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Arnawan Hasibuan
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Faculty of Engineering, Universitas Malikussaleh Kampus Unimal Bukit Indah, Blang Pulo, Kec. Muara Satu Lhokseumawe
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Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN)
Published by Universitas Malikussaleh
ISSN : -     EISSN : 26567520     DOI : -
Core Subject : Science, Engineering,
Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering
The "Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN)" is a scientific publication that compiles innovative works from researchers, academics, and practitioners in the field of multidisciplinary engineering. This proceeding serves as a platform to present cutting-edge research, studies, and discoveries shared during the ICOMDEN forum, organized by the international engineering community. The proceedings cover a wide range of disciplines in engineering, including but not limited to: Mechanical Engineering, Civil Engineering, Electrical and Electronics Engineering, Computer Science and Software Engineering, Materials Engineering, Industrial Engineering, Environmental Engineering, and other related fields. Each paper published in this proceeding undergoes a rigorous peer-review process to ensure high scientific quality and impactful contributions. By integrating perspectives from various engineering disciplines, the proceedings aim to foster cross-disciplinary collaboration and provide innovative solutions to complex challenges in the field of engineering. The ICOMDEN Proceedings highlight research and technological advancements relevant to industry and society, promoting the application of sustainable engineering practices. This publication is intended to be a key reference for researchers, students, and engineering professionals to expand their knowledge and generate new ideas in addressing global challenges in engineering.
Arjuna Subject : Teknik (semua kategori) - Teknik (Lain-Lain)
Articles 119 Documents
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The Sentiment Analysis of Comments on Youtube Channel Beauty Vlogger in Indonesian Language Using Support Vector Machine Method Siti Chairani Siregar; Rizal Tjuet Adek; Zahratul Fitri
Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN) Vol. 2 (2024): Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN)
Publisher : Faculty of Engineering, Malikussaleh University

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Abstract

YouTube has become a major platform for beauty vloggers to share product reviews, where user comments provide valuable feedback. This research aims to analyze the sentiment in comments from Indonesian speaking users on beauty vlogger channels, focusing on reviews for powder and skincare products, to capture the positive or negative sentiments. The study utilizes the Support Vector Machine (SVM) method for classification and the TF-IDF weighting technique, analyzing 1,000 comments split into 800 training data and 200 testing data. Sentiment classification was performed post-text preprocessing. The results demonstrate a model accuracy of 97%, with a precision of 98% and recall of 96%, indicating that SVM effectively identifies sentiment in user comments. This system provides valuable insights for beauty vloggers to understand product feedback and contributes to the development of similar applications in other industries.
Poverty Level Clustering in Districts/Cities Using the K-Medoids Method Based on Population Data Cut Syahira Salsabila; Eva Darnila; Cut Agusniar
Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN) Vol. 2 (2024): Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN)
Publisher : Faculty of Engineering, Malikussaleh University

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Abstract

Poverty is a serious problem that hinders economic development, especially in developing countries like Indonesia. Aceh Province, especially Bireuen, Aceh Utara, and Lhokseumawe City have significant poverty rates due to high population and limited job opportunities. The K-Medoids algorithm used in this research works well in clustering the sub-districts in the region, with the aim of assisting the government in making more effective decisions. The implementation results show the clustering for the poverty rate in Bireuen in 2021 obtained C1 58.82%, C2 29.41%, C3 11.76%, in 2022 obtained C1 58.82%, C2 29.41%, C3 11.76%, in 2023 obtained C1 64.71%, C2 17.65%, C3 17.65%. In Aceh Utara District, C1 62.96% was obtained, C2 33.33%, C3 3.70%, in 2022 C1 62.96%, C2 33.33%, C3 3.70%, in 2023 C1 51%, C2 44.44%, C3 3.70%. In the city of Lhokseumawe City obtained C1 25%, C2 50%, C3 25%, in 2022 C1 25%, C2 50%, C3 25%, in 2023 C1 25%, C2 25%, C3 50%. The percentage of these results shows that the poverty rate in the three regions increases every year and this requires special attention from the government to minimize the level of poverty through increasing employment, controlling the birth rate, and cash and non-cash assistance programs for poor families.
Application of the K-Medoids Clustering Method for Grouping High-Risk Areas of Violence Against Women and Children Annisa Afrilia Zahra Annisa; Rozzi Kesuma Dinata; Maryana
Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN) Vol. 2 (2024): Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN)
Publisher : Faculty of Engineering, Malikussaleh University

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Abstract

Violence against women and children has been increasing in both quantity and variety, necessitating special attention. This study aims to cluster areas prone to violence against women and children in North Aceh using the K-Medoids Clustering method. The data used includes physical, sexual, exploitation, and neglect violence, obtained from 542 villages sourced from Unit II PPA Polres North Aceh for the period of 2021-2023. The clustering is categorized into three clusters: very prone, prone, and not prone. The results show that in 2021, there were 16 very prone villages, 22 prone villages, and 506 not prone villages, with the smallest DBI value of 0.12263 from 8 trials. In 2022, there were 22 very prone villages, 18 prone villages, and 502 not prone villages, with a DBI value of 0.10517 from 10 trials. In 2023, there were 15 very prone villages, 11 prone villages, and 516 not prone villages, with a DBI value of 0.21408 from 6 trials. The developed web-based system, using PHP and UML, is expected to assist authorities in preventing and addressing violence in prone areas, thereby reducing the incidence of violence in North Aceh.
Implementation of the Double Exponential Smoothing Method in Predicting Palm Oil Harvest Yields Muhammad Raihan Rangkuti; Taufiq; Hafizh Al Kautsar Aidilof
Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN) Vol. 2 (2024): Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN)
Publisher : Faculty of Engineering, Malikussaleh University

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Abstract

Double Exponential Smoothing (DES) is a forecasting method that combines two main components: level and trend. This method is used for data that shows a trend pattern, meaning data that tends to increase or decrease over time. This study aims to implement the Double Exponential Smoothing method to predict oil palm yields at PT. Amal Tani. The data used in this study consists of historical oil palm yield data from 2019 to 2023. The prediction system designed is web-based, utilizing PHP programming language and MySQL database. The performance evaluation of the prediction model is conducted using the Mean Absolute Percentage Error (MAPE) and Mean Absolute Error (MAE) metrics. The study demonstrates that the Double Exponential Smoothing method can produce accurate and effective predictions. The implementation of this system facilitates data processing and the dissemination of information related to oil palm yields. The results indicate that this prediction model can assist the management of PT. Amal Tani in making more accurate yield forecasts, thereby increasing productivity and operational efficiency. The implementation of this method is also expected to ease the company’s decision-making process regarding production planning and seed planting. This study concludes that the Double Exponential Smoothing method is an effective and accurate tool for predicting oil palm yields and provides positive contributions to data management and decision-making processes at PT. Amal Tani. This study offers insights into the application of the Double Exponential Smoothing method in forecasting oil palm yields.
The Application of Greedy Algorithm in OLTC Tap Setting for Voltage Stability of a 60 MVA Power Transformer Ahmad Azhari Batubara; Misbahul Jannah; Muhammad; Rosdiana; Teuku Multazam
Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN) Vol. 2 (2024): Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN)
Publisher : Faculty of Engineering, Malikussaleh University

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Abstract

The On Load Tap Changer (OLTC) is an electrical device that functions as a tap changer under load, allowing the adjustment of transformer windings without requiring a power shutdown. To maintain a constant output voltage of 20 kV on the secondary side of a transformer, OLTCs are employed in 60 MVA power transformers. Voltage instability in a power generation system leads to increased OLTC operations. This study aims to analyze the optimization of OLTC tap position settings to enhance voltage stability in a 60 MVA power transformer using the Greedy Algorithm, based on primary voltage, secondary voltage, and OLTC tap position. The research was conducted over the course of one week, from June 1 to June 7, 2024. The results show that, when using the Greedy Algorithm, Transformer 1 required only 8 tap position changes, compared to 11 changes with manual calculations and actual data. Similarly, Transformer 2 experienced 7 tap changes, while manual calculations and actual data recorded 10 changes. These findings indicate that, by using the Greedy Algorithm, the transformer taps operate less frequently, which is beneficial for the longevity of the transformer taps. This study concludes that the Greedy Algorithm is effective as an optimization method for OLTC tap settings to maintain voltage stability in 60 MVA transformers.
Recommendation System For Choosing The Best Laptop For Informatics Students Using The SMART Method Depi Sihotang; Bustami; lidyarosnita
Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN) Vol. 2 (2024): Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN)
Publisher : Faculty of Engineering, Malikussaleh University

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Abstract

In the rapidly advancing digital era, the use of laptops has become an essential need, especially for students. The problem of choosing the right laptop is still often experienced by many students. This issue arises due to a lack of knowledge in selecting laptops with good specifications and affordable prices, so purchasing decisions are often based on friends' recommendations or advertisements that do not always meet their academic needs optimally. This research uses the Simple Multi Attribute Rating Technique (SMART) method. SMART is a flexible decision-making method. The process of determining the best laptop involves criteria such as price, processor type, monitor screen size, operating system, RAM, VGA type, and storage. The system provides solutions by using the SMART method to evaluate the weights and criteria that have been determined. The ranking process is carried out to determine the best laptop for students majoring in informatics. From 10 data samples for the Informatics department, the highest alternative value (A4) was obtained, namely "ACER Swift X 14 SFX14-71G-70KB" with a final score of 0.866666667, and the lowest alternative value (A8) was "ASUS VivoBook 14 A1404ZA-IPS321" with a final score of 0.166666667. The process of determining the best laptop using the Simple Multi Attribute Rating Technique (SMART) method aims to help informatics students choose laptops that suit their academic needs.
Implementation Of Agglomerative Clustering Method On Mapping Crime-Prone Areas Of Webgis-Based Lhokseumawe City Case Study Of Lhokseumawe Prosecutor's Office Teuku Ibrar Faturrahman Ibrar; Safwandi Safwandi; Zahratul Fitri Zahratul Fitri
Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN) Vol. 2 (2024): Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN)
Publisher : Faculty of Engineering, Malikussaleh University

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Abstract

The application of the Agglomerative Hierarchical Clustering method was carried out for mapping the Lhokseumawe City area, with a focus on sub-districts grouped by village and their crime rates. The types of crimes analyzed include drugs, oharda (violations of public order and security), and kamtibum (public order and security). The data used came from the Prosecutor's Office and was taken through the Department of Law, covering various crimes that are very detrimental to society. By utilizing Geographic Information System (GIS) technology, this system can provide clear visual information about the location of criminal incidents and the types of crimes that occur in each village. This clustering process allows for the grouping of villages that tend to have high crime rates, thus helping to identify areas that require more attention in law enforcement. The application of this clustering is not new, because previously many researchers and scientists have applied similar methods, but with different case studies. In this context, clustering helps provide more detailed insights into the distribution of crime at the village level, allowing for more focused and targeted prevention efforts.
Implementation of Triple Exponential Smoothing in Predicting Blood Stock Inventory Afif Diapari Ma'aruf Lubis Afif Diapari; Nurdin; Kurniawati
Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN) Vol. 2 (2024): Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN)
Publisher : Faculty of Engineering, Malikussaleh University

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Abstract

Blood availability is an important component for the Indonesian Red Cross (PMI) Blood Donor Unit (UDD) in maintaining blood supplies so that blood is not wasted and there is no shortage. This study aims to test the effectiveness of using the Triple Exponential Smoothing (TES) method in predicting blood stock inventory at UDD PMI. Triple Exponential Smoothing is a forecasting method that considers seasonal patterns in data, which is relevant in predicting blood demand based on historical data. This study began by collecting historical blood stock data from January 2019 to December 2023. Next, the data was analyzed to identify seasonal patterns and trends. This method is applied to the four main blood types (A, B, AB, and O) by calculating the accuracy value using Mean Absolute Percentage Error (MAPE) and Mean Absolute Error (MAE). The results show that the TES method can accurately predict blood availability and demand, with a low MAPE value of 2.15% for blood type A. For blood type B, the MAPE value is 1.38%, blood type O is 1.03%, and blood type AB is 2.42%. This research is expected to significantly contribute to more effective and efficient bloodstock management at PMI and become an academic reference for future blood stock forecasting studies.
Implementation Of The Support Vector Machine Method In Determining The Best Quality Of Sap Azhari Putra Sayani; Safwandi; Fajriana
Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN) Vol. 2 (2024): Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN)
Publisher : Faculty of Engineering, Malikussaleh University

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Abstract

Rubber trees (Hevea brasiliensis) are the main source of natural rubber and play an important role in Indonesia's industry. Determining the quality of rubber sap is a challenge for companies, as traditional manual processes are time-consuming and prone to human error. PT Poly Kencana Raya, a company in Besitang, North Sumatra, currently still uses conventional methods in determining the quality of rubber latex it produces. This research aims to design a web-based system with the application of the Support Vector Machine (SVM) method to facilitate the determination of rubber latex quality. SVM was chosen as a classification method because of its ability to determine the optimal hyperplane that can separate data from two different classes, namely feasible and unfit. The built system utilizes the main criteria such as tree age, tapping time, moisture content, color, and texture in determining the quality of the sap. Implementation. This study used 120 samples of test data, with accurate prediction results on 111 data, resulting in an accuracy rate of 92.5%. This decision support system is expected to increase efficiency and accuracy in rubber sap selection and support the development of rubber production quality in Indonesia. This research also opens up opportunities for further development by adding other classification methods for accuracy comparison or adding training data to optimize prediction results. Keywords: Rubber Trees, Support Vector Machine, Data Mining
HC-SR04 Sensor Implementation in an IoT-Based Fresh Fruit Bunch Filling Prototype for Vertical Sterilizer Selamat Meliala; Yogi Satya; Rosdiana Rosdiana; Muhammad Daud; Taufiq Taufiq
Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN) Vol. 2 (2024): Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN)
Publisher : Faculty of Engineering, Malikussaleh University

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Abstract

This study develops an IoT-based Fresh Fruit Bunch (FFB) filling prototype for vertical sterilizers using the HC-SR04 ultrasonic sensor to enhance the accuracy and efficiency of the filling process in palm oil mills. The system incorporates a non-contact distance sensor to ensure precise measurement and integrates IoT technology and a Telegram bot for real-time monitoring and automation. Testing results indicated that the HC-SR04 sensor achieved high accuracy, maintaining a low tool failure rate of 0.036%, making it highly reliable for industrial applications. Visual and audio indicators, including LEDs and buzzers, were used to enhance user awareness and safety during the filling process. By automating and optimizing FFB loading, the system minimizes operational inefficiencies commonly associated with manual filling methods and improves safety by reducing human intervention. These findings suggest that the developed prototype can provide significant operational benefits to the palm oil industry and other sectors requiring similar improvements in productivity and sustainability. Future research will focus on refining the prototype and evaluating its scalability for broader industrial use.

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