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Jurnal Tecnoscienza
Published by Universitas Kahuripan Kediri
ISSN : 25413295     EISSN : 26153319     DOI : -
Core Subject : Science, Education, Engineering,
Civil Engineering, Building, Construction & Architecture Computer Science & IT Engineering Mathematics Other
TECNOSCIENZA is an academic journal on the issued related to engineering, earth science, and technology. Published actually in April and October. It is open to all scientist, researchers, education practitioners, and other scholar. Therefore this journal welcomes to various topics that have recieved by Proffesors and Doctors specifying on related studies, and they come from reputable universities all over Indonesia and universities abroad.
Arjuna Subject : Teknik (semua kategori) - Teknik (Lain-Lain)
Articles 427 Documents
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Identifikasi Pola Risiko Pasien Polycystic Ovary Syndrome (PCOS) Menggunakan Algoritma K-Means Fany Charoliana Dewi; Melda Agarina
JURNAL TECNOSCIENZA Vol. 11 No. 1 (2026): JURNAL TECNOSCIENZA
Publisher : JURNAL TECNOSCIENZA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51158/31dat855

Abstract

Polycystic Ovary Syndrome (PCOS) is a complex endocrine disorder commonly affecting women of reproductive age and associated with reproductive and metabolic conditions. Therefore, a systematic data analysis approach is needed to identify PCOS risk patterns. This study aims to cluster PCOS patient data using the K-Means algorithm and analyze the resulting risk patterns. The data were obtained from a public Kaggle dataset consisting of 2,539 patient records, including demographic, hormonal, metabolic, reproductive, and lifestyle variables. The research methodology follows the Knowledge Discovery in Databases (KDD) process, which comprises data selection, preprocessing, transformation, data mining, evaluation, and interpretation. The K-Means algorithm was applied to group the data into three categories: low, moderate, and high risk. The results indicate that the clustering process produces groups with distinct characteristics based on data similarities. The identified patterns include characteristics such as Body Mass Index (BMI), menstrual cycle irregularities, and hormonal parameters. These findings provide an overview of PCOS patient characteristic patterns that may serve as supporting information for healthcare professionals in understanding patient data and improving public awareness of PCOS prevention and management. 
Rancang Bangun Sistem Smart Door Lock Berbasis ESP32 Dengan Verifikasi Biometrik dan Cloud Logging Mahendra; Mochammad Ilham Aziz; Saifulloh Azhar
JURNAL TECNOSCIENZA Vol. 11 No. 1 (2026): JURNAL TECNOSCIENZA
Publisher : JURNAL TECNOSCIENZA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51158/wkfbr722

Abstract

The rapid advancement of the Internet of Things (IoT) has driven the development of smarter and more integrated security systems. At CV. Indah Pratama, the continued use of conventional mechanical keys presents several challenges, including inefficient access management, the risk of lost or unauthorized use of keys, and the absence of a systematic access logging mechanism. This study developed an ESP32 -based Smart Door Lock system that integrates fingerprint authentication with real-time activity logging using Google Sheets. The research employed the Research and Development (R&D) method with the Waterfall development model, consisting of requirements analysis, system design, implementation, testing, and deployment. Data communication between the ESP32 and Google Sheets was established through Google Apps Script. System evaluation was conducted using Black Box Testing and latency testing to measure data transmission time to the cloud. The results demonstrate that the proposed system operates as intended by providing reliable fingerprint authentication, automatically unlocking the door, and recording access activities in real time. In addition, the fail-safe buffering feature ensures that data are securely stored during internet connectivity interruptions. Based on the testing results, the system achieved a 100% success rate with an average latency of 1.980 ms, demonstrating its effectiveness in improving access efficiency while providing transparent and well-structured access activity records. 
Penerapan K-Means Clustering untuk Pemetaan Pola Pelanggaran Kehadiran Siswa SMK Hidayatus Sholihin Muhamad Abdul Aziz; Widodo; Saifulloh Azhar
JURNAL TECNOSCIENZA Vol. 11 No. 1 (2026): JURNAL TECNOSCIENZA
Publisher : JURNAL TECNOSCIENZA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51158/eqt4te23

Abstract

Online attendance data has the potential to support decision-making in schools; however, conventional evaluations are generally limited to summarizing cumulative percentages, which are unable to distinguish specific patterns of student misconduct. This study aims to analyze patterns of attendance violations among students at SMK Hidayatus Sholihin based on data regarding disciplinary behavior, specifically tardiness and unexcused absences. The study applied the Knowledge Discovery in Databases (KDD) framework to data from 63 10th-grade students during the odd-numbered semester of 2025. Data processing was conducted using Altair AI Studio with the K-Means Clustering algorithm, while the number of clusters was determined using the Elbow Method, and validation was performed via the Silhouette Score, which yielded a score of 0.502. The results showed that the data could be reliably mapped into three clusters: Cluster 0, consisting of 16 students exhibiting a pattern of “Acute Truancy”; Cluster 1, consisting of 12 students exhibiting a pattern of “Moderate Tendency to Be Late”; and Cluster 2, consisting of 35 students exhibiting a pattern of “Acute Tardiness Violations.” These clustering results serve as the basis for formulating more targeted intervention strategy recommendations to support the enforcement of school rules and the fostering of student discipline.
Pengembangan Game Edukasi Calistung Berbasis Android Menggunakan Unity untuk Anak Usia Dini Suhairu Baridil Fuad; Muhammad Oktoda Noorrohman; Saifulloh Azhar
JURNAL TECNOSCIENZA Vol. 11 No. 1 (2026): JURNAL TECNOSCIENZA
Publisher : JURNAL TECNOSCIENZA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51158/vtwraq73

Abstract

The development of an Android-based educational game for reading, writing, and arithmetic (calistung) using Unity was carried out to provide an interactive learning medium for early childhood education. The method employed was Research and Development (R&D) using the Multimedia Development Life Cycle (MDLC) model, which consists of six stages: concept, design, material collecting, assembly, testing, and distribution. The developed game provides three main features: (1) reading activities using three-dimensional (3D) objects accompanied by pronunciation audio, (2) letter-writing activities through a tracing method with a level system and star rewards, and (3) arithmetic activities using interactive fruit images supported by score and life systems. Black Box Testing confirmed that all game functions operated as designed. In addition, User Acceptance Testing (UAT) involving 15 students from KB-TK Al-Ishyar located at Jl. Kisuryo Jati Selatan, RT 22, RW 08, Kedungturi Village, Taman Subdistrict, Sidoarjo Regency showed the application possesses good usability, effectively enhances learning interest and engagement, and was suitable as a supporting medium for developing basic literacy and numeracy skills in early childhood. 
Analisis Pengendalian Kualitas Statistik dan Perencanaan Desain Smart Garden Furniture Berbasis Python Data Library Onny Purnamayudhia; Subaderi; Ampar Jaya Suwondo
JURNAL TECNOSCIENZA Vol. 11 No. 1 (2026): JURNAL TECNOSCIENZA
Publisher : JURNAL TECNOSCIENZA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51158/4hgfnh63

Abstract

Synchronizing consumer preferences with manufacturing process reliability serves as a crucial pillar in assembling smart outdoor furniture. This study is directed toward combining the Quality Function Deployment (QFD) strategy via the House of Quality (HOQ) matrix alongside Statistical Quality Control (SQC), facilitated by Python Data Library computational algorithms. This quantitative analysis relies on questionnaire feedback from 50 participants and technical assessments of 40 representative prototype units. Instrument evaluation proves compliance with data validity and reliability requirements (Cronbach's Alpha = 0.724). The planning matrix computation positions the mechanical aspects of the main supporting pillars (TR5) as the highest manufacturing engineering focus, with a 22.08% contribution toward foundational stability. Conversely, statistical evaluation on the shop floor maps electrical outlet defects as the most dominant failure, reaching 55%, supported by p-chart control graph findings capturing an operational deviation in Batch 6 (p = 0.350 > UCL = 0.2895) with sub-optimal process capability index performance (Cpk = 0.86). The implementation of this programming-based closed-loop quality assurance scheme successfully eliminates informational barriers between departments through real-time and direct engineering specification updates and automated tolerance design alterations.
Pengembangan Sistem Informasi Edukasi Stunting dan Narkoba Berbasis Web Menggunakan Laravel di Desa Tinelo Zainudin Sidik; Abdul Rahman Ismail; Sarinah Pakpahan
JURNAL TECNOSCIENZA Vol. 11 No. 1 (2026): JURNAL TECNOSCIENZA
Publisher : JURNAL TECNOSCIENZA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51158/fnmdpd28

Abstract

Stunting prevalence in Gorontalo Province (23.8%) remains above the national figure (19.8%), and drug abuse still threatens adolescents. In Tinelo Village, prevention education still relies on face-to-face counselling and printed media, which are tied to a schedule, offer little interaction, and cannot be revisited by residents. A website was chosen because it opens in a mobile browser without installation and its content can be updated centrally by the village administrator. This study aims to develop a web-based stunting and drug-abuse education information system using Laravel 11 and Tailwind CSS, following Pressman's Waterfall model: communication, planning, modeling, construction, and deployment. The system offers seven features: Home, Animated Videos, Educational Materials, Quizzes, Voice of the Community, Prevention Tips, and Hotline, together with an Admin panel for managing content, quiz history, and testimonial approval. Functional evaluation used Black Box Testing with Equivalence Partitioning, while acceptance was measured through a Likert-scale User Acceptance Testing (UAT) on the user and Admin sides. All 11 Black Box scenarios passed. The UAT yielded 86.40% from 45 user respondents and 88.00% on the Admin side, both categorized as Very Good. The system lets residents revisit the material at any time and lets administrators update content and monitor understanding.
Optimasi Koefisien Single dan Double Exponential Smoothing Menggunakan Solver untuk Prediksi Produksi Gula Nasiona Gusman Simon
JURNAL TECNOSCIENZA Vol. 11 No. 1 (2026): JURNAL TECNOSCIENZA
Publisher : JURNAL TECNOSCIENZA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51158/kshsh624

Abstract

Sugar has an important in the national economy and food security; however, consumption levels continues to rise due to population growth and industrial expansion. Fluctuations in national sugar production—often falling short of demand—have created supply gaps and necessitated reliance on imports. To support strategic planning and balance supply and demand, this study forecasts national sugar production using historical data spanning 40 periods (1985–2024) from Statistics Indonesia (BPS) publications. The study’s main contribution is the use of Single Exponential Smoothing (SES) and Double Exponential Smoothing (DES) with MS Excel Solver to optimize the α and β coefficients, rather than relying on trial-and-error approaches or omitting detailed coefficient selection. Forecast results were evaluated using the Mean Absolute Percentage Error (MAPE) metric; both methods demonstrated high forecasting accuracy based on MAPE classification standards. A comparative analysis revealed nearly comparable performance, with SES yielding a slightly lower MAPE than DES. 

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