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Rekomendasi Perancangan Arsitektur Enterprise Pascamerger (Studi kasus: Universitas Telkom) Indra Lukmana Sardi; Kridanto Surendro
Indonesia Journal on Computing (Indo-JC) Vol. 1 No. 1 (2016): March, 2016
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21108/INDOJC.2016.1.1.23

Abstract

Merger merupakan kombinasi dari dua atau lebih perusahaan menjadi sebuah perusahaan tunggal yang mencakup akuisi serta bentuk lain dari penggabungan. Proses merger memiliki banyak tantangan pada tahap integrasi pascamerger (Trautwein, 1990). Proses integrasi dapat memicu berbagai masalah dan perubahan. Integrasi yang tidak baik dapat menyebabkan kegagalan pada proses merger secara keseluruhan (Shrivastava, 1986). Penelitian ini mencoba melakukan analisis dan merumuskan rekomendasi perancangan Arsitektur enterprise, yang dapat menanggulangi masalah-masalah yang akan muncul pada tahap integrasi pascaproses merger.  Dengan adanya perancangan arsitektur enterprise yang baik, diharapkan terwujudnya keselarasan antara teknologi informasi dan kebutuhan bisnis. Dengan menggunakan pendekatan tata kelola TI dan TOGAF ADM, maka dirancang tahapan-tahapan Arsiterktur enterprise yang terdiri dari Fase A Arsitektur Visi, Fase B Arsitektur Bisnis, Fase C Arsitektur Sistem Informasi, Fase D Arsitektur Teknologi, dan Fase E Peluang dan solusi. Akhirnya, penelitian ini dapat menghasilkan langkah dan hal penting yang perlu diperhatikan pascaproses merger pada sebuah perguruan tinggi.
ESTABLISHING MICROSOFT RESEARCH CENTRE IN INDONESIA: A ROAD PATH TOWARD EXPORTING INDONESIAN SOFTWARE Nurhajati Ma'mun; Wawan Dhewanto; Ronaldi Ronaldi; Kridanto Surendro; Basuki Sugiharto
Jurnal Teknobisnis Vol 2, No 1 (2006): Jurnal TEKNOBISNIS
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat- Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1189.903 KB) | DOI: 10.12962/j24609463.v2i1.2818

Abstract

Entering the 21st century, information and communication technolou (ICT) has become an un-separated part in daily human activities. ICT business has become the means in creating wealth and welfare for those commanding this technology. Indonesia with her abundance of people could have compete and create a mass of entrepreneurs in the ICT business. Lack of human development and other causes have brought Indonesia to become merely just user and buyer in the thriving business. The Government of Indonesia has long realized this and has made some efforts in closing the gap. President Yudhoyono 's visit the USA in 2005 has brought an early discussion whether Microsoft will open its research centre in Indonesia. The discussion arouse to a level that in the future Indonesia would able to export its software to the world market. There are steps to be taken and resources to be prepared. There are certain constrains for Indonesia to rise as the world software powerhouse in the future, including the ever changing environment of the software market, as some regard as maelstrom effect. This paper describes the steps should be taken to establish the Microsoft Research Centre in Indonesia and the link to make Indonesia as a world software exporter.
PEMODELAN REQUIREMENTS DALAM MENGKONSTRUKSI PERANGKAT LUNAK SELF-ADAPTIVE Aradea Aradea; Iping Supriana; Kridanto Surendro
Jurnal Ilmiah Teknologi Infomasi Terapan Vol. 2 No. 3 (2016)
Publisher : Universitas Widyatama

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (643.331 KB) | DOI: 10.33197/jitter.vol2.iss3.2016.106

Abstract

[Id]Mengkonstruksi perangkat lunak self-adaptive sangat berbeda dengan mengkonstruksi perangkat lunak non self-adaptive, hal ini menuntut banyak cara yang harus ditempuh untuk mencapai tujuan tersebut. Salah satunya adalah pada tahapan pemodelan requirements. Pendekatan yang digunakan saat melakukan pemodelan requirements untuk perangkat lunak self-adaptive, tidak cukup hanya menangkap kebutuhan sesuai dengan kondisi systems-as-is. Namun kebutuhan systems-to-be yang berhubungan dengan spesifikasi perilaku, dan kemampuannya untuk menangani perubahan ketika sistem sedang berjalan, merupakan faktor penting yang harus terpenuhi. Makalah ini membahas pemodelan requirements untuk mengembangkan self-adaptive systems, dengan mengintegrasikan pendekatan goal oriented requirements engineering dan feedback loop. Diawali dengan latar belakang, kemudian menguraikan penelitian terkait, dilanjutkan dengan konsep yang diusulkan beserta contoh penerapannya, dan diakhir bahasan kami menguraikan pekerjaan untuk masa depan serta kesimpulan.Kata kunci:Requirements modeling, goal oriented requirements engineering, self-adaptive systems, feedback loop[En]Construction of self-adaptive software is very different with the construction of non-self-adaptive software, its require many ways that must be through to gain these goals. one of them is on the requirement of modelling phase. The approach that used, when conduct modelling requirement is not enough to catch the needs appropriate with as-is system condition, but the requirement of to-be systems that connected with behaviour specification and its ability to handle transformation when system running is an important factor that must be fulfilled. this paper describes requirement modelling to develop self-adaptive systems, with goal oriented engineering integration approach and loop feedback. Started with the background, then untangle related research, continued with proposed concept and its implementation example, and in the last description, we untangle conclusion and our future works.Keywords: Requirements modeling, goal oriented requirements engineering, self-adaptive systems, feedback loop
Computing Game and Learning State in Serious Game for Learning Ririn Dwi Agustin; Ayu Purwarianti; Kridanto Surendro; Iping S Suwardi
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 13, No 4: December 2015
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v13i4.2248

Abstract

In order to support the adaptive SGfL, teaching materials must be represented in game component that becomes the target of adaptivity. If adaptive architecture of the game only use game state (GS) to recognize player's state, SGfL require another indicator -learning state (LS)- to identify the learning progress. It is a necessary to formulate computational framework for both states in SGfL.The computational framework was divided into two moduls, macro-strategy and micro-strategy. Macro-strategy control the learning path based on learning map in AND-OR Graph data stucture. This paper focus on the Macro-strategy modul, that using online, direct, and centralized adaptivity method. The adaptivity in game has five components as its target. Based on those targets, eight development models of SGfL concept was enumerated. With similarity and difference analysis toward possibility of united LS and GS in computational framework to implement the nine SGfL concept into design and application, there are three groups of the development models i.e. (1) better united GS and LS, (2) must manage LS and GS as different entity, and (3) can choose whether to be united or not. In the model which is united LS with GS, computing model at the macro-strategy modul use and-or graph and forward chaining. However, in the opposite case, macro-strategy requires two intelligent computing solutions, those are and-or graph with forward chaining to manage LS collaborated with Finite State Automata to manage GS. The proposed computational framework of SGfL was resulted from the similarity and difference analysis toward all possible representations of teaching materials into the adaptive components of the game. It was not dependent of type of learning domain and also of the game genre.
Feature selection to increase the random forest method performance on high dimensional data Maria Irmina Prasetiyowati; Nur Ulfa Maulidevi; Kridanto Surendro
International Journal of Advances in Intelligent Informatics Vol 6, No 3 (2020): November 2020
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/ijain.v6i3.471

Abstract

Random Forest is a supervised classification method based on bagging (Bootstrap aggregating) Breiman and random selection of features. The choice of features randomly assigned to the Random Forest makes it possible that the selected feature is not necessarily informative. So it is necessary to select features in the Random Forest. The purpose of choosing this feature is to select an optimal subset of features that contain valuable information in the hope of accelerating the performance of the Random Forest method. Mainly for the execution of high-dimensional datasets such as the Parkinson, CNAE-9, and Urban Land Cover dataset. The feature selection is done using the Correlation-Based Feature Selection method, using the BestFirst method. Tests were carried out 30 times using the K-Cross Fold Validation value of 10 and dividing the dataset into 70% training and 30% testing. The experiments using the Parkinson dataset obtained a time difference of 0.27 and 0.28 seconds faster than using the Random Forest method without feature selection. Likewise, the trials in the Urban Land Cover dataset had 0.04 and 0.03 seconds, while for the CNAE-9 dataset, the difference time was 2.23 and 2.81 faster than using the Random Forest method without feature selection. These experiments showed that the Random Forest processes are faster when using the first feature selection. Likewise, the accuracy value increased in the two previous experiments, while only the CNAE-9 dataset experiment gets a lower accuracy. This research’s benefits is by first performing feature selection steps using the Correlation-Base Feature Selection method can increase the speed of performance and accuracy of the Random Forest method on high-dimensional data.
ANALISIS DATA TRACER STUDY DENGAN MENGIDENTIFIKASI OUTLIER MENGGUNAKAN TEKNIK DATA MINING Dwi Welly Sukma Nirad; Kridanto Surendro
Jurnal Momentum ISSN 1693-752X Vol 20, No 2 (2018): Volume 20 No. 2 Agustus 2018
Publisher : ITP Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (170.108 KB)

Abstract

Melakukan drop out ataupun permintaan pengunduran diri terhadap mahasiswa merupakan salah satu hal yang dihindari oleh perguruan tinggi karena dapat mempengaruhi rating dan penilaian terhadap kampus. Perguruan tinggi akan meminta mahasiswa mengundurkan diri berdasarkan beberapa ketentuan, salah satunya jika nilai mahasiswa terbilang sangat rendah. Mahasiswa dengan nilai rendah diasumsikan tidak akan meraih penghasilan yang tinggi di masa depan, atau disebut tidak sukses. Oleh karenanya penelitian ini mengangkat data tracer study, sehingga bisa terlihat apakah asumsi tersebut tepat. Alumni yang drop out atau mengundurkan diri tetapi mampu memperoleh penghasilan tinggi ditentukan sebagai standar outlier dalam penelitian ini. Data outlier diperoleh dengan menggunakan teknik data mining, yaitu teknik association rule mining. Teknik ini membantu menemukan rule yang tepat dalam menentukan mahasiswa outlier. Hasil penelitian menunjukkan validitas derajat mahasiswa outlier serta rekomendasi keputusan untuk perguruan tinggi dalam menangani mahasiswa yang teridentifikasi sebagai outlier.