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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Jurnal Informatika Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Jurnal Ilmu Komputer dan Informasi Jurnal Sains dan Seni ITS IPTEK Journal of Proceedings Series IPTEK The Journal for Technology and Science Gamatika Prosiding Seminar Matematika dan Pendidikan Matematik JURNAL SOSIAL HUMANIORA (JSH) Semesta Teknika Elkawnie Register: Jurnal Ilmiah Teknologi Sistem Informasi Science and Technology Indonesia SUSTINERE: Journal of Environment and Sustainability Syntax Literate: Jurnal Ilmiah Indonesia Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control BAREKENG: Jurnal Ilmu Matematika dan Terapan JAIM (Jurnal Abdi Masyarakat) Jurnal Teknologi Dan Sistem Informasi Bisnis Indonesian Journal of Electrical Engineering and Computer Science Majalah Ilmiah Matematika dan Statistika (MIMS) Journal of Applied Data Sciences Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi Journal of Research in Social Science and Humanities COMSERVA: Jurnal Penelitian dan Pengabdian Masyarakat Malcom: Indonesian Journal of Machine Learning and Computer Science Sewagati International Journal of Computing Science and Applied Mathematics-IJCSAM
Mohammad Isa Irawan
Departemen Matematika Institut Teknologi Sepuluh Nopember Surabaya
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A Bibliometric Analysis of Metaheuristic Research and Its Applications Hendy, Hendy; Irawan, Mohammad Isa; Mukhlash, Imam; Setumin, Samsul
Register: Jurnal Ilmiah Teknologi Sistem Informasi Vol 9 No 1 (2023): January
Publisher : Information Systems - Universitas Pesantren Tinggi Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26594/register.v9i1.2675

Abstract

Metaheuristic algorithms are generic optimization tools to solve complex problems with extensive search spaces. This algorithm minimizes the size of the search space by using effective search strategies. Research on metaheuristic algorithms continues to grow and is widely applied to solve big data problems. This study aims to provide an analysis of the performance of metaheuristic research and to map a description of the themes of the metaheuristic research method. Using bibliometric analysis, we examined the performance of scientific articles and described the available opportunities for metaheuristic research methods. This study presents the performance analysis and bibliometric review of metaheuristic research documents indexed in the Scopus database between the period of 2016-2021. The overall number of papers published at the global level was 3846. At global optimization, heuristic methods, scheduling, genetic algorithms, evolutionary algorithms, and benchmarking dominate metaheuristic research. Meanwhile, the discussion on adaptive neuro-fuzzy inference, forecasting, feature selection, biomimetics, exploration, and exploitation, are growing hot issues for research in this field. The current research reveals a unique overview of metaheuristic research at the global level from 2016-2021, and this could be valuable for conducting future research.
Customer Churn Prediction Using the RFM Approach and Extreme Gradient Boosting for Company Strategy Recommendation Irawan, Mohammad Isa; Putris , Nadhifa Afrinia Dwi; Muhammad, Noryanti binti
Register: Jurnal Ilmiah Teknologi Sistem Informasi Vol 10 No 2 (2024): July
Publisher : Information Systems - Universitas Pesantren Tinggi Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26594/register.v10i2.4004

Abstract

Customers are vital assets in the growth and sustainability of business  organizations. However, customers may discontinue their engagement with a company and switch to competitors’ products or services for various reasons. This event referred to as customer churn. Losing customers significantly impacts a company's revenue, often resulting in financial decline. Churn events, which are subject to dynamic monthly changes, are further influenced by intense competition and rapid technological advancements. Analyzing customer characteristics is crucial to understanding customer behavior, with metrics such as recency, frequency, monetary (RFM) serving as key indicators of subscription and transaction patterns. The Extreme Gradient Boosting method is applied to address the challenge of classifying churn and non-churn customers. The prescriptive analytics process is carried out to identify the features most influential in prediction outcomes, enabling the formulation of strategic recommendations to mitigate churn problems. The integration of RFM analysis with the XGBoost method provides optimal results, particularly in the third segmentation, achieving an accuracy of = 0.98833, precession = 0.98768, recall = 0.98899, and f1-score = 0.98833. The prescriptive analytics process highlights three critical features, namely city factor, GMV generation, and total customer transaction generation. This findings demonstrate that the segmentation characteristics, data representation, and behavioral approach with RFM analysis have an effect on improving the performance of the model in churn prediction.
Inovasi Model Bisnis dan Pengukuran Tingkat Kesiapan Teknologi dalam Mengadopsi Omnichannel (Studi Kasus Informa) Maulana, Muhammad Agung Adi; Irawan, Mohammad Isa
Syntax Literate Jurnal Ilmiah Indonesia
Publisher : Syntax Corporation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36418/syntax-literate.v9i11.11758

Abstract

Perkembangan teknologi dan transformasi dalam transaksi barang dan jasa telah meningkatkan persaingan industri retail furniture terutama di antara perusahaan dengan jenis produk yang serupa. Meski PT Home Center Indonesia (Informa) telah mengalami peningkatan jumlah anggota (member) yang signifikan pada tahun 2023, hal ini belum diimbangi dengan pencapaian penjualan online yang optimal. Kontribusi penjualan online masih rendah meskipun ada peningkatan dalam jumlah pelanggan. Situasi ini menunjukkan perlunya strategi yang lebih efektif dalam memanfaatkan potensi digital. Penelitian ini menganalisis tingkat kesiapan teknologi di Informa dalam menerapkan omnichannel menggunakan Business Model Canvas (BMC) dan Technology Acceptance Model (TAM). Metode penelitian menggunakan SEM-PLS dengan data primer dari kuesioner kepada operator IT dan konsumen Informa. Hasil penelitian menunjukkan bahwa kesiapan teknologi di Informa merupakan faktor kunci dalam transformasi bisnis ini. Studi ini menyimpulkan bahwa investasi Informa dalam infrastruktur digital dan penerimaan teknologi sangat penting untuk meningkatkan kehadiran omnichannel serta menyarankan strategi digital lebih lanjut untuk memaksimalkan jangkauan pasar dan keterlibatan pelanggan.
Hybrid AHP Topsis Method for Selection and the Four Disciplines of Execution (4DX) for Monitoring the Animal Disturbance Reduction Program (Case Study: PLN UP3 East Bali) Mahardika, Kadek Eri; Irawan, Mohammad Isa
Syntax Literate Jurnal Ilmiah Indonesia
Publisher : Syntax Corporation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36418/syntax-literate.v10i4.58615

Abstract

PLN (Persero) East Bali Customer Service Implementation Unit is responsible for supplying electricity in Gianyar, Klungkung, Bangli, and Karangasem regencies. The high number of feeder disturbances, especially those caused by animals, significantly impacts the reliability and continuity of electricity supply, accounting for 115 incidents (37.33%) out of a total of 308 trips in the first semester of 2023. This study aims to determine the priority program for reducing animal-related disturbances using the hybrid Analytical Hierarchy Process (AHP) - Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method and to monitor its implementation using The Four Disciplines of Execution (4DX). The Delphi method established four evaluation criteria: ease of implementation, material cost, effectiveness, and power outage (KWH lost). Four alternatives were evaluated: installing palm fiber barriers, animal shields, heat shrink tubes, and tree pruning. The results indicated that tree pruning was the priority program. Implementation was monitored during the first semester of 2024 using the 4DX method, which showed a significant reduction in animal-related disturbances, decreasing from 115 incidents in the first semester of 2023 to 55 incidents in the first semester of 2024, representing a 52.21% year-over-year reduction. The implications of this study demonstrate that the hybrid AHP-TOPSIS and 4DX approaches effectively determine priorities and monitor program execution, significantly improving electricity supply reliability.
Exploring the Evolution of Electric Vehicle Charging Infrastructure: A Bibliometric Perspective on Public Electric Vehicle Charging Station Location Planning Notopramono, Hanna; Irawan, Mohammad Isa
MALCOM: Indonesian Journal of Machine Learning and Computer Science Vol. 6 No. 1 (2026): MALCOM January 2026
Publisher : Institut Riset dan Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57152/malcom.v6i1.2375

Abstract

The rapid expansion of electric vehicles (EVs) is a crucial factor in achieving low-carbon mobility and promoting sustainable regional development. The attainment of this objective depends on technological advancement, institutional readiness, spatial equity, and governance capabilities. The establishment of Stasiun Pengisian Kendaraan Listrik Umum (SPKLU) in Indonesia must be understood within a framework that connects infrastructure planning to social, economic, and political factors.   This research analyzes the evolution of international scientific dialogue regarding EV charging infrastructure through a bibliometric lens, focusing on publications from 2010 to 2025.  This study utilizes Scopus data and analytical tools, including VOSviewer and Publish or Perish, to identify leading authors, key journals, and emerging subject trends.   The results suggest that future SPKLU planning in Indonesia requires an integrated framework that aligns technological precision with public governance principles.   This approach should account for decentralization dynamics, regional disparities, and institutional capacity, ensuring that improvements to EV infrastructure contribute to carbon-reduction goals while fostering equitable and sustainable regional development.
Classification of Poverty Levels Using k-Nearest Neighbor And Learning Vector Quantization Methods Santoso Santoso; Mohammad Isa Irawan
(IJCSAM) International Journal of Computing Science and Applied Mathematics Vol. 2 No. 1 (2016)
Publisher : LPPM Institut Teknologi Sepuluh Nopember

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

Abstract

Poverty is the inability of individuals to fulfill the minimum basic needs for a decent life. The problem of poverty is one of the fundamental problems that become the central attention of the local government. One of the government efforts to overcome poverty is using the alleviation programs. Government often faces some difficulties to sort out of the poverty levels in the society. Therefore it is necessary to conduct a study that helps the government to identify the poverty level so that the aid did not miss the targets. In order to tackle this problem, this paper leverages two classification methods: k-nearest neighbor (k-NN) and learning vector quantization (LVQ). The purpose of this study is to compare the accuracy of the value of both methods for classifying poverty levels. The data attributes that are used to characterize poverty among others include: aspects of housing, health, education, economics and income. From the testing results using both methods, the accuracy of k-NN is 93.52%, and the accuracy of LVQ is 75.93%. It can be concluded that the classification of poverty levels using k-NN method gives better performance than using LVQ method.
Simulation of a Mathematical Model of Proteins Interaction on GLUT4 Translocation Ari Kusumastuti; Mohammad Isa Irawan; Kistosil Fahim; Nurul Anggraeni Hidayati; Anindita Sharkar
(IJCSAM) International Journal of Computing Science and Applied Mathematics Vol. 10 No. 2 (2024)
Publisher : LPPM Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j24775401.ijcsam.v10i2.4606

Abstract

Glucose is the energy source of cells. Glucose absorption into muscle cells is regulated by Insulin by involving the interaction of several proteins in a specific system. The system works for the translocation of GLUT4 to the cell membrane. GLUT4 is a transporter protein owned by every muscle cell, as an entry gate for glucose and an Insulin partner in maintaining homeostasis of blood glucose levels. After the Insulin activation occurs in the Insulin Receptor Substrate (IRS), it is followed by the activation of several proteins to regulate GLUT4 translocation, namely IRS, phosphatidylinositol 3-kinase (P13K), 3-phosphoinositide-dependent protein kinase-1 (PDK1/2) and serine/threonine-protein kinase (AKT). This study describes these processes in a mathematical model as a system of ordinary differential equations. The specific process modeled is the Insulin signal pathway that regulates GLUT4 translocation, which can be accessed on Kegg.jp. Moreover, string.db.org analysis results are used as a reference to prove the type of protein interaction. The formulated model is directed to coherently explain the flux changes of each protein involved in the system and stimulate easily. The simulation provides an overview of the protein dynamics in the system over time. Finally, the mathematical models and simulations will complement the basic understanding of the effect of glucose absorption on the translocation of GLUT4.
Sequence Alignment Using Nature-Inspired Metaheuristic Algorithms Muhammad Luthfi Shahab; Mohammad Isa Irawan
(IJCSAM) International Journal of Computing Science and Applied Mathematics Vol. 3 No. 1 (2017)
Publisher : LPPM Institut Teknologi Sepuluh Nopember

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

Abstract

The most basic process in sequence analysis is sequence alignment, usually solved by dynamic programming Needleman-Wunsch algorithm. However, Needleman-Wunsch algorithm has some lack when the length of the sequence which is aligned is big enough. Because of that, sequence alignment is solved by metaheuristic algorithms. In the present, there are a lot of new metaheuristic algorithms based on natural behavior of some species, we usually call them as nature-inspired metaheuristic algorithms. Some of those algorithm that are more efficient are firefly algorithm, cuckoo search, and flower pollination algorithm. In this research, we use those algorithms to solve sequence alignment. The results show that those algorithms can be used to solve sequence alignment with good result and linear time computation.
A Genetic Algorithm with Best Combination Operator for the Traveling Salesman Problem Muhammad Luthfi Shahab; Titin J. Ambarwati; Soetrisno Soetrisno; Mohammad Isa Irawan
(IJCSAM) International Journal of Computing Science and Applied Mathematics Vol. 5 No. 2 (2019)
Publisher : LPPM Institut Teknologi Sepuluh Nopember

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

Abstract

In this research, we propose a genetic algorithm with best combination operator (BC(x,y)O) for the traveling salesman problem. The idea of best combination operator is to find the best combination of some disjoint sub-solutions (also the reverse of sub-solutions) from some known solutions. We use BC(2,1)O together with a genetic algorithm. The proposed genetic algorithm uses the swap mutation operator and elitism replacement with filtration for faster computational time. We compare the performances of GA (genetic algorithm without BC(2,1)O), IABC(2,1)O (iterative approach of BC(2,1)O), and GABC(2,1)O (genetic algorithm with BC(2,1)O). We have tested GA, IABC(2,1)O, and GABC(2,1)O three times and pick the best solution on 50 problems from TSPLIB. From those 50 problems, the average of the accuracy from GA, IABC(2,1)O, and GABC(2,1)O are 65.12%, 94.21%, and 99.82% respectively.
Similarity Analysis of User Trajectories Based on Haversine Distance and Needleman Wunsch Algorithm Mohammad Jamhuri; Mohammad Isa Irawan; Imam Mukhlash
Elkawnie Vol. 7 No. 2 (2021)
Publisher : Faculty of Science and Technology Universitas Islam Negeri Ar-Raniry

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22373/ekw.v7i2.9232

Abstract

Abstract: In this paper, we discuss the similarity between two trajectories using the Needleman Wunsch algorithm. The calculation steps are interpolating the trajectory, calculating the distance between the trajectory coordinates, identifying the equivalent length, transforming trajectories into a sequence of alphabetic letters, aligning the sequences, and measuring the magnitude of the similarity based on the alignment results. The similarity obtained is compared directly to the length of the trajectories shared by the two lines. The calculation results show that the accuracy of the alignment method reaches more than 90%. Abstrak: Dalam tulisan ini dibahas cara perhitungan persentase kesamaan dari dua buah lintasan menggunakan algoritma Needleman Wunsch dan perhitungan secara manual berdasarkan irisan dari lintasan-lintasan tersebut. Pada perhitungan menggunakan algoritma Needleman Wunsch, tahapan-tahapan yang dilakukan adalah menginterpolasi lintasan, menghitung jarak antara titik-titik koordinat dari kedua lintasan, mengidentifikasi jarak yang ekivalen, mengubah lintasan menjadi sekuens huruf alfabet, menyejajarkan sekuens, dan menentukan besarnya kesamaan berdasarkan hasil penyejajaran. Kesamaan yang diperoleh dari metode penyejajaran dibandingkan secara langsung dengan panjang jalur yang dilalui bersama oleh kedua lintasan, hasil perhitungan menunjukkan bahwa akurasi metode penyejajaran mencapai lebih dari 90%.
Co-Authors AA. Masroeri Abduh Riski, Abduh Adrianus Bagas Tantyo Dananjaya Akhmad Arif Junaidi Alan Catur Nugraha Alexander Setiawan Alvida Mustika Rukmi Amira, Siti Azza Andreas Handojo Anindita Sharkar Antonio Galileo Tando Ari Kusumastuti Arie Dipareza Syafei Arifah, Enny Durratul Auliya Rahmayani Baiq Findiarin Billyan Berlian Rahmy Lidiawaty Chyntia Kumalasari Puteri Danang Wahyu Wicaksono Daniel Happy Putra Darmaji, Darmaji Darmawan, Didiet Edi Satriyanto Ekky Hidma Octia Rahmah Elly Matul Imah Elnora Oktaviyani Gultom Elsen Ronando Erna Apriliani Fahim, Kistosil Fendhy Ongko Giandi, Oxsy Ginardi, Raden Venantius Hari Hadi Prasetiya Haloho, Freddi Hartanto Setiawan Hendy Hozairi Imam Mukhlash Imam Mukhlash Ira Puspitasari Ketut Buda Artana Khilmy, Akhmad Ku Khalif, Ku Muhammad Naim Mahardika, Kadek Eri Mahdiyah, Umi Mardlijah - Maulana, Muhammad Agung Adi Mey Lista Tauryawati Mohamad Muhtaromi Mohammad Hamim Zajuli Al Faroby Mohammad Iqbal Mohammad Jamhuri Mohd Aziz, Mohd Khairul Bazli Muchamad Jati Nugroho Muhammad Ahnaf Amrullah Muhammad Athoillah, Muhammad Muhammad Fakhrur Rozi Muhammad Hajarul Aswad Muhammad, Noryanti Muhammad, Noryanti binti Mujiono, Edo Priyo Utomo Putro Ni Nyoman Tri Puspaningsih Notopramono, Hanna Nugraha, Arma Perwira Nurul Anggraeni Hidayati NURUL HIDAYAT Nurul Hidayat Pratama, Qoria Yudi Putri, Endah R.M. Putri, Endah Rokhmati Merdika Putris , Nadhifa Afrinia Dwi Rasyadan Taufiq Probojati Resi Arumin Sani Rita Ambarwati Rita Ambarwati Sukmono Robby Sepriadi Robin Wijaya, Robin Ronando, Elsen Rukmini, Meme Santoso Santoso Santoso Santoso Setiawan, Muhammad Nanda Setumin, Samsul Shahab, Muhammad Luthfi Siti Maghfiroh Soetrisno Soetrisno Sulastri Sulastri Theodora Tantri Trisnawati Titin J. Ambarwati Victory Tyas Pambudi Swindiarto YAN ADITYA PRADANA Yongky Ujianto Yuda Dian Harja Zulfa Afiq Fikriya