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All Journal International Journal of Advances in Applied Sciences IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Jurnal Informatika Jurnal Sarjana Teknik Informatika Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) International Journal of Advances in Intelligent Informatics Annual Research Seminar JITTER (Jurnal Ilmiah Teknologi Informasi Terapan) Jurnal Pemberdayaan: Publikasi Hasil Pengabdian Kepada Masyarakat Jurnal Informatika dan Rekayasa Perangkat Lunak
Ardiansyah, Ardiansyah
Universitas Ahmad Dahlan
Arts Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Earth & Planetary Sciences Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Social Sciences Other

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Journal : international journal of advances in intelligent informatics

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Analogy-based model for software project effort estimation Ardiansyah Ardiansyah; Murein Miksa Mardhia; Sri Handayaningsih
International Journal of Advances in Intelligent Informatics Vol 4, No 3 (2018): November 2018
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/ijain.v4i3.266

Abstract

Accurate effort estimation of software development plays an important role to predict how much effort should be prepared during the works of a software project so that it can be completed on time and budget. Some sectors, e.g. banking sectors, were renowned fields of software projects, not only due to its huge size of project, but also extremely expensive and takes a long time to completion. Project estimation is essential for software development project able to run on time and budget with maximum quality. This study aims to investigate the accuracy of software project effort estimation with the Analogy method using three parameters: Euclidean, Manhattan and Minkowski distance. Analogy based estimation consists several stage included similarity measure, analogy adaptation, estimation calculation and model evaluation. The results showed that the best combination of Analogy methods was using Manhattan distance with an accuracy of 50% MMRE, 28% MdMRE and Pred(25) 48%. Thus, we can concluded that this model can be used to predict accurately.
Optimizing Complexity Weight Parameter of Use Case Points Estimation using Particle Swarm Optimization Ardiansyah Ardiansyah
International Journal of Advances in Intelligent Informatics Vol 8, No 2 (2022): July 2022
Publisher : Universitas Ahmad Dahlan

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

Abstract

Among algorithmic-based software development effort estimation frameworks available, Use Case Points is one of the most used. Use Case Points is a well-known estimation framework designed mainly for object-oriented projects. Nevertheless, use case complexity weight is discontinuous, which can sometimes result in inaccurate measurements and abrupt classification of use case. This study investigates the potential of integrating particle swarm optimization with the Use Case Points framework, where PSO is utilized to optimize the modified use case complexity weight parameter. We designed and conducted an experiment based on real-life data set from three software houses. The accuracy and performance evaluation of the proposed model is compared with other published results, which are standardized accuracy, effect size, mean balanced residual error, mean inverted balanced residual error, and mean absolute error. Experimental results show that the proposed model generates the best value of standardized accuracy of 99.27% and an effect size of 1.15 over the benchmark models. The results of our study are promising for researchers and practitioners because the proposed model is actually estimating, not guessing, and generating meaningful estimation with statistically and practically significant.
Co-Authors Ajeng Wulandari Alfiana Novi Aulia Aman Fitrullah Anang Purnomo Angga Ibnu Barata Azhari, Ahmad Bestian Nur Affan Didit Setia Budi Efendi, Fery Sofian Eka Pitriyani Fajar Apriyanto Fajar Eko Susilo Fery Sofian Efendi Fiftin Noviyanto Fitrullah, Aman Furgandini Rencang Pambajeng Guntoro Guntoro Hendro Steven Tempake Indah Sawitri Ramonasari Leliyana, leni Riska Mateus Pinto Maulana, Suhadi Muhammad Imam Ghazali Muhammad Nur Widya Luthfiantoro Muhammad Renardi Haris Murein Mardhia Murein Miksa Mardhia Pinto, Mateus Pujianto Pujianto Pujianto, Pujianto Sasti Yudho Lukito Aji Siti Sariyanti Siti Wasilatus Sangadah Sri Handayaningsih Supriyanto Syaifullah Syaifullah Syaifullah, Syaifullah Tempake, Hendro Steven Tole Sutikno Tri Wahono Wahyuputra, lalu Bintang Widia Ningsih, Widia Zaka Ricky Soleh