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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

Author-ID : 240788

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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Articles

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Spatio-Temporal Deforestation Measurement Using Automatic Clustering Wina Rachmawan, Irene Erlyn; Barakbah, Ali Ridho; Harsono, Tri
EMITTER International Journal of Engineering Technology Vol 4 No 1 (2016)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Deforestation is one of the crucial issues in Indonesia. In 2012, deforestation rate in Indonesia reached 0.84 million hectares, exceeding Brazil. According to the 2009 Guinness World Records, Indonesia's deforestation rate was 1.8 million hectares per year between 2000 and 2005. An interesting view is the fact that Indonesia government denied the deforestation rate in those years and said that the rate was only 1.08 million hectares per year in 2000 and 2005. The different problem is on the technique how to deal with the deforestation rate. In this paper, we proposed a new approach for automatically identifying the deforestation area and measuring the deforestation rate. This approach involves differential image processing for detecting Spatio-temporal nature changes of deforestation. It consists series of important features extracted from multiband satellite images which are considered as the dataset of the research. These data are proceeded through the following stages: (1) Automatic clustering for multiband satellite images, (2) Reinforcement Programming to optimize K-Means clustering, (3) Automatic interpretation for deforestation areas, and (4) Deforestation measurement adjusting with elevation of the satellite. For experimental study, we applied our proposed approach to analyze and measure the deforestation in Mendawai, South Borneo. We utilized Landsat 7 to obtain the multiband images for that area from the year 2001 to 2013. Our proposed approach is able to identify the deforestation area and measure the rate. The experiment with our proposed approach made a temporal measurement for the area and showed the increasing deforestation size of the area 1.80 hectares during those years.

Decision Support System for Indonesian Government Fast E-Tendering Based on Vendor Classification Widodo, Edi Wahyu; Harsono, Tri; Barakbah, Ali Ridho
EMITTER International Journal of Engineering Technology Vol 4 No 1 (2016)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

In the last few years in the world of auctions, electronic auctions become a hot topic for discussion, especially in Indonesia. In Indonesia, the auction has been using online electronic system since 2007 with all its advantages and disadvantages. This system is one of a fairly successful program in a good governance. Until now, there are 620 government agencies in Indonesia have been using this electronic procurement systems[19]. The Government can perform a budget efficiency nearly 5% of the total budget by using today's electronic procurement system. The current system is good enough, but there are still some deficiencies found. Some of solutions to cover the deficiency offered in this paper. Starting from the classification of goods or services according to the UNSPSC, applying business classification with ISIC Indonesia in 2009, recording the activity of vendors for consideration decision, and implementing a decision support system using AHP to facilitate the auction committee to determine the winner. All of above matters are intended to improve the effectiveness and efficiency of the current system.

Javanese Character Feature Extraction Based on Shape Energy Wibowo, Galih Hendra; Sigit, Riyanto; Barakbah, Aliridho
EMITTER International Journal of Engineering Technology Vol 5 No 1 (2017)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Javanese character is one of Indonesia's noble culture, especially in Java. However, the number of Javanese people who are able to read the letter has decreased so that there need to be conservation efforts in the form of a system that is able to recognize the characters. One solution to these problem lies in Optical Character Recognition (OCR) studies, where one of its heaviest points lies in feature extraction which is to distinguish each character. Shape Energy is one of feature extraction method with the basic idea of how the character can be distinguished simply through its skeleton. Based on the basic idea, then the development of feature extraction is done based on its components to produce an angular histogram with various variations of multiples angle. Furthermore, the performance test of this method and its basic method is performed in Javanese character dataset, which has been obtained from various images, is 240 data with 19 labels by using K-Nearest Neighbors as its classification method. Performance values were obtained based on the accuracy which is generated through the Cross-Validation process of 80.83% in the angular histogram with an angle of 20 degrees, 23% better than Shape Energy. In addition, other test results show that this method is able to recognize rotated character with the lowest performance value of 86% at 180-degree rotation and the highest performance value of 96.97% at 90-degree rotation. It can be concluded that this method is able to improve the performance of Shape Energy in the form of recognition of Javanese characters as well as robust to the rotation.

Semantic Madurese Batik Search with Cultural Computing of Symbolic Impression Extraction and Analytical Aggregation of Color,Shape and Area Features Umam, Khotibul; Barakbah, Ali Ridho; Basuki, Achmad
EMITTER International Journal of Engineering Technology Vol 5 No 1 (2017)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Lack of information media about Madurese batik Causes low awareness of younger generation to maintain the production of Madurese batik. Actually, Madurese Batik also has a high philosophy, which the motif and colour reflect the character of the Madurese. Madurese Batik has useful motif as a mean of traditional communication in the form of certain cultural symbols. We collected images of Madurese Batik by identifying the impression of Madurese Batik motif taken from several literature books of Madurese Batik and also the results of observation of experts or craftsmen who understand about Madurese Batik. This research proposed a new approach to create on application which can identify Madurese Batik impression by using 3D-CVQ feature extraction methods to extract color features, and used Hu Moment Invariant for feature feature extraction. Application searching of Madurese Batik image has two ways of searching, those are based on the image input Madurese Batik and based on the input of impression Madurese batik. We use 202 madurese batik motifs and use search techniques based on colors, shapes and aggregations (color and shape combinations). Â Performance results using based on image queries used: (1) based on color, the average precision 90%, (2) based on shape, the average precision 85%, (3) based on aggregation, the average precision 80%, the conclusion is the color as the best feature in image query. While the performance results using based on the impression query are: Â (1) based on color, the average value of true 6.7, total score 40.3, (2) based on shape, the average value of true 4.1, total score 24.1, and (3) based on the aggregation, the average value of true 2.5, the total score is 13.8, the conclusion is the color as the best feature in impression query.

Data Mining Approach for Breast Cancer Patient Recovery Fahrudin, Tresna Maulana; Syarif, Iwan; Barakbah, Ali Ridho
EMITTER International Journal of Engineering Technology Vol 5 No 1 (2017)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Breast cancer is the second highest cancer type which attacked Indonesian women. There are several factors known related to encourage an increased risk of breast cancer, but especially in Indonesia that factors often depends on the treatment routinely. This research examines the determinant factors of breast cancer and measures the breast cancer patient data to build the useful classification model using data mining approach.The dataset was originally taken from one of Oncology Hospital in East Java, Indonesia, which consists of 1097 samples, 21 attributes and 2 classes. We used three different feature selection algorithms which are Information Gain, Fisherâ€™s Discriminant Ratio and Chi-square to select the best attributes that have great contribution to the data. We applied Hierarchical K-means Clustering to remove attributes which have lowest contribution. Our experiment showed that only 14 of 21 original attributes have the highest contribution factor of the breast cancer data. The clustering algorithmdecreased the error ratio from 44.48% (using 21 original attributes) to 18.32% (using 14 most important attributes).We also applied the classification algorithm to build the classification model and measure the precision of breast cancer patient data. The comparison of classification algorithms between NaÃ¯ve Bayes and Decision Tree were both given precision reach 92.76% and 92.99% respectively by leave-one-out cross validation. The information based on our data research, the breast cancer patient in Indonesia especially in East Java must be improved by the treatment routinely in the hospital to get early recover of breast cancer which it is related with adherence of patient.

Feature Extraction For Application of Heart Abnormalities Detection Through Iris Based on Mobile Devices Kusumaningtyas, Entin Martiana; Barakbah, Ali Ridho; Hermawan, Aditya Afgan
EMITTER International Journal of Engineering Technology Vol 5 No 2 (2017)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

As the WHO says, heart disease is the leading cause of death and examining it by current methods in hospitals is not cheap. Iridology is one of the most popular alternative ways to detect the condition of organs. Iridology is the science that enables a health practitioner or non-expert to study signs in the iris that are capable of showing abnormalities in the body, including basic genetics, toxin deposition, circulation of dams, and other weaknesses. Research on computer iridology has been done before. One is about the computer's iridology system to detect heart conditions. There are several stages such as capture eye base on target, pre-processing, cropping, segmentation, feature extraction and classification using Thresholding algorithms. In this study, feature extraction process performed using binarization method by transforming the image into black and white. In this process we compare the two approaches of binarization method, binarization based on grayscale images and binarization based on proximity. The system we proposed was tested at Mugi Barokah Clinic Surabaya.Â We conclude that the image grayscale approach performs better classification than using proximity.

Botnet Detection Using On-line Clustering with Pursuit Reinforcement Competitive Learning (PRCL) Mahardhika, Yesta Medya; Sudarsono, Amang; Barakbah, Ali Ridho
EMITTER International Journal of Engineering Technology Vol 6 No 1 (2018)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Botnet is a malicious software that often occurs at this time, and can perform malicious activities, such as DDoS, spamming, phishing, keylogging, clickfraud, steal personal information and important data. Botnets can replicate themselves without user consent. Several systems of botnet detection has been done by using classification methods. Classification methods have high precision, but it needs more effort to determine appropiate classification model. In this paper, we propose reinforcedÂ approach to detect botnet with On-line Clustering using Reinforcement Learning. Reinforcement Learning involving interaction with the environment and became new paradigm in machine learning. The reinforcement learning will be implemented with some rule detection, because botnet ISCX dataset is categorized as unbalanced dataset which have high range of each number of class. Therefore we implemented Reinforcement Learning to Detect Botnet using Pursuit Reinforcement Competitive Learning (PRCL) with additional rule detection which has reward and punisment rules to achieve the solution. Based on the experimental result, PRCL can detect botnet in real time with highÂ accuracy (100% for Neris, 99.9% for Rbot, 78% for SMTP_Spam, 80.9% for Nsis, 80.7% for Virut, and 96.0% for Zeus) and fast processing time up to 176 ms. Meanwhile the step of CPU and memory usage which are 78 % and 4.3 GBÂ for pre-processing, 34% and 3.18 GB for online clustering with PRCL, and Â 23% and 3.11 GB evaluation. The proposed method is one solution for network administrators to detect botnet which has unpredictable behavior in network traffic.

Classification of Radical Web Content in Indonesia using Web Content Mining and k-Nearest Neighbor Algorithm Subhan, Muh; Sudarsono, Amang; Barakbah, Ali Ridho
EMITTER International Journal of Engineering Technology Vol 5 No 2 (2017)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24003/emitter.v5i2.214

Radical content in procedural meaning is content which have provoke the violence, spread the hatred and anti nationalism. Radical definition for each country is different, especially in Indonesia. Radical content is more identical with provocation issue, ethnic and religious hatred that is called SARA in Indonesian languange. SARA content is very difficult to detect due to the large number, unstructure system and many noise can be caused multiple interpretations. This problem can threat the unity and harmony of the religion. According to this condition, it is required a system that can distinguish the radical content or not. In this system, we propose text mining approach using DF threshold and Human Brain as the feature extraction. The system is divided into several steps, those are collecting data which is including at preprocessing part, text mining, selection features, classification for grouping the data with class label, simillarity calculation of data training, and visualization to the radical content or non radical content. The experimental result show that using combination from 10-cross validation and k-Nearest Neighbor (kNN) as the classification methods achieve 66.37% accuracy performance with 7 k value of kNN method[1].

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)

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)

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.

Co-Authors A.A. Ketut Agung Cahyawan W Abd. Rasyid Syamsuri Achmad Basuki Achmad Basuki Achmad Basuki Achmad Basuki Achmad Thorikul Huda Adnan Rachmat Anom Besari Afrida Helen 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 Hermawan, Aditya Afgan Hermawan, Aditya Afgan Hidayah, Amalia Wirdatul Hidayah, Nadila Wirdatul Hisyam, Masfu Hisyam, Masfu 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 Izza Nur Afifah Khotibul Umam Kindarya, Fabyan Kohei Arai Kohei Arai Kurniasari, Arvita Agus Kurniasari, Arvita Agus Kusuma, Dedy Hidayat Kusuma, Harun Indra 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 Muh. Subhan 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 Oktavia Citra Resmi Rachmawati Oktavia Citra Resmi Rachmawati Piko Permata Ilham Prasetyo Primajaya, Grezio Arifiyan Puspasari Susanti 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 Setiawardhana Setiawardhana Shabirin, Irsal Silfiana Nur Hamida Sumarsono, Irwan Suryani, Indah Yudi Susetyoko, Ronny Syd. Ali Zein Farmadi, Syd. Ali Zein Tahta Alfina Tessy Badriyah Tessy Badriyah, Tessy Tita Karlita Tita Karlita Tita Karlita Tresna Maulana Fahrudin Tri Hadiah Muliawati, Tri Hadiah Tri Harsono Tri Harsono ULURRASYADI, FAIZ Wahjoe Tjatur Sesulihatien 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

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