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All Journal Prosiding SNATIKA Vol 01 (2011) AKSIOMA: Jurnal Program Studi Pendidikan Matematika The Asian Journal of Technology Management (AJTM) JURNAL NASIONAL TEKNIK ELEKTRO Jurnal Kajian Pembelajaran Matematika JOIV : International Journal on Informatics Visualization JMPM: Jurnal Matematika dan Pendidikan Matematika INOVISH JOURNAL BAREKENG: Jurnal Ilmu Matematika dan Terapan METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Buletin Ilmiah Sarjana Teknik Elektro Jurnal Pengabdian Masyarakat Asia International Journal of Progressive Mathematics Education Jikom: Jurnal Informatika dan Komputer Jurnal Informatika: Jurnal Pengembangan IT Jurnal ilmiah teknologi informasi Asia Limits: Journal of Mathematics and Its Applications
Lilis Widayanti
Institut Teknologi Dan Bisnis Asia Malang
Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Languange, Linguistic, Communication & Media Mathematics Mechanical Engineering Physics Transportation Other

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Utilizing AI to Optimize Product Sales at UD Bima Baru Widayanti, Lilis; Vivi Aida Fitria; Adriani Kala’lembang; Widya Adhariyanty Rahayu; Suastika Yulia Riska
Jurnal Pengabdian Masyarakat Vol. 6 No. 1 (2025): Jurnal Pengabdian Masyarakat
Publisher : Institut Teknologi dan Bisnis Asia Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32815/jpm.v6i1.2454

Abstract

Purpose: The study aims to evaluate the effectiveness of activities in reaching participants, achieving training goals, improving proficiency, and enhancing sales through AI technologies. Method: This study teaches and evaluates the use of AI in sales optimization through lectures, demonstrations, tasks, and question-and-answer meetings. How well the activity worked is judged by how well the players met the goals and understood the material. Practical Application: The participants from UD. Bima Baru showed high levels of enthusiasm and engagement during each session of the activity. This indicates the possibility for enhancing their skills, operational efficiency, and revenue, while also fostering collaboration and fostering creativity in the future. Conclusion: Artificial intelligence (AI) has considerable potential to augment sales for MSMEs, like UD Bima Baru, through data-driven decision-making. Effective AI adoption requires practical experience, underscoring the significance of collaboration between academia and MSMEs in providing education, training, and mentorship. This collaboration fosters technological adoption and enhances local economic growth by generating practical, concrete ideas. Future training must include sequential courses for MSMEs to leverage AI.
Boundless Creativity: Vlogging with a Smartphone in the Digital Era Kala'lembang, Adriani; Riska, Suastika Yulia; Widayanti, Lilis; Rahayu, Widya Adhariyanty; Fitria, Vivi Aida
Jurnal Pengabdian Masyarakat Vol. 6 No. 1 (2025): Jurnal Pengabdian Masyarakat
Publisher : Institut Teknologi dan Bisnis Asia Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32815/jpm.v6i1.2475

Abstract

Purpose: This community service aims to enhance the technical skills of students at SMK Negeri 12 Malang in digital vlog creation. Method: The program involves training sessions using lectures and hands-on practice to improve lighting techniques. Practical Application: This initiative has a significant impact on vlog production by following essential steps, including framing techniques, lighting, and video editing. Conclusion: This program enhances students' creativity and skills in vlog creation.
BOUNDEDNESS AND EXISTENCE ANALYSIS SOLUTION OF AN OPTIMAL CONTROL PROBLEMS ON MATHEMATICAL COVID-19 MODEL Hakim, Lukman; Widayanti, Lilis
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 2 (2024): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol18iss2pp0797-0808

Abstract

The investigation given right here is part of a literature review on mathematical models that apply analytical mathematics. The present work focuses on the COVID-19 model, which incorporates optimum control variables previously investigated and interpreted by Hakim. Depending on the current model, we will further develop the analysis and demonstrate the non-negativity condition as well as the boundedness criteria for the solutions. Additionally, we conduct several supplementary analyses by applying the Lipschitz function to examine the uniqueness of the solutions and the existence of the solution are hold on the autonomous system. This work to supports the previously findings that incorporating an optimal control into the model can reduce COVID-19 treat on public. Finally, that research verifies that the control variables used in the research satisfy all of the existence criteria, as outlined in Theorem 5 of this work.
Modified Orca Algorithm Based on the Navigation Behavior for Optimal Unit Commitment in Power Systems Widayanti, Lilis; Afandi, Arif Nur; Herwanto, Heru Wahyu
Buletin Ilmiah Sarjana Teknik Elektro Vol. 7 No. 3 (2025): September
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/biste.v7i3.13645

Abstract

This study presents the Novel Navigation Orca Algorithm (NNOA), an innovative optimization algorithm derived from Orca Algorithm (OA). NNOA addresses the unit commitment (UC), a complex issue in power systems that focuses on scheduling generator units to meet power demand while taking into account each generator's limitations, with the goal of lowering operating costs and gas emissions. NNOA exhibits orca hunting behavior through echolocation, utilizing the Doppler effect principle to promote adaptive movement and circumvent local optima, as in contrast to OA's wave-based exploration. The algorithm was evaluated utilizing IEEE 30-bus system data, focused on the Integrated Economic and Emission Dispatch (IEED) objective. The performance was evaluated against OA and Particle Swarm Optimization (PSO) through convergence analysis over 10 and 30 trials, each consisting of 100 iterations. NNOA decreased the IEED value by 1.33% in regard to OA and 1.51% in regard to PSO. NNOA achieved convergence in 10 iterations, whereas OA required 35, indicating 71.4% faster convergence rate. Wilcoxon rank-sum tests demonstrated significant differences between NNOA, OA, and PSO pairings. NNOA's per-iteration computation time exceeds the time needed by PSO, but it remains economical and profitable. Significantly, NNOA contributes minimizing the fuel consumption and emissions cost, which has a positive environmental impact. It effectively adheres to the required constraints, which include the hourly power demand and generator output limits. Future research is encouraged to apply NNOA to larger-scale power systems and explore its hybridization with PSO to enhance computational efficiency, result consistency, and robustness in practical grid operations.
Enhancing Accuracy in Stock Price Prediction: The Power of Optimization Algorithms Fitria, Vivi Aida; Widayanti, Lilis
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 23 No. 2 (2024)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v23i2.3785

Abstract

The purpose of this research was to improve the accuracy of stock price prediction by implementing optimization algorithms on forecasting methods, in this case, the exponential smoothing method. This research implemented the Particle Swarm Optimization (PSO) and Bat Algorithm metaheuristic optimization algorithms to determine the single-exponential smoothing method’s smoothing parameters. Before implementing the optimization algorithm, the way to determine the smoothing parameters was by trial-and-error method, which is considered less effective. Therefore, the novelty of this research is tuning the parameters of the exponential smoothing method using a comparison of two metaheuristic algorithms, namely the particle swarm optimization algorithm compared to the bat algorithm. The Single Exponential Smoothing method with PSO and Bat algorithms was proven to improve accuracy. The alpha parameter found by the PSO algorithm is 0.9346, and the bat algorithm is 0.936465. With a MAPE of 1.0311%, it was better than the MAPE generated in the Single Exponential smoothing method by trial and error of 1.0316%. This research contributes to providing insight that in a highly sensitive stock prediction situation, metaheuristic algorithms can be used to create more accurate and efficient prediction results.
SISTEM PENDUKUNG KEPUTUSAN EVALUASI HASIL BELAJAR SISWA DI SMK PGRI 3 SIDOARJO MENGGUNAKAN METODE FUZZY AHP (ANALYTICAL HIERARCHY PROCESS) Ahmad Husain Abiyyu; Lilis Widayanti
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 7 No. 2 (2023): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/jmika.Vol7No2.pp158-174

Abstract

Evaluation of student learning outcomes have an important role for teachers in knowing students abilities and in determining how to guide students. However, in its application to vocational high school PGRI 3 Sidoarjo, the teachers have difficulty regarding the assessment system to evaluate students learning outcomes, the difficulty is in the ranking process. Vocational high school 3 Sidoarjo still used the old and manual systems so the result is that the time needed is inefficient time and made the teachers difficult in processing data. The decision support system of students learning result evaluation at vocational high school 3 Sidoarjo using AHP fuzzy method. The goal is to facilitate the teacher in the student ranking process. The process in this system is the admin inputing students data, classes and scores after that the admin determines the value of each criterion and sub-criterion, then the ranking process is based on class. This decision support system's output is the ranking of students' classes. Using the test results from 20 students, the old system and the new system will be compared. As the result, based on 20 students score data, there were incompatible data, the amount of data were 4 data, with a system accuracy rate of 80%. Unsuitable data due to the old system using 2 criterion while the new system using 5 criterion in ranking.
Dinamika Solusi dan Kontrol Optimal Model Penyakit ISPA di Kota Malang Hakim, Lukman; Widayanti, Lilis
Limits: Journal of Mathematics and Its Applications Vol. 22 No. 3 (2025): Limits: Journal of Mathematics and Its Applications Volume 22 Nomor 3 Edisi No
Publisher : Pusat Publikasi Ilmiah LPPM Institut Teknologi Sepuluh Nopember

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

Abstract

The current research provides a mathematical model utilizing nonlinear ordinary differential equations to represent the spread of acute respiratory infections (ARI). The model is divided into five compartments: the susceptible population, the vaccinated population, the latent population, the infected population, and the recovered population. Through dynamic analysis, two equilibrium points were determined. The disease-free equilibrium point is stable under conditions, while the endemic equilibrium point exhibits asymptotic stability. The lsqcurvefit methods was implemented to estimate the parameters, facilitating accurate parameter approximation. The acquisition of estimated values was implemented in the sensitivity analysis, and several parameters sensitive to were obtained: the vaccination rate, the natural death rate, the mortality cause infection rate, and recovery rate. An optimal control problem was designed by incorporating two control variables: firstly, reducing the direct contact between the susceptible and infected populations, and the other focused on increasing the intensity of infected individuals. The solution of optimal control problem was derived using Pontryagin's Principle. The objective function was formulated as a Lagrange to minimize the number of latent and infected individuals, and maximizing the vaccinated and recovered populations. Finally, numerical simulations were performed to validate the theoretical analysis, demonstrating that the results in line with the objective function of optimal control and effectively support the proposed strategies for controlling the disease.
Orca Predation Algorithm as an Innovative Solution for IEEE 30 Bus Vivi Aida Fitria; Zahratul Laily Binti Edaris; Azwar Riza Habibi; Lilis Widayanti
JURNAL NASIONAL TEKNIK ELEKTRO Vol 14, No 3: November 2025
Publisher : Jurusan Teknik Elektro Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jnte.v14n3.1296.2025

Abstract

The effective operation of the IEEE 30 Bus power system requires economic dispatch optimization to minimize production costs, align energy supply with demand, and ensure system stability. This economic dispatch problem is complex due to its non-linear characteristics, interdependence between generators, and the need to combine cost minimization with power loss reduction. Conventional optimization techniques often struggle to find global solutions, easily get stuck in local optima, and require significant computational time. This study introduces the Orca Predation Algorithm (OPA) as a new approach to address these challenges. Inspired by the hunting behavior of orcas, OPA balances exploration and exploitation through two distinct phases: pursuit and attack. Evaluated on the IEEE 30-Bus system using power loss computation with coefficient B, the algorithm ensures that generator output power allocation meets demand at the lowest cost. OPA's performance is comprehensively compared with Particle Swarm Optimization (PSO), Grey Wolf Optimization (GWO), Whale Optimization Algorithm (WOA), and Bat Algorithm. The results consistently show that OPA achieves the lowest total cost of $772,754 while maintaining superior system stability and effectively minimizing power losses among the evaluated algorithms. These findings highlight the significant potential of OPA to enhance energy management and advance power system optimization.
Co-Authors A.N. Afandi Abdul Hadi Achlul Nizar Adriani Kala'lembang Adriani Kala’lembang Adriani Kala’lembang Ahmad Husain Abiyyu Aripriharta - Azwar Riza Habibi, Azwar Riza Fadhli Almu’iini Ahda Farokhah, Lia Fitria, Vivi Aida Hasanah, Mitahatul Heru Wahyu Herwanto Kala'lembang, Adriani Lukman Hakim Mufidatul Islamiyah Puji Subekti Santoso, Risa Suastika Yulia Riska Sulistyo, Danang Arbian Sundafa, Aldo Vivi Aida Fitria Widya Adhariyanty Rahayu Yudistira Arya Sapoetra Zahratul Laily Binti Edaris