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All Journal JUTI: Jurnal Ilmiah Teknologi Informasi Syntax Literate: Jurnal Ilmiah Indonesia Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) International Journal of Advances in Data and Information Systems Journal of Social Research Malcom: Indonesian Journal of Machine Learning and Computer Science Sewagati Jurnal Informatika Polinema (JIP)
Santoso, Bagus Jati
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Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Public Health Social Sciences Other

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Pelatihan Deployment Aplikasi Berbasis Website SMK Pawiyatan Surabaya Pratomo, Baskoro Adi; Zaini, Alfa Fakhrur Rizal; Teja, Andika Rahman; Prinandika, Arya Gading; Fadhila, Farah Dhia; Arsyad, Hammuda; Fikriansyah, Irsyad; Al Kanza, Kalyana Putri; Vinorian, Muhammad Ersya; Diani, Nabila A'idah; Pramudya, Rafli Raihan; Ahmad, Tohari; Santoso, Bagus Jati; Studiawan, Hudan; Shiddiqi, Ary Mazharuddin; Alzamzami, Moch. Nafkhan; Anggoro, Radityo; Djanali, Supeno; Ijtihadie, Royyana Muslim; Suadi, Wahyu
Sewagati Vol 8 No 5 (2024)
Publisher : Pusat Publikasi ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j26139960.v8i5.2091

Abstract

Permintaan akan tenaga kerja terampil di bidang pengembangan perangkat lunak dan website terus meningkat seiring dengan pertumbuhan industri teknologi informasi. Di tengah situasi ini, banyak sekolah yang berupaya memenuhi kebutuhan tersebut dengan membuka program-program pendidikan khusus dalam pengembangan perangkat lunak dan website . Salah satu contohnya adalah SMK Pawiyatan Surabaya. Sebagai respons terhadap kondisi ini, kami berencana untuk menyelenggarakan program pelatihan kompetensi yang fokus pada deployment aplikasi berbasis website . Strategi pelaksanaan program ini dirancang secara terstruktur, dimulai dari pembelajaran konsep dasar hingga penerapan praktis deployment aplikasi secara langsung. Selain itu, program ini akan dilengkapi dengan evaluasi progres berkala guna memantau dan meningkatkan pemahaman serta keterampilan peserta sepanjang program berlangsung. Output yang diharapkan dari program ini termasuk laporan kegiatan yang komprehensif, dokumentasi video untuk memperlihatkan tahapan pelaksanaan program, serta berita acara yang mencatat semua aspek terkait program pelatihan ini. Dengan mengimplementasikan program pelatihan kompetensi deployment aplikasi berbasis website ini, SMK Pawiyatan Surabaya diharapkan dapat memberikan kontribusi yang signifikan dalam mempersiapkan generasi muda Indonesia untuk menjadi tenaga kerja yang kompeten dan siap beradaptasi dengan dinamika industri teknologi informasi global.
ANSWERING WHY-NOT QUESTIONS ON REVERSE SKYLINE QUERIES OVER INCOMPLETE DATA Santoso, Bagus Jati; Connery, Tosca Yoel
JUTI: Jurnal Ilmiah Teknologi Informasi Vol 17, No. 1, Januari 2019
Publisher : Department of Informatics, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j24068535.v17i1.a824

Abstract

        Recently, the development of the query-based preferences has received considerable attention from researchers and data users. One of the most popular preference-based queries is the skyline query, which will give a subset of superior records that are not dominated by any other records. As the developed version of skyline queries, a reverse skyline query rise. This query aims to get information about the query points that make a data or record as the part of result of their skyline query.     Furthermore, data-oriented IT development requires scientists to be able to process data in all conditions. In the real world, there exist incomplete multidimensional data, both because of damage, loss, and privacy. In order to increase the usability over a data set, this study will discuss one of the problems in processing reverse skyline queries over incomplete data, namely the "why-not" problem. The considered solution to this "why-not" problem is advice and steps so that a query point that does not initially consider an incomplete data, as a result, can later make the record or incomplete data as part of the results. In this study, there will be further discussion about the dominance relationship between incomplete data along with the solution of the problem. Moreover, some performance evaluations are conducted to measure the level of efficiency and effectiveness.
CONTINUOUS MULTIQUERIES K-DOMINANT SKYLINE ON ROAD NETWORK Muttaqi, Syukron Rifail; Santoso, Bagus Jati
JUTI: Jurnal Ilmiah Teknologi Informasi Vol. 18, No. 2, July 2020
Publisher : Department of Informatics, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j24068535.v18i2.a999

Abstract

The increasing use of mobile devices makes spatial data worthy of consideration. To get maximum results, users often look for the best from a collection of objects. Among the algorithms that can be used is the skyline query. The algorithm looks for all objects that are not dominated by other objects in all of its attributes. However, data that has many attributes makes the query output a lot of objects so it is less useful for the user. k-dominant skyline queries can be a solution to reduce the output. Among the challenges is the use of skyline queries with spatial data and the many user preferences in finding the best object. This study proposes IKSR: the k-dominant skyline query algorithm that works in a road network environment and can process many queries that have the same subspace in one processing. This algorithm combines queries that operate on the same subspace and set of objects with different k values by computing from the smallest to the largest k. Optimization occurs when some data for larger k are precomputed when calculating the result for the smallest k so the Voronoi cell computing is not repeated. Testing is done by comparing with the naïve algorithm without precomputation. IKSR algorithm can speed up computing time two to three times compared to naïve algorithm.
Analisis Sentimen Ulasan Pengguna Aplikasi Mobile SP4N-LAPOR! dengan Pendekatan Machine Learning Sulistiowati, Yeni; Santoso, Bagus Jati
Jurnal Informatika Polinema Vol. 11 No. 3 (2025): Vol. 11 No. 3 (2025)
Publisher : UPT P2M State Polytechnic of Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33795/jip.v11i3.7189

Abstract

Kemajuan teknologi informasi di Indonesia telah mendorong peningkatan akses internet, yang kini mencapai 79,5% dari total populasi. Kondisi ini menciptakan peluang besar bagi digitalisasi layanan publik, termasuk penerapan Sistem Pengelolaan Pengaduan Pelayanan Publik Nasional (SP4N-LAPOR!). Aplikasi ini memungkinkan masyarakat untuk menyampaikan pengaduan dengan cepat dan transparan melalui berbagai platform, termasuk aplikasi mobile. Semakin populernya perangkat mobile semakin memperkuat peran SP4N-LAPOR! dalam mendorong partisipasi masyarakat dalam pengawasan pelayanan publik. Namun, sebagian besar penelitian sebelumnya masih terbatas pada analisis data kualitatif dan kuantitatif deskriptif, sehingga pengalaman serta perspektif pengguna sebagai elemen utama dalam aplikasi ini belum tergambar secara komprehensif. Untuk mengatasi keterbatasan tersebut, penelitian ini mengusulkan penggunaan analisis sentimen terhadap ulasan masyarakat yang diberikan melalui aplikasi mobile berbasis Android. Pendekatan ini bertujuan untuk mengidentifikasi permasalahan teknis serta memberikan gambaran mengenai kualitas layanan yang disediakan oleh penyelenggara. Analisis dilakukan menggunakan teknik Machine Learning dengan tiga model utama: Naive Bayes (NB), Support Vector Machine (SVM), dan kombinasi keduanya (NBSVM) dengan tambahan fitur ekspansi N-gram. Hasil pengujian menunjukkan bahwa model NBSVM memiliki performa terbaik dengan G-Mean sebesar 0.8451, Sensitivity sebesar 0.8227 dan F2 Score sebesar 0.8215, mengungguli model NB dan SVM. Hasil dari penelitian ini diharapkan dapat menjadi alat evaluasi yang efektif bagi penyelenggara pelayanan publik serta memperkuat peran pengawasan Ombudsman RI dalam pelaksanaan SP4N-LAPOR!.
Analysis of Helpdesk System Development in A Manufacturing Company using Design Thinking Approach Sofi, Khalis; Santoso, Bagus Jati
International Journal of Advances in Data and Information Systems Vol. 6 No. 1 (2025): April 2025 - International Journal of Advances in Data and Information Systems
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59395/ijadis.v6i1.1354

Abstract

The IT department is vital in manufacturing companies, including PT XYZ, where operations involve transforming raw materials into finished goods. With the complexity of these activities, IT support is essential for managing software and hardware that aligns with business processes. PT XYZ implemented a helpdesk system to streamline IT services but encountered communication issues in the ticketing feature, affecting system efficiency and effectiveness. This research aimed to improve communication between users and administrators to enhance efficiency in monitoring and maintaining IT infrastructure. The study used a design thinking approach, chosen for its collaborative, flexible, and adaptive nature. The process began with the empathize stage, using usability scales and in-depth interviews with users to identify pain points and gather insights. Define, ideate, and prototype stages involved brainstorming and designing solutions in collaboration with the IT team. Finally, the testing stage evaluated user feedback on the improved system. The redevelopment of the helpdesk system yielded significant results, including a 12.27-point increase in usability scale scores. Enhanced features addressed user needs effectively, and all components of the upgraded system were well-received during testing. The improvements led to more structured and systematic communication, making the helpdesk system at PT XYZ more effective and efficient.
MAPPING POTENTIAL ATTACKERS AGAINST NETWORK SECURITY USING LOCATION AWARE REACHABILITY QUERIES ON GEO SOCIAL DATA Firdausi, Hafara; Santoso, Bagus Jati; Qudus, Rohana; Ciptaningtyas, Henning Titi
JUTI: Jurnal Ilmiah Teknologi Informasi Vol. 19, No. 2, Juli 2021
Publisher : Department of Informatics, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j24068535.v19i2.a1071

Abstract

Attacks on network security can happen anywhere. Using Geo-Social Networks (GSN), i.e., a graph that combines social network data and spatial information, we can find the potential attackers based on the given location. In answering the graph-based problems, Reachability Queries are utilized. It verifies the reachability between two nodes in the graph. This paper addresses a problem defined as follows: Given a geo-social graph and a location area as a query point, we map potential attackers against network security using location-aware reachability queries. We employ the concepts of Reachability Minimum Bounding Rectangle (RMBR) and graph traversal algorithm, i.e., Depth-First Search (DFS), to answer the location-aware reachability queries. There are two kinds of the proposed solution, i.e., (1) RMBR-based solution map potential attackers by looking for intersecting RMBR values, and (2) Graph traversal-based solution map potential attackers by traversing the graph. We evaluate the performance of both proposed solutions using synthetic datasets. Based on the experimental result, the RMBR-based solution has much lower execution time and memory usage than the graph traversal-based solution.
A Tag-Constrained Top-k Shortest Path for Finding Diverse Routes Santoso, Bagus Jati; Tamtama Adi, Ibrahim; Ijtihadie, Royyana Muslim
Jurnal Nasional Pendidikan Teknik Informatika: JANAPATI Vol. 14 No. 2 (2025)
Publisher : Prodi Pendidikan Teknik Informatika Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/janapati.v14i2.95815

Abstract

The top-k shortest path problem is a fundamental topic in graph theory and pathfinding applications. Traditional approaches focus solely on finding k paths with the least total cost or distance, often resulting in highly similar paths that offer limited flexibility for user selection. Moreover, real-world navigation demands often involve additional user preferences, such as specific points of interest or required amenities along the route. Motivated by this observation, this paper proposes an efficient framework for answering top-k diverse path search queries incorporating user-specified tag preferences. Specifically, given a source and destination node, a set of user-defined tags, and a similarity threshold, our method retrieves k shortest paths that not only satisfy the user's tag constraints but also maintain diversity by ensuring that the similarity among the retrieved paths remains below a given threshold. The proposed solution employs a two-phase approach: (1) preprocessing the graph structure to generate a tag-based matrix and shortest path data for efficient query processing, and (2) a hybrid search strategy that combines a modified Dijkstra’s algorithm and depth-first search with pruning based on tag satisfaction and diversity checking. Extensive experiments on synthetic road network datasets demonstrate that our method achieves significant improvements in query processing efficiency and provides a higher degree of path diversity compared to conventional approaches. Our contributions include the formal definition of the top-k diverse path search with tag preferences, the development of an efficient search framework, and comprehensive experimental validations. The results suggest that the proposed framework effectively balances path optimality, tag satisfaction, and diversity, enabling a more flexible and user-centric pathfinding system.
Implementasi Feature Selection Menggunakan Boruta untuk Peningkatan Akurasi Model Lapser Prediction: Implementation of Feature Selection Using Boruta to Improve the Accuracy of the Lapser Prediction Model Saputra, Mochamad Gilang; Santoso, Bagus Jati
MALCOM: Indonesian Journal of Machine Learning and Computer Science Vol. 5 No. 3 (2025): MALCOM July 2025
Publisher : Institut Riset dan Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57152/malcom.v5i3.1992

Abstract

Memprediksi pelanggan lapser menjadi tantangan utama di sektor layanan data yang kompetitif, disertai tingginya biaya akuisisi pelanggan baru. Penelitian ini mengusulkan pendekatan feature selection menggunakan Boruta untuk meningkatkan akurasi model lapser, dengan menerapkan teknik wrapper pada Random Forest. Proses modeling lapser prediction menggunakan algoritma machine learning Gradient Boosting yang dianalisis sebelum dan sesudah seleksi fitur Boruta. Hasil eksperimen pada data menunjukkan bahwa Boruta efektif dalam meningkatkan metrik utama (akurasi, recall, dan AUC). Model Gradient Boosting meraih akurasi hingga 75.10%, recall 74.42%, dan AUC 82.18% setelah menggunakan Boruta. Sebelum menggunakan Boruta nilai akurasi 71.74%, recall 68.74%, dan AUC hanya 77.77%. Temuan tersebut menegaskan bahwa pendekatan yang diusulkan dapat memprediksi lapser secara lebih dini, serta membantu penyusun kebijakan menyusun strategi retensi pelanggan yang lebih efektif, sehingga meminimalkan potensi kerugian dan memperkuat daya saing di pasar.
Machine Learning-Based Prediction of Divorce Verdicts Using Posita Data and Imbalanced Data Handling: A Case Study in Padang Sidempuan Rahmadini, Rina; Santoso, Bagus Jati
International Journal of Advances in Data and Information Systems Vol. 6 No. 2 (2025): August 2025 - International Journal of Advances in Data and Information Systems
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59395/ijadis.v6i2.1405

Abstract

This study aims to develop a predictive model for divorce verdicts ("Granted" or "Rejected") in the Religious Courts of Indonesia using machine learning techniques. The dataset consists of 2,026 finalized divorce cases from the Religious Court of Padang Sidempuan between 2018 and 2025, incorporating structured variables and posita—narrative texts describing the plaintiff’s reasons for divorce. Keyword-based feature extraction was applied to transform these texts into interpretable indicators. To handle class imbalance, Synthetic Minority Over-sampling Technique (SMOTE) was implemented on the training data. Six classical machine learning algorithms were evaluated: Decision Tree, Naïve Bayes, K-Nearest Neighbors, Random Forest, LightGBM, and XGBoost. Performance was measured using accuracy, precision, recall, F1-score, F2-score, and AUC. The results indicate that Naïve Bayes achieved the highest recall (100%) for the “Granted” class, while LightGBM and XGBoost demonstrated the most balanced performance across both classes. Feature importance analysis revealed that mediation outcomes, domestic violence, and economic hardship were among the most influential factors in determining verdicts. The study highlights the applicability of interpretable machine learning in legal decision support and discusses limitations such as the single-court scope and challenges in predicting minority class outcomes. Future work may explore multi-jurisdictional data, deep learning approaches, and domain-specific embeddings for enhanced performance.
Decentralized Electronic Health Record Management with Semantic-Aware Hierarchical Encryption Kurniyanto, Firdaus Putra; Santoso, Bagus Jati
International Journal of Advances in Data and Information Systems Vol. 6 No. 2 (2025): August 2025 - International Journal of Advances in Data and Information Systems
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59395/ijadis.v6i2.1413

Abstract

The rising incidence of cyberattacks targeting electronic health records (EHR) in Indonesia necessitates a robust and context-aware data protection scheme. This paper proposes a decentralised EHR management system that leverages blockchain, IPFS, and a novel Semantic-Aware Hierarchical Encryption (SAHE) algorithm. SAHE enables multi-level access control based on data sensitivity semantics, ensuring privacy while maintaining usability for medical professionals. The system was implemented in a prototype environment and evaluated through stress testing with up to 200 users, achieving an average CPU usage of 55% and a memory consumption of 80.2 MB. Differential cryptanalysis demonstrated a strong avalanche effect (~50%), with no vulnerabilities found via OWASP ZAP scanning. This architecture offers a promising solution for privacy-preserving, patient-controlled EHR systems, particularly in regions with limited infrastructure.
Co-Authors Al Kanza, Kalyana Putri Alzamzami, Moch. Nafkhan Arsyad, Hammuda Ary Mazharuddin Shiddiqi Baskoro Adi Pratomo Connery, Tosca Yoel Diani, Nabila A'idah Fadhila, Farah Dhia Fikriansyah, Irsyad Firdausi, Hafara Henning Titi Ciptaningtyas Hudan Studiawan Khalis Sofi Kurniyanto, Firdaus Putra Mokh. Suef Mujahidin, Noor Qidam Muttaqi, Syukron Rifail Pramudya, Rafli Raihan Prinandika, Arya Gading Qudus, Rohana Radityo Anggoro, Radityo Rahmadini, Rina Royyana Muslim Ijtihadie Saputra, Mochamad Gilang Sulistiowati, Yeni Supeno Djanali Tamtama Adi, Ibrahim Teja, Andika Rahman Tohari Ahmad Vinorian, Muhammad Ersya Wahyu Suadi Winoto, Maria Nicolas Ganden Gondho Zaini, Alfa Fakhrur Rizal