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All Journal Sistemasi: Jurnal Sistem Informasi JURNAL MEDIA INFORMATIKA BUDIDARMA Jurnal Informatika Universitas Pamulang bit-Tech
Kartono Kartono
Department Of Mathematics, Faculty Of Science And Technology, Airlangga University, Indonesia
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

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Decision Support System for Optimizing Rastra Distribution Routes Using Genetic Algorithm Halimatuz Zuhriyah; D. Kartono; Purbandini Purbandini; Anindya Ananda Hapsari
Jurnal Informatika Universitas Pamulang Vol 8, No 2 (2023): JURNAL INFORMATIKA UNIVERSITAS PAMULANG
Publisher : Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/informatika.v8i2.33353

Abstract

Vehicle Routing Problem (VRP) is an optimal route design from a group of vehicles that deliver goods to a set of customers with a certain demand. VRP was widely studied as part of solving the distribution efficiency which minimizes the cost of traveled vehicle. Bulog Subdivre South Surabaya distribute Rastra to every village which has constraint of Multi depot and Split delivery (MDSDVRP). This study aims to minimize the traveled distance of MDSDVRP (Rastra distribution) using  Genetic Algorithm (GA) and to find out the efficiency of the route solution. The research covers the steps to solve MDSDVRP using GA to generate feasible and efficient solution route. Then development of a Decision Support System (DSS) that applies the algorithm is implemented on web platform and the result of route solution is presented on the mobile platform. The system testing is carried out to test the user satisfaction (83.8%) which found that overall users were considered very agree, good, like for each component of user satisfaction. The traveled distance is compared between GA route and routes of the original data from 2013-2017. The efficiency of GA was evaluated and found that the traveled distance from the previous route is reduced by 3.7% (444 km) and in 2017 is reduced the distance traveled by 9.5 % (1,093 km). The GA can generate a better solution and optimize the distance than the original route.
Analisis Sentimen Berbasis Aspek Ulasan Aplikasi Mobile JKN dengan Lexicon Based dan Naïve Bayes Salsabila Roiqoh; Badrus Zaman; Kartono Kartono
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 7, No 3 (2023): Juli 2023
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v7i3.6194

Abstract

Badan Penyelenggara Jaminan Sosial (BPJS) Kesehatan is a legal entity that provides social health insurance programs for the public released application called Mobile JKN to support various health services activities using users devices. Mobile JKN has not fully received a positive public perception and still has many shortcomings. It is necessary to conduct a deeper evaluation and analysis of the Mobile JKN. This study focuses on aspect-based sentiment analysis of user reviews on the Google Play Store to evaluate the Mobile JKN. The review data used are the last two versions, 4.2.3 and 4.3.0. This study was carried out by modeling aspects/topics using the Latent Dirichlet Allocation method and sentiment analysis using Naïve Bayes and Lexicon-Based methods. This research resulted in 3 aspects, namely Services and Features, Register and Login, and User Satisfaction. This was obtained based on the model with the highest coherence score of 0.6392 obtained in the model looping with the number of topics from 1 to 9, random state = 42, passes =50, and iteration = 60. Meanwhile, based on the sentiment analysis results, the Naïve Bayes method is better than the Lexicon-Based (Inset Lexicon) method. This is evident from performance of the Naïve Bayes with the highest accuracy score of 94.75% and Lexicon Based with Inset Lexicon obtained an accuracy score of 59.99%.
Optimizing Uncapacitated Facility Location Problem with Cuckoo Search Algorithm based on Gauss Distribution Mohammad Agung Nugroho; Eto Wuryanto; Kartono Faqih
Sistemasi: Jurnal Sistem Informasi Vol 12, No 2 (2023): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v12i2.2467

Abstract

The objective of this study was to assess the capability of the Gauss distribution-based Cuckoo Search algorithm (GCS) in solving the Uncapacitated Facility Location Problem (UFLP). UFLP is an optimization problem that there are number of locations available to be built a facility so that it can serve number of customers, assuming each facility has no limits to serve customers and only a single facility is allowed to provide services to each customer. The objective function of UFLP is to minimize the combined costs of constructing facilities in an area and providing services to customers. UFLP falls under the category of NP-Hard Problems, where the computation complexity increases with the size of the data. The Cuckoo Search algorithm, which mimics the breeding behavior of Cuckoo birds, has been extensively used to tackle optimization problems. GCS was introduced to overcome the weaknesses of Cuckoo Search algorithm in terms of computational time and search accuracy. GCS used Gaussian distribution instead of Levy Flight which based on Levy distribution. In this study, the GCS algorithm was implemented using JavaScript and the dataset used was obtained from ORLib. The research outcomes showed that the GCS algorithm could achieve optimal result in all dataset.
Enhancing Contractor Evaluation Using Fuzzy TOPSIS-Based Decision Support System Barry Nuqoba; Kartono; Faiz Haidar Satriani Adli; Faried Effendy; Taufik
bit-Tech Vol. 8 No. 1 (2025): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v8i1.2510

Abstract

Contractor evaluation remains a major challenge in safety-critical industries such as oil and gas, where the need to comply with stringent Health, Safety, and Environment (HSE) standards demands a robust and objective assessment mechanism. The existing manual evaluation methods are plagued by subjectivity, inconsistent data handling, and inability to resolve performance ties, leading to unreliable contractor differentiation. To address this problem, this study investigates how can a computational decision support framework minimize subjectivity and enhance ranking precision in contractor evaluations. It proposes a Decision Support System (DSS) based on the Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (Fuzzy TOPSIS) to improve the accuracy, transparency, and efficiency of evaluations within the Contractor Safety Management System (CSMS). The DSS integrates qualitative and quantitative criteria using fuzzy logic and expert-assigned linguistic weights. Developed following the Waterfall software development lifecycle, the system was validated using black box testing and applied to realistic simulated data from ten contractors evaluated across multiple criteria and subcriteria. Results demonstrate that the DSS effectively resolves score ties present in manual evaluations, enabling finer distinctions among contractors, with the highest closeness coefficient of 0.479 achieved by the top-ranked contractor. This value reflects a 47.9% closeness to the ideal performance profile, marking a significant improvement over binary or aggregate-based evaluation methods..User feedback confirmed high satisfaction with system usability and performance. The proposed DSS offers a robust and adaptable framework for contractor evaluation, enhancing decision-making accuracy and operational transparency in high-risk environments. Its novelty lies in the integration of fuzzy linguistic modeling within a CSMS context to operationalize HSE performance evaluations. Future research should focus on incorporating advanced fuzzy logic methods and artificial intelligence to facilitate real-time, dynamic contractor evaluations under uncertainty.
Co-Authors Anindya Ananda Hapsari Badrus Zaman Barry Nuqoba, Barry Eto Wuryanto Faiz Haidar Satriani Adli Faried Effendy Halimatuz Zuhriyah Mohammad Agung Nugroho Purbandini Soeparman, Purbandini Salsabila Roiqoh Taufik