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All Journal Compiler Jurnal Teknik Informatika (JUTIF)
Sambath, Khoem
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Computer Science & IT

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Implementation of Extreme Programming and Simple Additive Weighting for Web-Based Sales and Product Preference Analysis in Traditional Herbal Businesses Sumardiono, Sumardiono; Priyadi, Wiwit; Wicaksono, Harjunadi; Santosa, Hadi; Sambath, Khoem; Liefalza, Andi Daffa
Compiler Vol 14, No 1 (2025): May
Publisher : Institut Teknologi Dirgantara Adisutjipto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28989/compiler.v14i1.2966

Abstract

The rapid development of information technology encourages UMKM to adopt digital solutions to improve business effectiveness. This study aims to design a web-based herbal medicine sales information system at UMKM Griya Jamoe Klasik using the Extreme Programming (XP) method and implementing the Simple Additive Weighting (SAW) algorithm to analyze the best-selling herbal medicine products. The research approach used is quantitative descriptive, with data collection methods through observation, interviews, and questionnaires to 10 respondents over a period of one week. The criteria used in the analysis include price, taste, efficacy, and texture, each given a certain weight. The results of the SAW algorithm application show that the "Wedang Kencur" product is the best-selling herbal medicine with a preference value of 0.92, followed by "Wedang Mpon-mpon" at 0.85 and "Kunyit Asam" at 0.79. The system built is able to automate transaction recording, facilitate sales monitoring, and support accurate and fast data-based decision-making. This research contributes to increasing the competitiveness of UMKM in the digital era. Recommendations for further research are to expand the number of respondents, integrate online payment features, and develop mobile-based applications to reach a wider market.
Optimization of Software Effort Estimation Using Hybrid Consistent Fuzzy Preference Relation and Least Squares Support Vector Machine Lestari, Ika Indah; Purwanto, Adnan; Sulistiyasni, Sulistiyasni; Sambath, Khoem
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 6 (2025): JUTIF Volume 6, Number 6, Desember 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.6.5465

Abstract

The success of software project management hinges on the ability to reliably forecast development effort. However, achieving precise estimates is notoriously difficult, primarily due to inherent project complexities and numerous uncertain variables. While various techniques exist, no single method has proven consistently reliable, leading to inaccurate scheduling and cost overruns. This study aims to develop a more accurate and robust estimation model by hybridizing a multi-criteria decision-making (MCDM) method for handling uncertainty with a machine learning algorithm for predictive modeling. The proposed approach integrates the Consistent Fuzzy Preference Relation (CFPR) method to derive consistent weights for cost drivers from expert judgments. These weights are then used as Effort Adjustment Factors (EAF) to preprocess the COCOMO and NASA datasets, which are subsequently modeled using the Least Squares Support Vector Machine (LSSVM). Evaluation of the hybrid CFPR-LSSVM model confirmed its enhanced predictive accuracy. For the COCOMO dataset, the model yielded an MMRE of 28.463% and an RMSE of 0.4705. Its performance on the NASA dataset was particularly remarkable, with results indicating an MMRE of 1.104% and an RMSE of 0.4593, demonstrating a level of precision that underscores the model's effectiveness. This research contributes a novel hybrid framework that effectively combines consistent fuzzy preference handling with powerful non-linear regression. By providing a more structured and robust methodology for managing uncertainty, this approach offers a substantial advancement in software effort estimation, delivering more reliable predictions for improved project planning. 
Co-Authors Adnan Purwanto Harjunadi Wicaksono, Harjunadi Lestari, Ika Indah Liefalza, Andi Daffa Priyadi, Wiwit Santosa, Hadi Sulistiyasni . Sumardiono Sumardiono, Sumardiono