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All Journal JOURNAL OF SCIENCE AND SOCIAL RESEARCH Journal of Computer Networks, Architecture and High Performance Computing Jurnal Pemberdayaan Sosial dan Teknologi Masyarakat Jurnal Ilmiah Teknik Informatika dan Komunikasi Jurnal Pengabdian Masyarakat dan Riset Pendidikan Jurnal Intelek Dan Cendikiawan Nusantara Jurnal Intelek Insan Cendikia Merkurius: Jurnal Riset Sistem Informasi dan Teknik Informatika Sevaka: Hasil Kegiatan Layanan Masyarakat
Irwansyah, Bambang
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Religion Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Social Sciences Other

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Journal : JOURNAL OF SCIENCE AND SOCIAL RESEARCH

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PENERAPAN METODE ANALYTICAL HIERARCHY PROCESS (AHP) DALAM MENGANALISA NILAI PENYUSUTAN INVENTORI ASET PADA KANTOR BALAI DESA SIDOMULYO Irwansyah, Bambang
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol 8, No 3 (2025): August 2025
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v8i3.4235

Abstract

Abstract: Sidomulyo Village Hall Office, currently the agency has several assets including 1 computer unit, 4 air conditioners, 2 printers, and 1 television. And the second interview with noni as the Head of Finance (Village Treasurer) she stated that when calculating the depreciation of the residual value of assets in the Village Agency it is not optimal because it is still done conventionally such as manually calculated using a calculator in a book and has not been computerized. Produce an asset inventory application to make it easier to calculate the depreciation value of goods in the government agency Sidomulyo Village Hall Office. The purpose of this study is to change the manual calculation system into a computerized calculation system. The data used is asset data owned by the Sidomulyo Village Hall Office. The results of the AHP calculation test show that the depreciation of assets for Laptops, Printers, Photocopy Machines, AC, Digital, Wall Clocks, Fans, Refrigerators and Sound Systems is 30% and 32-inch TV Assets is 20%. Keywords: Inventory Application, AHP Method, Sidomulyo Village Hall Office, Web. Abstrak: Kantor Balai Desa Sidomulyo, saat ini instansi tersebut memiliki beberapa aset diantaranya komputer 1 unit, air conditioner 4 unit, mesin cetak (printer) 2 unit, dan televisi 1 unit. Dan wawancara kedua dengan noni sebagai Kaur Keuangan (Bendahara Desa) beliau menyatakan bahwa saat didalam perhitungan penyusutan nilai residu pada aktiva/aset di Instansi Desa tersebut belum maksimal karena masih dilakukan secara konvensional seperti dihitung manual menggunakan kalkulator dibuku dan belum terkomputerisasi. Menghasilkan aplikasi inventori aset agar lebih mudah dalam menghitung nilai penyusutan barang pada instansi pemerintahan Kantor Balai Desa Sidomulyo. Tujuan penelitian ini ialah mengubah sistem perhitungan manual menjadi sebuah sistem perhitungan yang sudah terkomputerisasi. Data yang digunakan berupah data aset yang dimiliki oleh Kantor Balai Desa sidomulyo. Hasil pengujian perhitungan AHP terlihat penyusutan aset Laptop, Printer, Mesin Foto Copy, AC, Digital, Jam Dinding, Kipas Angin, Kulkas dam sound System sebesar 30% dan Aset TV 32 Inci Sebesar 20%. Kata kunci: Aplikasi Inventori, Metode AHP, Kantor Balai Desa Sidomulyo, Web.
ANALISIS TINGKAT KEPARAHAN COVID-19 DI SUATU NEGARA MENGGUNAKAN METODE K-MEDOID CLUSTERING Amelia, Syahputri; Yusri, Eldo; Irwansyah, Bambang; Andira, Ayu; Sukri, Muhammad; Yafi, Muhammad Fauzan; Affandi, Muhammad
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol 9, No 1 (2026): February 2026
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v9i1.5787

Abstract

Abstract: This study aims to classify the severity of COVID-19 cases based on patient and region data using the K-Medoid Clustering method. COVID-19 has varying degrees of symptom severity, requiring cluster analysis to identify severity patterns to support decision-making in healthcare resource allocation and policy formulation. The data used included the number of positive cases, recovered cases, deaths, the average age of patients, and comorbidity levels. The results showed that the K-Medoid method was able to effectively cluster the data. In the raw dataset, the percentage of patients not infected with COVID-19 was 62.62%, while the percentage of infected patients was 37.38%. Based on sample characteristics, non-obese patients accounted for 74.54%, obese patients 25.46%, and patients with a combination of obesity and cardiovascular disease 0.57%. Keywords: Covid-19, Severity, K-Medoid Clustering, Data Mining Abstrak: Penelitian ini bertujuan untuk mengelompokkan tingkat keparahan kasus COVID-19 berdasarkan data pasien dan wilayah menggunakan metode K-Medoid Clustering. COVID-19 memiliki variasi tingkat keparahan gejala, sehingga diperlukan analisis klaster untuk mengidentifikasi pola keparahan yang mendukung pengambilan keputusan dalam alokasi sumber daya kesehatan dan perumusan kebijakan. Data yang digunakan meliputi jumlah kasus positif, kasus sembuh, kasus meninggal, usia rata-rata pasien, serta tingkat komorbiditas. Hasil penelitian menunjukkan bahwa metode K-Medoid mampu melakukan pengelompokan data secara efektif. Pada dataset mentah, persentase pasien tidak terjangkit COVID-19 sebesar 62,62%, sedangkan pasien terjangkit sebesar 37,38%. Berdasarkan karakteristik sampel, pasien non-obesitas memiliki persentase 74,54%, pasien obesitas 25,46%, dan pasien dengan kombinasi obesitas serta penyakit kardiovaskular sebesar 0,57%. Kata Kunci : Covid-19, Tingkat Keparahan, K-Medoid Clustering, Data Mining
IMPLEMENTASI ALGORITMA K-MEANS CLUSTERING UNTUK MENGELOMPOKKAN SISWA BERDASARKAN NILAI UTS, UAS, DAN TUGAS Irwansyah, Bambang; Daniswara, Daniswara; Handayani, Triana Puspa; Natasya, Nurul; Ardana, Abdul Aziz; Fauzar, Muhammad Fakhri; Hardiansyah, Fajar
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol 9, No 1 (2026): February 2026
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v9i1.5758

Abstract

Abstract : This study aims to apply the K-Means Clustering method to analyze and classify students’ academic performance based on Midterm Exam (UTS), Assignments, and Final Exam (UAS) scores at SMK Swasta Kualuh. The main problem faced by the school is the difficulty of analyzing students’ score data manually as the volume of data increases, which requires a more objective and structured approach. This research uses a quantitative approach with data mining techniques through the K-Means algorithm. The data were obtained from students’ academic scores and processed through data cleaning, determination of the number of clusters, distance calculation using Euclidean Distance, and iterative clustering until stable results were achieved. The results show that students were successfully grouped into three clusters: high-performing, average-performing, and low-performing students. The application of the K-Means method provides systematic insights into students’ academic performance and can support schools in making better decisions to improve learning quality. Keywords: K-Means Clustering, Data Mining, Student Performance, Academic Scores, Web. Abstrak : Penelitian ini bertujuan untuk menerapkan metode K-Means Clustering dalam menganalisis dan mengelompokkan prestasi akademik siswa berdasarkan nilai Ujian Tengah Semester (UTS), Tugas, dan Ujian Akhir Semester (UAS) di SMK Swasta Kualuh. Permasalahan yang dihadapi sekolah adalah sulitnya melakukan analisis data nilai siswa secara manual seiring dengan meningkatnya jumlah data, sehingga diperlukan metode yang lebih objektif dan terstruktur. Metode penelitian yang digunakan adalah pendekatan kuantitatif dengan teknik data mining menggunakan algoritma K-Means. Data yang digunakan berasal dari nilai akademik siswa yang kemudian diproses melalui tahap pembersihan data, penentuan jumlah klaster, perhitungan jarak menggunakan Euclidean Distance, serta iterasi hingga klaster stabil. Hasil penelitian menunjukkan bahwa data siswa berhasil dikelompokkan ke dalam tiga klaster, yaitu siswa berprestasi tinggi, sedang, dan rendah. Penerapan metode K-Means ini mampu membantu pihak sekolah dalam mengidentifikasi tingkat prestasi siswa secara lebih sistematis dan dapat dijadikan dasar dalam pengambilan keputusan untuk peningkatan kualitas pembelajaran. Kata kunci: K-Means Clustering, Data Mining, Prestasi Siswa, Nilai Akademik, Web.
Co-Authors Affandi, Muhammad Agrinda Aulia Lubis Agusman, Ridho Amelia, Syahputri Apdillah, Dicky Ardana, Abdul Aziz Arinda Faradillah Marpaung Armanda A. R, Kafilano Ayu Andira Az Zikri, Mhd Zahir Azhari, Dea Tiara Daniswara Daniswara, Daniswara Dea Tiara Azhari Dea, Emi Delyanti Putri Sitorus Devi Puspita Sari Dicky Apdilah Dilla Atika Sury Eldo Yusri Fahri Finanda Rizki Fajar Hardiansyah Fauzar, Muhammad Fakhri Ferry Cahyadi Hafiz, Utami Wardah Handayani, Triana Puspa Hardiansyah, Fajar Harmayani Harry Ardian Imam Arifin M. Fikri Gunawan Marpaung, Nasir Fadillah Muhammad Sukri Nabila Nabila, Nabila natasya, nurul Novica Jolyarni Dornik Nur'Arsy, Sultan Nico Nurdiani Rahmat Rahmat Rahmat Reza Fahlevi Rezki Abdillah Riswan Syahputra Damanik Rizky Febriansyah Santi Kayani Siregar Saputra, M Yoggi Septi Nur Selase Siti Ramadani Sultan Nico Nur'Arsy Syahputri Amelia Syahrul Syahrul Yafi, Muhammad Fauzan Yusri, Eldo Zulfaarrahman Zulfaarrahman