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Kab. aceh selatan,
Aceh
INDONESIA
Jurnal Inotera
Published by Politeknik Aceh Selatan
ISSN : 25487574     EISSN : 25811274     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering
Arjuna Subject : -
Articles 325 Documents
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Analysis and Prediction of Student Academic Performance Using the Random Forest Algorithm Wanto, Donna Oktar Endras; Dede Sahrul Bahri
Jurnal Inotera Vol. 11 No. 1 (2026): January-June 2026
Publisher : LPPM Politeknik Aceh Selatan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31572/inotera.Vol11.Iss1.2026.ID657

Abstract

Student academic performance is one of the important indicators of success in the learning process. Therefore, a method is needed that can analyze and accurately predict students' academic performance. This study aims to analyze and predict students' academic performance using the Random Forest algorithm. The dataset used consists of 649 student records with 33 attributes covering student characteristics, family background, social activities, and academic grades. The students’ final grade (G3) is used as the target variable in the classification process.The research stages include data exploration, data preprocessing, splitting the data into training and testing sets, building the Random Forest model, and evaluating the model. The results show that the Random Forest model is able to achieve an accuracy rate of 92.31%. Testing using a confusion matrix indicates that the model has a relatively low prediction error rate. In addition, testing using the cross-validation method produces an average accuracy of 91.21%, indicating that the model has good stability. Feature importance analysis shows that previous academic grades, namely G2 and G1, are the most influential factors affecting students' academic performance. The results of this study indicate that the Random Forest algorithm can be effectively used to predict students' academic performance and can assist educational institutions in data-driven decision-making.
Implementation of an Automatic Goods Delivery Scheduling System using a Heuristic Algorithm for Sinar Terang Buliding Store BSD Fauziana, Cantika Ayu; Galuh Saputri
Jurnal Inotera Vol. 11 No. 1 (2026): January-June 2026
Publisher : LPPM Politeknik Aceh Selatan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31572/inotera.Vol11.Iss1.2026.ID592

Abstract

This research aims to develop an automated delivery scheduling system for Toko Bangunan Sinar Terang BSD by applying a heuristic algorithm as an optimization approach for scheduling and route planning. The previous manual scheduling process often caused various inefficiencies, such as schedule conflicts, suboptimal route selection, longer travel times, and ineffective vehicle utilization. To address these issues, this study implements a heuristic algorithm capable of generating near-optimal solutions with fast computational time, especially for complex scheduling and distribution problems.The research process includes several stages: requirements analysis, system design, heuristic algorithm implementation, and system testing. The system is designed with a simple interface and structured workflow to ensure ease of use for store administrators. Black box testing demonstrates that all system functions operate according to the design, including data input, route determination, and automatic schedule generation. The implementation results show significant improvements in delivery efficiency, indicated by faster scheduling time, more optimal delivery routes, and better fleet utilization compared to the manual method. Therefore, the application of heuristic algorithms in the delivery scheduling system has proven effective in enhancing punctuality and service quality at Toko Bangunan Sinar Terang BSD. This study is expected to serve as a foundation for future system development, such as GPS integration and the use of more advanced optimization algorithms.
A Three-Layer Metadata Model for the Digital Inventory of Kasab Aceh Hardisal; M Arynal Ihsan
Jurnal Inotera Vol. 10 No. 2 (2025): July - December 2025
Publisher : LPPM Politeknik Aceh Selatan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31572/inotera.Vol10.Iss2.2025.ID597

Abstract

Kasab Aceh—raised gold-thread embroidery worked on velvet—embodies aesthetic, symbolic, and social meaning across Aceh’s regions. Yet its diverse forms and motifs remain unevenly documented in digital repositories, limiting preservation and scholarly reuse. This article presents a concise yet comprehensive, three-layer metadata model—descriptive, administrative, and structural—for the digital inventory of Kasab Aceh. The design adapts Dublin Core for interoperable description and aligns with CIDOC CRM to support event-centric semantics and future publication as Linked Open Data. We delineate core entities (Product, Motif, Artisan, Photo, Session, Region, Registration), cardinalities (e.g., Product–Motif M:N; Photo–Product N:1), normalization policies (centimeters/grams for measurements; free-text materials and colors), and session-based provenance. Results include an Entity–Relationship schema, illustrated instances from South Aceh fieldwork, and a validation regimen using SHACL constraints. We discuss practical trade-offs between field flexibility and data consistency, demonstrate how structural links to image-derivative files (mask/overlay/SVG/JSON) enable reproducible visual analytics, and outline pathways for semantic migration and public access. The model offers a durable foundation for culturally faithful curation and cross-disciplinary research.
Thermal Optimization of a Dual-Heater Snakehead Fish (Channa Striata) Extraction Chamber through CFD and Experimental Validation Izhary Siregar; Ahmad Jibril; Setyawan Dwi Nugroho; Agus Purwanto
Jurnal Inotera Vol. 11 No. 1 (2026): January-June 2026
Publisher : LPPM Politeknik Aceh Selatan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31572/inotera.Vol11.Iss1.2026.ID610

Abstract

This study investigates the thermal optimization of a rotary extraction chamber for snakehead fish (Channa striata) utilizing a dual-heater configuration. A synergistic two-stage methodology was employed, integrating Computational Fluid Dynamics (CFD) for numerical characterization of convective heat distribution with experimentalvalidation using a physical prototype. CFD simulations revealed a convection-dominated thermal field with a minimal thermal gradient of 8.3°C (63.52°C wall and 55.22°C center), ensuring a stable exposure temperature of approximately 60°C. Experimental trials across a range of 40–110°C and 60–180 minutes identified an optimal operating window of 80–90°C for 120 minutes, yielding a peak extraction volume of 46.4 mL. Quantitative trends indicated that while thermal energy facilitates albumin liberation, temperatures exceeding 100°C trigger a progressive decline in yield due to fluid evaporation and thermal degradation. The integration of dual-source heating and mechanical rotation, as validated by the close agreement between numerical and experimental data, establishes a scalable and predictable framework for high-efficiency protein extraction in fisheries mechanization.
Islamic Study Schedule Search Website in Jakarta with Automatic WhatsApp Reminder Feature Using Extreme Programming Method Wicaksono, Fahmi Perdana; Galuh Saputri
Jurnal Inotera Vol. 11 No. 1 (2026): January-June 2026
Publisher : LPPM Politeknik Aceh Selatan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31572/inotera.Vol11.Iss1.2026.ID612

Abstract

This paper presents the development of a website for searching Islamic study schedules in Jakarta equipped with an automatic reminder feature via WhatsApp. The system is designed for Muslim residents in Jakarta to provide easy access to accurate and up-to-date information on Islamic study activities. Users can search schedules based on location, study theme, and preacher. The reminder feature is integrated with WhatsApp to automatically notify users before scheduled activities. The development follows the Extreme Programming (XP) methodology, which includes planning, design, coding, and testing. System testing demonstrates that all implemented features function according to requirements.
Expert System for Diagnosing Monkeypox Using the Tsukamoto Method and Forward Chaining Marwati, Fingki; Ardianto
Jurnal Inotera Vol. 11 No. 1 (2026): January-June 2026
Publisher : LPPM Politeknik Aceh Selatan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31572/inotera.Vol11.Iss1.2026.ID658

Abstract

Monkeypox is a viral infectious disease that requires early detection to prevent wider transmission and ensure appropriate treatment. Limited public awareness and access to medical professionals may delay early diagnosis. Therefore, this study proposes the development of an Android-based expert system for early monkeypox diagnosis using the Forward Chaining inference method and the Tsukamoto fuzzy logic method. Forward Chaining is applied to perform rule-based reasoning based on user-input symptoms, while the Tsukamoto method is used to calculate the level of certainty of the diagnosis. The system was developed using the Waterfall model and tested with 20 case data samples. The evaluation results show that the system achieved an accuracy level of 85%, with 17 out of 20 diagnoses consistent with expert assessments. User testing involving 20 participants indicated that 90% of users found the application easy to use and informative. In addition, the system is capable of generating diagnostic results within 1–2 minutes, making it more efficient than manual consultation. The results demonstrate that the proposed system is effective and feasible as a decision-support tool for early monkeypox diagnosis.
Environmental Carrying Capacity and Community-Based Governance of Mangrove Ecotourism in Tomini Bay Anwar, Rustam; Abdurahman Kano Mohamad; Syaiful Umela; Romi Djafar
Jurnal Inotera Vol. 11 No. 1 (2026): January-June 2026
Publisher : LPPM Politeknik Aceh Selatan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31572/inotera.Vol11.Iss1.2026.ID678

Abstract

Mangrove ecotourism is increasingly promoted as a pathway to reconcile conservation, livelihood diversification, and coastal resilience, yet destination growth often outpaces ecological thresholds, institutional capacity, and community readiness. Building on the literature review in the International Journals and incorporating recent studies compiled in Journals, this article presents an updated integrative review on the role of carrying capacity in sustainable mangrove ecotourism, with strategic implications for Tomini Bay, Indonesia. Using only the uploaded extraction sources, the review synthesizes advances in ecological suitability assessment, physical-real-effective carrying capacity, community participation, governance arrangements, social feasibility, and tourism management innovation across Indonesia and comparable settings. The synthesis shows that carrying capacity should not be treated merely as a visitor quota; it functions as a multidimensional governance instrument linking ecosystem integrity, visitor experience, local welfare, infrastructure limits, and enforcement capacity. Recent studies also reveal a persistent gap between technical suitability analysis and day-to-day management, especially in zoning, monitoring, promotion, digital visitor control, and benefit sharing. For Tomini Bay, the review proposes a conservation-first, community-based, and adaptive-capacity model that combines spatial zoning, phased visitor limits, ecosystem monitoring, participatory governance, and blue-economy livelihood integration. The article contributes a comparative evidence base, a strategic framework, and a research agenda for emerging mangrove destinations.
Design and Development of a Web-Based Information System for Managing Marine Product Data at the Aceh Departement of Marine Affairs and Fisheries Suyanto, Prayoga Bima; Ully Muzakir; Mukhroji
Jurnal Inotera Vol. 11 No. 1 (2026): January-June 2026
Publisher : LPPM Politeknik Aceh Selatan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31572/inotera.Vol11.Iss1.2026.ID647

Abstract

This research aims to design and develop a web-based information system for managing marine product data at the Department of Marine and Fisheries of Aceh. The system was created to solve problems in data recording that were previously done manually using books and Excel spreadsheets, which often led to input errors, report delays, and difficulties in data retrieval. The development method used is the Waterfall model, which includes the stages of analysis, design, implementation, testing, and maintenance. The system was built using PHP, MySQL, and Bootstrap, featuring main functions such as marine product data input, automatic reporting, management of news and agendas, and public information display accessible to the community. Based on Black Box Testing, all system features functioned properly as expected. Furthermore, the user satisfaction questionnaire consisting of 20 statements yielded an average score of 4.42 (Very Satisfied category), indicating that the system provides ease, speed, and reliability in data management. The implementation of this system helps the Department of Marine and Fisheries of Aceh improve work efficiency, public information transparency, and support the digitalization of marine resource management in a sustainable manner.
Analisis Performa Voice Recognition Pada Smart Speaker Menggunakan Metode Random Forest Yani, Muhammad; Fikry, Muhammad; Hasibuan, Arnawan; Nurdin; Munirul Ula; Husaini
Jurnal Inotera Vol. 11 No. 1 (2026): January-June 2026
Publisher : LPPM Politeknik Aceh Selatan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31572/inotera.Vol11.Iss1.2026.ID654

Abstract

The development of Internet of Things (IoT) and artificial intelligence technology has driven the increasing use of voice user interfaces (VUI) as a more natural form of human-computer interaction. One widely used VUI implementation is voice recognition-based smart speakers. Despite its widespread adoption, voice recognition performance on smart speakers is not necessarily optimal when used in real-world conditions, particularly in far-field scenarios that are influenced by user distance, environmental noise, and system response time. This study aims to analyze and compare the voice recognition performance of Amazon Alexa smart speakers and the Interactive Speaker System as a non-vendor comparison system. Testing was conducted at varying user distances in a non-soundproof room to represent real-world operational conditions.The obtained performance data was analyzed using the Random Forest method as a classification tool due to its ability to handle multivariate data and nonlinear relationships between variables. The results showed that variations in user distance significantly affected the voice recognition performance of both systems, with a tendency for performance to decrease as distance increased. In addition, differences in system architecture characteristics also influenced the level of resilience to environmental conditions. The application of the Random Forest method also enabled the identification of dominant factors that influence the success of voice recognition. This research is expected to provide theoretical contributions in the study of voice recognition performance in far-field scenarios, as well as practical contributions as a basis for consideration in the selection and development of more reliable voice-based interaction systems in real environments.
Implementation of a Web Based influencer Recommendation System Using Content Filtering and Agile Development : A Case study at Ralya Management Rahadiani Atika Putri Nurjanah; Fajar Agung Nugroho
Jurnal Inotera Vol. 11 No. 1 (2026): January-June 2026
Publisher : LPPM Politeknik Aceh Selatan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31572/inotera.Vol11.Iss1.2026.ID591

Abstract

The development of digital marketing has led companies to increasingly rely on influencers as an effective promotional medium. However, selecting the right influencer remains a challenge because the process is often conducted manually and only considers basic attributes such as the number of followers and popularity level, this study focuses on developing a web-based influencer recommendation system that can provide more relevant and faster recommendations. The research was conducted on Ralya Management, an agency managing influencers in Indonesia that requires a system capable of improving the efficiency of influencer selection for various marketing campaigns. To achieve its objectives, this study adopts two main approaches. First, the Content-Based Filtering method is applied to match influencer content characteristics including category, keywords, engagement rate, and domicile with user preferences, resulting in more targeted recommendations. Second, the system development process utilizes the Agile Development method with the Scrum framework, enabling iterative, flexible, and adaptive development in response to influencer data updates.. The results show that the system is capable of producing more accurate influencer recommendations compared to the previous manual method. Additionally,. Overall, this system contributes significantly to enhancing the effectiveness of influencer marketing strategies, particularly for Ralya Management as the research subject.

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