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Metode Analisis Risiko Kerusakan Mesin Produksi di Indonesia: Literature Review Pamungkas, Iing; Irawan, Heri Tri; Basuki, Mahmud; Ridha, Arrazy Elba; Adib, Adib; Syahputra, Rizki Agam; Widarta, Fajar Okta
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Publisher : Universitas Teuku Umar

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Abstract

Production machines are specially designed to perform various tasks such as processing, assembly, packaging and more depending on the type of production and the industry involved. However, damage to production machines is unavoidable with such a task. Machine damage can occur due to various factors, such as excessive use, inadequate maintenance, worn components, design errors and many more. Damage to the machine certainly raises risks, both measurable risks and immeasurable risks. The risk of machine failure can have a serious impact on the productivity, reliability and operating costs of a business. The use and application of risk analysis methods or approaches can be used to minimize the occurrence of excessive risk. The purpose of this research is to find out various methods of risk analysis of production machine damage in various industries in Indonesia. This research uses a systematic method by reviewing the literature from various published articles which are then identified and analyzed which focus on various production machine damage risk methods used in various industries in Indonesia. The results of the study show that there are several methods of analyzing the risk of damage to production machines that are commonly used in Indonesia, such as failure mode and effect analysis (FMEA, FMECA, fuzzy FMEA), risk based maintenance (RBM), fault tree analysis (FTA), fishbone diagram, enterprise risk management (ERM), failure tracking matrix (FTM), total quality control (TQM), logic tree analysis (LTA), overall equipment effectiveness (OEE), Hazard operability (Hazop), and certainty factor and forward chaining. Some of these methods are generally integrated with various other methods or approaches to obtain optimal results.
Metode Analisis Kesehatan Dengan Mengguakan Machine Learning dan Data Mining : Literature Review Syahputra, Rizki Agam; Hanifah, Maulia Rahmi
Jurnal Industri dan Inovasi (INVASI) Vol 1, No 2 (2024): Maret
Publisher : Universitas Teuku Umar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64670/invasi.v1i2.9406

Abstract

Kesehatan merupakan aspek penting dalam masyarakat dan menjadi pondasi bagi kemajuan suatu negara. Negara yang berhasil memperkuat sistem kesehatannya akan memiliki masyarakat yang sejahtera. Pemerintah seringkali memprioritaskan kesehatan dan kesejahteraan masyarakat dalam agenda pembangunannya. Salah satu upaya yang dilakukan adalah pembangunan dan peningkatan pelayanan serta fasilitas kesehatan guna memastikan kesehatan bangsa dan tercapainya negara yang sehat. Penelitian ini bertujuan untuk menyelidiki berbagai metode analisis kesehatan yang dapat dipergunakan untuk memprediksi atau menyelesaikan masalah kesehatan sesuai kebutuhan. Metode penelitian ini melibatkan kajian literatur dari berbagai artikel yang diterbitkan dalam beberapa tahun terakhir. paper ini fokus pada analisis terhadap berbagai metode analisis kesehatan yang digunakan khususnya dalam pengunaan big data dan juga artificial inteligence. Berdasarkan analisis terhadap berbagai artikel jurnal, metode analisis kesehatan yang umum digunakan meliputi data mining, clustering, algoritma k-mean, naïve bayes, decision tree, support vector machine, neural network, k-nearest neighbor, rapidminer, algoritma C4.5, multiple linear regression, artificial intelligence, tensorflow, ssdmobilenet berbasis python, machine learning, classifier, backpropagation, prediksi, random forest, cross validation, dan confusion matrix. Meskipun beberapa metode tersebut umum digunakan, terdapat pula metode atau pendekatan lain yang dapat memberikan hasil yang lebih optimal dalam analisis kesehatan.
Structural Equation Modeling Analysis of Purchase Behavior of Halal Products Zuhri, Sarika; Ilyas, Ilyas; Erwan, Friesca; Syahputra, Rizki Agam; Sentia, Prima Denny; Noprita, Zikra
Indonesian Journal of Halal Research Vol 5, No 1 (2023): February
Publisher : UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/ijhar.v5i1.20170

Abstract

Indonesia is renowned for being home to the largest Islamic population globally, but the absence of a halal certification logo on products continues to be a cause for concern. For Muslim customers, their basic knowledge of halal ingredients written on the product is the only guide they can be relied on. Hence, it is crucial to understand the essential factors that influence their purchasing behavior regarding halal-certified products. This study uses the Theory of Planned Behavior (TPB) to examine Muslim customers' behavior, as a case study, in Banda Aceh. The TPB questionnaire, including attitude, subjective norm, perceived behavioral control, and purchase intention attributes, was distributed online to respondents in the Banda Aceh area using non-probability random sampling. Through Structural Equation Modeling (SEM) methodology and AMOS software, this research reveals a strong correlation between attitude and subjective norm with Muslim customers' purchasing intention. Moreover, purchasing intention shows a strong relationship with purchasing behavior. Consequently, attitude, subjective norm, and customers' intention are the critical factors that influence Muslim customers' behavior when purchasing halal-certified products in Indonesia.
The application of machine learning algorithms for assessing the maturity level of palm fruits as the prominent commodity in the Western-Southern Area of Aceh Syahputra, Rizki Agam; Widarta, Fajar Okta
Operations Excellence: Journal of Applied Industrial Engineering Vol. 16, No. 1, (2024): OE March 2024
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/oe.2024.v16.i1.102

Abstract

The potential of palm oil plantations in Aceh is substantial, with the province ranking eighth in Indonesia for palm oil cultivation. Aceh boasts a vast oil palm plantation area of 470.8 thousand hectares, comprising 44% of Aceh's total plantation land. Palm fruit quality directly impacts palm oil production, emphasizing the need for consistent maturity levels. To address this, computer algorithms, especially machine learning, have been applied. This study introduces the Self-Organizing Map (SOM) Algorithm for palm fruit maturity determination. SOM's reliability in capturing dataset topology offers a diverse classification process, revolutionizing palm fruit maturity detection and optimizing palm oil production. This study uses 40 dataset consisted of 20 mature and 20 unmature palm fruit image as the basis data which then converted into RGB and HSV value with Matlab engine. The result of the study indicates that the SOM algorithm is capable of classifying the maturity detection with 100% precision result. The SOM algorithm is synthesized in a Graphical User Interface that is capable of reading and classifying the input data into the output cluster.
Leveraging Machine Learning for Sentiment Analysis in Hotel Applications: A Comparative Study of Support Vector Machine and Random Forest Algorithms Suryadi, Suryadi; Syahputra , Dedek; Astrianda, Nica; Syahputra, Rizki Agam; Suhendra, Rivansyah
Brilliance: Research of Artificial Intelligence Vol. 4 No. 2 (2024): Brilliance: Research of Artificial Intelligence, Article Research November 2024
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v4i2.4877

Abstract

This research aims to conduct sentiment analysis on user reviews of hotel booking applications such as Trivago, Tiket, Booking, Traveloka, and Agoda, collected from the Google Play Store. The dataset used consists of 5,000 user reviews, with 80% of the data allocated for training and 20% for testing. Two algorithms applied in this study are Support Vector Machine (SVM) and Random Forest, with performance evaluation based on accuracy, precision, recall, and F1-score metrics. The test results show that the Random Forest algorithm delivers the best performance on the Trivago application with 94% accuracy, 94% precision, 100% recall, and a 97% F1-score. Random Forest proves to be more effective in handling diverse review data, while the Support Vector Machine (SVM) algorithm also produces good results in sentiment classification. This research contributes to the development of sentiment analysis based on user reviews, which can be utilized by app developers and hotel management to improve service quality and user experience.
Sentiment Analysis on Tabungan Perumahan Rakyat (TAPERA) Program by using Support Vector Machine (SVM) Syahputra, Rizki Agam; Arifin, Riski; ., Suryadi; Iqbal, Muhammad
Journal of Applied Informatics and Computing Vol. 8 No. 2 (2024): December 2024
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v8i2.8694

Abstract

This study aims to analyze public sentiment towards the Housing Savings Program (TAPERA) using the Support Vector Machine (SVM) algorithm. The dataset comprises 16,061 reviews about TAPERA which was gathered from web scrapping and YouTube API. The sentiment analysis results indicate that 99.8% of the reviews are negative, while only 0.2% are positive. The SVM model applied in this study achieved a very high accuracy rate of 99.81%. This indicates that the model is highly effective in classifying sentiments, particularly in identifying negative sentiments. The resulting confusion matrix shows the model's excellent performance in detecting negative sentiments, with no False Positives (FP) and a very high number of True Negatives (TN). However, the model exhibits weaknesses in detecting positive sentiments, as indicated by the presence of several False Negatives (FN) and the absence of True Positives (TP). The findings of this study suggest that the public generally holds a very negative view of the TAPERA program. This insight is crucial for program administrators to consider as they evaluate and improve the program based on negative feedback received from the public. Overall, this research provides important insights into public perceptions of TAPERA and underscores the need for better modeling for more representative sentiment analysis. These findings can serve as a basis for policymakers in designing more effective communication strategies and program improvements to increase public acceptance of TAPERA.
Structural Equation Modeling Analysis of Purchase Behavior of Halal Products Zuhri, Sarika; Ilyas, Ilyas; Erwan, Friesca; Syahputra, Rizki Agam; Sentia, Prima Denny; Noprita, Zikra
Indonesian Journal of Halal Research Vol. 5 No. 1 (2023): February
Publisher : UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/ijhar.v5i1.20170

Abstract

Indonesia is renowned for being home to the largest Islamic population globally, but the absence of a halal certification logo on products continues to be a cause for concern. For Muslim customers, their basic knowledge of halal ingredients written on the product is the only guide they can be relied on. Hence, it is crucial to understand the essential factors that influence their purchasing behavior regarding halal-certified products. This study uses the Theory of Planned Behavior (TPB) to examine Muslim customers' behavior, as a case study, in Banda Aceh. The TPB questionnaire, including attitude, subjective norm, perceived behavioral control, and purchase intention attributes, was distributed online to respondents in the Banda Aceh area using non-probability random sampling. Through Structural Equation Modeling (SEM) methodology and AMOS software, this research reveals a strong correlation between attitude and subjective norm with Muslim customers' purchasing intention. Moreover, purchasing intention shows a strong relationship with purchasing behavior. Consequently, attitude, subjective norm, and customers' intention are the critical factors that influence Muslim customers' behavior when purchasing halal-certified products in Indonesia.
Analysis of Factors Affecting Workforce Productivity in the Steel Tower Production Division of PT X Syahputra, Rizki Agam; Arifin, Riski; Pamungkas, Iing; Ridha, Arrazy Elba; Irawan, Risnadi; Nova, Nova
Jurnal Industri dan Inovasi (INVASI) Vol 2, No 2 (2025): Maret
Publisher : Universitas Teuku Umar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64670/invasi.v2i2.11774

Abstract

This study analyzes the impact of age, wages, work environment, working hours, and work experience on workforce productivity in the Steel Tower Production Division of PT X using multiple linear regression (SPSS 16). The analysis includes validity, reliability, multicollinearity, heteroscedasticity, and hypothesis testing. Results show no multicollinearity or heteroscedasticity issues. The R² value (0.545) indicates that 54.5% of productivity variance is explained by the independent variables, while 45.5% is influenced by other factors. However, F-test and T-test results indicate that none of the variables significantly affect productivity.This suggests that other factors, such as motivation or job satisfaction, may play a larger role. Future research should explore these aspects to gain deeper insights.
Sistem Dinamis sebagai Alat Analisis dan Pengambilan Keputusan di Indonesia: Literature Review Pamungkas, Iing; Akmal, Abdiel Khaleil; Irawan, Heri Tri; Syahputra, Rizki Agam; Ridha, Arrazy Elba; Zhaqiri, Hazdfi; Fadjrin, Sitti
Jurnal Industri dan Inovasi (INVASI) Vol 2, No 2 (2025): Maret
Publisher : Universitas Teuku Umar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64670/invasi.v2i2.11618

Abstract

This research aims to conduct a comprehensive literature review on the application of dynamic system simulation as a decision-making tool. This research is motivated by the complexity of modern problems that require appropriate analytical tools to support better decision-making. The method used in this research is a systematic literature review by following structured steps to ensure that this research is comprehensive and unbiased. The results of this study indicate that dynamic systems are powerful and relevant analytical tools across sectors. With its ability to model dynamic interactions and simulate future scenarios, dynamic systems can help stakeholders make better decisions and achieve more sustainable results in facing complex challenges in the modern era. This study also identifies several challenges in the application of dynamic system simulation, such as lack of awareness of its benefits, lack of expertise in building and analyzing simulation models, as well as limited in-depth research on its application in various contexts. Therefore, further research is needed to address these challenges and improve the application of dynamic system simulation in decision making.
Peningkatan Kompetensi Pengelola Website melalui Pelatihan Berbasis Andragogi di Lingkungan Perguruan Tinggi Syahputra, Rizki Agam; Rosalina, Dian; Maliza, Noer Octaviana; Kasmawati, Kasmawati; Safitriyawi, Roja; Lestari, Suci Ayu; Ulfah, Tya
Jurnal Pengabdian kepada Masyarakat Nusantara Vol. 6 No. 2 (2025): Jurnal Pengabdian kepada Masyarakat Nusantara Edisi April - Juni
Publisher : Lembaga Dongan Dosen

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Abstract

Pelatihan pengelolaan dan pengembangan website di Universitas Teuku Umar bertujuan untuk meningkatkan kompetensi para pengelola website di lingkungan fakultas dan unit kerja universitas. Dalam era digital ini, pengelolaan website yang efektif sangat penting untuk memastikan informasi yang disampaikan selalu up-to-date, menarik, dan mudah diakses oleh mahasiswa, dosen, serta masyarakat umum. Pelatihan ini melibatkan peserta dari berbagai fakultas dan unit kerja yang bertanggung jawab atas pengelolaan website, dengan tujuan untuk memastikan bahwa setiap bagian terkait memiliki keterampilan yang seragam dalam mengelola konten website. Materi pelatihan mencakup pengelolaan konten dan penggunaan sistem WordPress sebagai platform pengelolaan website yang fleksibel dan mudah digunakan. Pelatihan ini juga membahas pengelolaan warna dan konten sesuai dengan standar yang ditetapkan oleh masing-masing instansi. Hasil dari pelatihan menunjukkan bahwa peserta mampu mengatasi tantangan yang dihadapi dalam mengelola website, serta dapat langsung mempraktikkan pengetahuan yang diperoleh, seperti pengeditan konten dan pembaruan tampilan website. Keberhasilan pelatihan ini diharapkan dapat mendukung proses Re-Akreditasi dan peralihan status Universitas Teuku Umar menuju Badan Layanan Umum (BLU), serta memberikan kontribusi positif dalam meningkatkan kualitas pengelolaan website universitas di masa mendatang. Pelatihan ini diharapkan dapat dilanjutkan secara berkala untuk memperkuat kapasitas pengelola website dalam menghadapi perkembangan teknologi digital.