Majalah Ilmiah Teknologi Elektro
Majalah Ilmiah Teknologi Elektro (MITE) is peer review journal, published twice a year by the Study Program of Magister Electrical Engineering, Faculty of Engineering, Universitas Udayana. This journal discusses the scientific works containing results of research in the field of electrical, include power systems, telecommunications, informatics, and electronics. Authors are expected to include original scientific papers in accordance with the scope of the discussion of this journal including all aspects of the theory and practice are used.
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<![CDATA[Analisa Penggunaan Bahan Bakar Bioetanol Dari Limbah Kertas Sebagai Bahan Bakar Genset ]]>
<![CDATA[Yoppy Hartantio]]>;
<![CDATA[Rukmi Sari Hartati]]>;
<![CDATA[I Nyoman Satya Kumara]]>
<![CDATA[ Jurnal Teknologi Elektro Vol 17 No 3 (2018): (September - Desember) Majalah Ilmiah Teknologi Elektro ]]>
Publisher : <![CDATA[Program Studi Magister Teknik Elektro Universitas Udayana ]]>
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DOI: 10.24843/MITE.2018.v17i03.P19
<![CDATA[The high fuel demand in Indonesia has resulted in an increase in the ratio of imported fuels and weakened domestic energy security. In response to this, biofuels (BBN) was developed, one of which was bioethanol. The raw material for making bioethanol can be from a variety of objects, but paper is the most easily obtained bioethanol raw material around us. PT Temprina Media Grafika a subsidiary of Jawa Pos Group produces waste paper every day. From the waste is processed into bioethanol and is used as a generator fuel. From 1 kg of paper waste obtained 30 ml of bioethanol with a concentration of 86%. By mixing bioethanol in gasoline, a mixture of fuels called E85, E60 and E35 is obtained. While pure RON 88 gasoline from Pertamina is called E10. Through testing on the generator set with a load of 600 watts and 900 watts, measurements of voltage, power, frequency, RPM and SOFC were obtained that all parameters decreased when using bioethanol mixed fuels.]]>
<![CDATA[UMKM (Usaha Mikro Kecil dan Mene Implementasi Layanan Cloud Computing Software As a Service Pada Usaha Mikro Kecil dan Menengah ]]>
<![CDATA[Rifky Lana Rahardian]]>;
<![CDATA[Linawati Linawati]]>;
<![CDATA[Made Sudarma]]>
<![CDATA[ Jurnal Teknologi Elektro Vol 17 No 3 (2018): (September - Desember) Majalah Ilmiah Teknologi Elektro ]]>
Publisher : <![CDATA[Program Studi Magister Teknik Elektro Universitas Udayana ]]>
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DOI: 10.24843/MITE.2018.v17i03.P10
<![CDATA[MSMEs (Micro and Small and Medium Enterprises) have an important role now in the ASEAN economy. 96% of companies in ASEAN are MSMEs. Although MSMEs have shown their role, they still face various obstacles and constraints such as lack of information, weak branding, promotion and infrastructure. The application of information technology will certainly make it easier for MSMEs to strengthen branding, business processing and enable cooperation with other parties to provide added value to MSMEs. The application of cloud computing or cloud computing is considered suitable for MSMEs that have limited resources in the form of capital, human resources (HR) and information technology infrastructure. Responding to the importance of the application of information technology to these MSMEs, the research aims to design and build systems that can facilitate MSMEs by utilizing cloud computing technology with SAAS (software as a service). The system has been tested by testing carried out using the blackbox method which is considered to be running optimally, functionally the system built can produce the output expected by the MSMEe participants. Usability testing to measure the level of satisfaction (user satisfaction) with the usability scale (SUS) system method is also felt necessary so that the system is designed and built according to user needs and satisfaction. With the results of the calculation of SUS 72.25 which means that it belongs to class B or above the average makes SAAS cloud computing services a system that can be accepted by MSMEs participants in supporting their business.]]>
<![CDATA[Penerapan Metode Analytical Hierarchy Process pada Rekomendasi Keputusan Pemilihan SIM Card Provider ]]>
<![CDATA[Gde Brahupadhya Subiksa]]>;
<![CDATA[Lie Jasa]]>
<![CDATA[ Jurnal Teknologi Elektro Vol 17 No 3 (2018): (September - Desember) Majalah Ilmiah Teknologi Elektro ]]>
Publisher : <![CDATA[Program Studi Magister Teknik Elektro Universitas Udayana ]]>
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DOI: 10.24843/MITE.2018.v17i03.P01
<![CDATA[Abstract—SIM card provider is the center of mobile telecommunication such as telephones, texting, Internet or Blackberry messenger. Lately, the SIM card business development is be marked more kinds of SIM card offered by the provider company with various brands, features and facilities. This causes consumers find it difficult to choose the SIM card that suits their needs such as the phone call need, texting need, Internet and Blackberry package, and bonus that the consumer wants. From the problems above, consumer need a decision support system that can gives SIM card recommendation which suits the consumer’s needs. The SIM card provider decision-making selection can be complex because of the multiple purposes of consumer. One of the tools that are suitable to use for SIM card sorting priority is Analytic Hierarchy Process (AHP) that is developed by Thomas L. Saaty. The final result from this thesis is a system of SIM card provider selection decision-making support which suits with the consumer’s needs. The system is tested with data collection by using questionnaire, which aims to obtain data that is more accurate about the usefulness of the system that has been created. Data collection are through the 30 respondents who tried the system from the user side and 5 respondents who filled out questionnaires from the administrator side. The results of the data collection and analysis of data collected declare that this system has its deficiency, especially the difficulty of priority weighting of both.]]>
<![CDATA[Pengenalan Dan Klasifikasi Citra Tekstil Tradisional Berbasis Web Menggunakan Deteksi Tepi Canny, Local Color Histogram Dan Co-Occurrence Matrix ]]>
<![CDATA[I Putu Gd Sukenada Andisana]]>;
<![CDATA[Made Sudarma]]>;
<![CDATA[I Made Oka Widyantara]]>
<![CDATA[ Jurnal Teknologi Elektro Vol 17 No 3 (2018): (September - Desember) Majalah Ilmiah Teknologi Elektro ]]>
Publisher : <![CDATA[Program Studi Magister Teknik Elektro Universitas Udayana ]]>
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DOI: 10.24843/MITE.2018.v17i03.P15
<![CDATA[the use of traditional Indonesian textile motifs is influenced by elements of nature, environment and culture that develop in the community. Materials, motifs and techniques for making traditional textiles are different from one region to another. The use of information technology in preservation and providing knowledge to the public can made in the form of software that can match the pattern of images or photos while performing traditional textile classifications. The input in this study is an image of a patterned texture. The software through the pattern recognition process will perform calculations and produce values ??that can be matched in the sample database that has previously been processed. The method used is the color feature extraction with the Local Color Histogram method, texture feature extraction with the Co-occurrence matrix method, and the extraction of shape features with the Canny Edge Detection method. Each feature extraction will produce a vector. The data used consisted of 10 textile groups namely endek bali, songket bali, tenun dayak, tenun ikat, sasirangan, kain besurek, ulos, sutera bugis, kain gringsing. Classification method by using K-Nearest Neighborhood (K-NN). The results of this study are the highest accuracy values ??for extraction of texture features and the lowest accuracy values ??for the combination of extraction of shape and color features.]]>
<![CDATA[Penerapan Metode Clustering Text Mining Untuk Pengelompokan Berita Pada Unstructured Textual Data ]]>
<![CDATA[Nyoman Gede Yudiarta]]>;
<![CDATA[Made Sudarma]]>;
<![CDATA[Wayan Gede Ariastina]]>
<![CDATA[ Jurnal Teknologi Elektro Vol 17 No 3 (2018): (September - Desember) Majalah Ilmiah Teknologi Elektro ]]>
Publisher : <![CDATA[Program Studi Magister Teknik Elektro Universitas Udayana ]]>
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DOI: 10.24843/MITE.2018.v17i03.P06
<![CDATA[Good governance was a government whose programs were known and beneficial to the people. In Bali Provincial Government which has duty in disseminating information is Bureau of Public Relations Regional Secretariat Bali through media owned. Because at the time of news input to the media in this case Public Relations Bureau website was not included causing the emergence of problems in the form of difficulty knowing the news, which news that goes into certain categories. Clustering was a method to solve the problem. One of the algorithms used in the Clustering method is the K-Means algorithm. This study focused on designing to classify news data into a category using K-Means. To process the documents obtained to make it easier in the process of clustering, was done by preprocess documents first. Document preparation consists of case folding, tokenization, filtering and stemming. Tf-Idf was done to pass the weighting of the terms obtained on the preprocessed documents. From the results of experiments conducted using different amounts of data that are 50, 100, 200, 300, 400, and 500 data obtained results that the K-Means algorithm applied to cluster news, able to work and provide a satisfactory accuracy, Precision average of 73.11% while Recall of 69.65% and Purity of 0.80 for all test data. When viewed the comparison of each test data, the test on 50 data has the highest average precision and recall rate of 76.92% for its precision and for its recall of 79.58% while for Purity its highest value is on testing 300 data that is equal to 0.83.]]>
<![CDATA[Komputasi Paralel Menggunakan Model Message Passing Pada SIM RS (Sistem Informasi Manajemen Rumah Sakit) ]]>
<![CDATA[I Putu Adi Pradnyana Wibawa]]>;
<![CDATA[IA Dwi Giriantari]]>;
<![CDATA[Made Sudarma]]>
<![CDATA[ Jurnal Teknologi Elektro Vol 17 No 3 (2018): (September - Desember) Majalah Ilmiah Teknologi Elektro ]]>
Publisher : <![CDATA[Program Studi Magister Teknik Elektro Universitas Udayana ]]>
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DOI: 10.24843/MITE.2018.v17i03.P20
<![CDATA[Semakin berkembangnya teknologi akan berdampak pada pertumbuhan data yang pesat hingga melampaui batas kemampuan database manajemen tools yang ada. Salah satu sistem yang memiliki jumlah dan jenis data yang cukup besar adalah SIM RS (Sistem Informasi Manajemen Rumah Sakit). HPC (High Performance Computing) merupakan metode untuk mengatasi permasalahan yang memiliki kompleksitas tinggi terkait dengan beban pekerjaan dan penggunaan banyak data. Salah satu teknik yang digunakan dalam metode HPC adalah Komputasi Paralel. Penelitian ini berfokus pada perancangan komputasi paralel menggunakan model message-passing pada proses pencarian data pasien pada SIM RS. Komputasi paralel didesain dengan cara membagi data atau pekerjaan (komputasi) ke sejumlah komputer/CPU (master dan slave). Konfigurasi komputasi paralel pada komputer/CPU master dan slave menggunakan tahapan pada metode Foster yaitu Partisi, Komunikasi, Aglomerasi dan Pemetaan. Pengujian akan dilakukan dengan membandingkan waktu pengolahan data pasien antara sekuensial dan paralel. Selain itu komputasi paralel dirancang akan diuji menggunakan perhitungan Speed Up dan Efisieinsi. Hasil perancangan dan pengujian komputasi paralel menggunakan model message-passing membuktikan bahwa waktu pengolahan data pasien menggunakan program paralel mampu lebih cepat dibandingkan pengolahan data menggunakan topologi jaringan sekuensial/1 komputer/CPU. Pada pengujian speed up menunjukan adanya peningkatan kecepatan sampai pada penggunaan komputasi paralel pada 3 komputer/CPU. Sedangkan pada pengujian efisiensi nilai efisiensi tertinggi terdapat pada penggunaan 2 dan 3 komputer/CPU. Terjadinya penurunan nilai speed up dan efisiensi diakibatkan oleh jumlah data yang tergolong sedikit apabila ditangani oleh komputasi paralel menggunakan 7 komputer/CPU. Jadi semakin banyak jumlah komputer/CPU yang dilibatkan dalam komputasi paralel pada saat melakukan pemrosesan/pengolahan data, tidak berbanding lurus dengan waktu yang dibutuhkan dalam pemrosesan/ pengolahan data tersebut. Hal ini dikarenakan sebuah pekerjaan pemrosesan/pengolahan data dalam hal jumlah data yang ditangani memiliki batas ideal jumlah komputer/CPU yang menangani pekerjaan tersebut.]]>
<![CDATA[Implementasi Algoritma C5.0 pada Penilaian Kinerja Pegawai Negeri Sipil ]]>
<![CDATA[Putu Wirya Kastawan]]>;
<![CDATA[Dewa Made Wiharta]]>;
<![CDATA[Made Sudarma]]>
<![CDATA[ Jurnal Teknologi Elektro Vol 17 No 3 (2018): (September - Desember) Majalah Ilmiah Teknologi Elektro ]]>
Publisher : <![CDATA[Program Studi Magister Teknik Elektro Universitas Udayana ]]>
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DOI: 10.24843/MITE.2018.v17i03.P11
<![CDATA[Employees become the spearhead of every Company, whether it is run the business on manufacture or service. The position and role of public government employees as an element of civil servant obligate them to provide fair public services. Refers to those facts, the performance of public government employees needs to be well managed. The algorithm C5.0 is one of the decision tree algorithm which can process the employees performance data become an input for decision-making. Based on evaluation result of 184 employees performance datas, there was a high accurracy data in level 96.08%. Due to that result, the algorithm system can be developed become e-performance system which can predict or giving an advice in order to decision-making processes whether for assigning promotion, ranking or giving performance allowances.]]>
<![CDATA[Kajian dan Evaluasi Sistem Suplai Energi Listrik PLTS dan PLTB di Kampus Teknik Elektro Universitas Udayana Bukit Jimbaran Bali ]]>
<![CDATA[Intan Aprilia Medina]]>;
<![CDATA[I.A.D Giriantari]]>;
<![CDATA[I.W Sukerayasa]]>
<![CDATA[ Jurnal Teknologi Elektro Vol 17 No 3 (2018): (September - Desember) Majalah Ilmiah Teknologi Elektro ]]>
Publisher : <![CDATA[Program Studi Magister Teknik Elektro Universitas Udayana ]]>
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DOI: 10.24843/MITE.2018.v17i03.P02
<![CDATA[Hibrid PLTS dan PLTB dapat mengatasi permintaan energi listrik, sehingga diperlukan adanya sebuah pembangkitan listrik dengan sistem hibrid (PLTH). Salah satu penerapan konsep pembangkitan listrik hibrid dengan sistem jaringan mikro berada di Program Studi Teknik Elektro Fakultas Teknik Universitas Udayana Bukit Jimbaran, Bali. PLTH ini merupakan proyek kolaborasi antara Universitas Udayana dan Kementerian ESDM. PLTH di Teknik Elektro Udayana membutuhkan kajian dan evaluasi dari sistem suplai energi dari pembangkitan tenaga listrik tersebut agar mengetahui performa PLTS dan PLTB gedung DH. Studi ini menggunakan software HOMER (Hybrid Optimization Model For Electric Renewable) free trial version. Telah dilakukan analisis performa yang menunjukkan PLTS dan PLTB gedung DH tidak mampu memenuhi beban listrik pada bulan September, Oktober serta November 2017. Kondisi real produksi energi listrik dari PLTS mencapai 26.750,83 kWh per tahunnya, sedangkan simulasi HOMER sebesar 35.956 kWh per tahun. Kondisi real produksi energi listrik dari PLTB mencapai 4555,78 kWh per tahunnya, sedangkan simulasi HOMER lebih besar sebesar 33521 kWh per tahun. Seluruh produksi energi listrik simulasi HOMER lebih besar dari kondisi real. Pengurangan energi listrik setelah adanya hibrid ini mencapai 31306,62 kWh per tahun atau sebesar 64 % dari total beban listrik.]]>
<![CDATA[Genetic K-Means Algorithms, ASSU Analisis Peningkatan Kompetensi Mahasiswa Menggunakan Model Pembelajaran ASSURE berbasis Project-Based Learning ]]>
<![CDATA[Asri Prameshwari]]>;
<![CDATA[Rukmi Sari Hartati]]>;
<![CDATA[Made Sudarma]]>
<![CDATA[ Jurnal Teknologi Elektro Vol 17 No 3 (2018): (September - Desember) Majalah Ilmiah Teknologi Elektro ]]>
Publisher : <![CDATA[Program Studi Magister Teknik Elektro Universitas Udayana ]]>
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DOI: 10.24843/MITE.2018.v17i03.P16
<![CDATA[Sistem pembelajaran yang telah diterapkan dan dikembangkan bertujuan untuk meningkatkan, menguasai, memahami, dan menerapkan materi belajar untuk kemudian dijadikan suatu kompetensi dasar. Penelitian ini menganalisa hasil peningkatan kompetensi mahasiswa dalam mata kuliah teknologi informasi di STIKes Wira Medika Bali pada jenjang S1 Keperawatan dengan menggunakan sistem pembelajaran ASSURE berbasis Project-Based Learning. Metode yang digunakan dalam pengelompokkan hasil peningkatan tersebut menggunakan Genetic K-Means Algorithms, Metode ini dipilih karena mempunyai kinerja lebih optimal dari K-Means sederhana. Algoritma ini yang menggunakan natural selections untuk opitimalisasi menentukan initial seeds. Penentuan jumlah cluster yang digunakan dalam penelitian ini sebanyak tiga cluster dengan kategori tinggi, sedang dan rendah. Hasil dari penelitian ini untuk kategori sedang meningkat dengan range 3,92% dan 14%, untuk kategori rendah meningkat 31,37% dan 74%, untuk kategori tinggi menurun 35,29% dan 60%.]]>
<![CDATA[Penentuan Target Pajak Kendaraan Bermotor Di Provinsi Bali Menggunakan ARIMA Dan Algoritma Genetik ]]>
<![CDATA[I Gusti Ngurah Rai Dharma Widhura]]>;
<![CDATA[Made Sudarma]]>;
<![CDATA[Ruksi Sari Hartati]]>
<![CDATA[ Jurnal Teknologi Elektro Vol 17 No 3 (2018): (September - Desember) Majalah Ilmiah Teknologi Elektro ]]>
Publisher : <![CDATA[Program Studi Magister Teknik Elektro Universitas Udayana ]]>
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DOI: 10.24843/MITE.2018.v17i03.P07
<![CDATA[Bali Regional Income Board is a regional organization tasked with determining the amount of local tax revenue target for the next fiscal year. Currently still done manually in accordance with existing upgrading trends from previous years. So it needs to be done in way that can be measured and accurate forecasting. In recent studies, it shows that forecasting by combining conventional and artificial intelligence (hybrid) methods results in better forecasting accuracy. By that reason, the writer tries to forecast the target of revenue from Motor Vehicle Tax (PKB and BBNKB), which contribute 70% to Bali Province income by combining ARIMA method and Genetic Algorithm. The data used consisted of five groups: yearly and new Vehicles that have linear data types, and as Reverse Names, Entrance Mutations and Output Mutations that have non-linear data types. Each data group consisted of PKB and BBNKB, where it’s monthly realization data from 2011 to 2016 used to be training data and realization data for 2017 as test data. The Combined forecasting mechanism is performed using ARIMA to forecast linear data and using Genetic Algorithms for non-linear data. As a benchmark for combined forecasting using ARIMA and Genetic Algorithms, forecasting using ARIMA and Genetic Algorithms independently is used for all data types (linear and nonlinear). Testing is done by comparing data of forecasting result with that 3 different methods for year 2017 with data realization year 2017. Then the error percentage is counted using MAPE. From the test results obtained for ARIMA MAPE value of 3.63, Genetic Algorithm 4.72 and combined ARIMA and Genetic Algorithm of 1.13. Thus, the result of forecasting with combination ARIMA and Genetic Algorithm have the best result and then used to forecasting target of PKB for 2018 and so on]]>
