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Jurnal Penelitian Teknologi Informasi dan Sains
Published by INSTITUT TEKNOLOGI DAN BISNIS SEMARANG
ISSN : 29856280     EISSN : 29857635     DOI : 10.54066
Core Subject : Science,
Computer Science & IT
Ruang lingkup meliputi bidang Informatika, Teknik Mesin, Teknik Elektro,Teknik Sipil, Teknik Industri, Ilmu Komputer dan Sains.
Arjuna Subject : Ilmu Ekonomi, Ekonometrika dan Keuangan (semua kategori) - Ilmu Ekonomi, Ekonometrika dan Keuangan (Lain-Lain)
Articles 138 Documents
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Rancang Bangun Sistem Informasi Pendaftaran Magang Berbasis Web di Diskominfo Kabupaten Tegal Salma Nafisa Qurrotu’Aini; Slamet Wiyono; Zaenul Arif
Jurnal Penelitian Teknologi Informasi dan Sains Vol. 4 No. 1 (2026): : JURNAL PENELITIAN TEKNOLOGI INFORMASI DAN SAINS (JPTIS)
Publisher : Institut Teknologi dan Bisnis (ITB) Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54066/jptis.v4i1.4367

Abstract

The internship registration process at the Communication and Information Office of Tegal Regency is still carried out manually, resulting in several problems, such as lengthy registration procedures, difficulties in managing and retrieving data, and the risk of document loss. This study aims to design and develop a web-based internship registration information system that supports the registration, verification, selection, and information delivery processes in an integrated manner. The system was developed using the Waterfall method, which consists of requirements analysis, system design, implementation, and testing stages. The application was developed using the Laravel framework and MySQL database. System testing was conducted using the Black Box Testing method to ensure that all system functions operate according to user requirements.The results indicate that the developed system can simplify the internship registration process, improve data management efficiency, accelerate the selection process, and provide real-time registration status information to applicants. Based on the testing results, all system features function properly and meet the predetermined functional requirements.
Rancang Bangun Sistem Informasi Penjualan Mitra dan Pendapatan Secara Real-time Berbasis Web : Studi Kasus Es Teh Arjuna di Kota Tegal Farchatul Hudayah; Slamet Wiyono; Zaenul Arif
Jurnal Penelitian Teknologi Informasi dan Sains Vol. 4 No. 1 (2026): : JURNAL PENELITIAN TEKNOLOGI INFORMASI DAN SAINS (JPTIS)
Publisher : Institut Teknologi dan Bisnis (ITB) Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54066/jptis.v4i1.4383

Abstract

Advancements in information technology encourage MSMEs to utilize information systems to enhance the effectiveness of their business management. Es Teh Arjuna, an MSME in Tegal City, faces challenges in monitoring partner sales and managing revenue because transactions are recorded manually using disparate methods; this results in slow data recapitulation, a risk of recording errors, and difficulty for the business owner in quickly accessing sales information. This study aims to analyze requirements, design, develop, and test a web-based information system for partner sales and revenue that provides information in  real-time. The Waterfall model was used for system development, while data collection involved observation, interviews, and a literature review. The system was developed using PHP and MySQL and tested via Black Box Testing. The results demonstrate that the system successfully integrates sales data from all outlets into a centralized database, streamlining the management of products, outlets, employees, cashiers, and sales transactions, as well as facilitating the generation of revenue reports for specific periods. Furthermore, the system enables the business owner to monitor sales performance more quickly, accurately, and systematically, thereby supporting decision-making and improving the operational efficiency of Es Teh Arjuna.
Rancang Bangun Sistem Pendukung Keputusan Penilaian Guru Terbaik menggunakan Metode Simple Additive Weighting (SAW): Studi Kasus: MTS Mambaul Ulum Ma’rifatu Khirzah; Eko Budihartono; Zaenul Arif
Jurnal Penelitian Teknologi Informasi dan Sains Vol. 4 No. 2 (2026): Juni: JURNAL PENELITIAN TEKNOLOGI INFORMASI DAN SAINS (JPTIS)
Publisher : Institut Teknologi dan Bisnis (ITB) Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54066/jptis.v4i2.4406

Abstract

Teacher performance evaluation is a crucial factor in improving educational quality, but many schools still conduct it manually and subjectively, resulting in less transparent, time‑consuming, and error‑prone outcomes. This study aims to design and develop a web‑based decision support system using the Simple Additive Weighting (SAW) method for selecting the best teacher at MTs Mambaul Ulum. The system was developed using the Waterfall model with the Laravel 12 framework and MySQL database, incorporating two evaluator roles: the principal (assessing 5 criteria: teaching hours, responsibility, mastery of material, personality, and attendance) and the vice principal (assessing 4 criteria excluding personality). Data were collected through observation, interviews, and document review. System testing employed Black Box Testing and accuracy validation by comparing system outputs with manual Excel calculations. The results show that the SAW method effectively ranks teachers objectively, with Kusyanti achieving the highest score of 0.9450. The system attained 100% accuracy, as no difference was found between manual and system calculations. Moreover, the system reduced evaluation time from days to seconds and provides well‑documented results, thus supporting more transparent and accountable decision‑making. Therefore, this system proves to be reliable, objective, and efficient in assisting school administrators in evaluating teacher performance in a structured and fair manner.
Implementasi Algoritma Naïve Bayes untuk Deteksi Dini Risiko Hipertensi Berdasarkan Distribusi Usia pada Layanan Kesehatan Julio Warmansyah; Safrial Safrial; Alam Supriatna; Wiwit Thoyyibah
Jurnal Penelitian Teknologi Informasi dan Sains Vol. 4 No. 2 (2026): Juni: JURNAL PENELITIAN TEKNOLOGI INFORMASI DAN SAINS (JPTIS)
Publisher : Institut Teknologi dan Bisnis (ITB) Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54066/jptis.v4i2.4415

Abstract

Hypertension is one of the leading non-communicable diseases contributing significantly to cardiovascular morbidity and mortality worldwide. Despite the availability of extensive electronic medical record data in healthcare institutions, these data are often utilized only for administrative reporting rather than predictive analysis. Consequently, opportunities to identify age groups with a higher probability of developing hypertension remain underutilized. This study aims to implement the Naïve Bayes classification algorithm to analyze age distribution and classify the risk of hypertension among patients using healthcare data. The research adopted the Cross-Industry Standard Process for Data Mining (CRISP-DM) methodology, including business understanding, data understanding, data preparation, modeling, evaluation, and deployment. Patient medical record data consisting of demographic and clinical attributes, including age, systolic blood pressure, diastolic blood pressure, body weight, gender, and hypertension status, were processed using the Naïve Bayes algorithm. Model performance was evaluated using a confusion matrix by measuring accuracy, precision, recall, specificity, and balanced accuracy. The implementation demonstrates that the Naïve Bayes algorithm is capable of classifying hypertension risk efficiently while providing probabilistic information regarding age groups with a higher tendency to experience hypertension. The resulting classification model offers an effective decision-support tool for healthcare providers in conducting targeted screening, preventive interventions, and evidence-based health planning. The findings also indicate that data mining techniques can transform routinely collected medical records into valuable clinical knowledge for early hypertension prevention and healthcare decision-making.
Estimasi Permintaan Berbasis AI dan E-Commerce: Peran Analitik Big Data, Akurasi Prediksi, dan Optimasi Taryana Taryana; Ahmad Syamil; Soleman Soleman
Jurnal Penelitian Teknologi Informasi dan Sains Vol. 4 No. 1 (2026): : JURNAL PENELITIAN TEKNOLOGI INFORMASI DAN SAINS (JPTIS)
Publisher : Institut Teknologi dan Bisnis (ITB) Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54066/jptis.v4i1.4498

Abstract

This study aims to analyze the effect of artificial intelligence (AI)-based demand forecasting and big data analytics on inventory optimization through prediction accuracy among e-commerce actors or marketplace sellers in Curug. This research employed an explanatory quantitative approach involving 100 respondents selected through purposive sampling based on predefined criteria relevant to the research objectives. Data were collected using a structured Likert-scale questionnaire and analyzed using Structural Equation Modeling Partial Least Squares (SEM-PLS) by evaluating the measurement model, structural model, and mediation effects. The findings reveal that AI-based demand forecasting and big data analytics have a positive and significant effect on prediction accuracy. Furthermore, prediction accuracy has a positive and significant effect on inventory optimization and significantly mediates the relationship between AI-based demand forecasting, big data analytics, and inventory optimization. These findings indicate that the integration of AI and big data analytics contributes to more accurate demand prediction, leading to improved inventory management performance. The implication of this study suggests that e-commerce actors should improve data quality, analytical capability, and the adoption of predictive technologies to support more accurate, efficient, and responsive inventory decisions, thereby enhancing operational performance and competitiveness in responding to dynamic market demand.
Pengembangan Pariwisata Cerdas untuk Pelestarian Desa Wisata di Kabupaten Sumba Barat Daya: Pendekatan (UCD) Gergorius Kopong Pati; Trisno Trisno
Jurnal Penelitian Teknologi Informasi dan Sains Vol. 4 No. 1 (2026): : JURNAL PENELITIAN TEKNOLOGI INFORMASI DAN SAINS (JPTIS)
Publisher : Institut Teknologi dan Bisnis (ITB) Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54066/jptis.v4i1.4503

Abstract

Smart tourism development is an important strategy for strengthening the competitiveness of tourism villages while preserving local culture, environmental sustainability, and community life. Southwest Sumba Regency possesses natural and cultural tourism potential; however, its management faces limitations in information provision, digital promotion, community participation, and tourism services. This study aims to design a smart tourism development model to support the preservation of tourism villages in Southwest Sumba Regency using a User-Centered Design (UCD) approach. This approach places local communities, tourism village managers, tourists, local government, and business actors as users throughout the design process. The study employs a mixed-methods approach comprising field observation, interviews, focus group discussions, questionnaires, user-needs analysis, prototype development, and usability evaluation. The UCD stages include identifying the context of use, specifying user requirements, developing solutions, and conducting evaluations. The expected outcome is a smart tourism platform prototype that provides destination information, promotes local products, presents cultural event calendars, maps tourism locations, supports reservation services, and facilitates community participation. The study is also expected to produce a digital governance model grounded in cultural values, local wisdom, and sustainability principles. The targeted outputs include a system prototype, policy recommendations, a tourism village management model, and an article. The proposed model is expected to improve tourist experiences, expand market access, strengthen community capacity, and preserve tourism village identities sustainably. Technology is therefore positioned not merely as a promotional tool, but also as a means of documentation, education, decision-making, tourism impact monitoring, and inclusive, adaptive, and sustainable collaboration among stakeholders.
Perancangan Media Pembelajaran Gerbang Logika Menggunakan Markerless Berbasis Augmented Reality Venus Selvita; Putri Mandarani; Eko Kurniawanto Putra; Ganda Yoga Swara; Eva Yulianti
Jurnal Penelitian Teknologi Informasi dan Sains Vol. 4 No. 1 (2026): : JURNAL PENELITIAN TEKNOLOGI INFORMASI DAN SAINS (JPTIS)
Publisher : Institut Teknologi dan Bisnis (ITB) Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54066/jptis.v4i1.4513

Abstract

Logic gate learning is a fundamental topic in digital electronics; however, the learning process is often delivered theoretically with limited visualization of logic gate operations, making it difficult for students to understand the concepts. This study aims to design and develop an Augmented Reality (AR)-based learning media using a markerless approach with the 3D Object Tracking technique on Android devices. The application was developed using the Multimedia Development Life Cycle (MDLC) method, which consists of the stages of concept, design, material collection, development, testing, and distribution. The developed application provides three-dimensional visualization of logic gates, learning materials, interactive simulations, and quizzes. The application quality was evaluated based on the ISO/IEC 25010 standard, covering the aspects of Functional Suitability, Performance Efficiency, Usability, Compatibility, and Portability. The evaluation results showed that the application achieved a score of 100% in the Functional Suitability, Performance Efficiency, Compatibility, and Portability aspects. Meanwhile, the Usability evaluation obtained scores of 86,6% from respondents who had not previously studied logic gates and 89% from those who had, indicating that the application is categorized as highly feasible. Therefore, the developed markerless Augmented Reality-based learning media can serve as an interactive, engaging, and effective learning alternative for improving students' understanding of logic gate concepts.
Classification of Depression Labels Among Adolescents Using TabNet Classifier Based on the Interaction of Social Media Addiction, Stress, and Anxiety Factors Diokta Redho Lastin; Anisa Oktaviani; Puji Zulaikasari
Jurnal Penelitian Teknologi Informasi dan Sains Vol. 4 No. 1 (2026): : JURNAL PENELITIAN TEKNOLOGI INFORMASI DAN SAINS (JPTIS)
Publisher : Institut Teknologi dan Bisnis (ITB) Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54066/jptis.v4i1.4561

Abstract

Adolescent depression is an important mental health concern associated with psychological conditions and excessive digital media use. The extreme imbalance of depression labels in behavioral datasets can reduce the ability of classification models to recognize minority cases. This study aims to develop a TabNet-based deep learning model for classifying adolescent depression labels using social media addiction, stress, anxiety, and related behavioral features. The study used a secondary dataset consisting of 1,200 adolescent samples. Data preprocessing included categorical feature encoding, stratified training and testing data splitting, feature standardization, and the application of the Synthetic Minority Oversampling Technique (SMOTE) to the training data. The TabNet Classifier was trained using Cross-Entropy Loss and the Adam optimizer with a step-decay learning rate and early stopping mechanism. The experimental results showed an accuracy of 99.15%, precision of 98.32%, recall of 100%, F1-score of 99.15%, and ROC AUC of 1.0000, with optimal performance achieved at epoch 53. These findings indicate that TabNet can effectively learn psychological and digital behavioral patterns for adolescent depression label classification. The proposed approach provides a potential computational framework for data-driven mental health risk classification, although further validation using diverse empirical datasets is required.

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