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All Journal Journal of Mathematics Instruction, Social Research and Opinion INFOKOM
Erwanto, Muhammad
Unknown Affiliation
Humanities Computer Science & IT Education Languange, Linguistic, Communication & Media Mathematics Social Sciences

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Decision Tree Methodology (C4.5) for Predicting Students' Reading Interest in the Library SMK Negeri 1 Kota Cirebon Erwanto, Muhammad; Kosim, Kosim; Riyanto, Nur Bambang; Jogo, Sukmo Banyu
Journal of Mathematics Instruction, Social Research and Opinion Vol. 4 No. 1 (2025): March
Publisher : MASI Mandiri Edukasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58421/misro.v4i1.359

Abstract

Reading is one aspect of language skills that is actively receptive. The media used in reading is written language media. Reading is seeing and understanding the content of what is written, either spelling or pronouncing what is written. Reading activities are often socialised in education because reading is a very important activity to support teaching and learning activities at school. The facility provided by the school as a support in socialising reading activities for students is the library. Many students often utilise the SMK Negeri 1 Kota Cirebon library to carry out the borrowing process and read books there. Reading activities are an obligation that students must carry out, but students who carry out reading activities cannot be categorised as students with an interest in reading. The problem faced by the SMK Negeri 1 Cirebon City library is that it has not been able to predict or know the reading interests of students in the school library. This study uses data mining techniques with the C4.5 algorithm to predict student reading interest. This research produces rules to help SMK N 1 Cirebon City predict student reading interest in the school library. This step is done by designing a system model that uses the C4.5 algorithm to form a decision tree to produce a rule for predicting student reading interest. This research will produce valuable information about predicting student reading interest in the SMK Negeri 1 Cirebon City library using the C4.5 algorithm method.
Monte Carlo Simulation for Rattan Revenue: Production, Costs, and Demand Analysis Meyasha, Igen; Erwanto, Muhammad
Journal of Mathematics Instruction, Social Research and Opinion Vol. 4 No. 4 (2025): December
Publisher : MASI Mandiri Edukasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58421/misro.v4i4.721

Abstract

The rattan industry in Cirebon, Indonesia, is a significant part of the country's creative economy, but it faces several major challenges, including unstable production, fluctuating prices for raw materials, and uncertain demand, which make it difficult to predict income. The goal of this research is to create a quantitative model that can accurately forecast business income and help entrepreneurs make better financial decisions. The study employs the Monte Carlo simulation method to examine the impact of production levels, raw material costs, and demand on the revenue of rattan businesses. The simulation was run 10,000 times using probability distributions based on historical data. The results indicate that market demand and selling prices have the most significant positive impact on profits, while raw material costs have the most substantial negative effect on profits. The model illustrates the uncertainty of business conditions, with profit varying between IDR 19.5 billion and IDR 76.1 billion, averaging IDR 50.2 billion. The findings underscore the need to strike a balance between meeting growing demand and managing costs to achieve long-term profitability. This Monte Carlo-based model can be a valuable tool for rattan business owners and policymakers to support informed planning and mitigate risks.
PERBANDINGAN METODE MAUT DAN SMART UNTUK MENENTUKAN CALON PENERIMA BANTUAN RUMAH TIDAK LAYAK HUNI PADA DESA KADIPATEN Erwanto, Muhammad; Virgiyanti; Muthiah, Siti
INFOKOM Vol. 18 No. 2 (2025): JURNAL ILMIAH INFOKOM STIKOM POLTEK CIREBON
Publisher : STIKOM POLTEK CIREBON

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Abstract

Bantuan Rumah Tidak Layak Huni (RTLH) merupakan program pemerintah yang memberikan bantuandana untuk perbaikan rumah tidak layak huni. Desa Kadipaten adalah salah satu desa penerima bantuankelangsungan hidup kepada masyarakat yang berpenghasilan rendah, berupa perbaikan rumah yangkondisinya tidak layak untuk ditempati. Masalah yang terjadi pada instansi dalam menentukan calonpenerima bantuan rumah tidak layak huni adalah proses penentuan calon penerima bantuan masih bersifatsubjektif, artinya yang tidak berhak justru menerima bantuan tersebut. Berdasarkan permasalahantersebut, penulis membuat sistem pendukung keputusan yang dimana membandingkan metode MAUTdan SMART untuk mengatasi permasalahan tersebut. Untuk kriteria yang digunakan pekerjaan,penghasilan, jumlah tanggungan keluarga, material atap, material dinding, material lantai, mck dan statusrumah. Berdasarkan hasil perhitungan metode MSE, diperoleh hasil perhitungan perbandingan antarametode MAUT yaitu 444.3286 sedangkan SMART 443.9798. Dapat disimpulkan bahwa metode dengannilai akhir dari metode MSE yang lebih kecil yaitu metode SMART adalah metode terbaik dan dapatdirekomendasikan untuk menentukan calon penerima bantuan rumah tidak layak huni pada DesaKadipaten. Bedasarkan hasil penelitian dengan menggunakan dua metode yang berbeda menyatakanbahwa Sukarman dengan skor 0.900, Lilis Lismayanti dengan skor 0.888, Ahmad Subagjo dengan skor0.883, Ipah Saripah dengan skor 0.854 dan Riyanto dengan skor 0.846 ini direkomendasikan sebagaicalon penerima bantuan rumah tidak layak huni.
Co-Authors Jogo, Sukmo Banyu Kosim Kosim Meyasha, Igen Riyanto, Nur Bambang Siti Muthiah Virgiyanti