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Identifikasi Data Drifting pada Aplikasi Internet of Things (IoT) Yugopuspito, Pujianto; Kartika, Alessandro Luiz; Murwantara, I Made
Journal Information System Development (ISD) Vol 6, No 2 (2021): Journal Information System Development (ISD)
Publisher : UNIVERSITAS PELITA HARAPAN

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Seiring dengan perkembangan teknologi sekaligus meningkatnya kebutuhan akan informasi yang aktual dan nyata, aplikasi IoT pun terus dikembangkan dan menjadi marak di tengah masyarakat. Diperlukannya penelitian yang dapat mengevaluasi data stream yang telah ditangkap sensor dan mengidentifikasi penyimpangan data/concept drift. Penelitian ini menghasilkan dua kesimpulan, yaitu hasil pertama adalah pada tahapan evaluasi data, metode SGD Classifier yang memiliki nilai rata-rata tertinggi dibandingkan metode Hoeffding Tree dan Hoeffding Adaptive Tree pada setiap metrik. Hasil kedua adalah pada tahapan pengidentifikasian penyimpangan data/concept drift, metode Adaptive Windowing (ADWIN) lebih banyak mengidentifikasi penyimpangan data/concept drift dibandingkan dengan metode Page-Hinkley.

An adaptive IoT architecture using combination of concept-drift and dynamic software product line engineering I Made Murwantara; Pujianto Yugopuspito
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 19, No 4: August 2021
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v19i4.19012

Internet of things (IoT) architecture needs to adapt autonomously to the environment and operational to maintain their supreme services. One common problem in the IoT architecture is to manage the reliability of data services, such as sensors’ data, that only sending data to the collector via gateway. If there is a disruption of services, then it is not easy to manage the system reliability. To this, an adaptive environment which is based on software reconfiguration creates a great challenge to provide better services. In this work, the software product line engineering (SPLE) reconfigures the edge devices via rules and software architecture. To identify disruption of data services which can be detected based on anomaly and truncated data. Our work makes use of concept drift to provide a recommendation to the system manager. This is important to avoid misconfiguration in the system We demonstrate our method using an open-source internet of things portal system that integrated to a cluster of sensors which is attached to specific gateway before the data are collected into a cloud storage for further processes. In identifying drifting data, the adaptive sliding window (ADWIN) method outperforms the Page-Hinkley (PH) with more selective identification and sensitive reading.

Cluster-based water level patterns detection Friska Natalia Ferdinand; Yustinus Soelistio; Ferry Vincenttius Ferdinand; I Made Murwantara
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 17, No 3: June 2019
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v17i3.11774

Indonesian Disaster Data and Information in 2016 showed that flood has reached a soaring 32.2% overall. In one of the common flood region (2016), Tangerang, the flood had impacted 30,949, and destroys more than 400 residentials. In spite of this dreadful fact, Tangerang has no systematically ways of detecting the flood patterns. Therefore, there is urgency for a system that is able to detect potential flood risks in Tangerang. This study explores a mean to systematically find flood patterns in Tangerang and attempt to visualize the risks based on 11 years of data on four major river stations within Tangerang vicinity. All the data obtained from Ciliwung Cisadane River Basin Center (BBWS) between 2009 until 2017 with total data of 368,184 rows. This study proposes an interactive dashboard based on the water level data covering rivers of Angke, Pesanggrahan, and Cisadane. Three clustering methods are implemented, the K-Medoids, DBScan, and x-means, to segregate the water level data, taken from four stations obtained from Ciliwung Cisadane River Basin Center (BBWS), into meaningfull periodic flood patterns. The output of this research is an interactive dashboard created based on the newly found patterns. The dashboard is designed to be simple and easy to use for non-technical persons. We believe that the output of this research could be implemented into the decision-making process taken by the Ciliwung Cisadane River Basin Center (BBWS) in order to improve countermeasure attempts on the potentially flooded areas.

Comparison of machine learning performance for earthquake prediction in Indonesia using 30 years historical data I Made Murwantara; Pujianto Yugopuspito; Rickhen Hermawan
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 18, No 3: June 2020
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v18i3.14756

Indonesia resides on most earthquake region with more than 100 active volcanoes,and high number of seismic activities per year. In order to reduce the casualty, some method to predict earthquake have been developed to estimate the seismic movement. However, most prediction use only short term of historical data to predict the incoming earthquake, which has limitation on model performance. This work uses medium to long term earthquake historical data that were collected from 2 local government bodies and 8 legitimate international sources. We make an estimation of a mediumto-long term prediction via Machine Learning algorithms, which are Multinomial Logistic Regression, Support Vector Machine and Na¨ıve Bayes, and compares their performance. This work shows that the Support Vector Machine outperforms other method. We compare the Root Mean Square Error computation results that lead us into how concentrated data is around the line of best fit, where the Multinomial Logistic Regression is 0.777, Na¨ıve Bayes is 0.922 and Support Vector Machine is 0.751. In predicting future earthquake, Support Vector Machine outperforms other two methods that produce significant distance and magnitude to current earthquake report.

Towards Adaptive Sensor-cloud for Internet of Things I Made Murwantara; Hendra Tjahyadi; Pujianto Yugopuspito; Arnold Aribowo; Irene A. Lazarusli
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 16, No 6: December 2018
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v16i6.11557

The emerge of the Internet of Things (IoT) data as a commodity to optimize public services such as Fishing Locator has made sensor-cloud an important object. When sensors that are members of multiple IoT gateways can inter-operate at the same time for more than one application, it will reduce cost to deploy IoT infrastructure. However, reliability has also developed as the most important aspect for real-time data collection that should be streamed constantly. Due to uncertainty factors sensors failure is potentially occurred, then an adaptive approach should be addressed into this as to guarantee the flow of streaming data. This paper proposed an adaptive sensor-cloud mechanism to manage the reliability by using a runtime model approach where a transition model and dynamic software product line engineering will take place to weaving the system. Our technique is comparable to other approaches and can be implemented in many types of Cloud-based services.

Code Generator Python dari Bentuk XML Metadata Interchange (XMI) pada Unified Modeling Language (UML) 2.0 I Made Murwantara; Pujianto Yugopuspito; Johan Julianto Roestam
Seminar Nasional Aplikasi Teknologi Informasi (SNATI) 2005
Publisher : Jurusan Teknik Informatika, Fakultas Teknologi Industri, Universitas Islam Indonesia

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Unified Modeling Language (UML) code generator tools are available to parsing UML diagrams intosource code. Currently, UML 2.0 tools that can parse into Python’s source code are still in work planningphase. This research aims to create UML code generator that can parse XML Metadata Interchange (XMI) intoPython’s source code. XMI defines the design of program using UML 2.0 standard. Design process of thisprototype uses UML standard version 2.0. On this research, algorithm for rules of parsing XMI into Python’ssource code was created.Keywords: UML, Python, Parsing

Toward Remote Object Control Based on Python for Symbian S60 I Made Murwantara; Fanny Sinthia; Fransiscus Ati Halim
Seminar Nasional Aplikasi Teknologi Informasi (SNATI) 2007
Publisher : Jurusan Teknik Informatika, Fakultas Teknologi Industri, Universitas Islam Indonesia

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Nowadays mobile phones can be used to do various things, such as recording or watching videos,listening to music, and scheduling. With recent developments in communication technology, mobile phones iscapable to communicate with another device. A global standard to accomplish is Bluetooth. Using Bluetooth, amobile phone can communicate with other devices. The exchange of data between compatible devices is handledby the Bluetooth protocol. This makes it easy for the programmer to develop various wireless applications onmobile phones which support Bluetooth. This paper presenting the use of Bluetooth to control the movement ofan object in a computer using a mobile phone based on Symbian S60, using Python.Keywords: Symbian, S60, Bluetooth, Python, Remote Object Control.

Identifikasi Data Drifting pada Aplikasi Internet of Things (IoT) Pujianto Yugopuspito; Alessandro Luiz Kartika; I Made Murwantara
Journal Information System Development (ISD) Vol 6 No 2 (2021): Journal Information System Development (ISD)
Publisher : UNIVERSITAS PELITA HARAPAN

Show Abstract | Download Original | Original Source | Check in Google Scholar

Seiring dengan perkembangan teknologi sekaligus meningkatnya kebutuhan akan informasi yang aktual dan nyata, aplikasi IoT pun terus dikembangkan dan menjadi marak di tengah masyarakat. Diperlukannya penelitian yang dapat mengevaluasi data stream yang telah ditangkap sensor dan mengidentifikasi penyimpangan data/concept drift. Penelitian ini menghasilkan dua kesimpulan, yaitu hasil pertama adalah pada tahapan evaluasi data, metode SGD Classifier yang memiliki nilai rata-rata tertinggi dibandingkan metode Hoeffding Tree dan Hoeffding Adaptive Tree pada setiap metrik. Hasil kedua adalah pada tahapan pengidentifikasian penyimpangan data/concept drift, metode Adaptive Windowing (ADWIN) lebih banyak mengidentifikasi penyimpangan data/concept drift dibandingkan dengan metode Page-Hinkley.

Quality Attributes Decision Modeling for Software Product Line Architecture I Made Murwantara
Seminar Nasional Teknologi Informasi Komunikasi dan Industri 2011: SNTIKI 3
Publisher : UIN Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (362.957 KB)

Decision modeling is one of the most prominent activity for architecture design of a software product line architecture. The decision modeling supports the selection of suitable composition of software components from the architecture of member products of a product line. However, only little effort have been devoted to quality attributes. To address this shortcoming, this paper present a method that hybrid the Analytical Hierarchy Process and the Formal Concept Analysis. The key issue of decision modeling that assessing a quality attributes of an architecture configuration is to measure the impact of a quality attributes that made by the set of components. In this paper, we analyze the software components composition that corresponds to the quality attributes. An illustrative example based on the e-Learning software product line is presented to demonstrate of how the proposed approach works. Keywords: Software Product Line, Product Line Architecture, Decision Modeling, Analytical Hierarchy Process, Formal Concept Analysis, Software Architecture Design

PENGEMBANGAN SENSOR-CLOUD PADA SMART CITY UNTUK MENGHADIRKAN KETERSEDIAAN DATA WAKTU NYATA I Made Murwantara
Journal Information System Development (ISD) Vol 7 No 2 (2022): Journal Information System Development (ISD)
Publisher : UNIVERSITAS PELITA HARAPAN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19166/isd.v7i2.557

Pengembangan dan operasional dari sebuah Smart-City bergantung sepenuhnya pada lebih dari satu kelompok sumber data waktu nyata. Bentuk integrasi data ini kemungkinan dapat terwujud melalui manajemen Sensor-Fusion. Sumber daya utama untuk mencapai tujuan ini adalah denga keberadaan suatu kelompok sensor virtual yang dapat dipercaya kinerjanya yang adaptif terhadap perubahan lingkungan seperti permasalahan pengiriman data. Kestabilan operasional dari jaringan sensor harus dikedepankan karena sistem ini bergantung pada kondisi stabil tersebut. Menanggapi hal tersebut, suatu sistem waktu nyata yang terintegrasi secara kompleks atau rumit, umumnya, mengalami ketidakstabilan pengaliran data yang berakibat pada munculnya faktor penyimpangan. Dalam artikel ini, suatu pemikiran mengenai Sensor-Cloud yang menyediakan layanan pengaliran data waktu nyata dengan dasar berpikir bentuk virtualisasi akan diutarakan. Suatu pendekatan dengan konsep utama kombinasi dari Komputasi Awan, Internet of Things dan Akusisi data diajukan. Suatu demonstrasi sederhana untuk memperlihatkan kemampuan dari hasil penelitian ini akan diperlihatkan.

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