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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Jurnal Informatika Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Jurnal Ilmu Komputer dan Informasi Jurnal Sains dan Seni ITS IPTEK Journal of Proceedings Series IPTEK The Journal for Technology and Science CAUCHY: Jurnal Matematika Murni dan Aplikasi Gamatika Prosiding Seminar Matematika dan Pendidikan Matematik JURNAL SOSIAL HUMANIORA (JSH) Semesta Teknika Elkawnie Register: Jurnal Ilmiah Teknologi Sistem Informasi Science and Technology Indonesia Journal of Environment and Sustainability Syntax Literate: Jurnal Ilmiah Indonesia Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control BAREKENG: Jurnal Ilmu Matematika dan Terapan JAIM (Jurnal Abdi Masyarakat) Jurnal Teknologi Dan Sistem Informasi Bisnis Indonesian Journal of Electrical Engineering and Computer Science Majalah Ilmiah Matematika dan Statistika (MIMS) Airlangga Journal of Innovation Management Journal of Applied Data Sciences Journal of Research in Social Science and Humanities COMSERVA: Jurnal Penelitian dan Pengabdian Masyarakat Malcom: Indonesian Journal of Machine Learning and Computer Science Jurnal Indonesia Sosial Teknologi Sewagati International Journal of Computing Science and Applied Mathematics-IJCSAM
Mohammad Isa Irawan
Departemen Matematika Institut Teknologi Sepuluh Nopember Surabaya
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Journal : IPTEK Journal of Proceedings Series

 1 
A Hybrid Approach Support Vector Machine (SVM) – Neuro Fuzzy For Fast Data Classification Ronando, Elsen; Irawan, M. Isa; Apriliani, Erna
IPTEK Journal of Proceedings Series No 1 (2015): 1st International Seminar on Science and Technology (ISST) 2015
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j23546026.y2015i1.1097

Abstract

In recent decade, support vector machine (SVM) was a machine learning method that widely used in several application domains. It was due to SVM has a good performance for solving data classification problems, particularly in non-linear case. Nevertheless, several studies indicated that SVM still has some inadequacies, especially the high time complexity in testing phase that is caused by increasing the number of support vector for high dimensional data. To address this problem, we propose a hybrid approach SVM – Neuro Fuzzy (SVMNF), which neuro fuzzy here is used to avoid influence of support vector in testing phase of SVM. Moreover, our approach is also equipped with a feature selection that can reduce data attributes in testing phase, so that it can improve the effectiveness of time computation. Based on our evaluation in real benchmark datasets, our approach outperformed SVM in testing phase for solving data classification problems without significantly affecting the accuracy of SVM.
The Risk Assessment of Genset Installation Project Using Fault Tree Analysis In Indonesia Khilmy, Akhmad; Irawan, Mohammad Isa; Lidiawaty, Berlian Rahmy
IPTEK Journal of Proceedings Series No 3 (2020): International Conference on Management of Technology, Innovation, and Project (MOTIP) 2
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j23546026.y2020i3.11070

Abstract

The XYZ company had a project to install the generator set (genset) in several island in Indonesia. The project was estimated to finish in 10 months, but it delayed up to 20 months. This delayment made the company experience cost overruns. In the other hand, according to Indonesian Ministry of Energy and Mineral Resource (MSDM) in 2016, the electrification in this project area has not reached 100%. The area are including Kalimantan, West Nusa Tenggara (WTB), Papua, Sulawesi and Maluku. The tardiness was caused by the company can't mitigate the project risk optimally. Therefore this research aims to evaluate this genset installation project to assess the risk, thus in the next project the company can avoid project delay and the overruns cost. The research uses Fault Tree Analysis (FTA) in risk assessment to identify the basic event of the project’s problem. First, this research collect the report of the project. Second, this project collect the problems that caused project delay. There are 154 problems found in this research. The FTA method divides the problems found into 13 basic event. The highest risk that triggers problem for this project are from two basic events, which are user error with the probability rate 0,2013 and installation error with the probability rate 0,1494.
Analysis of Song Popularity in Business Digital Music Streaming for Increasing Quality Using Kohonen SOM Algorithm Chyntia Kumalasari Puteri; M. Isa Irawan
IPTEK Journal of Proceedings Series No 5 (2019): The 1st International Conference on Business and Management of Technology (IConBMT)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (466.783 KB) | DOI: 10.12962/j23546026.y2019i5.6282

Abstract

Consumption of digital music services has grown dramatically in recent years. There is an increase in music streaming consumption from 2015 to 2016, which is 76.4%. One of the most popular music streaming services, Spotify, has experienced an increase in customers from year to year. This increase enables businessmen / music producers to increase their business profits by analyzing music / songs to find out the audio attributes that make the song enjoyable for many people. Processing and analysis data are using Kohonen SOM Algorithm. The function is to find out which audio attribute groups are most liked by Spotify users where a good music is a music that can be used as a therapy. The result is LR = 0.1, PLR = 0.9, and epoch = 70 - 500, it can be concluded that cluster 2 is the cluster that has the most number of streams with 27 songs where the smallest DBI value is obtained at epoch = 200. Thus, with the statistic analysis, the obtained information is; it is expected that businessman / music producers can increase their business profits by improving their music quality that focus on songs with modes = 0 (Minor) and loudness features
Company Profit Prediction Based On Forecasting Of Port Throughput Using Time Series-Adaptive Neuro Fuzzy Inference System Victory Tyas Pambudi Swindiarto; Mohammad Isa Irawan
IPTEK Journal of Proceedings Series No 1 (2020): The 1st International Conference on Business and Engineering Management (IConBEM)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j23546026.y2020i1.11949

Abstract

As a maritime country, ports play an important role in economic development in Indonesia. Throughput is an important factor affecting Port Profits. This prediction is needed in an effort to find out the company's prospects, help estimate the long-term profitability of representatives, predict earnings, and estimate risk in investment. In this research, forecasting data throughput will be carried out, such as container traffic, number of ships, export traffics, goods traffic, animal flow and passenger traffic for the next year using Time Series-Adaptive Neuro Fuzzy Inference System (TS-ANFIS) as an input parameter in the decision support system. Before predicting the benefits of the port using the ANFIS method, principal component analysis (PCA) was applied to reduce parameters that did not sufficiently affect the profits of the port. The data used are time series data from 2009 to 2018. From the system built it is expected to be able to provide good results in predicting the value of port throughput using TS-ANFIS and to predict profit values using the ANFIS method. The best results from profit prediction using ANFIS obtained R2 of 0.947, RMSE of 28524582.39, MAPE of 14.74% and MAAPE of 0.145. From the prediction results, it can be used as a reference for company projections in investing, managing cash flow, managing assets and global bonds.
Analysis of Root Causes of Fire in Coal Fired Power Plant Using FMEA Study Case Method at PT. PJB UBJOM PACITAN Muchamad Jati Nugroho; M. Isa Irawan
IPTEK Journal of Proceedings Series No 3 (2020): International Conference on Management of Technology, Innovation, and Project (MOTIP) 2
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j23546026.y2020i3.11079

Abstract

Fire is one of the highest risks in using coal as fuel for electricity generation. Coal fires often occur in the area of coal handling facilities and are caused by damage to equipment, accumulation of coal dust that has not been cleaned and burning coal itself. This study aims to find out how the application of the FMEA method for the analysis of the root causes of fires in the Coal Power Plant with a case study of the Pacitan steam power plant uses a quantitative approach to find the root cause for prevention by respondents from PT. PJB UBJOM PACITAN at manager and supervisor level. In applying FMEA, the severity, events, and detection is needed to produce risk level figures which will be used as a step in determining the priorities of the company's mitigation management. Based on this study, 15 types of equipment failures were found in the operational coal handling facility at PT PJB UBJOM PACITAN. By using the FMEA method, 6 types of critical failures can be found that require more attention, namely dust on coal which has the potential to cause self-ignition, self-ignition of coal in the area, hot surface, self- combustion in coal yards and perforated crushing bodies.
Co-Authors AA. Masroeri Abduh Riski, Abduh Adrianus Bagas Tantyo Dananjaya Ahmad Ridwan Akhmad Arif Junaidi Alan Catur Nugraha Alexander Setiawan Alvida Mustika Rukmi Amira, Siti Azza Andreas Handojo Anindita Sharkar Antonio Galileo Tando Ari Kusumastuti Ari Kusumastuti Arie Dipareza Syafei Arifah, Enny Durratul Auliya Rahmayani Baiq Findiarin Billyan Chyntia Kumalasari Puteri Danang Wahyu Wicaksono Daniel Happy Putra Darmaji Darmaji Darmawan, Didiet Edi Satriyanto Ekky Hidma Octia Rahmah Elly Matul Imah Elnora Oktaviyani Gultom Elsen Ronando Erna Apriliani Fahim, Kistosil Fendhy Ongko Giandi, Oxsy Ginardi, Raden Venantius Hari Hadi Prasetiya Haloho, Freddi Hartanto Setiawan Hendy Hendy Hendy Hozairi Imam Mukhlash Imam Mukhlash Ira Puspitasari Juhari Juhari, Juhari Ketut Buda Artana Khilmy, Akhmad Ku Khalif, Ku Muhammad Naim Mahardika, Kadek Eri Mahdiyah, Umi Mardlijah - Maulana, Muhammad Agung Adi Mey Lista Tauryawati Mohamad Muhtaromi Mohammad Hamim Zajuli Al Faroby Mohammad Iqbal Mohammad Jamhuri Mohd Aziz, Mohd Khairul Bazli Mondal, Kartick Chandra Muchamad Jati Nugroho Muhammad Ahnaf Amrullah Muhammad Athoillah, Muhammad Muhammad Fakhrur Rozi Muhammad Hajarul Aswad Muhammad, Noryanti Muhammad, Noryanti binti Mujiono, Edo Priyo Utomo Putro Ni Nyoman Tri Puspaningsih Notopramono, Hanna Nugraha, Arma Perwira Nurul Anggraeni Hidayati NURUL HIDAYAT Nurul Hidayat Pratama, Qoria Yudi Putri, Endah R.M. Putri, Endah Rokhmati Merdika Putris , Nadhifa Afrinia Dwi Rasyadan Taufiq Probojati Resi Arumin Sani Rita Ambarwati Rita Ambarwati Sukmono Robin Wijaya, Robin Rohwana, Ulir Ronando, Elsen Rukmini, Meme Santoso Santoso Santoso Santoso Sepriadi, Robby Setiawan, Muhammad Nanda Setumin, Samsul Shahab, Muhammad Luthfi Siti Maghfiroh Soetrisno Soetrisno Sulastri Sulastri Titin J. Ambarwati Victory Tyas Pambudi Swindiarto YAN ADITYA PRADANA Yongky Ujianto Yuda Dian Harja Zulfa Afiq Fikriya