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All Journal Lontar Komputer: Jurnal Ilmiah Teknologi Informasi Jurnal Teknik ITS IPTEK Journal of Proceedings Series IPTEK The Journal for Technology and Science TELKOMNIKA (Telecommunication Computing Electronics and Control) JUTI: Jurnal Ilmiah Teknologi Informasi Jurnal Ilmiah Kursor Scan : Jurnal Teknologi Informasi dan Komunikasi Jurnal EECCIS Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Edukasi dan Penelitian Informatika (JEPIN) REKAYASA Journal of Information Systems Engineering and Business Intelligence Jurnal IPTEK Register: Jurnal Ilmiah Teknologi Sistem Informasi PROCEEDING IC-ITECHS 2014 Jurnal Inspiration Proceeding of the Electrical Engineering Computer Science and Informatics E-Dimas: Jurnal Pengabdian kepada Masyarakat Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer Digital Zone: Jurnal Teknologi Informasi dan Komunikasi CSRID (Computer Science Research and Its Development Journal) Melek IT: Information Technology Journal MATHunesa: Jurnal Ilmiah Matematika Jurnal Sistem Informasi Bisnis (JUNSIBI) Jurnal Nasional Teknik Elektro dan Teknologi Informasi Sewagati Jurnal Ilmu Sosial, Humaniora dan Seni Jurnal INFOTEL Journal of Information Technology and Cyber Security
Daniel Oranova Siahaan
Departemen Teknik Informatika Institut Teknologi Sepuluh Nopember Surabaya
Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Mechanical Engineering Physics Public Health Social Sciences Other

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Weighted k Nearest Neighbor Using Grey Relational Analysis To Solve Missing Value Desepta Isna Ulumi; Daniel Siahaan
IPTEK The Journal for Technology and Science Vol 29, No 3 (2018)
Publisher : IPTEK, LPPM, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (497.699 KB) | DOI: 10.12962/j20882033.v29i3.5011

Abstract

Software defect prediction model is an important role in detecting the most vulnerable component error software. Some research have been worked to improve the accuracy of the prediction defects of the software in order to manage human, costs and time. But previous research used specific dataset for software defect prediction model. However, there is no a generic dataset handling for software defect prediction model yet. This research proposed improvements to the results of the software defect prediction on the merged dataset, which is called generic dataset, with a number of different features. In order to balance the number of features, each dataset should be filled with a missing value. To fill the missing values, Weighted k Nearest Neighbor (WkNN) method was used. Then, after missing values were filled, Naïve Bayes was used to classify the selected features. This research needed to obtain a set of features which was relevant, then performed a feature selection method. The results showed that by using seven NASA public MDP datasets, Naïve Bayes with Information Gain (IG) or Symmetric Uncertainty (SU) feature selection presented the best balance value.Software defect, NASA public MDP, weighted KNN,Naive Bayes
Web-Based Tsunami Early Warning System Daniel Siahaan; Royke Wenas; Amien Widodo; Umi Yuhana
IPTEK The Journal for Technology and Science Vol 24, No 3 (2013)
Publisher : IPTEK, LPPM, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j20882033.v24i3.552

Abstract

Tsunami is a serious threat to the island nation such as Indonesia. The tsunami disasters that were occurred in some parts of Indonesia have immerged the need for tsunami early warning system that is reliable and can be applied to the Indonesian archipelago. North Sulawesi is one of the areas prone to tsunamis since this area lies in the path called the ring of fire's. This article describes a tsunami simulation application for the north coast of North Sulawesi. Web-based applications were built so that they can be monitored online from anywhere and at anytime. This system reads the real-time seismic data that affect the North Sulawesi region from a number of sources. Dynamic and static data that are received are processed using data mining method to predict the chances of a tsunami, while flood flooding algorithm is used to visualize the map of affected areas of North Sulawesi. The resulting information is available in detail in the form of web pages and also through short message to the relevant authorities handling of the tsunami disaster in order for them to act in accordance with applicable standard operating procedures. With this application, the public can obtain information that is more accurate. Relevant authorities can conduct tsunami disaster mitigation measures more effectively.
Algorithms Comparison for Non-Requirements Classification using the Semantic Feature of Software Requirement Statements Achmad An'im Fahmi; Daniel Siahaan
IPTEK The Journal for Technology and Science Vol 31, No 3 (2020)
Publisher : IPTEK, LPPM, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j20882033.v31i3.7606

Abstract

Noise in a Software Requirements Specification (SRS) is an irrelevant requirements statement or a non-requirements statement. This can be confusing to the reader and can have negative repercussions in later stages of software development. This study proposes a classification model to detect the second type of noise, the non-requirements statement. The classification model that is built is based on the semantic features of the non-requirements statement. This research also compares the five best-supervised machine learning methods to date, which are support vector machine (SVM), naïve Bayes (NB), random forest (RF), k-nearest neighbor (kNN), and Decision Tree. This comparison aimed to determine which method can produce the best non-requirements classification, model. The comparison shows that the best model is produced by the SVM method with an average accuracy of 0.96. The most significant features in this non-requirement classification model are the requirements statement or non-requirements, id statement, normalized mean value, standard deviation value, similarity variant value, standard deviation normalization value, maximum normalized value, similarity variant normalization value, value Bad NN, mean value, number of sentences, bad VB score, and project id.
Metrik Ergonomi Untuk Produk Perangkat Lunak Permainan Pada Aspek Kenyamanan Arif Susanto; Daniel Oranova Siahaan
Melek IT : Information Technology Journal Vol. 1 No. 1 (2015): Melek IT : Information Technology Journal
Publisher : Informatics Engineering Department-UWKS

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (244.866 KB) | DOI: 10.30742/melekitjournal.v1i1.35

Abstract

It is inevitable that humans have a limited ability to interact with a product or technology that is made. Limitations on the human body is the reason the importance of ergonomic aspects need to be implemented in the design of a product. In the field of information technology, research-related metric ergonomics of a product has been focused on hardware products, such as mouse, monitor and keyboard. This study builds a metric measurement of ergonomic comfort aspect to the game software products. This study primarily consists of several steps. First, an analysis of ergonomic aspects in comfort. Second, these aspects are mapped into the attributes that exist in software quality models like McCall, Boehm and ISO 9126/25010. Third, the preparation of ergonomics metrics based on an analysis of the test results in previous stages. Attributes that are considered relevant as a reference for the testing of the game software. Game software predetermined expert / expert tested the user directly to the start of the installation process until the stage play of the game software. From the analysis of the proposed ergonomics testing metrics, generated 11 software attributes offline games based desktop that can characterize whether a software-based desktop offline games comfortable or not.
Perbaikan Model Kebergunaan Pada Aplikasi Perangkat Bergerak Dengan Menambahkan Atribut Gejala Buruk Cahya Bagus Sanjaya; Daniel Siahaan
Melek IT : Information Technology Journal Vol. 1 No. 2 (2015): Melek IT : Information Technology Journal
Publisher : Informatics Engineering Department-UWKS

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (617.027 KB) | DOI: 10.30742/melekitjournal.v1i2.47

Abstract

Usability is a very important aspect and one of the key factors for the successful mobile application. Usability is an attribute to define the quality of user interface and the quality of interaction between user and application. Models to measure the usability of desktop application can not directly be used for mobile applications because of the differences between the characteristics of desktop applications and mobile applications. Previous research developed a model to measure usability on a mobile application. Somehow, it lacks recommendations for new user interface usability evaluation of the mobile application that is being measured and there is no weighting for each attribute. This study combines qualitative primary data taken from questionnaires and quantitative secondary data taken from the activity logs application (Bad Symptoms) when user run mobile application. Weighting for each attribute is done by an expert of mobile applications. Analytical Hierarchy Process (AHP) Method is used to analyze experimental data. Result from this research is a novel model to measure usability for mobile application that have a weight to each usability attributes and provides recommendation for improvement of existing user interfaces.
Peningkatan Kompetensi Guru-Guru Playgroup Dan TK Sepuluh Nopember Surabaya Melalui Pelatihan TIK Ahmad Saikhu; Daniel Oranova Siahaan; FX Arunanto; Rully Soelaiman; Fajar Baskoro
Sewagati Vol 5 No 1 (2021)
Publisher : Pusat Publikasi ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (874.427 KB)

Abstract

Keberadaan Playgroup dan Taman Kanak-kanak Sepuluh Nopember merupakan bagian dari sejarah panjang eksistensi perumahan dosen dan karyawan ITS. Awalnya lembaga ini didirikan atas inisiatif Dharma Wanita Unit ITS untuk mengakomodasi kebutuhan sekolah taman kanak-kanak bagi dosen dan karyawan ITS yang berdomisili di perumahan dinas ITS Keputih Sukolilo Surabaya. Sehingga lembaga ini pun dinamakan Taman Kanak-kanak Dharma Wanita ITS. Namun seiring dengan perkembangan wilayah Kecamatan Sukolilo, khususnya di Kelurahan Keputih yang begitu pesat dengan munculnya banyak pemukiman baru, maka siswa taman kanak-kanak inipun berkembang dengan menerima siswa-siswa dari luar perumahan dinas ITS. Dengan munculnya kebutuhan belajar bagi anak-anak balita, maka lembaga ini berkembang dengan membuka kelas playgroup. Untuk pengembangan kurikulum pengajarannya, selain berdasarkan ketentuan dan panduan yang dikeluarkan oleh Dinas Pendidikan Provinsi Jawa Timur, lembaga ini dapat menambahkan konten-konten pengajaran yang sesuai dengan karakteristik lembaga ini sendiri. Dalam kesempatan melaksanakan kegiatan pengabdian kepada masyarakat kali ini diajarkan kepada guru-guru playgroup dan Taman Kanak-kanak Sepuluh Nopember tentang merancang pembelajaran dengan memanfaatkan programmable robot untuk anak-anak. Kegiatan pembelajaran dengan menggunakan robot ini akan menarik minat anak-anak untuk secara tidak langsung mengenal dasar-dasar pemikiran yang terstruktur. Sementara dalam pelaksanaannya juga tidak tidak memerlukan investasi yang besar. Hanya cukup dengan seperangkat programmable robot beserta buku panduan untuk memprogramnya menggunakan Scratch.
KLASIFIKASI KEBUTUHAN PERANGKAT LUNAK BERDASARKAN KATEGORI ISO/IEC 25000 MENGGUNAKAN TEXTRANK DAN SVM Mutia Rahmi Dewi; Fatimatus Zulfa; Dady Khairul Imam; Daniel Oranova Siahaan
Jurnal Sistem Informasi Bisnis (JUNSIBI) Vol 4 No 2 (2023): Jurnal Sistem Informasi Bisnis (JUNSIBI)
Publisher : Program Studi Sistem Informasi Institut Bisnis dan Informatika (IBI) Kosgoro 1957

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55122/junsibi.v4i2.736

Abstract

Perancangan kebutuhan perangkat lunak merupakan langkah pertama yang harus dilakukan dalam perencanaan membangun perangkat lunak. Untuk mempermudah melakukan analisis, kebutuhan perangkat lunak dapat dikategorikan ke dalam standar kualitas. Salah satu standar kualitas dapat menggunakan ISO/IEC 25000. Seri ISO/IEC 25000 terdiri dari 8 karakteristik yaitu Functional Suitability, Performance Efficiency, Compatibility, Usability, Reliability, Security, Maintainability, dan Portability. Untuk mempermudah dan mempercepat analisis diperlukan klasifikasi secara otomatis. Berbagai metode klasifikasi terhadap standar kualitas kebutuhan perangkat lunak telah diusulkan. Pada penelitian ini, melakukan ekstraksi kata kunci dari kebutuhan perangkat lunak menggunakan metode TextRank untuk melakukan klasifikasi terhadap standar kualitas ISO/IEC 25000. Kata kunci yang telah diekstraksi mewakili istilah pada kebutuhan perangkat lunak. Sebanyak 154 kebutuhan dari 5 perangkat lunak diekstraksi menjadi 66 kata kunci yang akan digunakan untuk melakukan klasifikasi terhadap standar kualitas ISO/IEC 25000. Pada penelitian ini, didapatkan hasil presisi sebesar 83% dan recall sebesar 80.3% dengan menggunakan klasifikasi Support Vector Machine (SVM).
Perbaikan Prediksi Kesalahan Perangkat Lunak Menggunakan Seleksi Fitur dan Cluster-Based Classification Fachrul Pralienka Bani Muhamad; Daniel Oranova Siahaan; Chastine Fatichah
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 6 No 3: Agustus 2017
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1356.057 KB)

Abstract

High balance value of software fault prediction can help in conducting test effort, saving test costs, saving test resources, and improving software quality. Balance values in software fault prediction need to be considered, as in most cases, the class distribution of true and false in the software fault data set tends to be unbalanced. The balance value is obtained from trade-off between probability detection (pd) and probability false alarm (pf). Previous researchers had proposed Cluster-Based Classification (CBC) method which was integrated with Entropy-Based Discretization (EBD). However, predictive models with irrelevant and redundant features in data sets can decrease balance value. This study proposes improvement of software fault prediction outcomes on CBC by integrating feature selection methods. Some feature selection methods are integrated with CBC, i.e. Information Gain (IG), Gain Ration (GR), One-R (OR), Relief-F (RFF), and Symmetric Uncertainty (SU). The result shows that combination of CBC with IG gives best average balance value, compared to other feature selection methods used in this research. Using five NASA public MDP data sets, the combination of IG and CBC generates 63.91% average of balance, while CBC method without feature selection produce 54.79% average of balance. It shows that IG can increase CBC balance average by 9.12%.
Peningkatan Akurasi Estimasi Usaha dan Biaya COCOMO II Berdasarkan Gaussian dan BCO Rahmi Rizkiana Putri; Daniel Oranova Siahaan; Sarwosri
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 6 No 3: Agustus 2017
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1057.183 KB)

Abstract

An accurate effort and cost estimation provides good management for software projects. Less accurate estimation will affect the management of the software project and cause the ineffectiveness of the project development process. The addition of cost driver, introduced by Barry Boehm in 2000, is used in this paper to provide better accuracy, because it has covered the entire section in the estimation. However, in this paper, the accuracy of effort and cost estimation by COCOMO II Fuzzy Gaussian method is still far from actual effort. Therefore, the accuracy can still be increased using Bee Colony Optimization (BCO), as seen in the MMRE loyal results. The value of parameter A and B on COCOMO II is also changed with the initial gradual of 0.01 to give optimal value on a certain gradual. Based on the result of the implementation, the error accuracy of effort estimation and software project cost is reduced by 38%, compared to previous research. In conclusion, the proposed method can increase the accuracy of effort and cost estimation.
Ekstraksi Informasi Terkait Kebutuhan Perangkat Lunak dari Berita Daring dengan Menggunakan DomText-WMDS Mutia Rahmi Dewi; Indra Kharisma Raharjana; Daniel Siahaan; Nurul Jannah
JURNAL INFOTEL Vol 15 No 3 (2023): August 2023
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v15i3.950

Abstract

Currently, there are not many studies that assess software requirements extraction from non-software artifacts. Most of the research in these related areas are focuses on software artifacts such as project descriptions or user reviews as a source of requirements extraction. This research aims to identify relevant information to the software requirements from online news using the vector space model. This software requirements-related information can assist systems analysts in discovering the problem domain based on the lesson learned presented by stakeholders in online news. This research proposes DomText-WMDS to extract requirements-related information from online news. We used online news and public software requirements specification dataset to develop software-specific vocabulary using domain specificity technique. Then we expanded the specific vocabulary software to obtain more comprehensive results by building vector space model from online news documents. This updated version of software-specific vocabulary can be used for basic filtering of software requirements-related information that previously extracted using the part-of-speech (POS) chunking. This study improved the performance for extracting software requirements-related information, with precision and recall 61.09% and 60.66% compared to domain specificity approach that only manages to obtain 43.34% and 40.78%.
Co-Authors Aang Kisnu Darmawan Abd. Rasyid Syamsuri Achmad An'im Fahmi Achmad, Fariz Adi Kurniawan Aditya Eka Bagaskara Ahmad Saikhu Ahmadiyah, Adhatus Solichah Akbar, Rizky Januar Albert Bungaran Manik Amalia, Rosa Amien Widodo Andi Besse Firdausiah Andini Prastiwi Andrias Meisyal Yuwantoko Ansyah, Adi Surya Suwardi Anwari Anwari Anwari, Anwari Arif Djunaidy Arif Susanto Arif Wibisono Asyrofi, Raka Baskoro, Fajar Bawamenewi, Yuliaman Busro Umam Cahya Bagus Sanjaya Chastine Fatichah Dady Khairul Imam Damanik, Juli Yanti Darnoto, Brian Depandi Enda Desepta Isna Ulumi Dian Saputra Diana Purwitasari Divi Galih Prasetyo Putri Dzhalila, Dzhillan Eko Prasetyo Esti Yuniar Evi Triandini F.X. Arunanto Fachrul Pralienka Bani Muhamad Fachrul Pralienka Bani Muhamad Fajar Baskoro Fajar Baskoro Fatimatus Zulfa Ferdika Bagus Permana FX Arunanto Ghipari, Maulana Halawa, Enggi Hamidi, Mohammad Zaenuddin Hoiriyah Hoiriyah Hoiriyah, Hoiriyah I Gede Suardika I Made Mika Parwita Imam Kuswardayan Indra Kharisma Raharjana Irfandianto, Taqarra Rayhan Irsyad Arif Mashudi Istighfar, Muhammad Bagus Ivan Agung Pandapotan izqi Paradisiaca , Brian R Joko Prasetyo Karimi, Muhammad Ihsan Karolita, Devi Kusuma, Selvia Ferdiana Luh Putu Ary Sri Tjahyanti Manek, Patricia Gertrudis Mauladani, Furqon Maulida, Ainatul Mirotus Solekhah Mohammad Nazir Arifin Muhamad, Fachrul Pralienka Bani Muhammad Dery Rahma Muhammad Ihsan Karimi Mutia Rahmi Dewi Nafi', Abdun Nafingatun Ngaliah Nanang Fakhrur Rozi Nugroho, Tri Yulianto Nuralamsyah, Bintang Nurul Fajrin Ariyani Nurul Jannah Pasaribu, Monalisa Peter Gelu Pratama Wirya Atmaja Putra Kurniawan, Arya Putri, Rahmi Rizkiana Rahmi Rizkiana Putri Rakhmat Arianto Ramadhani, Nia Ratih Nur Esti Anggraini, Ratih Nur Esti Reza Fauzan Reza Fauzan Richard Alvin Sianturi Riduwan, Muhammad Risnauli Sumiati Sinaga Riyanarto Sarno Rizky Januar Akbar Royke Wenas Rully Soelaiman Rully Soelaiman Safitri, Winda Ayu Samosir, Hernawati Sari Sahadi, Fitria Vera Sarwosri Sarwosri Sarwosri Sarwosri Sarwosri Satrio Agung Wicaksono Shiddiqi, Ary Mazharuddin Siahaan, Gabriel Silaban, Monica Sinaga, Hasan Siti Rochimah Sitohang, Francisko Situmorang, Andreas Supriyanto, Ricky Tiurma Lumban Gaol Tony Dwi Susanto Toshihiro Kita Umam, Busro Umami, Izzatul Umi Yuhana Utomo Pujianto Vriza Wahyu Saputra Welly Purnomo Yuhana, Umi Laili Yuhana, Umi Laili Yunata Dede Pratiwi