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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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Neural Network for Earthquake Prediction Based on Automatic Clustering in Indonesia Mohammad Nur Shodiq; Dedy Hidayat Kusuma; Mirza Ghulam Rifqi; Ali Ridho Barakbah; Tri Harsono
JOIV : International Journal on Informatics Visualization Vol 2, No 1 (2018)
Publisher : Society of Visual Informatics

A model of artiï¬cial neural networks (ANNs) is presented in this paper to predict aftershock during the next five days after an earthquake occurrence in selected cluster of Indonesia with magnitude equal or larger than given threshold. The data were obtained from Indonesian Agency for Meteorological, Climatological and Geophysics (BMKG) and United States Geological Surveyâ€™s (USGS). Six clusters was an optimal number of cluster base-on cluster analysis implementing Valley Tracing and Hill Climbing algorithm, while Hierarchical K-means was applied for datasets clustering. A quality evaluation was then conducted to measure the proposed model performance for two different thresholds. The experimental result shows that the model gave better performance for predicting an aftershock occurrence that equal or larger than 6 Richterâ€™s scale magnitude.

Adaptive Neural Fuzzy Inference System and Automatic Clustering for Earthquake Prediction in Indonesia Mohammad Nur Shodiq; Dedy Hidayat Kusuma; Mirza Ghulam Rifqi; Ali Ridho Barakbah; Tri Harsono
JOIV : International Journal on Informatics Visualization Vol 3, No 1 (2019)
Publisher : Politeknik Negeri Padang

Earthquake is a type of natural disaster. The Indonesian archipelago located in the world's three mega plates; they are Australian plate, Eurasian plate, and Pacific plate. Therefore, it is possible for applied of earthquake risk of mitigation. One of them is to provide information about earthquake occurrences. This information used for spatiotemporal analysis of earthquakes. This paper presented Spatial Analysis of Magnitude Distribution for Earthquake Prediction using adaptive neural fuzzy inference system (ANFIS) based on automatic clustering in Indonesia. This system has three main sections: (1) Data preprocessing, (2) Automatic Clustering, (3) Adaptive Neural Fuzzy Inference System. For experimental study, earthquake data obtained Indonesian Agency for Meteorological, Climatological, and Geophysics (BMKG) and the United States Geological Survey’s (USGS), the year 2010-2017 in the location of Indonesia. Automatic clustering process produces The optimal number of cluster, that is 7 clusters. Each cluster will be analyzed based on earthquake distribution. Its calculate the b value of earthquake to get the seven seismicity indicators. Then, implementation for ANFIS uses 100 training epochs, Number of membership function (MFs) is 2, MFs type input is gaussian membership function (gaussmf). The ANFIS result showed that the system can predict the non-occurrence of aftershocks with the average performance of 70%.

Big Data Environment for Realtime Earthquake Data Acquisition and Visualization Louis Nashih Uluwan Arif; Ali Ridho Barakbah; Amang Sudarsono; Renovita Edelani
JOIV : International Journal on Informatics Visualization Vol 3, No 4 (2019)
Publisher : Politeknik Negeri Padang

Indonesia is a country that has the highest level of earthquake risk in the world. In the past 10 years, there have been ± 90,000 earthquake events recorded and always increasing along with the explosion of earthquake data occurs at any time. The process of collecting and analyzing earthquake data requires more effort and takes a long computational time. In this paper, we propose a new system to acquire, store, manage and process earthquake data in Indonesia in real-time, fast and dynamic by utilizing features in the Big Data Environment. This system improves computational performance in the process of managing and analyzing earthquake data in Indonesia by combining and integrating earthquake data from several providers to form a complete unity of earthquake data. An additional function is the existence of an API (Application Programming Interface) embedded in this system to provide access to the results of earthquake data analysis such as density, probability density function and seismic data association between provinces in Indonesia. The process in this system has been carried out in parallel and improved computing performance. This is evidenced by the computational time in the preprocessing process on a single-core master node, which requires 55.6 minutes, but a distributed computing process using 15 cores can speeds up with only 4.82 minutes.

Incremental Associative Mining based Risk-Mapping System for Earthquake Analysis in Indonesia Renovita Edelani; Ali Ridho Barakbah; Tri Harsono; Louis Nashih Uluwan Arif
JOIV : International Journal on Informatics Visualization Vol 3, No 4 (2019)
Publisher : Politeknik Negeri Padang

Indonesia is one of the largest archipelagic countries in the world that has the highest risk of an earthquake. The major causes of earthquakes in this country are plate movements and volcanic activity. Earthquakes in Indonesia has a cause and effect relationship between each province. This disaster caused severe damage including a lot of people to get killed, injured and lose their money and property. We must minimize the impact of the earthquake by forming earthquake risk mapping. The risk of seismicity in Indonesia can vary each year, so it needs to be analyzed how the changes in risk are each addition of earthquake data. This paper proposes an earthquake risk mapping system with Associative Mining based on incremental earthquake data that have the highest values of confidence rates from the seismic association between provinces in Indonesia. The system uses the Incremental Association rule method to see the trend in the value of changes in confidence for each addition of earthquake data every 5 years. This system proposes 3 main features, which are (1) Data Retrieval and Preprocessing, (2) Association Rule Mining, (3) Incremental Associative Mining based risk mapping. For the experimental study, the system used data from 1963-2018. The results show that the provinces of Maluku, North Maluku, Nusa Tenggara Timur, North Sulawesi, and Papua have an incremental association risk of an earthquake.

Komputasi Budaya Untuk Pencarian Gambar Semantik Pada Lukisan Budaya Indonesia Dengan Deteksi Dan Informasi Aliran Lukisan Ratri Cahyaning Winedhar; Ali Ridho Barakbah; Achmad Basuki; Arvita Agus Kurniasari
Jurnal Teknologi Informasi dan Terapan Vol 8 No 1 (2021)
Publisher : Jurusan Teknologi Informasi Politeknik Negeri Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25047/jtit.v8i1.224

Lukisan merupakan salah satu gambaran kompleks yang mencerminkan pengamatan dan perasaan seniman terhadap lingkungan. Kondisi ini memperluas kebutuhan akan sistem pendeteksi citra budaya karena masyarakat awam yang kurang memiliki pengalaman artistik akan sulit mendapatkan kesan lukisannya. Oleh karena itu, peneliti menekankan penerapan lukisan budaya Indonesia ke dalam aplikasi mobile. Sistem yang diusulkan telah diimplementasikan pada 239 lukisan budaya Indonesia yang terdiri dari lima kategori gaya lukisan. Kategorinya adalah abstraksionisme, naturalisme, ekspresionisme, realisme, dan romantisme. Sistem mengekstrak 3 fitur, yaitu fitur warna, bentuk, dan tekstur. Ekstraksi ciri warna menggunakan Histogram 3D Color Vector Quantization. Ekstraksi fitur bentuk menggunakan Connected Component Labeling Algorithm (CCL) dengan menghitung nilai area, diameter setara, luas, convex hull, soliditas, eksentrisitas, dan perimeter masing-masing objek. Ekstraksi fitur tekstur menggunakan Gabor Transformation dengan 40 kernel. Sedangkan untuk ekstraksi impresi dilakukan survey terhadap beberapa orang tentang impresi lukisan budaya Indonesia. Survei ini dilakukan terhadap responden yang memahami seni lukis seperti pelukis, pemerhati lukisan, dan orang-orang yang berkecimpung di dunia seni rupa. Untuk menunjukkan gaya lukisan peneliti menggunakan proses klasifikasi menggunakan K-Nearest Neighbor. Hasil eksperimen menunjukan fitur warna sebagai fitur terbaik dalam impression query

Analisa Perbandingan Metode Hierarchical Clustering, K-Means dan Gabungan Keduanya dalam Cluster Data (Studi Kasus: Problem Kerja Praktek Teknik Industri ITS) Tahta Alfina; Budi Santosa; Ali Ridho Barakbah
Jurnal Teknik ITS Vol 1, No 1 (2012)
Publisher : Direktorat Riset dan Pengabdian Masyarakat (DRPM), ITS

Saat ini, konsep data mining semakin dikenal sebagai tools penting dalam manajemen informasi karena jumlah informasi yang semakin besar jumlahnya. Salah satu teknik yang dikenal dalam data mining adalah clustering, berupa proses pengelompokan sejumlah data atau objek ke dalam cluster (group) sehingga setiap dalam cluster tersebut akan berisi data yang semirip mungkin dan berbeda dengan objek dalam cluster yang lainnya. Clustering memiliki dua metode, yaitu partisi dan hierarki. Dua metode ini memiliki kelebihan dan kekurangan masing-masing, dan dengan menggabungkan keduanya dapat diperoleh hasil cluster yang lebih baik. Dari hasil cluster dengan menggunakan data problem Kerja Praktek Jurusan Teknik Industri ITS, maka diperoleh hasil bahwa gabungan metode Single Linkage Clustering dan K-means memberikan hasil cluster yang lebih baik dengan parameter uji cluster variance dan metode silhouette coefisien.

Automatic User-Video Metrics Creations From Emotion Detection Darari Nur Amali; Adnan Rachmat Anom Besari; Ali Ridho Barakbah; Dias Agata
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 5: EECSI 2018
Publisher : IAES Indonesia Section

In this digital era, digital content especially video, is increasing in number from time to time. Typically, a video service provider like Youtube will perform video analysis based on the video content such as colours, textures, shapes, and other features that exist in video content. The result of this analysis was used to understand user preference and to personalize video for each user. With technological developments, especially in Machine Learning and Computer Vision technology, video analysis can be based on other things beyond the video. In this context, it is the audience's impression. Thus, with the analysis of audience impressions in real-time, it is expected that the video can be analysed using the emotion parameters of the audience while the video is playing, and this can be done automatically and real-time. This system generates impression statistic for each video which concluded from every user who has watched the video and save those data in the database. Method used to analyse the result is by recruiting respondent and give some questionnaires. Respondents were asked to watch some videos and were asked to compare the impression metric which created by the system with user's real impression. The result shos that the automatic video-metric creation from emotion detection has been able to measure user's impression of the video with more than 80% accuracy stated by 75% of 20 respondents of the survey.

Lyric Text Mining Of Dangdut: Visualizing The Selected Words And Word Pairs Of The Legendary Rhoma Irama’s Dangdut Song In The 1970s Era Tresna Maulana Fahrudin; Ali Ridho Barakbah
Systemic: Information System and Informatics Journal Vol. 4 No. 2 (2018): Desember
Publisher : Program Studi Sistem Informasi Fakultas Sains dan Teknologi, UIN Sunan Ampel Surabaya

Dangdut is a new genre of music introduced by Rhoma Irama, Indonesian popular musician who was the Legendary dangdut singer in the 1970s era until now. The expression of Rhoma Irama’s lyric has themes of the human being, the way of life, love, law and human right, tradition, social equality, and Islamic messages. But interestingly, the song lyrics were written by Rhoma Irama in the 1970s were mostly on the love song themes. In order to prove this, it is necessary to identify the songs through several approaches to explore the selected word and the relationship between word pairs. If each Rhoma Irama’s lyric is identified in text mining field, the lyric text extraction will be an interesting knowledge pattern. We collected the lyric from web were used as datasets, and then we have done the data extraction to store the component of lyric including the part and line of the song. We successfully applied the most word frequencies in the form of data visualization including bar chart, word cloud, term frequency-inverse document frequency, and network graph. As a results, several word pairs that often was used by Rhoma Irama in writing his song including heart-love (19 lines), heart-longing (13 lines), heart-beloved (12 lines), love-beloved (12 lines), love-longing (11 lines).

Semantic Information Retrival for Scientific Experimental Papers with Knowlege based Feature Extraction Nur Rosyid Mubatada'i; Ali Ridho Barakbah; Afrida Helen
Jurnal Inovtek Polbeng Seri Informatika Vol 4, No 1 (2019)
Publisher : P3M Politeknik Negeri Bengkalis

Sistem Navigasi dari Holonomic Mobile Robot untuk Membantu Tenaga Kesehatan dalam Pengiriman Logistik kepada Pasien Andy Yuniawan; Muhammad Rois; Indra Adji Sulistijono; Ali Ridho Barakbah; Zainal Arief
Jurnal Inovtek Polbeng Seri Informatika Vol 6, No 2 (2021)
Publisher : P3M Politeknik Negeri Bengkalis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35314/isi.v6i2.1989

Saat ini banyak tenaga kesehatan yang meninggal akibat terinfeksi oleh COVID-19. Hal tersebut terjadi akibat dari salah satu tugas tenaga kesehatan yaitu untuk menjalankan pengiriman logistik kepada pasien sehingga kontak antara tenaga kesehatan dan pasien COVID-19 sering terjadi. Mobile robot dianggap sebagai solusi yang tepat untuk mengatasi permasalahan tersebut. Dengan mobile robot, rumah sakit atau tempat untuk isolasi dapat meminimalkan kontak antara pasien yang terinfeksi dengan tenaga kesehatan dengan melakukan tugas pengiriman logistik. Untuk dapat mewujudkan tugasnya, mobile robot harus berinteraksi dengan lingkungan. Jika harus berinteraksi dengan lingkungan, ia harus dapat bernavigasi. Sistem navigasi merupakan sistem yang memandu mobile robot dari satu tempat ke tempat lainnya. Dalam penelitian ini, diterapkan sistem navigasi menggunakan position driver dan obstacle avoidance dengan fuzzy controller agar mobile robot mampu bergerak menghindari halangan ketika mencapai targetnya. Fuzzy controller digunakan pada obstacle avoidance karena merupakan algoritma untuk pengambilan keputusan yang memilik variabel lingustik yang mudah dipahami oleh manusia. Berdasarkan hasil pengujian yang telah dilakukan, mobile robot dengan sistem navigasi yang diusulkan dapat melakukan tugas pengiriman logistik sehingga dapat mengurangi kontak antara pasien COVID-19 dengan tenaga kesehatan.

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

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