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Retno Wahyusari
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Jurnal Ilmiah Informatika dan Komputer
Published by Sekolah Tinggi Teknologi Ronggolawe Cepu
ISSN : -     EISSN : 29621399     DOI : https://doi.org/10.51901/jiifkom.v3i1
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering
JIIFKOM: Journal of Scientific Informatics and Computers is a journal that contains scientific papers from researchers, academics, and practitioners, in the form of research results, literature reviews, and/or other forms of scientific writing, which specifically examines the field of Computer Science, among others as follows : Computer Science: Artificial Intelligence, Machine Learning, Data Mining, Expert System, Decision Support System Informatics: Web Programming, Mobile Computing, Computer Networks, Making Information Systems, Database Systems, Security Systems
Arjuna Subject : Ilmu Komputer (semua kategori) - Kecerdasan Buatan
Articles 6 Documents
 1 
Search results for , issue "Vol 3 No 2 (2024): JIIFKOM" : 6 Documents clear
SPK PENERIMAAN BLT DENGAN METODE SAW Amrozi, M Ali Ali; Safrudin, Moch. Yusuf; Pramita Widyassari, Adhika
JIIFKOM (Jurnal Ilmiah Informatika dan Komputer) Vol 3 No 2 (2024): JIIFKOM
Publisher : Jurusan Informatika STTR Cepu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51901/jiifkom.v3i2.413

Abstract

Bantuan Langsung Tunai (BLT) merupakan inisiatif pemerintah Indonesia untuk meringankan beban keuangan keluarga miskin. Namun identifikasi penerima BLT seringkali menimbulkan permasalahan mengenai validitas data dan transparansi seleksi. Pada penelitian ini, kami mengembangkan dan menerapkan sistem pendukung keputusan (SPK) dengan metode simple additive Weighting (SAW) untuk menentukan penerima BLT secara objektif. Metode SAW dipilih karena menyederhanakan pengambilan keputusan dengan menambahkan nilai tertimbang untuk berbagai kriteria seperti pendapatan, jumlah anggota keluarga, dan kondisi kehidupan. Hasil penelitian menunjukkan metode SAW efektif mengidentifikasi penerima BLT dengan mengurangi bias subjektif serta meningkatkan transparansi dan akurasi seleksi. Uji lapangan menunjukkan bahwa SPK berbasis SAW berkinerja baik. Penelitian ini diharapkan dapat membantu pemerintah dalam memanfaatkan teknologi informasi yang lebih efisien dan transparan untuk meningkatkan kualitas penyaluran BLT. Kata Kunci : Sistem pendukung keputusan, BLT, keluarga kurang mampu, pembobotan sederhana, transparansi, akurasi.
Perbandingan Metode TOPSIS Dan SAW Sebagai Sistem Pendukung Keputusan Dalam Menentukan Supplier Bahan Baku Sari, Hasna Yustika; Salma Salsabila, Andini; Pramita Widyassari, Adhika
JIIFKOM (Jurnal Ilmiah Informatika dan Komputer) Vol 3 No 2 (2024): JIIFKOM
Publisher : Jurusan Informatika STTR Cepu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51901/jiifkom.v3i2.414

Abstract

Choosing the right supplier is crucial for operational success in the era of globalization, as errors in supplier selection can negatively impact product quality, costs, and customer satisfaction. XYZ Company, engaged in the food processing sector, faces challenges in optimally selecting raw material suppliers. The Decision Support System (DSS) employs the Simple Additive Weighting (SAW) method and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to aid this process, where SAW offers simplicity and ease of implementation, while TOPSIS provides a more comprehensive assessment by considering the relative distance to positive and negative ideal solutions. This study compares the effectiveness of SAW and TOPSIS in supplier selection at XYZ Company, providing insights into the strengths and weaknesses of each method and serving as a reference for other companies facing similar challenges.
Multi-Objective Optimization By Ratio Analysis (MOORA) Sebagai Implementasi Rekomendasi Penghargaan Dosen Berbasis Website Iksan, Helmi; Wibowo, Setyoningsih; Handayanto, Agung
JIIFKOM (Jurnal Ilmiah Informatika dan Komputer) Vol 3 No 2 (2024): JIIFKOM
Publisher : Jurusan Informatika STTR Cepu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51901/jiifkom.v3i2.429

Abstract

Lecturers are professional educators and scientists with the main task of transforming, developing and disseminating science, technology and art through education, research and community service. Based on Republic of Indonesia Government Regulation Number 37 of 2009 concerning lecturers. Article 19 paragraph 1 states that lecturers who carry out their professional duties are entitled to receive awards. This shows that determining the right choice of award is very important for lecturers as an appreciation for their performance, so it is necessary to discuss and create a Decision Support System using the Multi-Objective Optimization by Ratio Analysis (MOORA) method as an implementation of recommendations for lecturer awards based on research and service performance. website-based community with the data used is data from lecturers from the Informatics Study Program, Faculty of Engineering and Informatics, taken from PGRI University Semarang. In building a Decision Support System application, the Waterfall method is used. For system modeling using Unified Modeling Language (UML), the software used to build this system uses the Hypertext Preprocessor (PHP) and XAMPP programming language as a connection to the database, namely MySQL. System testing uses User Acceptance Testing (UAT), black box and white box methods. With this lecturer reward system, it is hoped that it can encourage lecturers to achieve positively and be more productive.
Implementasi Data Mining Menggunakan Algoritma Apriori Dalam Menentukan Pola Penjualan Joko Handoyo; Handoyo, Joko; Rafiqasha, Reyhan Maulana
JIIFKOM (Jurnal Ilmiah Informatika dan Komputer) Vol 3 No 2 (2024): JIIFKOM
Publisher : Jurusan Informatika STTR Cepu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51901/jiifkom.v3i2.434

Abstract

Toko Singgah Mata, a company that sells safety and security equipment, located in Kendilan Sambong Village, is facing several problems that require creative solutions. One of the main problems is the uncomputerization of business processes and the high stock of unsold goods due to a lack of buyer attraction. Shop owners need to develop creative ideas to increase sales by arranging ordering patterns that are attractive to consumers. In an effort to increase the efficiency of preparing order patterns, shops can utilize data mining techniques. By using the Apriori algorithm, transaction data from interviews with shop staff can be processed to determine the most effective combination in product sales. The analysis was carried out on transaction data from January to June 2023, involving 122 Singgah Mata store transactions. The results of analysis using the Apriori algorithm produce four association rules based on parameters with a minimum support value of 10% and a minimum confidence value of 10%. The lift ratio value obtained is greater than 1, indicating that the rule has a positive correlation. The application of the Apriori algorithm to the Singgah Mata store information system produces results that are consistent with manual analysis. This system proves its usefulness in forming an effective sales strategy. With a trial success rate of 89.2%, the functional results of the tested cases show excellent system performance, giving confidence that the application of this technology can make a positive contribution to increasing sales and operational efficiency of Singgah Mata stores.
Penerapan Kombinasi Genetic Algorithm (GA) dan Bees Algorithm (BA) untuk Penjadwalan Matakuliah Praktikum Putro, Dwi Purnomo; Suryani, Puput Eka; Wahyusari, Retno
JIIFKOM (Jurnal Ilmiah Informatika dan Komputer) Vol 3 No 2 (2024): JIIFKOM
Publisher : Jurusan Informatika STTR Cepu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51901/jiifkom.v3i2.437

Abstract

A perfect solution to the challenging issue of course scheduling is needed to prevent scheduling conflicts and guarantee a fair allocation of courses. The effectiveness of genetic algorithms (GA) and genetic algorithms combined with bee algorithms (GA+BA) for automatic course scheduling is compared in this study. this research also investigates the enhancement of performance by the use of the Bee Algorithm, a recognized expert in exploration and exploitation techniques. According to experimental data, when compared to GA alone, GA+BA consistently yields greater fitness values but the computation time increases. The results show that GA only achieves an average fitness value of 0.86, while GA+BA achieves an average fitness value of 0.98. However, GA+BA calculates an average computing time of 14.41 seconds slower, than GA which takes 8.59 seconds. These findings show that combining BA into the GA framework is able to optimally improve the solution to the problem of scheduling practicum courses. This study shows that GA+BA is a successful method in terms of automatic course scheduling, which provides a solution for use in actual.
Pemodelan Dicision Tree Untuk Analisis Penjualan Barang Pada Koperasi Dwi Makmur Desa Menden Junaidi, Muksan SAN; Valentika, Mia Nanda; Wibawa, Eka Satria
JIIFKOM (Jurnal Ilmiah Informatika dan Komputer) Vol 3 No 2 (2024): JIIFKOM
Publisher : Jurusan Informatika STTR Cepu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51901/jiifkom.v3i2.439

Abstract

The Dwi Makmur Menden Cooperative located in Mendenrejo Village, which is engaged in savings and loan businesses and goods stores. Service problems often arise in stores due to running out and delays in stock of goods. The purpose of this research is to produce a rule or rules between goods that are often sold simultaneously with classification techniques and to determine the level of consumer purchases in associations between product combinations. The research data is taken from the sale of goods for the 2020 period, where there are often problems with the availability of goods on stock cards. The decision tree algorithm from the rapidminer application will be used as a classification process tool. The results from the decision tree clearly show that the import results from selling prices that are categorized as in demand are sales of goods greater than (>) than 87250, while those categorized as not selling are sales of goods that are less than (<) than 87250. With unit prices less than (<) 75000 and the unit price is greater (>) than 75000.

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