Jurnal INTI Nusa Mandiri merupakan jurnal yang diperuntukan keilmuan Computer science (Ilmu Komputer). kajian keilmuan mencakupi tentang komputasi, perangkat lunak (software). Ilmu komputer mencakup beragam topik yang berkaitan dengan komputer, mulai dari analisis data science, algoritma sampai subyek yang lebih konkret seperti bahasa pemrograman, perangkat lunak. Ilmu Komputer lebih menekankan pada pemrograman komputer, dan rekayasa perangkat lunak (software), pemrograman science Jurnal INTI Nusa Mandiri terakreditasi SINTA 4 dan memiliki P-ISSN: 0216-6933 (Media Cetak), E-ISSN: 2685-807X (Media Onlie). Jurnal INTI Nusa Mandiri terbit 1 (satu) tahun sebanyak 2 (dua) kali terbit, pada bulan Februari dan Agustus.
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FORMULASI MODEL SPASIOTEMPORAL DIGITAL TWIN DALAM SIMULASI DAMPAK KENAIKAN MUKA AIR LAUT
Sea level rise (SLR) due to climate change poses an existential threat to coastal areas, especially in archipelagic countries such as Indonesia. An effective policy response requires simulation tools that can represent spatial and temporal dynamics in an integrated manner. This study formulates and tests a spatiotemporal model based on Digital Twin to simulate the impact of SLR on infrastructure, settlements, and coastal ecosystems. This model combines satellite altimetry data (Sentinel-3), bathymetry data, a 2D hydrodynamic model (Delft3D), and CMIP6 climate projections (SSP2-4.5 and SSP5-8.5) within a cloud-based Digital Twin framework. The case study was conducted in urban coastal areas with high subsidence, which are among the areas with the highest rates of land subsidence in the world. The simulation covers KMA scenarios up to 2050, with a spatial resolution of 5 meters and daily temporal resolution. The results show that in the SSP5-8.5 scenario, up to 68% of urban coastal areas with high subsidence will be below the average sea level in 2050 without intervention. This spatiotemporal model achieved a flood prediction accuracy of 91.3% (based on spatial IoU) compared to historical tidal flood data from 2020–2024. In addition, the system allows for the evaluation of the impact of mitigation infrastructure such as the North Coast Sea Wall (NCICD). This study proves that the formulation of spatiotemporal models in Digital Twin provides a critical foundation. Additionally, the system enables the evaluation of the impact of mitigation infrastructure such as the North Coast Sea Wall (NCICD).
Copyright (c) 2026 Zainul Mufid, Ahmad Gani, Trisna Fajar Prasetyo http://creativecommons.org/licenses/by-nc/4.0
RANCANG BANGUN SISTEM INFORMASI UKK MANDIRI SMK BERBASIS WEB DENGAN INTEGRASI ADDIE DAN SCRUM
The digital transformation of vocational education necessitates competency-based assessment systems that are integrated, accountable, and data-driven. This study develops a web-based UKK Mandiri Information System through an integrative ADDIE–Scrum formulation that operationally maps the relationship between instructional design for competency assessment and iterative software engineering processes. A Research and Development (R&D) approach was employed, involving needs identification through interviews, observations, and document analysis within the implementation context of UKK Mandiri at SMK YPC Tasikmalaya. The system was developed using a three-tier architecture with role-based access control and an automated competency achievement validation mechanism. Testing results demonstrate functional conformance across all core modules, cross-browser compatibility, and baseline security validation. Expert evaluation yielded a mean score of 4.40 (SD = 0.72; α = 0.91; 95% CI [3.89–4.91]), categorized as “Highly Feasible.” The findings indicate improved administrative efficiency, consistency in score calculation, and enhanced traceability of competency assessments, while reinforcing the integration between instructional design and agile software development through a documented and replicable coordinative model
Copyright (c) 2026 Alamsyah Firdaus, Taofik Muhammad, Alfadl Habibie, Imam Amirulloh, Ilpan Rusilpan http://creativecommons.org/licenses/by-nc/4.0
PERANCANGAN SISTEM INFORMASI E-COMMERCE BERBASIS WEBSITE PADA PT. BIMANTARA SAKTI PERSADA MENGGUNAKAN METODE WATERFALL
The development of digital technology encourages companies to implement information systems with the aim of improving operational effectiveness and competitive ability in the market. PT. Bimantara Sakti Persada, which previously conducted sales processes traditionally, faces challenges such as limitations in marketing reach, the possibility of errors in transaction recording, and delays in preparing sales reports. This study aims to design and create a website-based e-commerce information system by utilizing the Waterfall method as a solution to the existing problems. The Waterfall method is implemented through a series of steps that include needs analysis, system design, implementation, testing, and evaluation and maintenance. The designed system provides various functions such as member registration, product management, shopping cart, payment processing, and transaction verification. The system assessment is carried out by conducting functional testing using the Black Box Testing approach as well as testing the utilization of the system by the admin and sales team. The test results show that all system functions operate according to the specified requirements. Based on usage evaluation results, the system is capable of replacing the manual sales process with a more structured computerized system, thereby facilitating transaction recording and the preparation of sales reports. Comparisons of conditions before and after the system's implementation indicate an increase in efficiency in transaction management as well as ease of access to sales information in real time. Thus, the developed web-based e-commerce information system can support PT. Bimantara Sakti Persada's sales process more effectively and in an integrated manner
Copyright (c) 2026 Mohamad Rifa Yusro, Siti Masturoh http://creativecommons.org/licenses/by-nc/4.0
RANCANG BANGUN SISTEM INFORMASI E-BOOKING PENYEWAAN MOBIL BERBASIS WEB MENGGUNAKAN PENDEKATAN OOAD
The manual system employed by PT. ACM Mahadat—a car rental service company—resulted in significant operational issues, including irregular schedules, data recording errors, and slow service, which contrasted sharply with consumer expectations for efficient and secure services. This study aims to design and build a web-based car rental e-booking information system to simplify the reservation process and manage data in real-time. The chosen methodology is Object-Oriented Analysis and Design (OOAD), a systematic approach that concentrates on the concept of objects as the fundamental system elements. The design documentation utilizes Unified Modeling Language (UML) notation, including the Use Case Diagram (functional requirements), Activity Diagram (process flow), Sequence Diagram (object interactions), and Class Diagram (static system structure). The resulting system is designed to be modular and flexible, offering a user-friendly interface for customers to view, select, and book cars easily. It also helps the Admin manage booking and rental data more efficiently, and its core authentication features are validated through Black Box Testing. This implementation is expected to support the digitalization of PT. ACM Mahadat's business processes and enhance the company's competitiveness in the information technology era.
Copyright (c) 2026 Muamar Fallahi, Ridan Nurfalah, Inka Syaifa Fauzia, Samuel Tarigan http://creativecommons.org/licenses/by-nc/4.0
PERANCANGAN SISTEM INFORMASI PENGARSIPAN SURAT MASUK DAN SURAT KELUAR PADA PABAN III/LATGA SOPS TNI
The previously manual system at the Paban III/Latga Sops TNI posed several limitations, such as difficulties in document retrieval, risk of archive loss, and inefficiency in letter management. This study aims to design a structured and computerized information system for archiving incoming and outgoing mail documents. In this research, the software development method used is the Waterfall model, consisting of requirement analysis, system design, implementation, testing, and evaluation phases. The result is a web-based system built using PHP programming language and MySQL database, which effectively supports digital management of incoming and outgoing correspondence in a fast and well-documented manner. The system was tested using Black Box method and user acceptance questionnaires, showing that the application met the functional requirements and is feasible for use in the operational environment of Paban III/Latga Sops TNI.
Copyright (c) 2026 Andri Januar, Yuri Warman, Shinta Oktaviana R http://creativecommons.org/licenses/by-nc/4.0
KLASIFIKASI JENIS IKAN AIR TAWAR MENGGUNAKAN ALGORITMA CNN DAN ARSITEKTUR ALEXNET
Freshwater fish are an important commodity in the fishing industry that requires an accurate classification system. This study aims to develop a freshwater fish classification system using the Convolutional Neural Network (CNN) algorithm with AlexNet architecture, as well as applying data augmentation techniques to improve model accuracy. The dataset used consists of 488 images of five types of freshwater fish, namely catfish, baung fish, tapah fish, juaro fish, and patin fish, which were then augmented into 68,400 images. The model was trained using the Adam optimizer, with a batch size of 16, a learning rate of 1e-5, and 200 epochs. The results of the experiment show that the model achieved a training accuracy of 71.09%, a validation accuracy of 85.00%, and a testing accuracy of 80.29%. Precision reached 0.8310, Recall 0.7909, and F1-score 0.7912, indicating the model's excellent performance in classifying freshwater fish species. This research is expected to support the development of an automatic classification system for the freshwater fisheries industry
Copyright (c) 2026 Ahmad Rizky, Dedy Hermanto http://creativecommons.org/licenses/by-nc/4.0
DETEKSI ULASAN FIKTIF SKINCARE BERBAHASA INDONESIA PADA SITUS FEMALE DAILY MENGGUNAKAN METODE SVM
The increasing popularity of e-commerce and online review platforms has encouraged consumers to rely more heavily on reviews before purchasing skincare products. However, the proliferation of fake reviews presents a new challenge for consumers in making decisions. This study aims to detect fake reviews of skincare products by applying the Support Vector Machine (SVM) algorithm as the main model. Data was taken from the Female Daily website, which contains a collection of reviews of COSRX skincare products. This study applied text mining and data preprocessing techniques to prepare 8,880 unstructured reviews into a format ready for analysis. The SVM model was used to detect genuine and fake reviews based on linguistic patterns in the text. The test results showed excellent accuracy, with the model accurately predicting 5,900 fake reviews and 2,758 genuine reviews, with an error rate of only around 2.5% of the total data. These findings indicate that SVM is an effective method for detecting fake skincare product reviews and has the potential to be implemented as a decision support tool for consumers and online review platforms.
Copyright (c) 2026 Audy Hafiza Bilqis, Farizatul Azna, Dwi Widdi, Nayla Eka Hidayat, Tasya Ramadhinta http://creativecommons.org/licenses/by-nc/4.0
OPTIMALISASI PREDIKSI JARAK TEMPUH KENDARAAN LISTRIK MENGGUNAKAN XGBOOST DAN FEATURE SELECTION RANDOM FOREST
Electric vehicle (EV) adoption is increasing with increasing awareness of clean energy and environmental concerns. However, range anxiety, the uncertainty in estimating driving range, remains a major barrier. This study aims to develop a predictive model for EV range based on technical specifications to provide more accurate estimates and alleviate user concerns. A Machine Learning approach is applied, using Random Forest for feature selection and XGBoost as the primary prediction algorithm. The dataset consists of 478 EV records with 22 attributes, including battery capacity, efficiency, dimensions, and speed. Key features affecting range prediction include battery_capacity_kWh, efficiency_wh_per_km, and height_mm. The XGBoost model demonstrates strong predictive performance with an R² of 0.978, an MAE of 10.555, and an RMSE of 15.180. These results suggest that combining Random Forest and XGBoost offers a promising solution to improve the accuracy of EV range estimation, potentially reducing range anxiety and supporting wider EV adoption
Copyright (c) 2026 M. Rangga Ramadhan Saelan, Riyan Latifahul Hasanah, Siti Fauziah http://creativecommons.org/licenses/by-nc/4.0
CLUSTERING WILAYAH KEMISKINAN MULTIDIMENSI DI INDONESIA MENGGUNAKAN ALGORITMA FUZZY C-MEANS DAN OPTICS
A multidimensional approach to mapping poverty in Indonesia necessitates the use of the Human Development Index (HDI), Poverty Line, and Expenditure per Capita. This study aims to evaluate the performance of two clustering algorithms with distinct paradigms the centroid-based Fuzzy C-Means (FCM) and the density-based OPTICS in profiling poverty across 501 regencies and cities. Experimental results indicate that OPTICS achieved high internal validity, with a Silhouette Score of 0.7301 and a Davies-Bouldin Index (DBI) of 0.329. Significantly, OPTICS identified 94% of the data as noise. This finding reveals a fundamental characteristic: the distribution of socio-economic data in Indonesia is highly heterogeneous and sparse, lacking inherently dense cluster structures. Conversely, FCM, employing a soft clustering approach, successfully accommodates the ambiguity of data boundaries and provides comprehensive segmentation across all regions. Despite yielding lower validity metrics (Silhouette Score 0.3894), FCM was selected as the final model because it satisfies the practical requirements of the application, which demands complete coverage mapping. This study concludes that a soft clustering approach is more applicable than density-based clustering for analyzing highly heterogeneous data such as that found in Indonesia
Copyright (c) 2026 Nicholas Eugene Supardi , Teny Handhayani, Irvan Lewenusa http://creativecommons.org/licenses/by-nc/4.0
IMPLEMENTASI METODE USER CENTERED DESIGN PADA APLIKASI KORAN DIGITAL RADAR KARAWANG
The rapid development of digital technology has required print media to adapt in order to remain relevant and competitive in the information era. Radar Karawang, as a local daily newspaper, needs to undergo digital transformation through the development of an Android-based digital newspaper (e-paper) application. This study aims to design the User Interface (UI) and User Experience (UX) of the Radar Karawang digital newspaper application using the User-Centered Design (UCD) method and to evaluate the usability level of the developed application. The UCD method was implemented through several stages, including user needs analysis, prototype or wireframe design, design evaluation based on user feedback, and application implementation. Data were collected through questionnaires distributed to 13 respondents who represented potential users of the application. Usability evaluation was conducted using the System Usability Scale (SUS) method with a Likert scale to measure ease of use, efficiency, and user satisfaction. The evaluation results show that the Radar Karawang digital newspaper application achieved an average SUS score of 74, which falls into the Acceptable category with a Good adjective rating. Nevertheless, this study has several limitations, particularly related to the limited number of respondents and the use of a single usability evaluation method. Therefore, future research is recommended to involve a larger and more diverse group of respondents and to combine other usability evaluation methods to obtain more comprehensive results
Copyright (c) 2026 Normah Normah, Ainun Zumarniansyah, Agus Echtiyar http://creativecommons.org/licenses/by-nc/4.0
MODEL KLASIFIKASI PENERIMA PROGRAM KARTU INDONESIA PINTAR MENGGUNAKAN METODE XGBOOST
Poverty is one of the major factors contributing to the low quality of education in Indonesia. The Smart Indonesia Program (Program Indonesia Pintar) is a cash assistance program distributed through the Smart Indonesia Card (Kartu Indonesia Pintar/KIP) to support students from economically disadvantaged families, ranging from elementary to higher education levels. This study aims to classify students who are eligible to receive the Smart Indonesia Card using the XGBoost method, with a case study conducted at SMPN 02 Kebun Tebu. The dataset used in this study consists of independent and dependent variables. The independent variables include father’s age, mother’s age, father’s education level, mother’s education level, father’s income, mother’s income, number of family dependents, and students’ academic average scores. The dependent variable is the eligibility status of KIP recipients as the target class. Two classification models were developed using data split ratios of 70:30 and 80:20. The model with a 70:30 data split achieved an accuracy of 0.9048, a precision of 0.9034, a recall of 0.9072, and an F1-score of 0.9053. Meanwhile, the model with an 80:20 data split demonstrated better performance, with an accuracy of 0.9167, a precision of 0.9149, a recall of 0.9189, and an F1-score of 0.9169. The optimal model obtained from this study can be utilized by schools to support policy decision-making in determining eligible Smart Indonesia Card recipients, ensuring that educational assistance is distributed accurately, adequately, and equitably
Copyright (c) 2026 Andi Nurkholis, Styawati Styawati, Susi Susi, Alifah Chairul Munawar http://creativecommons.org/licenses/by-nc/4.0
STUDI KOMPARATIF ALGORITMA C4.5 DAN RANDOM FOREST PADA DIGITALISASI UMKM KABUPATEN TEGAL
Digital transformation has become an essential necessity for Micro, Small, and Medium Enterprises (UMKM) to enhance their competitiveness in the era of Industry 4.0. However, in Tegal Regency, the level of digitalization adoption among MSMEs remains varied and tends to be low, thus requiring further investigation. This study aims to compare the performance of the C4.5 and Random Forest algorithms in classifying the level of digitalization of MSMEs in Tegal Regency. This research employs the CRISP-DM methodology, which includes business understanding, data understanding, data preparation, modeling, evaluation, and implementation. Primary data were collected through questionnaires distributed to 100 MSME respondents and processed using RapidMiner. The results indicate that the Random Forest algorithm demonstrates superior performance, achieving an average F1-score of 89.63%, accuracy of 91.43%, while the C4.5 algorithm records an average F1-score of 86.24%, accuracy of 90%. The highest F1-score for both algorithms is observed in the low digitalization category at 95%, which is consistent with the data distribution showing that the majority of MSMEs (59%) fall within this category. This study systematically integrates the CRISP-DM approach from business understanding to model implementation, resulting in a structured data analysis workflow that can be replicated by local governments or future researchers. Another novelty of this study lies in the finding that although Random Forest exhibits better classification performance than C4.5, the majority of MSMEs remain at a low level of digitalization. These results provide practical contributions as a basis for formulating more targeted and sustainable MSME digitalization policies at the local
Copyright (c) 2026 Gita Iftah Royani, Nur Syifa Amelia, Marlina, Fani Nurona Cahya http://creativecommons.org/licenses/by-nc/4.0
PENINGKATAN AKURASI KNN DALAM PREDIKSI KELULUSAN MAHASISWA MELALUI OPTIMASI PARAMETER PSO
Predicting student graduation is a crucial aspect in supporting academic planning and ensuring timely completion of studies. However, no prior research has specifically applied the integration of K-Nearest Neighbor (KNN) and Particle Swarm Optimization (PSO) for graduation prediction using student data. This study aims to evaluate the effectiveness of combining KNN and PSO in improving classification accuracy. The KNN algorithm is used for classification, while PSO is implemented as a feature selection technique to identify the most relevant attributes. A dataset of 750 student records was processed through data preprocessing and attribute weighting using PSO, followed by model training and evaluation with 10-fold cross-validation. The evaluation results show that the KNN+PSO model improves accuracy from 80.91% to 84.31%, along with increases in precision and recall. These findings indicate that PSO enhances the performance of KNN, particularly in identifying students likely to graduate on time
Copyright (c) 2025 Yessica Fara Desvia, Febryawan Yuda Pratama, Ganda Wijaya http://creativecommons.org/licenses/by-nc/4.0
PERANCANGAN SISTEM SIMPAN PINJAM MENGGUNAKAN OBJECT-ORIENTED SOFTWARE ENGINEERING PADA PT. AUTO PRIMA MAKMUR
PT Auto Prima Makmur Jakarta still faces challenges in managing its savings and loan system, which is currently conducted manually. These problems include recording errors, administrative delays, and a lack of transparency, all of which reduce efficiency, accuracy, and the ability to monitor transactions in real time. This situation also increases the risk of data manipulation and loss, slows down member services, and potentially undermines trust in the company’s credibility. To address these issues, this study aims to design a web-based savings and loan information system that can enhance efficiency, accuracy, security, and transparency in managing employee savings and loans. The proposed system is designed to process transactions, reporting, and monitoring quickly and accurately, while minimizing the risk of errors and data duplication. The development method used is Object-Oriented Software Engineering (OOSE), which emphasizes the use case approach with simple notation yet covers all stages of software engineering. This approach enables the design of a structured, flexible software architecture capable of effectively managing system objects. The analysis results indicate that implementing a web-based system can accelerate savings and loan transactions, simplify reporting and monitoring, and improve data security. In addition, real-time data availability will assist management in making faster and more accurate decisions. Therefore, the implementation of this system will not only digitize the company’s business processes but also improve service quality, strengthen competitiveness, and support the company’s sustainability in facing the challenges of the digital era
Copyright (c) 2025 Moh. Mahar Faisol -, Ridan http://creativecommons.org/licenses/by-nc/4.0
ANALISIS KEPUASAN PENGGUNA WEBSITE LIGA ARLOJI MENGGUNAKAN METODE END USER COMPUTING SATISFACTION (EUCS)
The evolution of information technology plays a significant role in accelerating digital transformation across various sectors, including the wristwatch retail industry. The Liga Arloji website is utilized as a medium for promotion and online transactions, which needs to be evaluated in terms of user satisfaction. This study aims to analyze the level of user satisfaction with the performance of the Liga Arloji website using the End User Computing Satisfaction (EUCS) method, in which the components analyzed include five dimensions: content, accuracy, format, ease of use, and timeliness. The methodology of this study is based on a quantitative approach, using a questionnaire as the data collection instrument distributed to 68 selected respondents. The data were processed using the EUCS calculation formula and tested for validity and reliability using SPSS. Based on the data analysis, the findings show that all EUCS dimensions received scores falling into the “Satisfied” to “Very Satisfied” classification. The content dimension achieved an average score of 4.19, accuracy scored 4.13, format scored 4.18, ease of use scored 4.15, and the timeliness dimension received the highest score of 4.22. These findings indicate that user satisfaction with the website is relatively high, particularly in terms of timely information and presented content, while the system’s reliability and accuracy were rated as moderately satisfactory. This study provides several recommendations, including improving data accuracy and enhancing system reliability. The results are expected to serve as a key reference for the future development of e-commerce-based websites
Copyright (c) 2026 Asni Zalukhu, Siti Nurlela http://creativecommons.org/licenses/by-nc/4.0
PENGEMBANGAN CHATBOT TELEGRAM FAQ LAYANAN ICT MENGGUNAKAN ALGORITMA RANDOM FOREST DAN METODE WORD2VEC
In today's digital era, chatbots have become an essential tool for businesses to improve interaction with customers. A responsive and efficient chatbot can help customer service agents be happier, improve customer satisfaction, and resolve issues faster. The study aims to create a Telegram-based chatbot that uses the Random Forest algorithm and the Word2Vec method to answer questions about ICT services. The development was carried out by collecting a dataset of questions and answers from FAQs (Frequently Asked Questions) of ICT services. Then, the Random Forest algorithm is used to classify the questions. In addition, the Word2Vec method is used to create vector representations of words in questions and answers. This improves the chatbot's ability to understand complex questions. The test results show that the chatbot gets an accuracy of 91.28%, a precision of 93.56%, a recall of 91.28% and an F1-Score of 91.42% and can provide relevant and accurate answers to user questions. Therefore, the development of this chatbot using the Random Forest algorithm and the Word2Vec method can be an effective solution to improve customer service in the field of ICT services
Copyright (c) 2025 Muhammad Arif Setiyawan, Erina Divaa Kenoya http://creativecommons.org/licenses/by-nc/4.0
PENENTUAN PRIORITAS PENGEMBANGAN DESA WISATA RINTISAN KOTA PURWAKARTA MENGGUNAKAN METODE MULTI ATTRIBUTE UTILITY THEORY
A Tourism Village can be understood as a village that organizes tourism activities due to the tourist attractions arising from the characteristics of the local community’s life, including various attractions available within the village itself. Each tourism village needs to be supported by tourist attractions, accessibility, and amenities, which include the potential of cultural tourism as well as natural tourism. The purpose of this research is to design and develop a Decision Support System for Determining the Priority of Pioneer Tourism Village Development using the Multi Attribute Utility Theory (MAUT) method. The urgency of this research lies in the need for DISPORAPARBUD Purwakarta to have a tool to assist in making strategic decisions related to the development of pioneer tourism villages. The methodology used in developing this system is the Waterfall model. The system is designed using PHP with the CodeIgniter 3 framework, MySQL as the database, and Unified Modeling Language (UML) for system modeling. The main criteria used in the MAUT calculation include public facilities, homestay management, local crafts, local arts, and local food. The results of the calculation using the MAUT method show that Batu Nunggal Margaluyu Tourism Village ranks first with a preference value of 100, Sasanakerta Tourism Village ranks second with a value of 96, and Sumbersari Tourism Village ranks third with a value of 90. Therefore, these three tourism villages are the best recommendations to be prioritized in the development of tourism villages in Purwakart
Copyright (c) 2025 Lia Fitriyanti, Mochzen Gito Resmi, Dede Irmayanti http://creativecommons.org/licenses/by-nc/4.0
REKOMENDASI PEKERJAAN BIDANG EKONOMI : SISTEM REKOMENDASI MENGGUNAKAN CONTENT BASED
The recommendation system was developed to assist students of the Institut Teknologi dan Bisnis Widya Gama Lumajang, particularly those from the Faculty of Economics and Business, in determining their preferred career options. This system helps students by providing various job references that match their individual criteria. The data was collected from a tracer study, which includes information such as academic grades, non-academic achievements, job positions, company names, salaries received. From the total dataset, 1,120 records were deemed valid and used in the research process. The aim of this research is to assist students by providing job recommendations based on similar criteria between current students and alumni. The method applied in this study is quantitative experimental research based on data mining, with the main approach being Content-Based filtering and the MLP (Multi-Layer Perceptron) Classifier algorithm. The data was split into two parts: 65% for training and 35% for testing. This division aims to allow the model to learn from most of the data while also being tested for accuracy using unfamiliar data. The recommendation model was developed using the MLP Classifier algorithm with a hidden_layer_size configuration of 100 neurons and a max_iter of 200 iterations. For the initial test, 10 sample data points were used to evaluate the model’s performance. During training, the loss value was monitored to assess how well the model understood the data and adjusted its internal weights. With this configuration, the system is expected to provide accurate job recommendations based on the user’s profile and academic history.
Copyright (c) 2025 Abdur Rouf, Hasyim Asy’ari , Maysas Yafi Urrohman, Febriane Devi Rahmawati http://creativecommons.org/licenses/by-nc/4.0
PERANCANGAN APLIKASI TIKET IT HELPDESK UNTUK MENINGKATKAN EFEKTIVITAS LAYANAN TEKNOLOGI INFORMASI
Effective and responsive Information Technology (IT) services play a crucial role in supporting organizational operations. However, in practice, ASPAN Company still faces challenges in recording, monitoring, and resolving IT incidents due to the absence of an integrated system. This study aims to design an IT Helpdesk ticketing application that enhances the effectiveness of IT services through a systematic, fast, and measurable incident management process. The research adopts the waterfall methodology and qualitative data collection using a case study approach through direct observation involving IT staff and service users. The result of this study is a web-based application that enables users to create incident report tickets, track ticket status, and provide feedback on the services received. The system also provides performance reports that are useful for service evaluation. The implementation results demonstrate a significant improvement in IT service performance, where the average incident resolution time decreased from 2.5 hours to 1.5 hours. Furthermore, the system facilitates real-time ticket tracking, historical issue management, and structured performance reporting to support IT service evaluation. With the implementation of the IT Helpdesk ticketing application, the IT issue-handling process becomes more efficient, well-documented, and ultimately improves the overall quality of Information Technology services within ASPAN company
Copyright (c) 2025 veron vaskarian karwur, Ramdha, Alvi, Fahmi, rocci, Riyan, Siti Nurhasanah Nugraha http://creativecommons.org/licenses/by-nc/4.0
EVALUASI PENERIMAAN MAHASISWA TERHADAP APLIKASI AKADEMIK MOBILE: PENDEKATAN TECHNOLOGY ACCEPTANCE MODEL (TAM)
Mobile applications are widely used in educational environments to accelerate various academic and administrative tasks. Their presence has enhanced service effectiveness, expedited decision-making, and improved the digital campus ecosystem. This study was conducted to evaluate the acceptance level of MyNusa Student, a mobile-based academic application for students. The Technology Acceptance Model (TAM) framework was employed in this research to assess students’ acceptance of the MyNusa Student application. A total of 238 respondents, all registered students using the application, provided data for this study. Data analysis was carried out using Structural Equation Modeling (SEM) with a Partial Least Squares (PLS) approach to examine the relationships among variables: Perceived Ease of Use, Perceived Usefulness, Attitude Toward Using, Behavioral Intention to Use, and Actual Usage. The results indicated that all relationships among variables were statistically significant. The most influential relationship was observed between Perceived Ease of Use and Perceived Usefulness, followed by the relationship between Attitude Toward Using and Behavioral Intention to Use, and subsequently, Actual Usage. The findings suggest that the primary elements influencing students’ positive perceptions of the application—which in turn affect their intention and actual usage patterns—are their evaluations of its usefulness and utility. The practical implications highlight the need for continuous improvement in usability and utility aspects, with a focus on enhancing ease of use, optimizing core features such as real-time data updates, and improving technical as well as system security aspects.
Copyright (c) 2025 Muji Ernawati, Eni Heni Hermaliani, Evita Fitri, Siti Nurhasanah Nugraha http://creativecommons.org/licenses/by-nc/4.0
RANCANG BANGUN APLIKASI PENGELOLAAN PPH 21 PADA CV.ECS CONSULTING SERVICES DENGAN PENDEKATAN RAD
Income Tax (PPh) 21 often poses a challenge for companies and employees in managing tax payments efficiently and accurately. CV. ECS Consulting Service, which currently uses Microsoft Excel for PPh 21 calculations, faces risks of errors and time-consuming manual processes. This research aims to develop a web-based PPh 21 calculation application using the Rapid Application Development (RAD) method tailored to the company’s needs. Data collection methods include direct observation and literature study, while the application development method adopts RAD, which is iterative and responsive to changing requirements. The scope of the research includes user interface design, development of calculation algorithms, employee data processing, and ensuring data security. The application was tested using Black Box testing to ensure all features function properly, User Acceptance Testing (UAT) to assess whether it meets user needs, and performance testing to evaluate the website’s speed and stability. Black Box testing was conducted on six cases, and UAT was carried out directly with users. The results showed that the application passed all tests and met the required functionalities. Performance testing also indicated that the system is fairly stable, although further improvement is needed for long-term use or during high traffic.
Copyright (c) 2025 Aji Yunisyaputra, Syarif Hidayatulloh http://creativecommons.org/licenses/by-nc/4.0
ANALISIS FAKTOR – FAKTOR PENERIMAAN DAN PENGGUNAAN APLIKASI SEABANK DAN BANK JAGO DENGAN MODEL UTAUT2
In recent years, banking in Indonesia has undergone significant transformation through the use of technology, as reflected in the increase in digital transactions, which reached Rp15,881.53 trillion, a year-on-year growth of 16.15%. This study employs the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) model to analyze the factors influencing the acceptance and use of Seabank and Bank Jago digital banking applications. This study is a quantitative research using a survey method involving 632 student respondents in North Sumatra up to Lhokseumawe, analyzed using descriptive statistics and hypothesis testing based on Structural Equation Modeling (SEM). The results of the descriptive statistical analysis showed that the average user response to the Seabank app was 87.02% and Bank Jago was 84.82%, both falling into the “strongly agree” category, indicating a positive response. Hypothesis analysis revealed that social influence, facilitating conditions, price value, habits, behavioral intention, and usage behavior significantly influence the acceptance of the Seabank app. For Bank Jago, the significant influencing factors are social influence, price value, habits, behavioral intention, and usage behavior. The findings of this study confirm the applicability of UTAUT2 in the context of digital banking in Indonesia and provide practical insights for app developers and policymakers to encourage the adoption of digital banking services.
Copyright (c) 2025 Helvina Agil Agil, Rahma Fitria Rahma, Zalfie Ardian Zalfie http://creativecommons.org/licenses/by-nc/4.0
PENGEMBANGAN SISTEM ROBOT PENJELAJAH BERBASIS MQTT MITIGASI BENCANA DENGAN DUKUNGAN IMAGE PROCESSING
Disaster mitigation is a global challenge that requires innovation to enhance the effectiveness of emergency response, particularly in the rapid and safe detection of victims. Although much research focuses on optimizing individual components such as sensors or algorithms, a gap remains in the development of holistically integrated frameworks. This study develops and evaluates an integrated explorer robot system based on Message Queuing Telemetry Transport (MQTT) and artificial intelligence for real-time disaster victim detection. Using a Design Science Research approach, the system architecture integrates an explorer robot based on ESP32-CAM and GPS for data acquisition, a central server running the You Only Look Once (YOLO) algorithm for image analysis, and involves a human operator for critical decision validation. Experimental results show that the system can detect victims with an average accuracy of 87.3% across various simulated scenarios. Communication via the MQTT protocol proved to be highly reliable and efficient, with an average latency of 127 ms and a packet loss rate of only 2.3%, enabling swift coordination between components. This research successfully validates an effective and replicable end-to-end architectural model, thereby presenting a practical blueprint for the development of low-cost Search and Rescue (SAR) robotic systems
Copyright (c) 2025 Riadi Marta Dinata, Muhammad Ikrar Yamin, Agus Sofwan, Ariman Ariman, Niko Purnomo Niko http://creativecommons.org/licenses/by-nc/4.0
AI-DRIVEN ACADEMIC SCREENING: PENGEMBANGAN SISTEM REVIEWER OTOMATIS BERBASIS AI AGENT
An artificial intelligence (AI)-based research proposal submission system is an innovative solution to improve efficiency and transparency in the academic selection process. This study develops a web-based system using the Laravel framework integrated with AI Agent to automatically review the title and abstract of lecturers' research proposals. This system is designed with a hybrid training approach, combining Supervised Learning (labeled data) and Reinforcement Learning from Human Feedback (RLHF), and utilizing Natural Language Processing (NLP) techniques for semantic analysis. The implementation results show that the system is able to evaluate research proposals with high accuracy, including checking title-abstract alignment, identifying problem backgrounds, and assessing originality. The system also provides real-time statistics and evaluation records, supporting more objective decision making. The contribution of the research lies in the use of AI to automate academic processes, reduce the workload of human reviewers, and improve the integrity of the research roadmap
Copyright (c) 2026 Verry Riyanto, Andi Saryoko, Anton, Lia Mazia, Nurmalasari, Tati Mardiana http://creativecommons.org/licenses/by-nc/4.0
RANCANG BANGUN SISTEM INFORMASI MANAJEMEN DISTRIBUSI QURBAN
One of the most important aspects of Eid al-Adha celebrations is the distribution of sacrificial meat. However, the process of distributing sacrificial meat often faces various challenges, such as inaccurate data collection, difficulty in tracking the amount of sacrificial meat, and a lack of transparency and efficiency. The objective of this study is to design and develop an application that can enhance efficiency, accuracy, and accountability in the distribution of sacrificial meat through the systematic use of information technology. This study employs the waterfall method, which involves several sequential stages: needs analysis, system design, implementation, and testing. This system was developed to support the performance of the sacrificial committee in managing data on sacrificial animals, information on recipients, the distribution process of meat, and the documentation of all activities in a digital and real-time manner. In the user interface (front end), the Next.js/React.js framework is combined with Tailwind CSS to produce a responsive and user-friendly interface. Meanwhile, the server side (back end) was developed using Laravel as a reliable and efficient PHP framework, and MySQL as a database to store all information related to distribution. The result of this research is a web-based application prototype featuring animal sacrifice data collection, beneficiary data recording, and distribution report generation. It is hoped that this application will facilitate more organized and effective distribution of sacrificial meat
Copyright (c) 2025 Nanang Ruhyana, Ani Oktarini Sari, Tati Mardiana, Achmad Bayhaqy, Andri Agung Riyadi , Setiaji Setiaji http://creativecommons.org/licenses/by-nc/4.0
IMPLEMENTASI METODE EXTREME MENGGUNAKAN ALGORITMA MACHINE LEARNING UNTUK KLASIFIKASI JENIS FASHION ALAS KAKI
This research explores the application of Extreme Learning Machine (ELM) for classifying types of fashion footwear. The increasing number of e-commerce transactions and the use of visual media in marketing demand an efficient and accurate automated system to identify various types of footwear such as shoes, sandals, and slip-ons. Conventional classification systems often encounter challenges in handling variations in shape, color, and lighting conditions in footwear images. ELM, with its unique approach of assigning random weights in the hidden layer, offers a potential solution to these issues. In this study, a classification system was developed consisting of several stages, including the collection of diverse footwear image data, image preprocessing to improve quality and reduce noise, feature extraction relevant for distinguishing footwear types, and finally, classification using the ELM algorithm. The preprocessing process involved color conversion from RGB to HSV to reduce sensitivity to lighting variations, as well as thresholding to produce binary images. Extracted features included geometric characteristics such as area, perimeter, and aspect ratio. The system’s performance was evaluated using standard metrics such as accuracy, precision, and recall. The results showed an accuracy value of 83.3%. In addition, the model evaluation demonstrated very good results: precision reached 83.3%, recall 83.3%, and F1-Score 91%, indicating that ELM is effective in classifying types of fashion footwear. This study contributes to the development of intelligent, efficient, and accurate classification systems for applications in the fashion industry, while also opening opportunities for further research in optimizing ELM parameters and exploring more representative features
Copyright (c) 2025 Dina Selvia, Sela Ramadani http://creativecommons.org/licenses/by-nc/4.0
ANALISIS SENTIMEN APLIKASI TIKTOK SHOP SELLER CENTER MENGGUNAKAN NAIVE BAYES, SVM DAN LOGISTIC REGRESSION
The rapid growth of e-commerce has driven the emergence of new platforms such as TikTok Shop Seller Center, which is now integrated with Tokopedia. Increasing competition among digital platforms has made service quality and user experience key success factors. In this context, user reviews and feedback serve as crucial data sources that reflect satisfaction, complaints, and expectations toward the application. However, the large and diverse volume of reviews renders manual analysis inefficient. Therefore, an automated approach such as sentiment analysis is required to classify user opinions quickly and accurately. This study aims to perform sentiment analysis on TikTok Shop Seller Center user reviews using Naïve Bayes, Support Vector Machine (SVM), and Logistic Regression algorithms to determine the best-performing model. The dataset was obtained from the Kaggle platform and underwent preprocessing, including case folding, tokenization, stemming, and TF-IDF weighting. Model evaluation was conducted using confusion matrix and ROC curve, along with performance metrics such as accuracy, precision, recall, and F1-score. The results show that the SVM algorithm outperformed Naïve Bayes and Logistic Regression, achieving 93.75% accuracy, 93.78% precision, 95.65% recall, 94.70% F1-score, and an AUC of 0.98, categorized as Excellent Classification. Thus, SVM proved to be the most effective algorithm for classifying user review sentiments on TikTok Shop Seller Center.
Copyright (c) 2025 Elly Indrayuni, Acmad Nurhadi http://creativecommons.org/licenses/by-nc/4.0
IMPLEMENTASI METODE CLUSTERING UNTUK PEMETAAN WILAYAH PRODUKSI DAN EKSPOR KOPI DI INDONESIA
Coffee is one of the main agricultural commodities in Indonesia, but the distribution of production and export contribution is still uneven. This study aims to map the patterns of coffee production and export in Indonesia using clustering methods, namely K-Means and Hierarchical Agglomerative Clustering (AHC). The data used includes coffee production by province and regency (2015–2022), as well as coffee export data by destination country (2016–2023), obtained from BDSP and BPS. The system is developed in the form of an interactive website that allows users to upload datasets, select clustering methods, and view analysis results in the form of tables, graphs, and interactive maps. Clustering quality is evaluated using the Silhouette Score and Davies-Bouldin Index (DBI). The testing results show that the optimal number of clusters is two for all datasets, with the highest Silhouette score reaching 0.85 and the lowest DBI of 0.21, indicating good clustering quality. AHC is more effective in analyzing export and provincial-level production data, while K-Means performs better for regency-level data. This system is expected to provide insights into the distribution patterns of coffee production and exports and support decision-making in the agricultural sector, particularly for coffee commodities.
Copyright (c) 2025 Arya Dwi Saputra, Jefri Jaya, Teny Handhayani, Manatap Sitorus Dolok Lauro http://creativecommons.org/licenses/by-nc/4.0
RANCANG BANGUN APLIKASI PREDIKSI TAGIHAN AIR BERBASIS WEB MENGGUNAKAN REGRESI LINIER BERGANDA
The management of water billing in the PAMSIMAS service in Sidobandung Village is still conducted manually and does not provide early information regarding bill estimates, often resulting in delayed payments by customers. This study aims to design and develop a web-based water bill prediction application using the Multiple Linear Regression (MLR) method, capable of delivering fast, accurate, and accessible billing estimates. The dataset used in this research consists of historical monthly water usage and billing data from January to December 2024, with a structure comprising 231 rows of customer data and 30 feature columns. The research stages include data preprocessing, model training using MLR, integration of the model into a web-based system, and evaluation of prediction results using the Mean Squared Error (MSE) and R-squared ( ) metrics. Evaluation results showed that the model achieved an MSE of 18,882 and an of 0,8, indicating a fairly good and stable prediction performance. The system allows customers to log in, view predicted water bills for the 13th month based on previous data, and access graphical visualizations of usage and cost trends. Meanwhile, the admin can efficiently manage customer data through a dedicated dashboard. With the implementation of this application, the management and prediction process of water billing becomes more transparent, efficient, and helps customers in planning their water expenses more precisely .
Copyright (c) 2025 Arum Fatmawati Arum , Afril Efan Pajri, Sahri http://creativecommons.org/licenses/by-nc/4.0
SISTEM INFORMASI MANAJEMEN ARSIP PADA DIREKTORAT TEKNOLOGI INFORMASI KEIMIGRASIAN
In this research case study, the storage of letter archives at the Directorate of Immigration Information Technology is still done manually where all letter archive documents are stored by employees on their respective Personal Computers. Records management that is done manually by storing files on Personal Computer rarely has a regular backup mechanism so that if a document is lost it is difficult to recover it. So, an innovation is needed in the form of a website-based archive storage information system. The purpose of this research is to facilitate employees who are appointed as letter archive managers and facilitate the search for archives needed by the leadership. In this study, researchers used the scrum method or model with stages namely product backlog, sprints, scrum meetings and demos. The stages of the Agile method in this study include system analysis, design, development, testing, deployment, system evaluation and maintenance. The programming language used in building archive management information system applications at the directorate of immigration information technology is using the PHP (Hypertext Preprocessor) and JavaScript programming languages. The results showed that the web-based archive management information system has been successfully designed. This system overcomes difficulties in searching for archives, reduces the risk of data loss, and optimizes the management of incoming and outgoing mail archives. With this system, officers in each section can manage the storage of letter archives and enable data management and document searches that were previously time-consuming now become faster and more efficient.
Copyright (c) 2025 Sani Abdurahman, Juarni Siregar http://creativecommons.org/licenses/by-nc/4.0