptability to the digital transformation in the Society 5.0 era. The program also demonstrated that AI literacy plays a significant role in supporting students’ readiness for technology-driven educational and professional environments. Therefore, hybrid AI literacy training can serve as an effective and relevant model for developing digital competencies in higher education and supporting the transformation of education in the Society 5.0 era.
Perbandingan K-Means, DBSCAN, dan Louvain pada Peserta Pendidikan Kesetaraan di Kabupaten Balangan Ida Ariyani Hasanah; Riama Simanjuntak; Arief Wibowo
Jurnal Algoritma Vol 23 No 1 (2026): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.23-1.3350

Abstract

Penelitian ini bertujuan menganalisis pola pengelompokan peserta pendidikan kesetaraan melalui pendekatan clustering secara komparatif menggunakan tiga algoritma, yaitu K-Means (berbasis centroid), DBSCAN (berbasis kepadatan), dan Louvain (berbasis graf). Dataset yang digunakan terdiri dari 1.057 peserta dengan atribut numerik dan kategorik yang mencerminkan karakteristik heterogen. Tahapan penelitian meliputi pra-pemrosesan data dan implementasi algoritma clustering pada dataset yang sama untuk menjaga konsistensi perbandingan. Evaluasi dilakukan menggunakan Silhouette Score dan Davies-Bouldin Index (DBI) sebagai validasi internal, serta validasi eksternal melalui konfirmasi pakar guna memastikan relevansi hasil secara kontekstual. Hasil penelitian menunjukkan bahwa K-Means dan DBSCAN menghasilkan nilai Silhouette Score sebesar 0,040 yang mengindikasikan kualitas pemisahan cluster yang rendah serta dominasi satu cluster besar. DBSCAN memiliki keunggulan dalam mendeteksi noise, namun belum mampu meningkatkan kualitas pemisahan secara signifikan pada data dengan tingkat homogenitas tinggi. Sebaliknya, algoritma Louvain menghasilkan struktur komunitas yang lebih seimbang dengan rasio ketimpangan yang rendah, sehingga lebih mampu merepresentasikan hubungan relasional antar data yang tidak sepenuhnya terwakili oleh pendekatan berbasis jarak. Penelitian ini memberikan kontribusi melalui analisis komparatif lintas pendekatan clustering pada konteks pendidikan kesetaraan serta integrasi validasi kuantitatif dan kontekstual. Temuan ini menegaskan bahwa pendekatan berbasis graf lebih adaptif untuk data dengan tingkat homogenitas tinggi dan berpotensi menjadi dasar dalam segmentasi peserta guna mendukung pengambilan keputusan berbasis data yang lebih efektif dalam sektor pendidikan.  
Model Rekomendasi Karier Lulusan Sekolah Menengah Kejuruan Berdasarkan Kompetensi dan Bakat Menggunakan Perbandingan Algoritma Apriori dan FP-Growth Tarwan; Eko Aji Putra; Arief Wibowo
Jurnal Algoritma Vol 23 No 1 (2026): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.23-1.3410

Abstract

The increasingly dynamic development of the job market requires Vocational High School (SMK) graduates to possess adaptive abilities, not only in mastering vocational competencies but also in determining appropriate career paths. However, in reality, many SMK graduates still experience difficulties in choosing careers that align with their competencies and talents. This condition highlights the need for a systematic approach capable of providing data-driven career recommendations. This study aims to develop a data-based career recommendation system using the Apriori and FP-Growth algorithms to identify relationship patterns among vocational competencies, students’ academic talents, and alumni tracer study data. The study offers a new approach to career recommendation systems for Vocational High Schools by integrating students’ academic data and alumni post-graduation histories (tracer studies) within a single pattern analysis framework. In addition to generating association rules that can easily be used as a basis for decision-making, the system also incorporates validation from guidance and counseling teachers (BK teachers) to strengthen data-driven career decisions. Talents are classified into two categories, namely exact/science-oriented and non-exact/non-science-oriented, based on comparisons between average Mathematics grades and non-science subject grades from semesters 1 to 6. Alumni tracer data include post-graduation status (employment, higher education, or others), job relevance, competency certificates, and the positions or work sectors pursued. Subsequently, each student and alumni entity was transformed into transactional data analyzed using the Apriori and FP-Growth algorithms to discover association rules between student profiles and career recommendations. The analysis results indicate strong relationships between combinations of talents and vocational competencies with specific career choices. The inclusion of data from guidance and counseling teachers serves as qualitative input that strengthens the validity of the system’s results. This system can be utilized by schools, guidance counselors, and students as a decision-support tool for making more objective and data-driven career decisions. Therefore, the system supports a vocational education direction that is more integrated with labor market needs.
Perbandingan Apriori dan FP-Growth dalam Association Rule Pola Pembelian Sparepart Preventive Maintenance Anita; Arief Wibowo
Jurnal Algoritma Vol 23 No 1 (2026): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.23-1.3427

Abstract

Spare part inventory management is an important aspect of preventive maintenance activities. This study aims to analyze the performance comparison between the Apriori and FP-Growth algorithms in identifying spare part purchasing patterns for preventive maintenance activities. The main problem in spare part management is the lack of optimal inventory planning, which can lead to overstock or stock shortages. The method used in this study is Association Rule Mining with two algorithms, namely Apriori and FP-Growth, applied to spare part purchasing transaction data. The analysis process was conducted through data preprocessing, frequent itemset generation, and association rule formation using minimum support and confidence parameters. The results indicate that the FP-Growth algorithm performs more efficiently than Apriori in terms of computation time and the ability to handle large datasets. Meanwhile, the Apriori algorithm is easier to implement and understand. The resulting association patterns can be used as a basis for decision-making in more effective and efficient spare part inventory management. Therefore, this study is expected to contribute to improving data-driven preventive maintenance strategies.
Co-Authors - Arientawati - Sumardianto Abdul Rachman Achadi, Abdul Haris Adita, Ita Afifah Khaerani Afifatussalamah, Rizka Ahmad Sururi Ahmad Sururi Akbar, Ahmad Aldizar Al Fatach, M Khabib Anggraini, Julaiha Probo Anita Anita Diana Antika Zahrotul Kamalia Anugrah Sandy Yudhasti Anuqman Fitriadi Apriati Suryani Ardhianto, Angga Ardianah, Eva Ari Wibowo Arief Umarjati Asep Permana Atik Ariesta Bayu Sadewo Bayu Satria Pratama Binarto, Antonius Jonet Bintang, Bagus Boerhan Hidayat, Boerhan Chairul Rizal Chintya Paramitha Danar Wido Seno Danniswara, Ahmad Deni Mahdiana Diah Indriani Didik Hariyadi Raharjo Didin Muhidin Dwi Kristanto Dwi Yulianti Dyah Retno Utari Dyah Retno Utari, Dyah Retno Ebine, Masato Efendi, Irman Eko Aji Putra Endah Sarah Wanty Fajar Siddik Chaniago Farah Chikita Venna Farid Setiawan Farid Setiawan, Farid Febrilliani, Jihan Sastri Fenny Irawati Ferdian, Sevtian Fernando, Donny Firman Noor Hasan Firmanty Mustofa, Vina Fitri Nur Masruriyah, Anis Fitri Rachmilah Fadmi Fitriadi, Rifqi Fitriani, Netty Fransiska Vina Sari Frenda Farahdinna Fried Sinlae Ghapur, Abdul Gurdani Yogisutanti Hadidtyo Wisnu Wardani Hananto, Agustia Handoko, Andy Rio Hanindita, Meta Herdiana Hari Basuki Notobroto Haris Achadi, Abdul HARIYANTO HARIYANTO Harun Nasrullah Hassan, Shiza Hayatul Khairul Rahmat Henry Henry Herriyawan, Herriyawan Hidayat, Manarul Hidayat, Sarifudlin Huda, Ratu Najmil Ida Ariyani Hasanah Indah Rizky Mahartika Indra Indra Inge Virdyna Irfan Hadi Irfan Nurdiansyah Istiqoomatun Nisaa Jasmine, Meuthia Joko Sutrisno Jovansgha Avegad Jumaryadi, Yuwan Kanasfi, Kanasfi Karyaningsih, Dentik KRESNO YULIANTO Kresno Yulianto KUNTORO Kuntoro Kuntoro Kurnia Setiawan Kutanto, Haronas Larasati, Pamela Linda Lingga Desyanita Luthfi Akbar Ramadhan Mahmudah Mahmudah Mailana, Agus Manurung, Ridho Parmonangan Maria Adiningsih Marlina, Hesti Martens, Brigitta Griselda Maskur A, Moch Riyadi Megananda Hervita Permata Sari Megawati, Rina Miechael, Miechael Miftahul Arifin Miftahul Arifin Mochammad Rizky Royani Moh Makruf Monica, Silvi Muhamad Fadel Muhammad Bagus Bintang Timur, Muhammad Bagus Bintang Muhammad Febrian Rachmadhan Amri Muhammad Noor Hasan Siregar Muhammad Risky Mulyati Mulyati Nazihah, Fasya Nendi, Nendi Ningrum, Yogi Ajeng Nugroho, Angelika Pratiwi Widya Nur Aisiyah Widjaja, Nur Aisiyah Nur Rohman Nurcahya, Gelar Nurfadhiilah, Annisa Nurfidaus, Yasmine Nursyi, Muhamad Pattipeilohy, William Frado Pattipeilohy, William Frado Pebriaini, Prisma Andita Popalia, Qamarullah Poppy Ruliana Pradiptha, Anindya Putri Prastiyo, Krisna Probo Anggraini, Julaiha Purwadi Purwadi Putra, Andi Agung Putra, Rinaldi Febryatna Duriat Rachmah Indawati Rahman, Fathin Aulia Rahmawati, Nur Anisah Rakhman, Abdulah Rakhmat Rakhmat Rakhmat Rakhmat RAMAYU, I Made Satrya Rangkuti, Muhammad Yusuf Rizqon Ratna Ayu Sekarwati Ratna Ayu Sekarwati Relawanto, Bowo Ria Puspitasari Riama Simanjuntak Ridho Dwi Maulida Rika Nurhayati Riki Ramdani Saputra Rina Megawati Ririh Yudhastuti Risaychi, Diva Ajeng Brillian Ristiana, Ina Riza, Yeni Rizkiyanto, Muhamad Ardiansyah Roedi Irawan Rojakul, Rojakul Rosita Dewi, Erni Ruliana, Poppy Rusdah Ruwirohi, Jan Everhard Ryo Tanaka Sabirin, Sahril Sadewo, Bayu Santoso, Febrina Mustika Saptari Wijaya Mulia Sari Anggar Kusuma Melati Sari, Fransiska Vina Sari, Wulan Novita Sasongko, Raden Satiri Satiri, Satiri Selamet Riyadi Selly Rahmawati Selly Rahmawati Septian Firman S Sodiq Septiani, Riska Setya Haksama Setyowati, Erlin Shofinurdin Shofinurdin Siddik Chaniago, Fajar Sigit Ari Saputro Sigit Budi Nugroho Siregar, Sutan Syahdinullah SITI NURUL HIDAYATI Sitti Aliyah Azzahra Soenarnatalina Melaniani Sudewo, Andika Hasbigumdi Sugiyarta, Ahmad Sujiharno Sujiharno Sumarna, Presma Dana Scendi Suntoro, Dimas Fahmi Supiyandi Supiyandi Syahirah, Afifah Tarmudzi, Rizky Tarwan Tiaharyadini, Rizka Triantoro, Ery TRISNAWATI, WULAN Tulus Yuniasih Umam, Mohamad Hafidhul Vasthu Imaniar Ivanoti Wahyu Cesar Wahyu Desena Wahyudi, Widi Wahyuni, Chatarina Unggul Wangsajaya, Yosia Heartha Dhalasta Wasis Budiarto Wibiyanto, Alif Dewan Daru Widiyaningrum, Diyah Kiki Widyanto, Tetrian Windhu Purnomo Yahya Darmawan Yudanto, Satyo Zakaria Anshori Zaqi Kurniawan