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All Journal Jurnal Penelitian Sistem Informasi Repeater: Publikasi Teknik Informatika dan Jaringan
Harninda Br Keliat
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Computer Science & IT Decision Sciences, Operations Research & Management

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Sistem Pendukung Keputusan Pemilihan Susu Formula pada Balita Menggunakan Metode Simple Additive Weighting (SAW) Dwi Fitri Rahayu; Elisa Br Sembiring; Harninda Br Keliat; Safrizal Safrizal
JURNAL PENELITIAN SISTEM INFORMASI (JPSI) Vol. 3 No. 1 (2025): JURNAL PENELITIAN SISTEM INFORMASI
Publisher : Institut Teknologi dan Bisnis (ITB) Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54066/jpsi.v3i1.2991

Abstract

Formula milk is packed with essential nutrients. It contains beneficial components such as carbohydrates, proteins, fats, vitamins, sodium, DHA, and more. High-quality formula milk should not lead to gastrointestinal issues such as diarrhea, vomiting, or problems with digestion, nor should it cause coughing, breathing difficulties, or skin reactions due to an incorrect formula choice. This research aims to explore how mothers select suitable formula milk for their babies. The study utilizes the SIMPLE ADDITIVE WEIGHTING (SAW) method to determine alternative options based on pre-assigned weights and criteria. Following this, the ranking method is applied to identify the best alternative. According to the findings, five alternatives were evaluated: MORINAGA CHIL KID, LACTOGEN, SGM, BEBELOVE, and NUTRIBABY ROYAL 1. Additionally, five criteria were considered: Milk Price, Safety (Bpom Certification, Halal, etc.), Nutritional Content (Protein, Calcium, Iron, Vitamins, etc.), Taste (Natural Sweetness, Vanilla, Honey), and Market Availability.
Penggunaan Metode Rough Set untuk Menentukan Tingkat Kesiapan Siswa dalam Menghadapi ANBK di SMP Negeri 2 Kuala Harninda Br Keliat; Novriyenni Novriyenni; Tio Ria Pasaribu
Repeater : Publikasi Teknik Informatika dan Jaringan Vol. 3 No. 3 (2025): Juli : Repeater : Publikasi Teknik Informatika dan Jaringan
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/repeater.v3i3.619

Abstract

The Computer-Based National Assessment (ANBK) is an essential instrument designed to comprehensively measure student competence, including literacy, numeracy, and character aspects. However, in practice, many students still face various challenges during preparation, such as cognitive limitations, psychological readiness, and technical barriers, which affect their overall readiness to participate in ANBK. This study aims to analyze the readiness level of students at SMP Negeri 2 Kuala by employing the Rough Set method. The variables examined include digital literacy, subject matter understanding, psychological readiness, and school facility support. Data were collected from 250 ninth-grade students through structured questionnaires and subsequently processed using the Rosetta software to perform attribute reduction and generate decision rules. The findings indicate that digital literacy, subject matter understanding, and psychological readiness are the most influential variables in determining student readiness, while facility support serves only as a complementary factor. The extraction process generated seven decision rules with an accuracy level of 100%, which effectively classified students into three readiness categories: highly ready, ready, and less ready. These results confirm that the Rough Set method is highly effective for identifying dominant factors and producing decision rules that can guide schools in developing targeted strategies to enhance student readiness for ANBK.
Co-Authors Dwi Fitri Rahayu Elisa Br Sembiring Novriyenni Novriyenni Safrizal Safrizal Tio Ria Pasaribu