Articles
<![CDATA[ANALISIS DATA GANGGUAN KERUSAKAN MESIN PRODUKSI MENGGUNAKAN TEKNIK ASSOCIATION RULES ]]>
<![CDATA[Iveline Anne Marie]]>;
<![CDATA[Lukmanul Hakim]]>;
<![CDATA[Dedy Sugiarto]]>;
<![CDATA[Winnie Septiani]]>
<![CDATA[ Jurnal Ilmiah Teknik Industri Vol 7, No 1 (2019): Jurnal Ilmiah Teknik Industri (Jurnal Keilmuan Teknik dan Manajemen Industri ) ]]>
Publisher : <![CDATA[Program Studi Teknik Industri, Fakultas Teknik Universitas Tarumanagara ]]>
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DOI: 10.24912/jitiuntar.v7i1.5035
<![CDATA[Association rules merupakan salah satu teknik data mining yang digunakan untuk menentukan korelasi dari sebuah dataset terkait keputusan yang akan diambil. PT Z adalah perusahaan penghasil komponen otomotif yaitu battery untuk kendaraan bermotor. Gangguan kerusakan mesin produksi pada perusahaan mempengaruhi tercapainya Key Performance Indicator (KPI) Divisi Perawatan pada PT Z. Penelitian ini bertujuan untuk mendapatkan hasil pemetaan dan analisis gangguan kerusakan mesin yang terjadi dengan menggunakan teknik Association Rules sehingga dapat diberikan rekomendasi kegiatan pengendalikan gangguan kerusakan untuk divisi Maintenance. Tahapan penelitian dimulai dengan melakukan kegiatan pengumpulan data kerusakan mesin. Berdasarkan data yang diperoleh dilakukan pengkategorian untuk variabel analisis terpilih. Berikutnya data yang diperoleh akan diolah dengan menggunakan teknik Association Rule untuk melihat pola yang terjadi dengan bantuan packages arules software R. Hasil analisis menunjukkan bahwa terdapat hubungan yang kuat antara kerusakan pada shift 2 untuk jenis kerusakan mekanik, serta kerusakan pada shift 3 dengan lama perbaikan sedang dan tingkat resiko yang tinggi memiliki peluang kejadian yang lebih tinggi jika dibandingkan kejadian lainnya. Perusahaan sebaiknya menyediakan kebutuhan staf mekanik, peralatan dan suku cadang yang memadai pada shift 2 dan shift 3 sehingga dapat meminimasi durasi perbaikan mesin dan mencapai target KPI divisi Maintenance.]]>
<![CDATA[Perbandingan Peramalan Harga Beras Menggunakan Metode ARIMA pada Amazon Forecast dan Sagemaker ]]>
<![CDATA[Is Mardianto]]>;
<![CDATA[Muhamad Ichsan Gunawan]]>;
<![CDATA[Dedy Sugiarto]]>;
<![CDATA[Abdul Rochman]]>
<![CDATA[ Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 4 No 3 (2020): Juni 2020 ]]>
Publisher : <![CDATA[Ikatan Ahli Informatika Indonesia (IAII) ]]>
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DOI: 10.29207/resti.v4i3.1902
<![CDATA[Rice is one of the main commodities of trade in Indonesia. PT Food Station as the management company of Cipinang Rice Main Market every day publishes data on price, type of rice and the amount of rice that enters and exits Jakarta area. This study aims to forecast rice prices in the Jakarta area using data held by PT FoodStation during the 2016-2018 data period. Rice price prediction is carried out for the next 30 days using the Auto Regressive Integrated Moving Average (ARIMA) method on the Amazon Forecast and Amazon Sagemaker platforms. The ARIMA model is a form of regression analysis that measures the strength of one dependent variable that is relatively influential on other change variables. The ARIMA model is a special type of regression model in which the dependent variable is considered stationary and the independent variable is the lag or previous value of the dependent variable itself and the error lag. ARIMA is a combination of auto-regressive and moving average processes. The final result obtained in this experiment is that the ARIMA model on Amazon Sagemaker cloud computing is superior when compared to Amazon Forecast. From the experimental results obtained the results of Amazon Sagemaker RMSE (313.379941) are smaller than Amazon Forecast (322.4118029). So it can be concluded that the ARIMA model run at Amazon Sagemaker is more accurate than Amazon Forecast for forecasting the price of rice for 30 days at the Cipinang Rice Main Market]]>
<![CDATA[Uji Validasi Algoritme Self-Organizing Map (SOM) dan K-Means untuk Pengelompokan Pegawai ]]>
<![CDATA[Titik Susilowati]]>;
<![CDATA[Dedy Sugiarto]]>;
<![CDATA[Is Mardianto]]>
<![CDATA[ Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 4 No 6 (2020): Desember 2020 ]]>
Publisher : <![CDATA[Ikatan Ahli Informatika Indonesia (IAII) ]]>
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DOI: 10.29207/resti.v4i6.2492
<![CDATA[Managing employee work discipline needs to be done to support the development of an organization. One way to make it easier to manage employee work discipline is to group employees based on their level of discipline. This study aims to group employees based on their level of discipline using the Self Organizing Map (SOM) and K-Means algorithm. This grouping begins with collecting employee attendance data, then processing attendance data where one of them is determining the parameters to be used, then ending by implementing the clustering algorithm using the SOM and K-Means algorithms. The results of grouping that have been obtained from the implementation of the SOM and K-Means algorithms are then validated using an internal validation test consisting of the Dunn Index, the Silhouette Index and the Connectivity Index to obtain the best number of clusters and algorithms. The results of the validation test obtained 3 best clusters for the level of discipline, namely the disciplinary cluster, the moderate cluster and the undisciplined cluster.]]>
<![CDATA[Product Quality Improvement Through Training on Tempeh Packaging at PRIMKOPTI SWAKERTA Semanan ]]>
<![CDATA[Anik Nur Habyba]]>;
<![CDATA[Indah Permata Sari]]>;
<![CDATA[Dorina Hetharia]]>;
<![CDATA[Dedy Sugiarto]]>
<![CDATA[ ABDIMAS: Jurnal Pengabdian Masyarakat Vol. 4 No. 2 (2021): ABDIMAS UMTAS: Jurnal Pengabdian Kepada Masyarakat ]]>
Publisher : <![CDATA[LPPM Universitas Muhammadiyah Tasikmalaya ]]>
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DOI: 10.35568/abdimas.v4i2.1466
<![CDATA[Packaging is the first thing seen in a product and today many companies are focused on developing product packaging designs to compete in the market. The improvements in the type and design of packaging can be done PRIMKOPTI SWAKERTA Semanan to maintain customer loyalty. The purpose of this dedication is to provide knowledge of more environmentally friendly packaging alternatives to support the sustainable development of the tempeh industry and its processing in Semanan. Devotional activities begin with an introductory survey and then continue with training conducted online with the devotional team and tempeh craftsmen. The delivery of several training materials was done in parallel related to quality improvement, some of these materials such as the application of Good Manufacturing Practice, maintenance of production machines and food packaging. The survey results showed that 66.7 % of craftsmen use clear plastic with a simple design and some do not even use labels. The remaining 33.3 % of tempeh craftsmen use a combination of aluminium foil and plastic packaging. Alternative solutions are provided in improving the quality of tempeh products through banana leaf packaging. Banana leaves help the process of fermentation on tempeh and also increase consumer interest in buying because it is preferred. Kraft paper packaging is recommended for use because it can reduce the risk of rancidity on tempeh chips and extend the shelf life. Semanan tempeh makers can use this food packaging alternative to attract back consumers' interest that decreased during the pandemic.]]>
<![CDATA[PERANCANGAN KNOWLEDGE MANAGEMENT SOLUTION UNTUK UKM MAKANAN ]]>
<![CDATA[Titik Yusrini]]>;
<![CDATA[Dedy Sugiarto]]>;
<![CDATA[Gatot Budi Santoso]]>
<![CDATA[ Prosiding Seminar Nasional Pakar Prosiding Seminar Nasional Pakar 2019 Buku I ]]>
Publisher : <![CDATA[Lembaga Penelitian Universitas Trisakti ]]>
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DOI: 10.25105/pakar.v0i0.4142
<![CDATA[UKM Makanan Aneka Kue adalah salah satu UKM yang terdapat di daerah Pegadungan, Jakarta Barat. Di ukm ini terdapat pengetahuan yang belum di dokumentasikan yang dapat memicu hilangnya pengetahuan apabila ukm tidak memiliki knowledge management solution. Untuk itu Knowledge ini harus dikelola (managed) karena harus direncanakan dan diimplementasikan. Untuk mengelola pengetahuan dibutuhkan knowledge management yang meliputi knowledge capture, knowledge organizing, knowledge distribution dan knowledge sharing. Tujuan dari penelitian ini yaitu mendapatkan rancangan Knowledge Management Solution berupa sistem pakar yang dapat digunakan oleh UKM Makanan. Metode yang digunakan dengan melakukan penilaian kebutuhan dengan cara melakukan wawancara seputar informasi mengenai unit kerja operasional serta penyebaran kuisioner kepada karyawan dengan mengajukan beberapa pernyataan berdasarkan kategori pengetahuan, analisis kebutuhan dan analisis sistem, desain dan implementasi.]]>
<![CDATA[Peramalan harga beras IR64 kualitas III menggunakan metode Multi Layer Perceptron, Holt-Winters dan Auto Regressive Integrated Moving Average ]]>
<![CDATA[Anung B. Aribowo]]>;
<![CDATA[Dedy Sugiarto]]>;
<![CDATA[Iveline Anne Marie]]>;
<![CDATA[Jeany Fadhilah Agatha Siahaan]]>
<![CDATA[ Ultimatics : Jurnal Teknik Informatika Vol 11 No 2 (2019): Ultimatics : Jurnal Teknik Informatika ]]>
Publisher : <![CDATA[Faculty of Engineering and Informatics, Universitas Multimedia Nusantara ]]>
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DOI: 10.31937/ti.v11i2.1246
<![CDATA[This paper aims to present the analysis of price movements of IR64 quality III at the Cipinang Rice Main Market (PIBC) and the accuracy comparison of forecasting using Multi Layer Perceptron (MLP), Holt-Winters, and Auto Reggressive Integrated Moving Average (ARIMA) method. The data are daily price from 1 January 2016 to 31 May 2018 sourced from PT. Food Station. The analysis shows that the price of IR64 quality III rice tends to rise towards the end of 2016 and 2017. This is related to the decrease in the level of rice supply by January each year which encourages PT Food Station to conduct market operations to control the price of rice in the market. The results of accuracy comparison show that the MLP produces a value of Root Mean Square Error (RMSE) of 5,67, Holt-Winters exponential smoothing with trend and additive seasonal component produces a value RMSE of 70.71 and ARIMA method with parameters (1,1,2) resulted in RMSE values of 58.71. The RMSE values of the MLP method have smaller values than the Holt Winter and ARIMA methods which indicate that the MLP method is more accurate]]>
<![CDATA[Komparasi Metode Multilayer Perceptron (MLP) dan Long Short Term Memory (LSTM) dalam Peramalan Harga Beras ]]>
<![CDATA[Steven Sen]]>;
<![CDATA[Dedy Sugiarto]]>;
<![CDATA[Abdul Rochman]]>
<![CDATA[ Ultimatics : Jurnal Teknik Informatika Vol 12 No 1 (2020): Ultimatics : Jurnal Teknik Informatika ]]>
Publisher : <![CDATA[Faculty of Engineering and Informatics, Universitas Multimedia Nusantara ]]>
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DOI: 10.31937/ti.v12i1.1572
<![CDATA[Rice is one of the main commodities in Indonesian society. The main problem with rice nationally is inflation of rice prices. Therefore, this research predicts the price of rice using Multilayer Perceptron (MLP) artificial neural network architecture and deep learning: Long Short Term Memory (LSTM) to anticipate these problems. The data used in this study are real data on rice prices during 2016 - 2019 obtained from PT. Food Station. The total dataset is 1307 with the distribution of 1123 as data train and 184 as test data. The final results obtained in this study are LSTM superior to MLP, with the value of Root Mean Square Error (RMSE) training data: 0.49 RMSE loss value of test data is 0.27. The most optimal LSTM model from 3 tests was carried out, namely the number of hidden layers = 16 and epochs = 150 times.]]>
<![CDATA[Peramalan Utilisasi Perangkat Jaringan dan Bandwidth Dengan Metode Holt-Winters dan Multi Layer Perceptron ]]>
<![CDATA[Muhammad Taufiq]]>;
<![CDATA[Dedy Sugiarto]]>;
<![CDATA[Abdul Rochman]]>
<![CDATA[ Ultimatics : Jurnal Teknik Informatika Vol 12 No 1 (2020): Ultimatics : Jurnal Teknik Informatika ]]>
Publisher : <![CDATA[Faculty of Engineering and Informatics, Universitas Multimedia Nusantara ]]>
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DOI: 10.31937/ti.v12i1.1575
<![CDATA[Network devices become an important medium for transferring data from one node to another node in the form of switches, routers or network security devices. The reliability of network devices must be maintained both in terms of device resources and bandwidth. The study was conducted by applying the Holt-Winters and Multi Layer Perceptron (MLP) method to network device and bandwidth data utilization. The two methods are compared to assess which accuracy is better when applied to network device and bandwidth utilization data by calculating Root Mean Squared Error (RMSE) and Mean Absolute Percentage (MAPE). The results of the measurement of accuracy in the network device testing data, MLP produces a value of RMSE of 5,67 and MAPE of 2.34, and Holt-Winters produces a value of RMSE of 14.56 and MAPE of 2.95. For the results of the measurement of accuracy in the bandwidth testing data with MLP produces a value of RMSE of 0.13 and MAPE of 7.27, and Holt-Winters produces RMSE values of 2.59 and MAPE of 134.31. Based on the results of these measurements it is concluded that the MLP method has a smaller error value compared to the Holt-Winters method applied to network device and bandwidth utilization data with a span of 3 years historical data.]]>
<![CDATA[The Elastic Stack Ability Test To Monitor Slowloris Attack on Digital Ocean Server ]]>
<![CDATA[Is Mardianto]]>;
<![CDATA[Dedy Sugiarto]]>;
<![CDATA[Krisna Aditama Ashari]]>
<![CDATA[ Ultimatics : Jurnal Teknik Informatika Vol 13 No 2 (2021): Ultimatics : Jurnal Teknik Informatika ]]>
Publisher : <![CDATA[Faculty of Engineering and Informatics, Universitas Multimedia Nusantara ]]>
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DOI: 10.31937/ti.v13i2.2209
<![CDATA[Servers have a central role in computer network. The server is in charge of serving user requests with various types of services. Every server activity in handling these things will generate different types of logs. Information from this large amount of logs is often ignored and has not been widely used as material for analyzing the performance of the server itself. In this study, Elastic Stack is functioned as a system that handles upstream to downstream processes starting from collection, transformation, and storage as well as graphical visualization of the Nginx web server given an attack scenario in the form of massive incoming connection requests and server login access attempts. The Elastic Stack components used as log collectors are Filebeat and Metricbeat for system metric data. For testing attacks using the Slowloris tool which will consume web server resources. The results of the research that have been carried out are when there are 500 incoming connections, the web server can serve requests normally, at 1000 connections there are some packets that are not served, the server becomes unable to access when it reaches a total of 2000 incoming connections. Metric data in the form of CPU Usage and Memory Usage are affected, although not significantly. Identification of IP Address shows the source of the attack comes from Singapore, according to the domicile of the attacker's computer. All access data in the form of username, time, origin of region trying to enter the server are recorded by the system.]]>
<![CDATA[Usulan Penentuan Waktu Garansi Perakitan Alat Medis Examination Lamp di PT. Tesena Inovindo ]]>
<![CDATA[Johnson Saragih]]>;
<![CDATA[Dedy Sugiarto]]>;
<![CDATA[Grace Listiani]]>
<![CDATA[ Seminar Nasional Teknologi Informasi Komunikasi dan Industri 2016: SNTIKI 8 ]]>
Publisher : <![CDATA[UIN Sultan Syarif Kasim Riau ]]>
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<![CDATA[Tujuan dari penelitian ini adalah untuk menentukan waktu garansi yang optimal produk Examination Lamp.Seperti yang kita ketahui waktu garansi adalah suatu cara yang diberikan produsen ke konsumen untuk menjamin kualitas dari produk yang ditawarkan.Semakin lama waktu garansi yang ditawarkan kepada konsumen akan memberikan sinyal bahwa produk tersebut semakin berkualitas.PT Tesena Inovindo adalah sebuah perusahaan yang bergerak dibidang perakitan alat alat medis,yaitu inkubator,infant warmer,examination lamp,hospital bed dan lain sebagai-nya.Selama ini kebijakan yang diterapkan oleh perusahaan untuk waktu garansi adalah selama 12 bulan, padahal waktu garansi seharusnya diberikan bedasarkan tingkat keandalan suatu produk.Oleh karena itu perlu dilakukan evaluasi terhadap waktu garansi yang telah diberikan perusahaan selama ini.Kebijakan garansi yang digunakan dalam penelitian ini adalah menggunakan model Jun Bai dan Hoang Pham dan berdasarkan pengolahan data yang telah dilakukan diperoleh total biaya penghematan sebesar 47,05 % bila dibandingkan dengan total biaya garansi yang telah dikeluarkan oleh perusahaan.Kata kunci: examinition lamp, model jun bai dan hoang pham, waktu garansi]]>
