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All Journal JURNAL SISTEM INFORMASI BISNIS Elkom: Jurnal Elektronika dan Komputer Prosiding Seminar Nasional Sains Dan Teknologi Fakultas Teknik Jurnal Transformatika Scientific Journal of Informatics Jurnal Informatika Upgris Prosiding 2nd Seminar Nasional IPTEK Terapan (SENIT) 2017 Progresif: Jurnal Ilmiah Komputer Jurnal Teknologi Informasi dan Komunikasi Journal of Engineering, Electrical and Informatics (JEEI) INFORMATIKA Jurnal Pengabdian Mandiri Jurnal Publikasi Ilmu Komputer dan Multimedia Jurnal Teknik Informatika dan Teknologi Informasi Jurnal Manajemen Informatika & Teknologi Jurnal Publikasi Teknik Informatika (JUPTI) Community: Jurnal Pengabdian Pada Masyarakat Journal of Technology Informatics and Engineering Seminar Nasional Teknologi dan Multidisiplin Ilmu SWAGATI: Journal of Community Service Saturnus: Jurnal Teknologi dan Sistem Informasi Systematic Literature Review Journal Journal of Engineering, Electrical and Informatics Global Science: Journal of Information Technology and Computer Science
Toni Wijanarko Adi Putra
Universitas Sains Dan Teknologi Komputer
Agriculture, Biological Sciences & Forestry Arts Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Health Professions Languange, Linguistic, Communication & Media Mechanical Engineering Nursing Public Health Social Sciences Other

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KETRAMPILAN KOMPUTER GRAFIS UNTUK MENINGKATKAN KREATIVITAS WIRAUSAHA REMAJA DI MASJID DI KECAMATAN GAJAHMUNGKUR Nur Hakim, Fitro; Solechan, Achmad; Kusumo, Haryo; Fitrianto, Yuli; Wijanarko Adiputro, Toni
Community : Jurnal Pengabdian Pada Masyarakat Vol. 4 No. 3 (2024): November : Jurnal Pengabdian Pada Masyarakat
Publisher : LPPM Sekolah Tinggi Ilmu Ekonomi - Studi Ekonomi Modern

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/d3e59c41

Abstract

Permasalahan yang dihadapi oleh mitra pengabdian remaja masjid antara lain: banyak remaja masjid tidak memahami perangkat lunak grafis atau prinsip desain grafis, dan desain acara masjid harus sesuai dengan nilai-nilai dan kebutuhan komunitas. Remaja masjid mungkin memerlukan waktu untuk memahami dan menerapkan elemen desain yang tepat, serta mengatur waktu mereka antara kegiatan masjid, sekolah, dan aktivitas lain. Kegiatan pengabdian ini dilaksanakan di masjid remaja di Kecamatan Gajah Mungkur, khususnya di masjid MTA Gajah Mungkur. Para remaja menerima pelatihan langsung dan mendapatkan pendampingan langsung secara bertahap.  Dalam waktu satu hari, kegiatan ini diikuti oleh sepuluh remaja dari masjid MTA Gajahmungkur, dan dipandu oleh lima pemateri atau dosen dari Universitas Sains dan Teknologi Komputer dan Stikes Telogorejo. Ada berbagai metode pembelajaran, seperti ceramah, praktik, dan tanya jawab, untuk melakukan kegiatan ini. Setelah kegiatan pengabdian masyarakat di MTA Kecamatan Gajahmungkur, yang terdiri dari ceramah dan pelatihan di bidang pelatihan bagi para peserta (remaja masjid), dapat disimpulkan bahwa para peserta mengikuti pelatihan keterampilan komputer grafis. Mereka memperhatikan materi pelatihan seperti desain grafis untuk pemberdayaan komunitas dan desain grafis untuk mendukung produktivitas.
Systematic Literature Review : Analysis of the Impact of Supply Chain Automation on Worker Welfare in the Sustainable Industrial Sector Toni Wijanarko Adi Putra; Aslina Baharum
Systematic Literature Review Journal Vol. 1 No. 1 (2025): Januari: Systematic Literature Review Journal
Publisher : International Forum of Researchers and Lecturers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70062/slrj.v1i1.51

Abstract

This study aims to explore the impact of supply chain automation on workers’ well-being in the sustainable industrial sector through a Systematic Literature Review (SLR) approach. The transformation driven by Industry 4.0 technologies such as artificial intelligence (AI), Internet of Things (IoT), and blockchain, has presented significant challenges and opportunities. This study identifies the impacts of automation on workers’ economic, social, and psychological aspects, including changes in skills requirements, reduction of manual employment, and its effects on mental health. In addition, this study also highlights the importance of sustainability in automation implementation, by balancing economic efficiency, environmental preservation, and social welfare. By integrating the results of studies from various literatures, this study provides recommendations for policies that support sustainability and social inclusiveness, as well as strategic guidance for industries in adopting supply chain automation sustainably.
Perancangan dan Implementasi Sistem Informasi Presensi Pegawai Berbasis Web Menggunakan Fingerspot pada KPP Pratama Alex Ristanto Pratama; Eko Siswanto; Toni Wijanarko Adi Putra; Budi Hartono; Arsito Ari Kuncoro
Jurnal Manajemen Informatika & Teknologi Vol. 6 No. 1 (2026): Mei : Jurnal Manajemen Informatika & Teknologi
Publisher : LPPM Sekolah Tinggi Ilmu Ekonomi - Studi Ekonomi Modern

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/mhjsx258

Abstract

Employee attendance is a crucial component of human resource management, particularly in government institutions such as the Tax Service Office (KPP) Pratama. The manual attendance system previously used is prone to fraud, inefficient in data processing, and time-consuming during recap. This study aims to design and implement a web-based employee attendance information system integrated with Fingerspot biometric devices to improve accuracy, security, and efficiency in attendance management. The research employs the Research and Development (R&D) method using the Borg & Gall model, which includes stages of preliminary study, system design, product development, expert validation, limited trials, revisions, and implementation. The system was developed using the Laravel (PHP) framework and a MySQL database, integrated with the Fingerspot API to synchronize attendance data in real time. Validation results from three experts produced an average feasibility score of 4.32 out of 5, indicating that the system is highly suitable for use. Trials conducted with 10 KPP Pratama employees showed that 90% of respondents found the system more practical and 100% stated that it effectively prevents attendance fraud. Furthermore, the monthly attendance recap time was significantly reduced from 3 days to less than 1 hour. Therefore, this system has proven to be a reliable digital solution that supports transparent and accountable personnel management within KPP Pratama.
Pengembangan Aplikasi Chat Bot Whatsapp, Telegram, dan Website Laporan untuk Instansi Pemerintah Disperkim Pool Seroja Kota Semarang Berbasis Natural Language Processing Endrahadi Rahadian; Toni Wijanarko Adi Putra; Budi Hartono; Arsito Ari Kuncoro; Eko Siswanto
Jurnal Manajemen Informatika & Teknologi Vol. 6 No. 1 (2026): Mei : Jurnal Manajemen Informatika & Teknologi
Publisher : LPPM Sekolah Tinggi Ilmu Ekonomi - Studi Ekonomi Modern

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/fzgtt673

Abstract

The rapid development of information and communication technology has encouraged government agencies to improve the quality of public services through digital transformation. This research focuses on developing a multi-platform chatbot application integrated with WhatsApp, Telegram, and a web-based reporting system to support the public service operations of DISPERKIM POOL Seroja, Semarang City. The main issues identified include limited access to information, dependency on office hours, and increased workload for staff in handling repetitive inquiries from the public. Using a methodology that includes needs analysis, system design, implementation, and testing, the chatbot was developed using Natural Language Processing (NLP) to understand user intent in natural Indonesian language and provide accurate, real-time automated responses. The implementation results show that the system performs effectively, achieving an intent recognition accuracy rate of over 85% and an average response time of less than three seconds. User testing also indicates high satisfaction levels, as the chatbot significantly simplifies access to information and facilitates faster reporting processes. Overall, the system enhances public service efficiency, reduces the burden on DISPERKIM staff, and supports the government's digital transformation agenda toward smart and responsive public services.
EXPLORATION OF AMPLITUDE CODING CAPACITIES FOR Q-ML MODEL Unang Achlison; Dendy Kurniawan; Toni Wijanarko Adi Putra; Siswanto Siswanto
Journal of Engineering, Electrical and Informatics Vol. 2 No. 3 (2022): Oktober: Journal of Engineering, Electrical and Informatics:
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jeei.v2i3.916

Abstract

Quantum computing implements computation adopting environmental phantasm and the foundation of quantum mechanics to clear up the issues. This design of calculation has been demonstrated to serve the acceleration of some modern processing issues. Current evolution in quantum technology is emerging, and the application of learning design to this current instrument is developing. With enough prospects, the application of quantum development in the area of Machine Learning has come clear. This research develops a TensorFlow Quantum (TF-Q) software framework model for machine learning functions. The two models advanced the application of material coding techniques from amplitude coding to constructing a case in the quantum learning model. This study aimed to explore the scope of amplitude coding to serve enhanced case establishment in learning techniques and in-depth investigation of data sets that bring insight into the practice data adopting the “Variational Quantum Classifier” (VQ-C). The emergence of this current method raises the investigation of how best this tool can be adopted, the aim is to provide several analysis explanations for the element of quantum machine learning that can be applied given the constraints of the actual device. The results of this study indicate there are clear advantages to adopting amplitude coding over another technique as demonstrated by adopting the combination of quantum-humanistic neural networks in TF-Q. In addition, the different preprocessing steps can generate more aspect-affluent data while using VQ-C the no-charge lunch assumption dominance for quantum learning technique for humanistic models. The material even though conceal in quantum by unadvanced data preparation steps but involves new ways of understanding and appreciating these new methods. Future studies will lack expansion into multi-type of analysis models that are sufficiently advanced to be relevant in work similar to this.
Cash Sales Information System Multiuser Based On Human Computer Facilities Semarang Dwi Prasetyaningsih; Fujiama Diapoldo Silalahi; Toni Wijanarko Adi Putra
Journal of Engineering, Electrical and Informatics Vol. 3 No. 1 (2023): Februari : Journal of Engineering, Electrical and Informatics
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jeei.v3i1.2859

Abstract

Sarana Insan Computer (SIK), a sales company operating in the computer sector in Central Java, has utilized Information Systems even though they are not yet well integrated between one system and another. Therefore, in this thesis the author will develop a cash sales system model by choosing SIK as the research object. The cash sales information system created includes a system for ordering goods, sending goods, sales returns and cash sales reports. This research aims to make it easier to present reports directly, accurately, quickly and to enable systems that do not yet exist to be integrated into an integrated system. So that the cash sales information system can be implemented well, a software development process is carried out which is based on correct software engineering. The software development model used in this research is a multiuser development model. Information technology which is developing rapidly today really provides support for the development of a cash sales information system for a computer sales company such as SIK, especially with the use of computer-based information technology or better known as a Computer Based Information System, because of the use of computer technology in a system. information will be able to process data more quickly with minimal error rates, save labor and save costs. The Cash Sales Information System is designed using direct data processing methods. The use of the direct data processing method is intended so that every incident of cash sales information can be processed directly. The procedures that will be processed consist of the administration section which handles administration, the purchasing section which handles incoming goods, the sales section which handles customer service and the computer goods sales section, the personnel section and the leadership itself.
Explainable End-to-End Autonomous Driving Using Vision-Based Deep Learning in Safety-Critical Scenarios Sasmoko, Dani; Adi Supriyono, Lawrence; Wijanarko Adi Putra, Toni
Global Science: Journal of Information Technology and Computer Science Vol. 1 No. 4 (2025): December: Global Science: Journal of Information Technology and Computer Scienc
Publisher : International Forum of Researchers and Lecturers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70062/globalscience.v1i4.185

Abstract

End-to-end autonomous driving has emerged as a promising paradigm in which deep neural networks directly map raw visual inputs to continuous control actions. Despite its effectiveness, this approach suffers from limited transparency, posing significant challenges for deployment in safety-critical driving scenarios. This study addresses the lack of interpretability in vision-based end-to-end autonomous driving systems and aims to analyze model decision-making behavior under critical conditions such as sharp steering maneuvers and abrupt control transitions. To this end, an explainable end-to-end autonomous driving framework is proposed, combining a convolutional neural network trained via imitation learning with gradient-based visual attribution techniques, including Grad-CAM. The model predicts continuous steering, throttle, and braking commands directly from front-facing camera images, while explainability mechanisms are applied to reveal input regions influencing each control decision. Model performance is evaluated using both prediction accuracy and safety-oriented behavioral metrics. Experimental results show that the proposed explainable model achieves lower control prediction errors compared to a baseline end-to-end CNN, reducing steering mean squared error from 0.034 to 0.031, throttle error from 0.021 to 0.019, and brake error from 0.018 to 0.016. Moreover, safety-oriented analysis indicates improved driving stability, with steering variance reduced from 0.087 to 0.072 and abrupt control changes decreased from 14.6 to 10.3 events. Visual explanations consistently highlight road surfaces and lane-related structures during complex maneuvers, indicating reliance on semantically meaningful cues. In conclusion, the results demonstrate that integrating explainability into end-to-end autonomous driving not only preserves predictive performance but also correlates with smoother and more stable driving behavior. This framework contributes to the development of transparent and trustworthy autonomous driving systems suitable for safety-critical applications
IMPLEMENTASI ALGORITMA BASE64 PADA SISTEM LOGIN MENGGUNAKAN JSON WEB TOKEN (JWT) UNTUK AUTENTIKASI WEB Ulil Asyhar; Budi Hartono; Toni Wijanarko Adi Putra
JURNAL TEKNOLOGI INFORMASI DAN KOMUNIKASI Vol. 17 No. 1 (2026): Maret
Publisher : UNIVERSITAS STEKOM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/jtikp.v17i1.1311

Abstract

Authentication security is a crucial aspect of web application development, particularly in login systems that function as the primary gateway to an application or web service. The authentication process plays a vital role in ensuring that only authorized users can access the system, thereby preventing data breaches, information misuse, and potential system damage. Traditional login methods that store passwords in plain text or rely solely on session IDs are vulnerable to theft and session hijacking. This research proposes the implementation of JSON Web Tokens(JWT) with Base64 encoding, integrated through Web Service technology, to enhance login system security. JWT is a JSON-based token standard used for secure information exchange between clients and servers. The token consists of three parts—header, payload, signature—each encoded using Base64URL. Base64 is an encoding method that converts binary data into ASCII text, making it safe for transmission over HTTP protocols. In this implementation, the bcrypt algorithm is utilized for password hashing, ensuring that the original password is never stored directly in the database. The Web Service acts as an intermediary for communication between the client and server without the need to store session data on the server. During login, the system verifies credentials, generates a JWT token, and sends it to the client for subsequent authenticated requests. Testing results demonstrate improved security, as tokens can be verified without maintaining server-side sessions, while Base64 encoding ensures safe data transmission. This implementation is expected to serve as a practical solution and reference for future advancements in web application security.
Utilizing Explainable AI for Interpreting Machine Learning Model Results in Ceria Credit Scoring Roni Eka Setiawan; Toni Wijanarko Adi Putra; Budi Hartono
Progresif: Jurnal Ilmiah Komputer Vol 21, No 2 (2025): Agustus
Publisher : STMIK Banjarbaru

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35889/progresif.v21i2.2769

Abstract

This study aims to improve the transparency of machine learning models in credit scoring using various Explainable Artificial Intelligence (XAI) methods. The methods used include SHAP, BRCG, ALE, Anchor, and ProtoDash to explain the prediction results of machine learning models, namely logistic regression, XGBoost, and random forest. This study applies a quantitative approach with a comparative method, where Ceria loan application data from Bank Rakyat Indonesia (BRI) is analyzed using a machine learning model, then evaluated using the Explanation Consistency Framework (ECF). The results show that the XAI method can improve understanding of model decisions, with SHAP and ALE effective for global explanations, while Anchor and ProtoDash provide in-depth insights at the individual level. Evaluation using ECF shows that the post-hoc method has high consistency, although Anchor has limitations in the aspect of axiom identity. In conclusion, the XAI method can help improve trust and transparency in credit scoring at BRI.Keywords: Explainable Artificial Intelligence; Credit Scoring; Machine Learning; Model Interpretability; Explanation Consistency Framework AbstrakPenelitian ini bertujuan untuk meningkatkan transparansi model pembelajaran mesin dalam penilaian kredit menggunakan berbagai metode Explainable Artificial Intelligence (XAI). Metode yang digunakan antara lain SHAP, BRCG, ALE, Anchor, dan ProtoDash untuk menjelaskan hasil prediksi model pembelajaran mesin yaitu regresi logistik, XGBoost, dan random forest. Penelitian ini menggunakan pendekatan kuantitatif dengan metode komparatif, dimana data pengajuan pinjaman Ceria dari Bank Rakyat Indonesia (BRI) dianalisis menggunakan model machine learning, kemudian dievaluasi menggunakan Explanation Consistency Framework (ECF). Hasilnya menunjukkan bahwa metode XAI dapat meningkatkan pemahaman keputusan model, dengan SHAP dan ALE efektif untuk penjelasan global, sementara Anchor dan ProtoDash memberikan wawasan mendalam pada tingkat individu. Evaluasi menggunakan ECF menunjukkan bahwa metode post-hoc memiliki konsistensi yang tinggi, meskipun Anchor memiliki keterbatasan pada aspek identitas aksioma. Kesimpulannya, metode XAI dapat membantu meningkatkan kepercayaan dan transparansi dalam credit scoring di BRI.Kata Kunci: Explainable Artificial Intelligence; Credit Scoring; Machine Learning; Model Interpretability; Explanation Consistency Framework
Co-Authors Achmad Solechan Adi Supriyono, Lawrence Agung Surono Ahmad Ashifuddin Aqham Aldho Dwi Kurniawan Alex Ristanto Pratama Arditya Himawan Arsito Ari Kuncoro Aslina Baharum Budi Hartono Budi Hartono budi hartono Budi Hartono Chandani, Chicie Chicie Chandani Danang Danang Dani Sasmoko Dendy Kurniawan Devi Astri Nawangnugraeni Dimas Rahardian Dwi Prasetyaningsih Edy Siswanto Eko Siswanto Eko Siswanto Endrahadi Rahadian Endro Farhan Afif Ilmi Febryantahanuji Febryantahanuji Fitro Nur Hakim Fitro Nur Hakim Fujiama Diapoldo Silalahi Fujiama Diapoldo Silalahi Hakim , Fitro Nur Haryo Kusumo Haryo Kusumo Iman Saufik Suasana Isaac Vital Jarot Dian Susatyono Kusumo, Haryo Kusworo Adi M. Zakki Abdillah Migunani Migunani Mohamad Irkam Nuris Dwi Setiawan R Rizal Isnanto Roni Eka Setiawan Rusito Siswanto Siswanto Siswanto Siswanto Siswanto, Edy Solikhin Solikhin Sulartopo Sulartopo Ulil Asyhar Unang Achlison Victor Gayuh Utomo Wibowo, Mars Caroline Yehezkiel Yanu Putranto Yuli Fitrianto Zaenal Mustofa