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Jurnal EECCIS
Published by Universitas Brawijaya
ISSN : 19783345     EISSN : 24608122     DOI : -
Core Subject : Engineering,
Engineering
EECCIS is a scientific journal published every six month by electrical Department faculty of Engineering Brawijaya University. The Journal itself is specialized, i.e. the topics of articles cover electrical power, electronics, control, telecommunication, informatics and system engineering. The languages used in this journal are Bahasa Indonesia and English.
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Articles 9 Documents
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Search results for , issue "Vol. 14 No. 1 (2020)" : 9 Documents clear
Perbandingan Metode Cost Sensitive pada Decision Tree dan Naïve Bayes untuk Klasifikasi Data Multiclass M Aldiki Febriantono; Sholeh Hadi Pramono; Rahmadwati Rahmadwati
Jurnal EECCIS (Electrics, Electronics, Communications, Controls, Informatics, Systems) Vol. 14 No. 1 (2020)
Publisher : Fakultas Teknik, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/jeeccis.v14i1.625

Abstract

Abstrak– Knowledge discovery is the method of extracting information from data in making informed decisions. Seeing as classifiers do have a lot of learning patterns in the data, testing an imbalanced dataset becomes a major classification issue. The cost-sensitive approach on the decision tree C4.5 and nave Bayes is used to solve the rule of misclassification. The glass, lympografi, vehicle, thyroid, and wine datasets were collected from the UCI Repository and included in this analysis. Preprocessing attribute selection with particle swarm optimization was used to process the data collection. Besides, the cost-sensitive decision tree C4.5  and the cost-sensitive naive Bayes method were used in the research. On the glass, lympografi, vehicle, thyroid, and wine datasets, the accuracy of the test results was 72.34 %, 68.22 %, 75.68 %, 93.82 %, and 93.95 %, respectively, using the cost-sensitive decision tree C4.5. While the cost-sensitive naive Bayes method outperforms the others by 32.24 %, 82.61 %, 25.53 %, 97.67 %, and 94.94 % on the dataset, respectively.
Evaluation of Implementation Context Based Clustering In Fuzzy Geographically Weighted Clustering-Particle Swarm Optimization Algorithm Siti Nurmardia Abdussamad; Suci Astutik; Achmad Effendi
Jurnal EECCIS (Electrics, Electronics, Communications, Controls, Informatics, Systems) Vol. 14 No. 1 (2020)
Publisher : Fakultas Teknik, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/jeeccis.v14i1.609

Abstract

This paper contains an evaluation of the implementation Context Based Clustering method into Fuzzy Geographically Weighted Clustering-Particle Swarm Optimization (FGWC-PSO) algorithm on 11 variable from data factors causing the spread of dengue in East Java. Integration of Particle Swarm Optimization as a metaheuristic algorithm makes the computation run longer so, the solution in this paper is FGWC-PSO will be combined with context based clustering to produce a hybrid method (CFGWC-PSO) which can shorten the computational time of the clustering algorithm. Context based clustering in this paper will use 3 ways, namely by using random values, using Fuzzy C-Means (FCM), and using mean and standard deviations. CFGWC-PSO algorithm using number of clusters = 2 and CFGWC-PSO will be evaluated using IFV index, based on processing results found that the best clustering algorithm is CFGWC-PSO using FCM
Sistem Deteksi Cuaca Berdasarkan Analisis Histogram HCL Menggunakan Algoritma k-Nearest Neighbor ( KNN ) Siti Hariani
Jurnal EECCIS (Electrics, Electronics, Communications, Controls, Informatics, Systems) Vol. 14 No. 1 (2020)
Publisher : Fakultas Teknik, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/jeeccis.v14i1.626

Abstract

Abstrak - Belakangan ini cuaca ekstrim yang berubah – ubah yang tidak dapat ditebak sering terjadi yang mengganggu aktivitas sehari  - hari. Untuk itu diperlukan suatu sistem yang dapat mendeteksi kondisi cuaca berdasarkan citra awan.  Oleh Karena penulis pada penelitian ini akan membuat sistem pendeteksi kondisi cuaca berdasarkan citra awan. Pada sistem ini, penulis akan melakukan penelitian dengan melalui video digital yang direkam menggunakan Handphone yang di lengkpai dngan fiture perekam video untuk mendaptkan citra pada awan. Penulis akan melakukan perekaman kondisi cuaca awan sekitar dalam waktu yang singkat hanya dalam  jangka waktu 5 menit. Setelah itu video yang telah direkam akan diekstraksi ciri dengan metode histogram warna terhadap citra awan yang telah ditangkap oleh Camera vido digital. Kemudian dilakukan proses klasifikasi menggunakan algoritma k-Nearest Neighbor. Algoritma klasifikasi yang digunakan dalam tugas akhir ini adalah k-Nearest Neighbor, yang diharapkan mampu untuk mengenali citra awan dan mengklasifikasi kondisi cuaca. Berdasarkan pengujian yang dilakukan, sistem menghasilkan tingkat akurasi sebesar 84,21%. Kondisi cuaca yang diprediksi adalah kondisi cerah berawan, berawan, hujan, malam cerah dan malam hujan.
Implementation of Support Vector Machine - Recursive Feature Elimination for MicroRNA Selection in Breast Cancer Classification Ratih Permatasari; Adi Wibowo
Jurnal EECCIS (Electrics, Electronics, Communications, Controls, Informatics, Systems) Vol. 14 No. 1 (2020)
Publisher : Fakultas Teknik, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/jeeccis.v14i1.602

Abstract

Breast cancer is the most frequent cancer caused death among women. An attempt to reduce death cases caused by breast cancer, was to detect cancer cells when it still in early stage. MicroRNA is one of the biomarker for cancer that can be used to detect cancer cell even in its early stage. However, MicroRNA data tends to have thousand types of expression which required a lot of costs if it examined one by one thoroughly. Feature selection method can be used to extract important MicroRNAs that support clasification process between normal people and people with breast cancer. Support Vector Recursive Feature Elimination (SVM-RFE) is one of the feature selection method that can be used to select MicroRNA data. This research aims to produce the best smallest subset that contains selected MicroRNA expressions using the SVM-RFE as feature selection method. This experiment result showed that the best selected subset was able to provide 99% classification accuracy with only 3 MicroRNA expressions, where 2 from 3 selected MicroRNA hold potential as a biomarker of breast cancer.
Cover Jurnal EECCIS Vol 14 No.1 April 2020 Editor Jurnal
Jurnal EECCIS (Electrics, Electronics, Communications, Controls, Informatics, Systems) Vol. 14 No. 1 (2020)
Publisher : Fakultas Teknik, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/jeeccis.v14i1.676

Abstract

Daftar Isi Jurnal EECCIS Vol.14 No.1 IMPLEMENTATION OF SUPPORT VECTOR MACHINE - RECURSIVE FEATURE ELIMINATION FOR MICRORNA SELECTION IN BREAST CANCER CLASSIFICATIONRatih Permatasari (pp. 1-5)PRAKIRAAN KEBUTUHAN ENERGI LISTRIK DENGAN JARINGAN SARAF TIRUAN (ARTIFICIAL NEURAL NETWORK) METODE BACKPROPAGATION TAHUN 2020-2025Diah Setyowati (pp. 6-9)EVALUATION OF IMPLEMENTATION CONTEXT BASED CLUSTERING IN FUZZY GEOGRAPHICALLY WEIGHTED CLUSTERING-PARTICLE SWARM OPTIMIZATION ALGORITHMSiti Nurmardia Abdussamad (pp. 10-15)FILTER BAND PASS FREKUENSI RADIO FM DENGAN METODE M-DERIVEDKoes Koes Janto (pp. 16-20)PERBANDINGAN METODE COST SENSITIVE PADA DECISION TREE DAN NAÏVE BAYES UNTUK KLASIFIKASI DATA MULTICLASSM Aldiki Febriantono (pp. 21-26)SISTEM DETEKSI CUACA BERDASARKAN ANALISIS HISTOGRAM HCL MENGGUNAKAN ALGORITMA K-NEAREST NEIGHBOR ( KNN )Siti Hariani (pp. 27-30)NAIVE BAYES METHOD TO ANALYZE SENTIMENT ACCURACY ON YOUTUBE COMMENTSAditiya Rahman (pp. 31-34)KOMPARASI PROTOKOL KOMUNIKASI PADA SISTEM PRODUKSI SIBER-FISIK BERBASIS IEC 61499Rico Aryandaru, Awang Noor Indra Wardana, Agus Arif (pp. 35-40)
Naive Bayes Method to Analyze Sentiment Accuracy on YouTube Comments Aditiya Rahman; Fadhil Rahmat; Sumarni Adi
Jurnal EECCIS (Electrics, Electronics, Communications, Controls, Informatics, Systems) Vol. 14 No. 1 (2020)
Publisher : Fakultas Teknik, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/jeeccis.v14i1.627

Abstract

The revolution on social media has attracted users to video sharing sites like YouTube. This site is the most popular social media site where people see, share and interact by commenting on videos. There are various types of videos shared by users such as songs, movie trailers, news, entertainment etc. Some time ago the most trending video was a video about World War III (WWIII / WW3). Analyzing comments from videos about WW3 gives viewers opinions about WW3. Study the sentiments expressed in this commentary whether WW3 gets positive or negative feedback. The machine learning algorithm, Naive Bayes, is used in comments to find out its sentiments. The test results of 1500 data produced 30.3% positive sentiment and 60.6% negative sentiment, with an accuracy of 78.17%.
Prakiraan Kebutuhan Energi Listrik Dengan Jaringan Saraf Tiruan (Artificial Neural Network) Metode Backpropagation Tahun 2020-2025 Diah Setyowati; Said Sunardiyo
Jurnal EECCIS (Electrics, Electronics, Communications, Controls, Informatics, Systems) Vol. 14 No. 1 (2020)
Publisher : Fakultas Teknik, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/jeeccis.v14i1.604

Abstract

Kebutuhan energi listrik merupakan salah satu hal utama yang diprioritaskan oleh penyedia listrik. Perlunya dilalukan perencanaan terhadap pemenuhan kebutuhan energi listrik oleh penyedia listrik setiap tahunnya. Penelitian dilakukan untuk memprediksi kebutuhan energi listrik PT PLN (Persero) UP3 Semarang tahun 2020-2025 dengan mengembangkan suatu model Jaringan Saraf Tiruan metode Backpropagation menggunakan software Matlab. Beberapa variabel yang digunakan yaitu jumlah penduduk, jumlah pelanggan, PDRB, daya tersambung, beban puncak dan total produksi energi listrik. Variabel tersebut merupakan beberapa faktor yang mempengaruhi peningkatan  kebutuhan energi listrik. Hasil penelitian menghasilkan Mean Absolute Percentage Error (MAPE) sebesar 0,4% dan Growth of Total % (GOT %) sebesar 2,7% setiap tahunnya.
Komparasi Protokol Komunikasi pada Sistem Produksi Siber-Fisik berbasis IEC 61499 Rico Aryandaru; Awang Noor Indra Wardana; Agus Arif
Jurnal EECCIS (Electrics, Electronics, Communications, Controls, Informatics, Systems) Vol. 14 No. 1 (2020)
Publisher : Fakultas Teknik, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/jeeccis.v14i1.630

Abstract

The change in the concept of an automation pyramid into an automation cloud in a cyber-physical production system makes data communication no longer stratified but can be done directly between devices. Based on IEC 61499, which defines the function blocks for building such communications, communication protocols can be run on various devices. Several communication protocols that can fulfill these requirements are OPC-UA, FBDK / IP, and MQTT. The research was conducted by comparing the three communication protocols for latency parameters and their jitters. The test method used to compare latency parameters is the variance analysis test and the Tukey test. The jitter value of the protocols are compared to the standard deviation parameter. The test results showed that the MQTT communication protocol had a faster latency value, with a 95% confidence level. The standard deviation of the variation value for OPC-UA, FBDK / IP, and MQTT showed the jitter value of 0.72 seconds, 0.35 seconds, and 0.64 seconds. Comparing the three communication protocols' standard deviation values showed that the FBDK / IP communication protocol has significantly less jitter than the OPC-UA and MQTT communication protocols.
Filter Band Pass Frekuensi Radio FM dengan Metode m-derived Koes Koes Janto
Jurnal EECCIS (Electrics, Electronics, Communications, Controls, Informatics, Systems) Vol. 14 No. 1 (2020)
Publisher : Fakultas Teknik, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/jeeccis.v14i1.611

Abstract

Paper Sistem komunikasi nirkabel (wireless) merupakan andalan terselenggarnya integrasi sistem telekomunikasi secara global. Salah satu penyelenggaraan siaran radio frequency modulation (FM) dialokasikan pada pita frekuensi 87,6 – 107,9 MHz. Untuk menghindari terjadinya interferensi kanal bersebelahan, dibutuhkan perangkat filter yang berfungsi membatasi pita frekuensi pancaran sinyal pada frekuensi yang tidak diinginkan. Filter yang memiliki performansi cukup baik dengan tingkat kecuraman yang cukup tinggi yaitu menggunakan BPF m-derived dengan menambahkan jumlah elemen yang lebih banyak. Untuk mendapatkan performansi dilakukan pengujian parameter filter antara lain bandwidth passband, bandwidth stopband, shape factor, insertion loss, dan pelemahan. Pada penelitian ini dilakukan pengukuran BPF (tanpa m-derived) menggunakan 7 elemen dihasilkan BW passband sebesar 25 MHz dari frekuensi 86 MHz sampai 111 MHz, sedangkan pada BW stopband sebesar 67 MHz dari frekuensi 67 MHz sampai 130 MHz, shape factor 2,52, insertion loss maksimum sebesar 6 dB dan insertion loss minimum sebesar 3 dB. Sedangkan BPF m-derived dihasilkan BW passband sebesar 29 MHz dari frekuensi 79 MHz sampai 115 MHz, sedangkan pada BW stopband sebesar 53 MHz dari frekuensi 67 MHz sampai 132 MHz, shape factor 1,83, insertion loss maksimum sebesar 4,5 dB dan insertion loss minimum sebesar 1,5 dB. Dengan demikian BPF m-derived mempunyai performansi parameter lebik baik dibandingkan dengan BPF tanpa m-derived.Kata kunci : band pass filter, m-derived, insertion loss, bandwidth, shape factor

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