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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 CAUCHY: Jurnal Matematika Murni dan Aplikasi Gamatika Prosiding Seminar Matematika dan Pendidikan Matematik JURNAL SOSIAL HUMANIORA (JSH) Semesta Teknika Elkawnie Register: Jurnal Ilmiah Teknologi Sistem Informasi Science and Technology Indonesia 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 Limits: Journal of Mathematics and Its Applications International Journal of Computing Science and Applied Mathematics JAIM (Jurnal Abdi Masyarakat) Jurnal Teknologi Dan Sistem Informasi Bisnis Indonesian Journal of Electrical Engineering and Computer Science Majalah Ilmiah Matematika dan Statistika (MIMS) Airlangga Journal of Innovation Management Journal of Applied Data Sciences Journal of Research in Social Science and Humanities COMSERVA: Jurnal Penelitian dan Pengabdian Masyarakat Jurnal Indonesia Sosial Teknologi Sewagati Limits: Journal of Mathematics and Its Applications
Mohammad Isa Irawan
Departemen Matematika Institut Teknologi Sepuluh Nopember Surabaya
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Efforts to Increase Electricity Sales at Pln Ulp Belawan Customer Service Zone Using AHP-ANP Method Implementation Sepriadi, Robby; Irawan, Mohammad Isa
Journal of Research in Social Science and Humanities Vol 5, No 1 (2025)
Publisher : Utan Kayu Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47679/jrssh.v5i1.281

Abstract

Abstract Electricity sales represent a crucial aspect of the business operations of the Perusahaan Listrik Negara (PLN). PLN is required to continuously improve its electricity sales strategies and enhance its services to meet the growing demands of its customers. PLN’s Customer Service Unit (ULP) Belawan is located in the northern part of Medan City, North Sumatra Province. PLN ULP Belawan serves a total of 75,931 customers with a total installed capacity of 220.28 MVA. In 2023, electricity sales reached 484.86 GWh, which is 105.63% of the target. The sales target for 2024 has been set at 524.46 GWh. This thesis aims to present the results of customer zoning prioritization that can be used to improve service delivery more effectively within PLN ULP Belawan. Through the weighting process using Analytic Hierarchy Process (AHP) and Analytic Network Process (ANP), as multi-criteria decision-making methods, were to optimize criteria and contribute to enhancing electricity sales performance. Each customer zone was evaluated based on several criteria, including system reliability, electricity usage regulation (P2TL), improvement of disturbance and complaint services, replacement of electricity meters, enforcement of the 720-hour usage regulation, connection criteria, cash-in performance, and accurate meter reading. The research successfully identified customer zones based on priority criteria. For the criterion of Electricity Usage Regulation (P2TL), the total energy recorded was 341,841 kWh across 173 kWh meters. Of this total, Zone 12 contributed the most with 277,019 kWh, followed by Zone 14 with 43,098 kWh, and Zone 6 with 20,914 kWh. In the Accurate Meter Reading criterion, the total energy achieved was 157,311 kWh from 815 kWh meters. Zone 14 contributed the highest amount at 67,564 kWh, followed by Zone 12 with 48,580 kWh, and Zone 6 with 41,167 kWh. Meanwhile, for the criterion of Electricity Meter Replacement, the total energy gained was 65,559 kWh from 505 kWh meters, with the largest contribution coming from Zone 6 (26,910 kWh), followed by Zone 12 (26,688 kWh), and Zone 14 (11,961 kWh). 
Carbon Price Prediction by Incorporating Fossil Fuel Prices Using Long Short-Term Memory with Temporal Pattern Attention (TPA-LSTM) Mujiono, Edo Priyo Utomo Putro; Mukhlash, Imam; Pradana, Yan Aditya; Putri, Endah R.M.; Irawan, Mohammad Isa
Science and Technology Indonesia Vol. 10 No. 3 (2025): July
Publisher : Research Center of Inorganic Materials and Coordination Complexes, FMIPA Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26554/sti.2025.10.3.856-865

Abstract

Reliable carbon price prediction can help to stabilize the carbon market, minimize financial risks for investors, and encourage innovation in green industries. The forecasts have a crucial role in reaching advanced goals for reducing emissions, aiding the shift toward an economy with reduced carbon emissions, and lessening the adverse effects of climate change overall. This paper proposes applications of LSTM with Temporal Pattern Attention (TPA-LSTM) to predict carbon price fluctuations. The prediction of carbon price fluctuations not only draws on its own historical information but also from its main predictors, including fossil fuel prices from 2018 to 2023. The TPA-LSTM method is a combined method that uses the LSTM layer as the initial input of the model. Furthermore, the output generated by the LSTM layer serves as the input to the TPA layer, which is then used to predict the carbon price for the following day. The model is tested by predicting the test data and calculating the evaluation results. The experimental results indicate that TPA-LSTM has surpassed other models in accuracy by showing better performance based on MSE, RMSE, MAE, and MAPE metrics.
Penentuan Prioritas Pemeliharaan Trafo Distribusi dengan Integrasi Metode Delphi dan AHP Haloho, Freddi; Irawan, Mohammad Isa
COMSERVA : Jurnal Penelitian dan Pengabdian Masyarakat Vol. 5 No. 3 (2025): COMSERVA: Jurnal Penelitian dan Pengabdian Masyarakat
Publisher : Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59141/comserva.v5i3.3252

Abstract

Distribution transformer maintenance plays a critical role in ensuring the continuity and reliability of PLN’s electricity supply. Currently, PLN employs a Condition-Based Maintenance (CBM) approach, relying on a Health Index (HI) derived from Tier 1 and Tier 2 inspection outcomes. However, in practice, determining maintenance priorities remains largely dependent on the intuition and technical experience of decision-makers, leading to potential inconsistencies in decision-making. Additionally, the absence of a structured weighting mechanism among HI parameters and unclear relevance of indicators used further hampers valid and reliable decision-making aligned with current operational conditions. This research aims to propose a structured and adaptive Health Index evaluation method through the integration of the Delphi and Analytical Hierarchy Process (AHP) methods. The Delphi method was employed to identify the most relevant parameters based on expert consensus, while the AHP method provided logical and consistent weighting among these parameters. Although AHP does not entirely eliminate subjectivity, as it still depends on expert judgments, it offers a systematic and transparent way to manage conflicting criteria effectively. The Delphi application yielded seven sub-criteria parameters grouped into three main criteria: oil leakage, transformer body temperature, load percentage, grounding value, physical condition, transformer age, and neutral current percentage. Based on AHP analysis, the oil leakage parameter was identified as having the highest weighting (0.23), indicating its significant impact on transformer performance. Applying this methodology to 253 distribution transformers resulted in prioritizing maintenance into three categories: Priority I (4 transformers), Priority II (54 transformers), and Priority III (195 transformers). The findings and validation from this study demonstrate that a structured, weighting-based approach significantly enhances the accuracy and transparency of decision-making processes in asset maintenance management.
APPLICATION OF CLASSIFICATION BASED ASSOCIATION (CBA) FOR MONKEYPOX DISEASE DETECTION Pratama, Qoria Yudi; Irawan, Mohammad Isa
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 19 No 1 (2025): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol19iss1pp595-602

Abstract

Monkeypox is a zoonotic disease that can be transmitted from animals to humans. The monkeypox virus is the cause of monkeypox disease, which belongs to the orthopoxvirus family. Although the mortality rate from monkeypox is not as high as COVID-19, this virus can be the cause of the next global pandemic if the epidemic worsens. Therefore, it is very important to carry out proper surveillance and prevention to prevent the spread of this disease. In this study, researchers developed another method to detect monkeypox disease based on its symptoms using the classification by association (CBA) method. CBA integrates the advantages of classification and association analysis, allowing the classification process and a deeper understanding of the strength of the relationship between features in the dataset through the analysis of metrics such as support and confidence. Based on the results of the experiments in this study, an accuracy of 68.64%, a precision of 92.21%, and a sensitivity of 71.09% were obtained. In this case, the accuracy obtained is still low, but the results of other metrics show that the CBA model performs fairly well in predicting the positive class with high precision.
DIGITALISASI PEMASARAN DAN SISTEM KEUANGAN PADA INDUSTRI RUMAH TANGGA COCONUT OIL KEDIRI Irawan, Mohammad Isa; Mukhlash, Imam; Rukmini, Meme; Hendy; Hidayat, Nurul; Rukmi, Alvida Mustika; Iqbal, Mohammad; Probojati, Rasyadan Taufiq
Jurnal Abdi Masyarakat Vol. 8 No. 1 (2024): Jurnal Abdi Masyarakat November 2024
Publisher : Universitas Kadiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30737/jaim.v8i1.6045

Abstract

Industri rumah tangga (IRT) minyak kelapa d’Hayfa Sukses Berkah memproduksi minyak kelapa murni Abila. Minyak kelapa yang dihasilkan memiliki kualitas yang tidak kalah baik dengan minyak kelapa yang dihasilkan industri besar. Beberapa kendala usaha yang dihadapi diantaranya sistem keuangan usaha yang belum tertata dan minimnya pemahaman pemilik dan staf dalam membuat laporan keuangan membuat usaha ini sulit berkembang. Tercampurnya keuangan usaha dan rumah tangga juga menjadi kendala internal. Selain memproduksi minya kelapa murni, dHayfa Sukses Berkah juga memiliki produk-produk turunan berbahan dasar minyak kelapa yang belum banyak diketahui masyarakat. Kegiatan pengabdian masyarakat ini dikembangkan sebuah sistem keuangan terkomputerisasi dan pemasaran digital bagi produk minyak kelapa Abila dan produk turunannya. Perkembangan sistem keuangan terkomputerisasi menunjukkan dampak positif dalam pengelolaan mitra. Pemanfaatan marketplace menunjukkan potensi dalam memperluas jangkauan pasar dan meningkatkan penjualan.
Penentuan Prioritas Pemeliharaan Trafo Distribusi dengan Integrasi Metode Delphi dan AHP Haloho, Freddi; Irawan, Mohammad Isa
COMSERVA : Jurnal Penelitian dan Pengabdian Masyarakat Vol. 5 No. 3 (2025): COMSERVA: Jurnal Penelitian dan Pengabdian Masyarakat
Publisher : Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59141/comserva.v5i3.3252

Abstract

Distribution transformer maintenance plays a critical role in ensuring the continuity and reliability of PLN’s electricity supply. Currently, PLN employs a Condition-Based Maintenance (CBM) approach, relying on a Health Index (HI) derived from Tier 1 and Tier 2 inspection outcomes. However, in practice, determining maintenance priorities remains largely dependent on the intuition and technical experience of decision-makers, leading to potential inconsistencies in decision-making. Additionally, the absence of a structured weighting mechanism among HI parameters and unclear relevance of indicators used further hampers valid and reliable decision-making aligned with current operational conditions. This research aims to propose a structured and adaptive Health Index evaluation method through the integration of the Delphi and Analytical Hierarchy Process (AHP) methods. The Delphi method was employed to identify the most relevant parameters based on expert consensus, while the AHP method provided logical and consistent weighting among these parameters. Although AHP does not entirely eliminate subjectivity, as it still depends on expert judgments, it offers a systematic and transparent way to manage conflicting criteria effectively. The Delphi application yielded seven sub-criteria parameters grouped into three main criteria: oil leakage, transformer body temperature, load percentage, grounding value, physical condition, transformer age, and neutral current percentage. Based on AHP analysis, the oil leakage parameter was identified as having the highest weighting (0.23), indicating its significant impact on transformer performance. Applying this methodology to 253 distribution transformers resulted in prioritizing maintenance into three categories: Priority I (4 transformers), Priority II (54 transformers), and Priority III (195 transformers). The findings and validation from this study demonstrate that a structured, weighting-based approach significantly enhances the accuracy and transparency of decision-making processes in asset maintenance management.
Studi Komparatif antara Jaringan Syaraf Tiruan Boltzman Machine dan Algoritma Genetika untuk Optimasi Traveling Salesman Problem Mohammad Isa Irawan
Limits: Journal of Mathematics and Its Applications Vol. 1 No. 1 (2004): Limits: Journal of Mathematics and Its Applications Volume 1 Nomor 1 Edisi Nove
Publisher : Pusat Publikasi Ilmiah LPPM Institut Teknologi Sepuluh Nopember

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

Abstract

Traveling Salesman Problem (TSP) dikenal sebagai suatu permasalahan optimasi klasik dan Non Deterministic Polynomial-time Complete (NPC). Permasalahan ini melibatkan se- orang salesman yang harus melakukan kunjungan sekali pada semua kota sebelum kembali ke kota awalnya, sampai akhirnya perjalanan itu disebut sempurna. Penyelesaian dari ma- salah ini adalah mencari nilai optimum yang paling murah, misalkan perjalanan dengan jarak terpendek atau yang mempunyai total harga yang termurah. Dalam paper ini akan dianalisis penyelesaian TSP dengan JST Boltzman Machine dan Algoritma Genetika. Dari hasil komparasi tersebut ternyata JST Boltzman Machine mem- berikan hasil lebih baik untuk menyelesaikan masalah TSP. Kata kunci : Jaringan Syaraf Tiruan, Boltzman Machine , Algoritma Genetika, TSP.
PENGKLASTERAN DATA KATEGORIS DENGAN ALGORITMA SHARED NEAREST NEIGHBOR Alvida Mustikarukmi; M. Isa Irawan; Nurul Hidayat
Limits: Journal of Mathematics and Its Applications Vol. 6 No. 1 (2009): Limits: Journal of Mathematics and Its Applications Volume 6 Nomor 1 Edisi Mei
Publisher : Pusat Publikasi Ilmiah LPPM Institut Teknologi Sepuluh Nopember

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

Abstract

Pengklasteran objek data merupakan salah satu cara untuk mempermudah dalam membaca data, terutama data berdimensi tinggi. Obyek-obyek data berada dalam satu klaster jika mempunyai kesamaan yang tinggi, dan sebaliknya, berada pada klaster berbeda jika menunjukkan ketidaksamaan. Data kategoris merupakan jenis data yang sering digunakan pada database/dataset. Data teks merupakan salah satu data kategoris. Pengklasteran dengan algoritma shared nearest neighbor (SNN) didasarkan pada anggapan bahwa titik-titik akan berada dalam klaster yang sama jika jumlah shared nearest neighbor melebihi ambang batas yang ditentukan. Algoritma SNN mampu memberikan hasil pengklasteran data teks dengan baik, dimana teks dengan tingkat kesamaan yang ditentukan, akan berada pada klaster yang sama.
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.
Co-Authors AA. Masroeri Abduh Riski, Abduh Adrianus Bagas Tantyo Dananjaya Ahmad Ridwan Akhmad Arif Junaidi Alan Catur Nugraha Alexander Setiawan Alvida Mustika Rukmi Alvida Mustikarukmi Amira, Siti Azza Andreas Handojo Antonio Galileo Tando Ari Kusumastuti Arie Dipareza Syafei Arifah, Enny Durratul Auliya Rahmayani Baiq Findiarin Billyan 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 Hendy Hendy Hozairi Imam Mukhlash Imam Mukhlash Ira Puspitasari Juhari Juhari, Juhari 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 Mondal, Kartick Chandra 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 Nugraha, Arma Perwira 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 Robin Wijaya, Robin Rohwana, Ulir Ronando, Elsen Rukmini, Meme Santoso Santoso Sepriadi, Robby Setiawan, Muhammad Nanda Setumin, Samsul Shahab, Muhammad Luthfi Siti Maghfiroh Soetrisno Soetrisno Sulastri Sulastri Titin J. Ambarwati Victory Tyas Pambudi Swindiarto YAN ADITYA PRADANA Yongky Ujianto Yuda Dian Harja Zulfa Afiq Fikriya