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All Journal JURNAL SISTEM INFORMASI BISNIS Elkom: Jurnal Elektronika dan Komputer Bulletin of Electrical Engineering and Informatics Prosiding Seminar Nasional Sains Dan Teknologi Fakultas Teknik Jurnal Transformatika Scientific Journal of Informatics Register: Jurnal Ilmiah Teknologi Sistem Informasi Jurnal Informatika Upgris Prosiding 2nd Seminar Nasional IPTEK Terapan (SENIT) 2017 Progresif: Jurnal Ilmiah Komputer Jurnal Teknologi Informasi dan Komunikasi Jurnal Sosial dan Teknologi INFORMATIKA Jurnal Pengabdian Mandiri Jurnal Teknik Informatika dan Teknologi Informasi Jurnal Manajemen Informatika & Teknologi Jurnal Riset Rumpun Seni, Desain dan Media (JURRSENDEM) 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 International Journal of Information Technology and Business Systematic Literature Review Journal Journal of Engineering, Electrical and Informatics Global Science: Journal of Information Technology and Computer Science Jurnal Publikasi Sistem Informasi dan Manajemen Bisnis Jurnal Publikasi Ilmu Komputer dan Multimedia Jurnal Publikasi Teknik Informatika
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 Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mechanical Engineering Nursing Public Health Social Sciences Other

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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
Explainable End-to-End Autonomous Driving Using Vision-Based Deep Learning in Safety-Critical Scenarios Dani Sasmoko; Lawrence Adi Supriyono; Toni Wijanarko Adi Putra
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
Manajemen Webinar Terintegrasi Berbasis Web dan Pengembangan Sistem Perpustakaan Digital untuk Divisi Pelatihan SDM Rizal Dewo Susanto; Toni Wijanarko Adi Putra; Eko Siswanto
Jurnal Publikasi Sistem Informasi dan Manajemen Bisnis Vol. 5 No. 2 (2026): Mei : Jurnal Publikasi Sistem Informasi dan Manajemen Bisnis
Publisher : Pusat Riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jupsim.v5i2.6992

Abstract

The rapid growth of digital technology has transformed how organizations manage human resource training. PT Bisnis Digital Ekonomi (BDE), through its HR Master Division, conducted 16 webinar series with 2,851 participants between July 2025 and February 2026; however, all administrative processes were managed manually across disconnected platforms including Zoom, Google Drive, and spreadsheets, resulting in fragmented knowledge assets and operational inefficiency. This study aims to design and develop an integrated web-based webinar management and Digital Library system for the HR Master Division using the Waterfall method. Data were collected through direct observation and semi-structured interviews with two division staff members. The system was built using PHP Laravel with MVC architecture and MySQL database, supporting four user roles: Super Admin, HR Master Admin, Trainer, and Employee. Black Box Testing across 24 test scenarios yielded a 100% success rate with no critical bugs detected. The system successfully consolidates webinar scheduling, participant registration, digital attendance, material archiving, and report export into a single platform accessible via hrmasterid.com, eliminating cross-platform fragmentation. This study contributes a replicable integrated training information system model for corporate HR divisions facing similar knowledge management challenges.
Explainable Clinical Risk Prediction from EHR Tabular Data using Monotonic Constraints and Calibrated Probabilities Danang Danang; Toni Wijanarko Adi Putra
Jurnal Riset Rumpun Seni, Desain dan Media Vol. 2 No. 1 (2023): April : Jurnal Riset Rumpun Seni, Desain dan Media
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jurrsendem.v2i1.9197

Abstract

Tabular-based clinical risk prediction models are extensively applied in medical decision support systems; however, two major challenges often reduce their reliability: predictions that contradict basic clinical logic and poorly calibrated probability outputs that weaken threshold-based decision making. This study investigates explainable binary risk prediction using the processed Cleveland subset of the UCI Heart Disease dataset as a public clinical benchmark. A lightweight and CPU-efficient pipeline is proposed by employing an XGBoost classifier integrated with monotonic constraints on clinically relevant features, followed by probability calibration through post-hoc methods, including Platt scaling, temperature scaling, and isotonic regression on a separate validation set. Model performance is assessed in terms of discrimination capability using AUROC, AUPRC, F1-score, sensitivity, and specificity, while probability reliability is evaluated using ECE and Brier score metrics. A monotonicity audit is also conducted through counterfactual feature sweeps to measure violation rates. In addition, the model is applied for risk stratification into low-, medium-, and high-risk categories with corresponding event-rate reporting. The findings demonstrate that isotonic regression improves probability reliability without degrading discrimination performance. Furthermore, the monotonicity audit reveals no observed violations for constrained features. Overall, the integration of monotonic constraints and probability calibration produces more decision-ready risk estimates for threshold-based clinical decision support while maintaining transparency through SHAP-based analysis.
Sistem Presensi Otomatis untuk Gereja dengan Teknologi RFID dan Penyimpanan Data Terstruktur Andra Matarisman; Khoirur Rozikin; Toni Wijanarko Adi Putra
Jurnal Sosial Teknologi Vol. 6 No. 7 (2026): Jurnal Sosial dan Teknologi
Publisher : CV. Green Publisher Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59188/jurnalsostech.v6i7.32929

Abstract

Gereja Sidang Jemaat Kristus (GSJK) Palangkaraya masih menerapkan sistem presensi manual di mana petugas mencatat kehadiran jemaat saat ibadah berlangsung lalu menginputnya ke sistem secara manual setelah ibadah selesai. Proses ini rentan terhadap kesalahan pencatatan (human error), duplikasi data, serta menyulitkan rekapitulasi secara berkala. Penelitian ini bertujuan merancang dan membangun sistem presensi otomatis berbasis Radio Frequency Identification (RFID) menggunakan mikrokontroler ESP32 yang terintegrasi dengan Firebase Realtime Database dan dashboard monitoring berbasis web. Metode pengembangan yang digunakan adalah model prototype. Perangkat keras dirancang menggunakan modul RFID RC522, ESP32, LCD 16x2 I2C, dan piezo buzzer. Perangkat lunak terdiri dari firmware ESP32 berbasis C++ dan dashboard web berbasis HTML, CSS, dan JavaScript. Pengujian sistem dilakukan menggunakan metode black box testing pada 48 skenario dengan tingkat keberhasilan 100%. Hasil pengujian validitas kelayakan oleh dosen pakar memperoleh skor rata-rata 4.0 dari 4.0 (Sangat Layak), dan uji penerimaan pengguna (UAT) memperoleh skor 3,93 dari 4,00 (Sangat Layak). Sistem ini berhasil mencatat kehadiran jemaat dalam waktu kurang dari satu detik dengan rata-rata latensi sinkronisasi data ke Firebase sebesar 0,6 detik, serta mengeliminasi entri data manual.
PELUANG BISNIS PADA PENERAPAN INDUSTRIAL INTERNET OF THING (IIoT) Achmad Solechan; Jarot Dian Susatyono; Toni Wijanarko AP.; Febryantahanuji Febryantahanuji
Jurnal Publikasi Ilmu Komputer dan Multimedia Vol. 1 No. 3 (2022): September: Jurnal Publikasi Ilmu Komputer dan Multimedia
Publisher : Pusat Riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jupikom.v1i3.784

Abstract

This research was conducted using qualitative methods and exploratory literature review, where after a number of journal references were collected, a theoretical study, research results and discussion of this literature review article were carried out in the Industrial Internet of Things (IIoT) concentration. This research presents the results of a study of business opportunities from the use of the Industrial Internet of Things (IIoT). IoT can be implemented in various fields of the modern economy, for example: health, environment, defence, quality control, transportation, logistics, clean water, building / construction, industrial production / manufacturing, energy sources, agriculture and plantations. By utilizing IIoT, companies can benefit from technology investments made from saving operational costs and increasing company revenue. The suggestions for this research include the need to develop the implementation of IIoT in various fields so that it is more effective, efficient and provides convenience to companies. Future research needs to analyze opportunities, challenges and directions for future research work related to IIoT regarding the benefits of using IIoT technology including real-time, coexistence, interoperability, optimal security and privacy.
Accurate hybrid prediction model for poverty line, number, and percentage of impoverished individuals Toni Wijanarko Adi Putra; Yohanes Suhari; Achmad Solechan; Solikhin Solikhin; M. Zakki Abdillah
Bulletin of Electrical Engineering and Informatics Vol 15, No 1: February 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v15i1.10533

Abstract

Poverty remains a major social issue in many developing countries, including Indonesia, as seen in the Central Java region. Over the last five years, the number of impoverished people in Central Java has shown fluctuations, with data from the Central Statistics Agency indicating figures of 3,897.20 thousand (2018), 3,743.23 thousand (2019), 3,980.90 thousand (2020), 4,109.7 thousand (2021), and 3,831.44 thousand (2022). Analyzing these trends is crucial for future poverty reduction efforts. This study aims to develop a web-based predictive system capable of forecasting the poverty line, as well as the number and percentage of poor residents in Central Java. The research utilizes a hybrid forecasting model that integrates the Holt-Winters triple exponential smoothing (HWTES) method with fuzzy time series (FTS), alongside algorithmic approaches such as rate of change (RoC) and frequency-based segmentation. The model's accuracy, evaluated using the average absolute percentage error (MAPE), shows low error rates: 0.9% for the number of impoverished people, 1.6% for the percentage, and 0.7% for the poverty threshold. Compared to the standard HWTES model, this hybrid model demonstrates greater precision. As a result, it can serve as an effective tool to support strategic planning and enhance poverty alleviation programs in Central Java.
PERANCANGAN DAN IMPLEMENTASI PENGGUNAAN BARCODE READER PADA SISTEM APLIKASI PEMBAYARAN SPP BERBASIS WEB Zaenal Mustofa; Toni Wijanarko Adi Putra
Jurnal Publikasi Teknik Informatika Vol. 1 No. 1 (2022): Januari : Jurnal Publikasi Teknik Informatika
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jupti.v1i1.95

Abstract

Along with the rapid development of technology, especially in the field of information technology, it demands almost every part of our lives to take advantage of it. Especially in daily work that demands a fast, precise and accurate process. Therefore, at this time information technology cannot be separated from part of our daily work processes. To get fast work results, it needs to be supported by simple and applicable tools. Madrasah Tsanawiyah (MTs) Jepara is a junior secondary level formal education institution which is geographically located in Karangawen Village, Karangawen District, Demak Regency, with a total of about 800 students divided into 25 classes. To serve student payments with a large number of students, MTs Jepara is no longer serving manually, namely by writing in a book to record payment transactions, but has used a student financial payment application created using Microsoft Access. With this application, all student financial payment transactions can be accessed easily and quickly which are served by Administrative Staff to support the work process. The purpose of this research is to build a school financial payment system with barcode tools at MTs Jepara Demak to help speed up data input on the student financial payment application at MTs Jepara Demak so that services in student financial payments at MTs Jepara Demak become faster. In this study, the application used is Microsoft Access programming using Barcode Reader as a tool
A Web-Based Forecasting Approach to Estimating the Number of Low-Income Households Eligible for Social Food Aid Using Holt’s Double Exponential Smoothing Mukhamad Masrur; Solikhin Solikhin; Muhammad Walid Syahrul Churum; M. Zakki Abdillah; Toni Wijanarko Adi Putra
Register: Jurnal Ilmiah Teknologi Sistem Informasi Vol 11 No 2 (2025): July
Publisher : Information Systems - Universitas Pesantren Tinggi Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26594/register.v11i2.4922

Abstract

This work presents a web-based forecasting methodology for predicting the quantity of low-income households qualified for social food assistance utilizing Holt’s Double Exponential Smoothing (HDES) technique. Precise assessment is crucial for governmental bodies and social welfare organizations to guarantee efficient aid distribution and effective resource allocation. The proposed method amalgamates time series forecasting models with a web-based application to deliver real-time predictions and accessibility for decision-makers. Historical data on low-income household statistics were employed to formulate and authenticate the forecasting model. The findings indicate that HDES delivers dependable short-term predictions with low error rates, accurately reflecting patterns in the data. This online application offers policymakers an effective means for monitoring socio-economic trends and enhancing the responsiveness of social assistance initiatives. This research contributes by integrating statistical forecasting with web-based applications to aid social policy decisions.
Co-Authors Achmad Solechan Agung Surono Ahmad Ashifuddin Aqham Aldho Dwi Kurniawan Alex Ristanto Pratama Andra Matarisman Arditya Himawan Arsito Ari Kuncoro Aslina Baharum Budi Hartono Budi Hartono Budi Hartono budi hartono Chandani, Chicie Chicie Chandani Danang Danang Danang, Danang Dani Sasmoko 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 Khoirur Rozikin Kusumo, Haryo Kusworo Adi Lawrence Adi Supriyono M. Zakki Abdillah Migunani Migunani Mohamad Irkam Muhammad Walid Syahrul Churum mukhamad masrur Nuris Dwi Setiawan R Rizal Isnanto Rizal Dewo Susanto Roni Eka Setiawan Rusito Siswanto Siswanto Siswanto Siswanto Siswanto, Edy Solikhin Solikhin Solikhin Solikhin Sulartopo Sulartopo Ulil Asyhar Unang Achlison Victor Gayuh Utomo Wibowo, Mars Caroline Yehezkiel Yanu Putranto Yohanes Suhari Yuli Fitrianto Zaenal Mustofa