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All Journal Jurnal Teknik ITS Techno.Com: Jurnal Teknologi Informasi Register: Jurnal Ilmiah Teknologi Sistem Informasi ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika EMITTER International Journal of Engineering Technology Proceeding of the Electrical Engineering Computer Science and Informatics JOIV : International Journal on Informatics Visualization Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control INOVTEK Polbeng - Seri Informatika Systemic: Information System and Informatics Journal Jurnal Mantik Jurnal Teknologi Informasi dan Terapan (J-TIT) Journal of Applied Engineering and Technological Science (JAETS) Abdimas: Jurnal Pengabdian Masyarakat Universitas Merdeka Malang Indonesian Journal of Electrical Engineering and Computer Science GUYUB: Journal of Community Engagement Journal of Applied Data Sciences El-Mujtama: Jurnal Pengabdian Masyarakat The Indonesian Journal of Computer Science
Ali Ridho Barakbah
Politeknik Elektronika Negeri Surabaya
Religion Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mechanical Engineering Social Sciences Other

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Rule-based Sentiment Degree Measurement of Opinion Mining of Community Participatory in the Government of Surabaya Putra, Berlian Juliartha Martin; Helen, Afrida; Barakbah, Ali Ridho
EMITTER International Journal of Engineering Technology Vol 6 No 2 (2018)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (423.153 KB) | DOI: 10.24003/emitter.v6i2.275

Abstract

Diskominfo Surabaya, as a government agency, received much community participatory for improvement of governmental services, with increasing number of 698, 2717, 4176 and 4298 participatory data respectively in 2011, 2012, 2013 and 2014. It is challenging for Diskominfo Surabaya to set a target by giving the response back within 24 hours. Due to task complexity to address the degree of participatory and to categorize the group of participatory, they faced difficulty to fulfill the target. In this research, we present a new system for measuring the sentiment degree of community participatory. We provide 5 functions in our system, which are: (1) Data Collection, (2) Data Preprocessing, (3) Text Mining, (4) Sentiment Analysis and (5) Validation. We propose our rule-based technique for the sentiment analysis of opinion mining with detection of 8 important parts, which are (1) Verb, (2) Adjective, (3) Preposition, (4) Noun, (5) Adverb, (6) Symbol, (7) Phrase, and (8) Complimentary. For applicability of our proposed system, we made a series of experiment with 410 data of community participatory in Twitter for Diskominfo Surabaya and compared with other sentiment classification algorithms which are SVM and Naive Bayes Classifier. Our system performed 77.32% rate of accuracy and outperformed to other comparing algorithms.
Spatio Temporal with Scalable Automatic Bisecting-Kmeans for Network Security Analysis in Matagaruda Project Hisyam, Masfu; Barakbah, Ali Ridho; Syarif, Iwan; S, Ferry Astika
EMITTER International Journal of Engineering Technology Vol 7 No 1 (2019)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (715.88 KB) | DOI: 10.24003/emitter.v7i1.340

Abstract

Internet attacks are a frequent occurrence and the incidence is always increasing every year, therefore Matagaruda project is built to monitor and analyze internet attacks using IDS (Intrusion Detection System). Unfortunately, the Matagaruda project has lacked in the absence of trend analysis and spatiotemporal analysis. It causes difficulties to get information about the usual seasonal attacks, then which sector is the most attacked and also the country or territory where the internet attack originated. Due to the number of unknown clusters, this paper proposes a new method of automatic bisecting K-means with the average of SSE is 93 percents better than K-means and bisecting K-means. The usage of big spark data is highly scalable for processing massive data attack.
Content-Dependent Image Search System for Aggregation of Color, Shape and Texture Features Kurniasari, Arvita Agus; Barakbah, Ali Ridho; Basuki, Achmad
EMITTER International Journal of Engineering Technology Vol 7 No 1 (2019)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (717.8 KB) | DOI: 10.24003/emitter.v7i1.361

Abstract

The existing image search system often faces difficulty to find a appropriate retrieved image corresponding to an image query. The difficulty is commonly caused by that the users’ intention for searching image is different with dominant information of the image collected from feature extraction. In this paper we present a new approach for content-dependent image search system. The system utilizes information of color distribution inside an image and detects a cloud of clustered colors as something - supposed as an object. We applies segmentation of image as content-dependent process before feature extraction in order to identify is there any object or not inside an image. The system extracts 3 features, which are color, shape, and texture features and aggregates these features for similarity measurement between an image query and image database. HSV histogram color is used to extract color feature of image. While the shape feature extraction used Connected Component Labeling (CCL) which is calculated the area value, equivalent diameter, extent, convex hull, solidity, eccentricity, and perimeter of each object. The texture feature extraction used Leung Malik (LM)’s approach with 15 kernels.  For applicability of our proposed system, we applied the system with benchmark 1000 image SIMPLIcity dataset consisting of 10 categories namely Africans, beaches, buildings historians, buses, dinosaurs, elephants, roses, horses, mountains, and food. The experimental results performed 62% accuracy rate to detect objects by color feature, 71% by texture feature, 60% by shape feature, 72% by combined color-texture feature, 67% by combined color-shape feature, 72 % combined texture-shape features and 73% combined all features.
Cluster-Based News Representative Generation with Automatic Incremental Clustering Shabirin, Irsal; Barakbah, Ali Ridho; Syarif, Iwan
EMITTER International Journal of Engineering Technology Vol 7 No 2 (2019)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24003/emitter.v7i2.378

Abstract

Nowadays, a large volume of news circulates around the Internet in one day, amounting to more than two thousand news. However, some of these news have the same topic and content, trapping readers among different sources of news that say similar things. This research proposes a new approach to provide a representative news automatically through the Automatic Incremental Clustering method. This method began with the Data Acquisition process, Keyword Extraction, and Metadata Aggregation to produce a news metadata matrix. The news metadata matrix consisted of types of word in the column and news section of each line. Furthermore, the news on the matrix were grouped by the Automatic Incremental Clustering method based on the number of word similarities that arised, calculated using the Euclidean Distance approach, and was done automatically and real-time. Each cluster (topic) determined one representing news as a Representative News based on the location of the news closest to the midpoint/centroid on the cluster. This study used 101 news as experimental data and produced 87 news clusters with 85.14% precision ratio.
Classification and Risk-Mapping of River Water Quality in Surabaya with Semantic Visualitzation Miko, Taufan Radias; Harsono, Tri; Barakbah, Aliridho
EMITTER International Journal of Engineering Technology Vol 7 No 2 (2019)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24003/emitter.v7i2.393

Abstract

River water pollution is one of the environmental problems that occur in Surabaya. The amount of industrial waste and household waste makes Surabaya River water easily polluted every day, besides that there are also many people who are not aware about the quality of river water in Surabaya. In this paper, we present a new system to classify water quality of river in surabaya. The system involve a semantic visualization of risk-mapping for the river, so that the people of Surabaya are easier to get information about the quality of Surabaya River water. In this paper, we measured the water quality of Surabaya River using Horiba sensor measuring instruments using 5 parameters, namely temperature, PH, DO, Turbidity, TDS. These five parameters are input variables for calculating water quality with the methods applied in this research. We use the Storet Method to determine the quality of Surabaya River water. The results of the Storet Method explained that there were 0.03% of the data on lightly polluted water quality and there were 37.41% of the data being moderately polluted and there were 59.29% of the data heavily polluted. The results of the calculation using the Storet method concluded that the condition of Surabaya River water quality was not good. We also apply the rule of the Storet Method to the Neural Network by using Surabaya River water quality data as learning data and gave performance 70.02% accuracy.
Spatio-Temporal Associative Mining for Earthquake Data Distribution in Indonesia Edelani, Renovita; Barakbah, Aliridho; Harsono, Tri
EMITTER International Journal of Engineering Technology Vol 7 No 2 (2019)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24003/emitter.v7i2.428

Abstract

Indonesia is a country that has the highest seismically activity in the world. This country has really high earthquake frequency because of it traversed by three plate meeting plate and located in Ring of Fire area. The shaking events from an earthquake are very strong and propagate in all directions, capable of destroying even the strongest civilian buildings, so there is no doubt that there are many victims of human lives. The other facts, earthquake in Indonesia have seismic relation between the provinces. In this paper, we present a new earthquake Spatio-temporal mapping system based on the association confidence value from the result of associative mining process on earthquake data distribution in Indonesia. The system proposed three main functions which are (1) Data Acquisition which taken from four data provider, then preprocess and combine it become one, (2) Associative Mining process to get the rule of association earthquake between provinces in Indonesia, and (3) Earthquake Association Spatio-Temporal Model from the highest confidence value and Visualization. We use data from several earthquake data providers from 1900 until 2018. To perform our proposed Spatio-temporal earthquake association mapping system, we divided the data to become a 5-year discrete partition. After that, we mining the rule and get the highest confidence value from each period. This confidence value is used for modeling and visualization of our Spatio-temporal mapping system. As a result of this study, we manage to generate earthquake association risk mapping from 13 provinces that had earthquake connectivity between each other. The provinces are Aceh, Sumatera Utara, Bengkulu, East Java, Bali, NTB, NTT, Maluku, North Maluku, Gorontalo, North Sulawesi, Papua dan West Papua.
Co-Authors A.A. Ketut Agung Cahyawan W Abd. Rasyid Syamsuri Achmad Basuki Achmad Basuki Achmad Basuki Achmad Basuki Adnan Rachmat Anom Besari Afifah, Izza Nur Afrida Helen Afrida Helen, Afrida Agata, Dias Agus Kurniasari, Arvita Ahsan, Ahmad Syauqi Al Islami, M Tafaquh Fiddin Alde, Muhammad Riski Alfi Fadliana Amali, Darari Nur Amalia Wirdatul Hidayah Amalo, Elizabeth Anggraeni Amang Sudarsono, Amang Andhik Ampuh Yunanto Andy Yuniawan ANITA DAMAYANTI Anom Besari, Adnan Rachmat Arna Fariza Arvita Agus Kurniasari Aziz, Adam Shidqul Bayu Dwiyan Satria Bima Sena Bayu Dewantara Budi Santosa Dadet Pramadihanto Dadet Pramadihanto Darari Nur Amali Desi Amirullah, Desi Desy Intan Permatasari, Desy Intan Devira Nanda Kuswhara, Devira Nanda Dewanto, Raden Sanggar Dias Agata Edelani, Renovita Edi Satriyanto Entin Martiana Kusumaningtyas Fahrudin, Tresna Maulana Fahrudin, Tresna Maulana Fauzi Nafi'Ubadah, Kriza Febrianto, Ardiansyah Indra Ferry Astika Saputra Haikal Yuniarta Krisgianto, Ricko Hamida, Silfiana Nur Hermawan, Aditya Afgan Hermawan, Aditya Afgan Hidayah, Amalia Wirdatul Hidayah, Nadila Wirdatul Hisyam, Masfu Hisyam, Masfu Huda, Achmad Thorikul I Made Akira Ivandio Agusta Idris Winarno Idris Winarno Ilham Iskandariansyah Indah Yulia Prafitaning Tiyas, Indah Yulia Prafitaning Indra Adji Sulistijono Insani, Fawzan Irene Erlyn Wina Rachmawan, Irene Erlyn Wina Isbat Uzzin Nadhori, Isbat Uzzin iwan Syarif Iwan Syarif Khotibul Umam Kindarya, Fabyan Kohei Arai Kohei Arai Kurniasari, Arvita Agus Kurniasari, Arvita Agus Kusuma, Dedy Hidayat Kusuma, Selvia Ferdiana Louis Nashih Uluwan Arif M Udin Harun Al Rasyid, M Udin Harun Mahardhika, Yesta Medya Marlisa Sigita, Marlisa Maulana, Wahyu Ikbal Mayangsari, Mustika Kurnia Miko, Taufan Radias Mirza Ghulam Rifqi Mirza Ghulam Rifqi Mohammad Nur Shodiq Mohammad Nur Shodiq Mohammad Nur Shodiq, Mohammad Nur Mu'arifin, Mu'arifin Muarifin ., Muarifin Muarifin Muarifin Muhammad Alfian Muhammad Rois Muhammad Wahyu Nugroho Sakti Nadila Wirdatul Hidayah Nana Ramadijanti, Nana Ni'Ma, Najma Akmalina Nur Rosyid Mubatada'i Nur Rosyid Mubtadai, Nur Rosyid Oktavia Citra Resmi Rachmawati Piko Permata Ilham Prasetyo Primajaya, Grezio Arifiyan Puspasari Susanti Putra, Berlian Juliartha Martin Rachmawati, Oktavia Citra Resmi Rasyada, Ihda Ratri Cahyaning Winedhar Renovita Edelani Ridho, Bistiana Syafina Riyanto Sigit Riyanto Sigit, Riyanto Rizka Rahayu Sasmita Rudi Kurniawan S, Ferry Astika S, Ferry Astika Sa'adah, Umi Saputra, Muhammad Krisnanda Vilovan Sesulihatien, Wahjoe Tjatur Setiawardhana Setiawardhana Setiawardhana, Setiawardhana Shabirin, Irsal Subhan, Muh Sumarsono, Irwan Suryani, Indah Yudi Susanti, Puspasari Susetyoko, Ronny Syd. Ali Zein Farmadi, Syd. Ali Zein Tahta Alfina Tessy Badriyah Tessy Badriyah, Tessy Tita Karlita Tita Karlita Tresna Maulana Fahrudin Tri Hadiah Muliawati, Tri Hadiah Tri Harsono Tri Harsono ULURRASYADI, FAIZ Wahjoe Tjatur Sesulihatien Wahjoe Tjatur Sesulihatien Wahyu Widodo Wibowo, Galih Hendra Wibowo, Galih Hendra Widodo, Edi Wahyu Wina Rachmawan, Irene Erlyn Wina Rachmawan, Irene Erlyn Yuliana Setiowati, Yuliana Zainal Arief