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All Journal Jurnal Teknologi Industri Pertanian Jurnal Bahana Manajemen Pendidikan Prosiding Seminas Competitive Advantage Explore: Jurnal Sistem Informasi dan Telematika (Telekomunikasi, Multimedia dan Informatika) Speed - Sentra Penelitian Engineering dan Edukasi Sinergi Jurnal Optimasi Sistem Industri Jurnal Edukasi dan Penelitian Informatika (JEPIN) Prosiding Semnastek Jurnal Ilmiah Teknik Industri Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Seminar Nasional Teknologi Informasi Komunikasi dan Industri Prosiding Seminar Nasional Pakar Jurnal ULTIMATICS QARDHUL HASAN: MEDIA PENGABDIAN KEPADA MASYARAKAT Abdimas Umtas : Jurnal Pengabdian kepada Masyarakat Jurnal Ilmiah Teknik Industri Abdimas Universal Jurnal Teknologi Informasi : Jurnal Keilmuan dan Aplikasi Bidang Teknik Informatika NUSANTARA: Jurnal Pengabdian Kepada Masyarakat Proceeding ISETH (International Summit on Science, Technology, and Humanity) Jurnal AKAL: Abdimas dan Kearifan Lokal JURNAL TEKNIK INDUSTRI JURNAL ABDI MASYARAKAT INDONESIA (JAMIN) Literasi: Jurnal Pengabdian Masyarakat dan Inovasi Intelmatics Jurnal Pengabdian Masyarakat dan aplikasi Teknologi Jurnal Informatika: Jurnal Pengembangan IT Jurnal Pengabdian Kepada Masyarakat Radisi
Dedy Sugiarto
Universitas Trisakti
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Mechanical Engineering Medicine & Pharmacology Public Health Social Sciences Transportation Other

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PERBANDINGAN KINERJA KLASIFIKASI SENTIMEN ULASAN PRODUK PEMBELIAN BERAS DI MARKETPLACE SHOPEE Dedy Sugiarto; Syandra Sari; Anung Barlianto Ariwibowo; Fitria Nabilah Putri; Dimmas Mulya; Tasya Aulia; Arviandri Naufal Zaki
Jurnal Teknologi Informasi: Jurnal Keilmuan dan Aplikasi Bidang Teknik Informatika Vol. 17 No. 1 (2023): Jurnal Teknologi Informasi : Jurnal Keilmuan dan Aplikasi Bidang Teknik Inform
Publisher : Universitas Palangka Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This study aims to compare the performance of product purchase sentiment classification in market place shopee using four classification algorithms, namely support vector machine (SVM), naïve bayes (NB), logistic regression (LR),  k-nearest neighbor (KNN) and associated with the feature extraction model used, namely term frequency - inverse document. frequency (TF-IDF) and bag of word (BOW).   Data collection was carried out by extracting rice product review data through the Shopee website using a web scraping technique which was then saved in the form of a file with CSV format. The number of product reviews obtained is 3531 reviews and after pre-processing through the elimination of duplicate reviews, there are 464 reviews with details 16.17% having a negative label (rating 1 or 2), 15.52% having a neutral label (rating 3), and 68.32% have a positive label (rating 4 or 5). The composition of the rankings shows that the data is not balanced. The experimental results show that the combination of LR with TF-IDF shows the best performance with an accuracy of 80%.
Risk Mitigation Strategy for Coal Transshipment Noufal Zhafira; Triwulandari Satitidjati Dewayana; Dedy Sugiarto
Jurnal Optimasi Sistem Industri Vol. 22 No. 1 (2023): Published in May 2023
Publisher : The Industrial Engineering Department of Engineering Faculty at Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/josi.v22.n1.p9-21.2023

Abstract

Coal transshipment necessitates efficient and prompt execution, devoid of any delays or work-related accidents. Numerous events during the transshipment process have the potential to disrupt operations and pose substantial risks. This research aims to examine the risks associated with coal transshipment by leveraging ISO 31000:2018 as the risk analysis framework. Additionally, it seeks to prioritize risk mitigation strategies employing the Techniques for Other Preferences by Similarity to Ideal Solutions (TOPSIS) methodology. Data collection for this study involved surveys and expert discussions to comprehensively analyze all risks by ISO 31000:2018 guidelines. The findings were then visualized through the use of a fishbone diagram, which facilitated the identification and understanding of the generated risks. The analysis revealed several threats that could impact the coal transshipment process. These major threats include natural disasters, equipment failures, shipping accidents, health risks for workers, fire hazards, operational delays, inefficient loading and unloading processes, and transportation accidents. The proposed mitigation strategies such as designing SOPs, developing emergency response plans, implementing safety measures, providing training, conducting risk assessments, and ensuring equipment maintenance, are academically supported and practical in their application. However, challenges such as financial constraints, resistance to change, and the dynamic nature of the process need to be overcome for effective implementation. Organizations can enhance safety and operational efficiency in coal transshipment by carefully managing resources, engaging stakeholders, and continuously evaluating and improving strategies. Overall, the proposed strategies offer a feasible and proactive means to mitigate threats and promote a safer and more efficient transshipment process.
Pengaruh Supply Chain Management Practices, Logistic Performance dan Human Resource Management terhadap Company Performance dengan Competitive Advantage sebagai Variabel Mediasi Wahyuni Wahyuni; Dedy Sugiarto
Jurnal Bahana Manajemen Pendidikan Vol 12, No 2 (2023): Volume 12 Nomor 2 Tahun 2023
Publisher : Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/jbmp.v12i2.124830

Abstract

Penelitian ini bertujuan untuk menginvestigasi pengaruh Praktek Manajemen Rantai Pasok (Supply Chain Management Practice), Kinerja Logistik (Logistic Performance), dan Manajemen Sumber Daya Manusia (Human Resource Management) terhadap Kinerja Perusahaan (Company Performance), dengan Keunggulan Bersaing (Competitive Advantage) sebagai variabel mediasi. Penelitian ini dilaksanakan di empat perusahaan rokok di Kabupaten Tulungagung. Sampel penelitian sebanyak 100 responden dipilih melalui teknik purposive sampling. Metode analisis yang diterapkan dalam penelitian ini adalah Partial Least Square - Structural Equation Modeling (PLS-SEM). Data dianalisis menggunakan perangkat lunak statistik khusus untuk PLS-SEM. Hasil analisis menunjukkan bahwa keunggulan bersaing memainkan peran signifikan sebagai variabel mediasi antara praktek manajemen rantai pasok dan kinerja perusahaan. Namun, dalam konteks pengaruh rantai pasok manajemen terhadap kinerja perusahaan, keunggulan bersaing tidak memiliki peran mediasi yang signifikan. Penelitian ini memberikan kontribusi dalam pemahaman tentang hubungan kompleks antara praktek manajemen rantai pasok, kinerja logistik, manajemen sumber daya manusia, keunggulan bersaing, dan kinerja perusahaan. Implikasi manajerial dari penelitian ini dapat membantu perusahaan dalam merencanakan strategi yang lebih efektif untuk meningkatkan kinerja mereka dengan memanfaatkan faktor-faktor yang terlibat dalam perusakan nilai perusahaan
Perolehan Informasi Kembali (Information Retrieval/IR) Menggunakan Topic Modelling untuk Dataset Tempo Wilda Anggriani; Syandra Sari; Anung B. Ariwibowo; Dedy Sugiarto
Intelmatics Vol. 1 No. 2 (2021): Juli - Desember
Publisher : Penerbitan Universitas Trisakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25105/itm.v1i2.5030

Abstract

In the era of technology as it is today, many technologies and information are growing. The presence of information technology makes it easy for everyone to find information. Usually people use search engines like Google, Yahoo, etc. to find information., many technologies and information are growing. The presence of information technology makes it easy for everyone to find information. Usually people use search engines like Google, Yahoo, etc. to find information.Search engines really help humans to get information. Usually the search engine is one example of information retrieval (Information Retrieval / IR). Documents that produced by search engines are relevant documents based on user requests.In this study, the author implemented the IR process to find relevant documents based on existing queries. The results will be compared with relevant documents from previous research using the same dataset, namely the Tempo dataset from 2000 to 2002. This can find out how far the performance of the method used in this research is based on previous research. The method used in this research is the doc2vec method.From the results obtained using the doc2vec model, the smaller the epoch on the doc2vec model, the smaller the results of the average percentage similarity between the relevant documents produced by the doc2vec model and the relevant documents beforehand. While the results of the percentage similarity average of the doc2vec model are based on the vector size which is after the vector size 30 the result is above 35%. Epoch which produces the highest percentage average is epoch 25 from epoch 25, 50, 75, and 100. Vector size that produces the highest average percentage similarity is vector size 40 from vector size 10, 20, 30, 40, 50, 60, 70, 80, 90, and 100. The highest results of the highest percentage similarity are generated by the doc2vec model that uses epoch 25 and vector size 40 is 41,930. In the era of technology as it is today, many technologies and information are growing. The presence of information technology makes it easy for everyone to find information. Usually people use search engines like Google, Yahoo, etc. to find information., many technologies and information are growing. The presence of information technology makes it easy for everyone to find information. Usually people use search engines like Google, Yahoo, etc. to find information.Search engines really help humans to get information. Usually the search engine is one example of information retrieval (Information Retrieval / IR). Documents that produced by search engines are relevant documents based on user requests.In this study, the author implemented the IR process to find relevant documents based on existing queries. The results will be compared with relevant documents from previous research using the same dataset, namely the Tempo dataset from 2000 to 2002. This can find out how far the performance of the method used in this research is based on previous research. The method used in this research is the doc2vec method.From the results obtained using the doc2vec model, the smaller the epoch on the doc2vec model, the smaller the results of the average percentage similarity between the relevant documents produced by the doc2vec model and the relevant documents beforehand. While the results of the percentage similarity average of the doc2vec model are based on the vector size which is after the vector size 30 the result is above 35%. Epoch which produces the highest percentage average is epoch 25 from epoch 25, 50, 75, and 100. Vector size that produces the highest average percentage similarity is vector size 40 from vector size 10, 20, 30, 40, 50, 60, 70, 80, 90, and 100. The highest results of the highest percentage similarity are generated by the doc2vec model that uses epoch 25 and vector size 40 is 41,930.
Ekstraksi Informasi Menggunakan Named Entity Recognition dan Pembuatan Association Rule Pada Dokumen Direktori Putusan Mahkamah Agung Republik Indonesia Muhammad Rizky Fadila Afgan; Syandra Sari; Anung B. Ariwibowo; Dedy Sugiarto
Intelmatics Vol. 2 No. 1 (2022): Januari-Juni
Publisher : Penerbitan Universitas Trisakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25105/itm.v2i1.5031

Abstract

Land is fundamental to the needs of human life. Humans carry out activities on the ground, so that they are obstructed from getting all human activities both directly and indirectly carried out on the ground. Land is a natural resource that is given by God Almighty to the Indonesian people as national wealth and is a means of meeting all life activities that are important for human life. In this case everyone must need land. Land is often used as a case by disputes, because of the limited area of landInvolved a lot of land The author will extract information in the Directory file Decision Mahkmah Agung is done to produce a named entity taken from the file. PDF extracted. In this study, the author uses the introduction of an entity named (NER Entity Recognition or NER). NER is used to retrieve named entities. After that the author uses the Association Rule to inform data in the form of graphs for analysis Land is fundamental to the needs of human life. Humans carry out activities on the ground, so that they are obstructed from getting all human activities both directly and indirectly carried out on the ground. Land is a natural resource that is given by God Almighty to the Indonesian people as national wealth and is a means of meeting all life activities that are important for human life. In this case everyone must need land. Land is often used as a case by disputes, because of the limited area of land                                Involved a lot of land The author will extract information in the Directory file Decision Mahkmah Agung is done to produce a named entity taken from the file. PDF extracted. In this study, the author uses the introduction of an entity named (NER Entity Recognition or NER). NER is used to retrieve named entities. After that the author uses the Association Rule to inform data in the form of graphs for analysis
Perancang Data Warehouse Dan Visualisasi Data Mutu Penerimaan Beras Nita Chairunnisa; Dedy Sugiarto; Teddy Siswanto
Intelmatics Vol. 2 No. 2 (2022): Juli-Desember
Publisher : Penerbitan Universitas Trisakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25105/itm.v2i2.5037

Abstract

Rice is a staple food consumed by a large portion of the Indonesian population. Each region has its own rice production so that it has different qualities.. Indonesia itself has specific standards for good quality rice. In order for rice can be distributed evenly throughout the archipelago, Indonesia has a rice management organization, one of which is PT Food Station Tjipinang Jaya. Rice from various suppliers must be recorded and checked for quality. Making a Data Warehouse needs to be implemented so that it is easily collected and analyzes the data received and can be used as a reference for decision making. To build a data warehouse can use Extract, Transform and Load (ETL) available in Pentaho Data Integration. Data that has been entered into the data warehouse can be visualized using Python to make further decisions.
Designing Data Warehouse For Forecast and Data Visualization of Sales Nutrition Products Jeany Fadhilah Agatha Siahaan; Dedy Sugiarto; Teddy Siswanto
Intelmatics Vol. 1 No. 2 (2021): Juli - Desember
Publisher : Penerbitan Universitas Trisakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25105/itm.v1i2.5235

Abstract

Sales data can be processed in such a way that it can become information that is used as material for analysis and consideration in making decisions. This study aims to visualize PT XYZ sales data for nutritious intake products and predict sales figures for 2018 and 2019. Data is obtained directly from PT XYZ by submitting a request for data withdrawal. Data on sales of nutritious beverage products for the last 5 years are processed using Pentaho tools with ETL method (extract, transform, load) then predicted sales figures for 2019 using R programming language with ARIMA and Holt-Winters methods after which data will be visualized using Powe BI so that the display of data presentation is more interesting and informative. To find out the compatibility in using the forecasting method, the writer will compare RSME numbers from both methods and use the method with the smallest RSME number.
Business Intelligence Design for Data Visualization and Drug Stock Forecasting Novenia Eka Warestika; Dedy Sugiarto; Teddy Siswanto
Intelmatics Vol. 1 No. 1 (2021): January
Publisher : Penerbitan Universitas Trisakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25105/itm.v1i1.7407

Abstract

Klinik Pratama is one form of service provided by the Ministry of Communication and Information of the Republic of Indonesia in protect employees from health disorders that could affect employee productivity. In its development, the clinic often finds problems, one of them is often a shortage or excess the drug stock on a running period. Therefore, it be required a design of an Business Intelligence that manages complex data into a data visualization forecasting of the future stock of drugs. Historical data processing of the drug is done with process of Extract, Transform and Load (ETL) using the Spoon Pentaho Data Integration tools. While the visualization of drug stock data and forecast results is done using Microsoft Power BI (Business Intelligence) tools and for forecasting is done with Artificial Neural Network method by RStudio tools. The results of forecasting the amount of stock out of drug samples using the Artificial Neural Network method obtained an MSE value of 67.72 and RMSE 8.22 which means that this forecast has a good ability with the resulting error rate is relatively small. From this research, the Klinik Pratama of the Ministry of Communication and Information can easily understand and analyze drug stock data and can support operational decision making The results of forecasting the amount of stock out of drug samples using the Artificial Neural Network method obtained an MSE value of 67.72 and RMSE 8.22 which means that this forecast has a good ability because the resulting error rate is relatively small. From this research, Klinik Pratama of the Ministry of Communication and Information can easily understand and analyze drug stock data and can support operational decision making The results of forecasting the amount of stock out of drug samples using the Artificial Neural Network method obtained an MSE value of 67.72 and RMSE 8.22 which means that this forecast has a good ability with the resulting error rate is relatively small. From this research, Klinik Pratama of the Ministry of Communication and Information can easily understand and analyze drug stock data and can support operational decision making.
Perancangan Business Intelligence Data Ketersediaan Obat di Puskesmas Curug Tangerang Mohamad Dimas Budisantoso; Dedy Sugiarto; Teddy Siswanto
Intelmatics Vol. 2 No. 1 (2022): Januari-Juni
Publisher : Penerbitan Universitas Trisakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25105/itm.v2i1.12451

Abstract

Puskesmas Curug merupakan layanan pusat kesehatan masyarakat yang berlokasi di kecamatan Curug, Kabupaten Tangerang. Sebagai tempat pelayanan kesehatan, maka diperlukan ketersediaan stok obat untuk menjamin proses pelayanan Kesehatan berjalan dengan baik terutama dalam mendapatkan obat di Puskesmas. Namun faktanya di puskesmas sering terjadi jumlah obat mengalami surplus dan defisit stok pada saat periode berjalan. Hal ini dapat memengaruhi kegiatan operasional pelayanan dalam mengelola stok obat-obatan. Maka dari itu, dibutuhkan perancangan Business Intelligence yang mengelola sebuah data kompleks menjadi data yang tervisualisasikan untuk proses peramalan stok obat di periode yang akan datang. Pengolahan data stok obat dsetiap periode dilakukan dengan Proses ETL (Extract, Transform, and Load) menggunakan tools Spoon Pentaho Data Integration. Sedangkan visualisasi data stok obat dari hasil peramalan menggunakan tools Microsoft Power BI dan R Studio, untuk peramalan digunakan metode ARIMA yang memiliki signifikansi kemampuan peramalan yang baik, sebab memiliki MAPE diangka <10%, dan 10 – 20%.
Pelatihan Penerapan Metode Statistika dan Integrasi Google Workspace untuk Visualisasi Data dengan Platform Google Data Studio di SMA Negeri 17 Jakarta Idriwal Mayusda; Elfira Febriani; Dedy Sugiarto; Ratna Mira Yojana
Abdimas Universal Vol. 5 No. 2 (2023): Oktober
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Balikpapan (LPPM UNIBA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36277/abdimasuniversal.v5i2.304

Abstract

Teaching and learning activities in schools aim not only to provide knowledge to students but also to open their minds so that they can give meaning to the knowledge they receive. SMA Negeri 17 Jakarta is one of the best public schools in DKI Jakarta province. Improving the quality of education is one of the focuses of SMA Negeri 17, evidenced by the transformation of the digital learning platform after the covid-19 pandemic. Aiming to support the development of Education at SMA Negeri 17, the Industrial Engineering Department of Trisakti University carried out Community Service Activities with the theme Training on the Application of Statistical Methods and Google Workplace Integration in Educational and Teaching Evaluation. PkM activities will be carried out with training on the Google Workspace platform and Google Data Studio, which are accessible statistical data processing applications belonging to the Google platform. This platform can be used by teachers at SMA Negeri 17 for various educational activities, both for the teaching process and for improving school management. The results of the training showed that the teachers' knowledge and skills increased by 96.67% from the previous 14.67%. This activity is expected to increase teachers' knowledge and abilities in using the Google Workspace for Education platform for statistical analysis in the form of data visualization using Google Data Studio tools.
Co-Authors A.A. Ketut Agung Cahyawan W Abdul Rochman Abdul Rochman Ahmad Zuhdi Ainul Yaqin Ainul Yaqin Aji Saputra Annisa Dewi Akbari, Annisa Dewi Anung B Ariwibowo Anung B. Aribowo Ariwibowo, Anung B Ariwibowo, Anung B. Arviandri Naufal Zaki Ashari, Krisna Aditama Azhar Rizki Zulma Betha Ariandini Binti Solihah Chani Anugerah Cicilia Puji Rahayu Dadan Umar Daihani Dadang Surjasa, Dadang Dara Mustika Dimmas Mulya Dita Mayasai Dorina Hetharia Dorina Hetharia Dorina Hetharia Elfira Febriani Ema Utami Emelia Sari Fajar Anzari Farhan Hashfi Febriana Lestari Firdasari, Elita Wahyu Fitria Nabilah Putri Gatot Budi Santoso Grace Listiani Gunawan, Muhamad Ichsan Gunawan, Muhammad Ichsan Habyba, Anik Nur Harahap, S.TP, M.Si, Elfira Febriani I Nyoman Kresna Ida Jubaedah Ida Jubaidah Idriwal Mayusda Ilham, Moch Ilham A Illah Sailah Indah Permata Sari Is Mardianto Is Mardianto Is Mardianto Is Mardianto, Is Iveline Anne Marie Iwan Purwanto Jeany Fadhilah Agatha Siahaan Jeany Fadhilah Agatha Siahaan Johnson Saragih Khoirun nisa Krisna Aditama Ashari Lukmanul Hakim Lukmanul Hakim M Syamsul Ma’arif Marimin , Martino Luis Mohamad Dimas Budisantoso Muhamad Ichsan Gunawan Muhamad Ichsan Gunawan Muhammad Hidayat Tullah Muhammad Rizky Fadila Afgan Nadia, Alya Shafa Nita Chairunnisa Noufal Zhafira Novenia Eka Warestika Nur Hadi Nurachman, Nurochman Nurlailah Badariah Octavianus, M Arya PUDJI ASTUTI Putri Shan Randy Andy Ratna Mira Yojana Ratna Shofiati Ratna Shofiati Reyhan Dwi Putra Reyhan Dwi Putra Rianti Dewi Sulamet-Ariobimo Ricky Saputera Ridho Rachmat Giffary Rina Fitriana Rina Fitriana, Rina S. Dewayana, Triwulandari Sari, Debby Kumala Sari, Syandra Setiawan, Ibnu Fajar Shan ASP, Putri Steven Sen Suharto Honggokusumo Sukardi Sukardi Syandra Sari Syandra Sari Syandra Sari Tamaulina Br Sembiring Tasya Aulia Teddy Siswanto Teddy Siswanto Teddy Siswanto Teddy Siswanto Teddy Siswanto, Teddy Tiena Gustina Amran Tiena Gustina Amran Titik Susilowati Titik Yusrini Triwulandari S Dewayana Triwulandari S. Dewayana Triwulandari Satitidjati Dewayana Viera Astry Wahyu Hidayat Wahyu Hidayat wahyuni wahyuni Wawan Kurniawan Wilda Anggriani Winnie Septiani Winnie Septiani Winnugroho Wiratman, Manfaluthy Hakim, Tiara Aninditha, Aru W. Sudoyo, Joedo Prihartono Winona, Aisyah Vasthi Yojana, Ratna Mira Yuli Kurnia Ningsih