Article Per Year (5 Year)
p-Index From 2021 - 2026
9.193
P-Index
This Author published in this journals
All Journal JURNAL MEDIA INFORMATIKA BUDIDARMA JMM (Jurnal Masyarakat Mandiri) JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI JISTech (Journal of Islamic Science and Technology) JSiI (Jurnal Sistem Informasi) J-SAKTI (Jurnal Sains Komputer dan Informatika) JURIKOM (Jurnal Riset Komputer) JURTEKSI Jurdimas (Jurnal Pengabdian Kepada Masyarakat) Royal JOURNAL OF SCIENCE AND SOCIAL RESEARCH Jurnal Riset Informatika EDUMATIC: Jurnal Pendidikan Informatika Jurnal Teknologi Informasi dan Pendidikan Building of Informatics, Technology and Science Jurnal Sistem Informasi dan Informatika (SIMIKA) Community Development Journal: Jurnal Pengabdian Masyarakat Jurnal Teknik Informatika (JUTIF) Jutsi: Jurnal Teknologi dan Sistem Informasi Journal of Social Responsibility Projects by Higher Education Forum J-SAKTI (Jurnal Sains Komputer dan Informatika) J-Com (Journal of Computer) Jurnal Ipteks Terapan : research of applied science and education Jurnal Informatika dan Teknologi Informasi Digital Transformation Technology (Digitech) Jurnal Pemberdayaan Sosial dan Teknologi Masyarakat Jurnal Pengabdian Harapan Bangsa Jurnal Teknologi Ilmu Komputer Jurnal Ekonomi, Bisnis & Entrepreneurship (e-Journal)
Kifti, Wan Mariatul
Universitas Royal
Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Public Health Social Sciences Veterinary Other

Published : 73 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 73 Documents
Search

 4   5   6   7   8 
TOPSIS-BASED SYSTEM FOR THE SELECTION OF TRAINING PARTICIPANT CANDIDATES AT THE ASAHAN MANPOWER OFFICE Guntur Maha Putra; Wan Mariatul Kifti; Putri Amanda Nurhayati
JURTEKSI (jurnal Teknologi dan Sistem Informasi) Vol. 12 No. 2 (2026): Maret 2026
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Royal Kisaran

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33330/jurteksi.v12i2.4516

Abstract

Abstract: Job training is one of the government’s efforts to improve the quality of human resources so that they possess competencies that meet labor market demands. The process of selecting training participants at the Department of Manpower of Asahan Regency is still carried out manually, which can lead to subjectivity and inefficiency in determining the most eligible candidates. This study aims to develop a decision support system using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method to assist the selection process objectively and systematically. The study applies four evaluation criteria, namely education level, age, work experience, and interview, with a dataset consisting of 31 training candidates. The system is developed as a web-based application using PHP programming language and MySQL database. The TOPSIS method is applied through decision matrix normalization, weighting, determination of positive and negative ideal solutions, and preference value calculation to produce a ranking of candidates. The results show that the proposed system can provide objective recommendations for selecting training participants, improve the efficiency of the selection process, and support decision makers in producing more accurate and reliable decisions. Keywords: decision support system; selection; training; TOPSIS. Abstrak: Pelatihan tenaga kerja merupakan salah satu upaya pemerintah dalam meningkatkan kualitas sumber daya manusia agar memiliki kompetensi yang sesuai dengan kebutuhan dunia kerja. Proses pemilihan calon peserta pelatihan di Dinas Tenaga Kerja Kabupaten Asahan selama ini masih dilakukan secara manual sehingga berpotensi menimbulkan subjektivitas dan kurang efektif dalam menentukan peserta yang paling layak. Penelitian ini bertujuan untuk membangun sistem pendukung keputusan menggunakan metode Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) untuk membantu proses seleksi peserta pelatihan secara objektif dan sistematis. Penelitian ini menggunakan empat kriteria penilaian yaitu pendidikan, usia, pengalaman kerja, dan wawancara dengan jumlah data sebanyak 31 calon peserta pelatihan. Sistem dikembangkan berbasis web menggunakan bahasa pemrograman PHP dan database MySQL. Metode TOPSIS digunakan untuk melakukan normalisasi matriks keputusan, pembobotan, penentuan solusi ideal positif dan negatif, serta perhitungan nilai preferensi untuk menghasilkan perankingan peserta pelatihan. Hasil penelitian menunjukkan bahwa sistem yang dibangun mampu memberikan rekomendasi peserta pelatihan secara objektif, meningkatkan efisiensi proses seleksi, serta membantu pihak dinas dalam pengambilan keputusan yang lebih akurat. Kata kunci: pelatihan; seleksi; sistem pendukung keputusan; TOPSIS.
Data Mining Dengan Pendekatan Multiple Linear Regression Untuk Prediksi Hasil Panen Padi Alwi Syahbirin; William Ramdhan; Wan Mariatul Kifti
JURNAL RISET KOMPUTER (JURIKOM) Vol. 13 No. 2 (2026): April 2026
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v13i2.9652

Abstract

The rice agricultural sector plays an essential role in Asahan Regency, but current harvest predictions are still carried out conventionally and subjectively. This causes data inaccuracies that impact uncertainty in logistics planning and production policies by the local government. Therefore, this study aims to build a more accurate rice harvest prediction model to assist the Department of Agriculture of Asahan Regency in making strategic decisions. The research methodology used is data mining techniques by implementing the multiple linear regression method, utilizing historical data on land area and rainfall to predict harvest yields. The main results of this study indicate that the web-based prediction model designed is capable of performing valid calculations, producing a harvest projection for 2025 of 54,308.79 tons that aligns with mathematical model calculations. The implication of this research is that the relevant agencies have a reliable decision support tool for planning food security, irrigation systems, and fertilizer provision more efficiently, thereby minimizing errors caused by manual calculations
DETERMINATION OF PRIORITIES OF ELEMENTARY SCHOOL REHABILITATION AT ASAHAN USING SIMPLE ADDICTIVE WEIGHT Aprillia, Dian; Ramdhan, William; Kifti, Wan Mariatul
Jurnal Riset Informatika Vol. 4 No. 4 (2022): September 2022
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (775.325 KB) | DOI: 10.34288/jri.v4i4.193

Abstract

In the budgeting process for school building rehabilitation activities in Asahan Regency, there are still inaccuracies in selecting prioritized primary schools for rehabilitation. This study aimed to apply the Simple Additive Weighting (SAW) method to determine five primary schools that were prioritized for repair. This research method uses quantitative methods. The data source comes from the East Kisaran and West Kisaran Elementary Schools. The data were analyzed using the SAW method based on the criteria weight depending on the matrix value and normalization. The results showed the 5 largest criteria weights, namely UPTD SDN 010097 Selawan (0.940), UPTD SDN 014689 Lestari (0.884), UPTD SDN 010039 Sentang (0.880), SD Taman Kasih Karunia (0.847), and UPTD SDN 018453 Siumbut-Umbut (0.820). ). This study concluded that the double exponential smoothing method could make it easier to determine which primary school decisions are prioritized for rehabilitation.
Co-Authors Ade Nurainun Adnan Fauzi Ahmad Muhazir Alwi Syahbirin Amalia Amalia Amalia Amalia Amalia Amalia, Laily Rizky Annisa Azzahra Apriaji Kurniawan Aprillia, Dian Ari Dermawan Arip Muhridan Arju Devpriandi Siahaan Arridha Zikra Syah Bachtiar Efendi Bachtiar Efendi, Bachtiar dermawan, ari Dian Aprillia eka eka Enda Triswati Endra Saputra Frans Andrean Hasibuan Guntur Maha Putra Gustin, Sela Habibullah . Hasian, Irene Helmiah, Fauriatun Herman Saputra Herman Saputra Hutapea, Tiofani Br. Imam Wahyudi Indrawan, Imam Wahyudi Indah Pratiwi, Enggy Indahini, Sri Jeperson Hutahaean Jhonson Efendi Hutagalung Lubis, Adi Prijuna Lubis, Syafaat Sufi M Irfan Fahmi M. Zulfakhri Jain Mayang Sari, Windy Astika Muhammad Amin Muhammad Novri Rachmawan Muti'ah, Rahma Nabila, Inaya Nasrun Marpaung Nasution, Rama Danil Fahri Ningrum, Mawar Puspitha Nofriadi, Nofriadi Novianti Novianti Nur Aini Nur Aini Nur Wati Nuriadi Manurung Nuriadi Manurung Nursia, Akris Nursia Nurwati Nurwati Nurwati Nurwati Puspita Deri Syahfitri Putri Amanda Nurhayati Putri Indriani Rahayu, Elly Raja Fazlun Dinara Ramdhan, William Reski Ramadhan Siregar Risnawati Risnawati Rohminatin Rohminatin Rohminatin Rohminatin Rohminatin Rohminatin, Rohminatin SANTOSO SANTOSO Santoso Santoso SATRIYAS ILYAS Sela Gustin Siagian, Yessica Siregar, Beni Harianto Siti Mujiatun Sri Okta Purnamasari Suci Andriyani Sudarmin Sudarmin Sudarmin Sudarmin Sudarmin Sudarmin Sumarlin Sumarlin Syafaat Sufi Lubis Syahira Syahira Tri Anjar Ningsih Vira Fahrani Waji Datur Rahmi Sipahutar Wan Mhd Iqbal Muttaqin William Ramdhan William Ramdhan Windy Astika Mayang Sari Windy Swaradana Yessica Siagian Zulfi Azhar