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Algoritma General and Test Menggunakan Metode Depth First Search Dalam Penentuan Jalur Rute Terpendek Putri, Weni Lestari; Jarti, Nanda
Brahmana : Jurnal Penerapan Kecerdasan Buatan Vol 4, No 2 (2023): Edisi Juni
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/brahmana.v4i2.190

Abstract

General and Test is a branch of knowledge that is included in the field of artificial intelligence. Success in using the system is the basic goal of artificial intelligence itself. General and test works in solving problems and finding the best solution which is used as a reference in determining the path to find the smallest value so that you can quickly go to the place to be visited and can save time and money while traveling to the location. General and test has the concept of looking for the smallest alternative path by how to find all the path values to be visited, after being processed as a whole for each path, alternative starling values will be obtained which can be used as directions. The way the General and test method works is to combine Depth First Search with a backracking system. All solutions must be discussed in full prior to testing. The procedure for working with this method must be carried out systematically in order to get a good solution. General and test has a working principle (1). Generate possible solutions (2). Test whether the solution is correct according to the required criteria. (3). If a solution has been found then exit, but if it has not been found then the next step is to repeat the steps until you find the highest result that can be used as a reference in finding the path with the least or shortest distance. The problem in this study is the lack of information in passing the smallest path because there are many paths that must be chosen to get to the destination. The benefit of this research is to help the user in providing information on the path to be passed so as to save time and costs. Alternative results are obtained that can be used as a solution, namely the A-B-G-J-M-T line = 23+15+5+11=54 KM. This discussion can be used as a reference by traders in finding the shortest alternative so as to save travel costs and time
Sistem Pengambilan Keputusan Rekomendasi Pemberian Kredit dengan Metode Simple Additive Weighting Putri, Weni Lestari
Brahmana : Jurnal Penerapan Kecerdasan Buatan Vol 5, No 1 (2023): Edisi Desember
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/brahmana.v5i1.272

Abstract

The decision-making system produces recommendations for parties entitled to obtain loans in accordance with predetermined provisions. There are 5 criteria that are used as a reference in providing credit loans in terms of Characteristics, Capacity, Condition, Capital and Collateral. Each criterion has a different value so a Simple Additive Weighting (SAW) method is needed to produce a decision. The way the Simple Additive Weighting (SAW) method works is by entering each weight value in each criterion. The advantage of the SAW method is that it has the ability to carry out assessments more precisely because it is based on the criteria values and preference weights that have been determined and can select the best alternative from a number of existing alternatives, apart from that because there is an improvement process after determining the weight value for each attribute. The final results of the research recommended obtaining a loan in the name of Kamedia Kemala with a value of 0.8248.
ANALISIS SIMULASI MONTE CARLO DALAM MEMPREDIKSI PERMINTAAN JASA SERVICE KOMPUTER PADA HANIFNAFI COMPUTER BATAM Putri, Weni Lestari; Jarti, Nanda
Jurnal Liga Ilmu Serantau Vol. 3 No. 1 (2026): Jurnal Liga Ilmu Serantau
Publisher : LPPM Universitas Ibnu Sina

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36352/jlis.v3i1.1390

Abstract

Penelitian ini bertujuan untuk memprediksi permintaan produk dan mengoptimalkan persediaan pada Hanifnafi Computer Batam menggunakan Simulasi Monte Carlo melalui perangkat lunak Jamovi. Ketidakpastian pasar retail komputer di Batam menuntut metode peramalan yang lebih akurat daripada sekadar perhitungan rata-rata. Dengan menggunakan data historis penjualan dua tahun terakhir, simulasi dijalankan sebanyak 10.000 iterasi untuk memetakan probabilitas permintaan di masa depan. Hasil analisis menunjukkan bahwa permintaan paling mungkin berada pada rentang 35–45 unit, dengan risiko stok tidak laku sebesar 14% dan peluang lonjakan permintaan sebesar 11%. Penelitian ini menyimpulkan bahwa penggunaan simulasi Monte Carlo membantu pemilik usaha dalam menetapkan safety stock yang tepat guna meminimalkan kerugian akibat penumpukan barang atau kehabisan stok
Pembelajaran Berbasis Proyek Menggunakan Trainer Simulator AC Energi Hijau untuk Meningkatkan Kompetensi Guru SMK Yunesman, Yunesman; Yasra, Refdilzon; Putri, Weni Lestari
Jurnal SOLMA Vol. 15 No. 1 (2026)
Publisher : Universitas Muhammadiyah Prof. DR. Hamka (UHAMKA Press)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22236/solma.v15i1.21414

Abstract

Background: This study was motivated by the low competence of vocational high school teachers in understanding and applying green energy concepts and learning technologies relevant to industrial needs. This condition highlights the need for training to improve teachers’ ability to meet workforce demands and align with the Indonesian Government’s Nawacita program to strengthen human resource quality. The purpose of this study was to determine the effectiveness of technology-based green energy training in improving teachers' competence at SMK Aljabar Batam. Method: The research employed a quantitative, one-group pretest–posttest design. Data were collected through pre- and post-tests, participant satisfaction questionnaires, and supporting interviews. Results: The results showed an average improvement in teacher competence of 30.2%, covering technical skills, understanding of green energy, pedagogical ability, and technology integration in learning. The participants’ satisfaction level was very good, with an average score of 4.66. Conclusion: The technology-based green energy training effectively improved vocational teachers’ competencies and can serve as a sustainable professional development model to enhance educational quality and national competitiveness.