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Jurnal Ilmiah Computer Science
Published by PT. SNN Media Tech Press
ISSN : -     EISSN : 30267145     DOI : https://doi.org/10.58602/jics
Core Subject : Science, Engineering,
Computer Science & IT Decision Sciences, Operations Research & Management Engineering
Jurnal Ilmiah Computer Science (JICS) is a periodical scientific journal that contains research results in the field of informatics and computer science from all aspects of theory, practice and application. Papers can be in the form of technical papers or surveys of recent developments research (state-of-the-art). Topics cover the following areas (but are not limited to): Artificial Intelligence Decision Support Systems Intelligent Systems Business Intelligence Machine Learning Data mining Network and Computer Security Optimization Soft Computing Software Engineering Pattern Recognition Information System
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 6 Documents
 1 
Search results for , issue "Vol. 2 No. 2 (2024): Volume 2 Number 2 January 2024" : 6 Documents clear
Multiple Criteria Decision Making Penentuan Juara Lomba Roasting Kopi Menggunakan Multi-Attributive Border Approximation Area Comparison Sintaro, Sanriomi
Jurnal Ilmiah Computer Science Vol. 2 No. 2 (2024): Volume 2 Number 2 January 2024
Publisher : PT. SNN MEDIA TECH PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58602/jics.v2i2.16

Abstract

Multiple Criteria Decision Making (MCDM) is an approach used to evaluate and select alternatives based on several criteria or factors. The purpose of this study is to apply the Multi-Attributive Border Approximation Area Comparison (MABAC) method in determining the winner of the coffee roasting competition using criteria namely fragrance, flavor, aftertaste, acidity, body, sweetness, balance, and cup to profile. With the help of the MABAC method, it will make it easier for the competition committee to determine the winner of the coffee roasting competition. The ranking results using the final results of the MABAC method for rank 1 were obtained with a final score of 8,525 on behalf of participant William, rank 2 was obtained with a final score of 5,525 on behalf of participant Firman, and rank 3 was obtained with a final value of 2,525 on behalf of participant Aditya.
Penerapan Teknologi Quick Response Code dan First in First out Berbasis Web Pada Sistem Pemesanan Rosella, Rosella; Priandika, Adhie Thyo; Puspaningrum, Ajeng Savitri
Jurnal Ilmiah Computer Science Vol. 2 No. 2 (2024): Volume 2 Number 2 January 2024
Publisher : PT. SNN MEDIA TECH PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58602/jics.v2i2.17

Abstract

Problems that occur from the order side are errors in recording or taking customer orders. This can result in incorrect order delivery or customers who are dissatisfied with the service. If the booking system is inefficient, the booking may take too long to process. The implementation of ordering and payment systems using Quick Response Code (QR Code) technology and First in First Out (FIFO) methods has delivered significant results in improving operational efficiency and customer experience. The use of QR Codes allows customers to easily scan codes on menus or products they order using their mobile devices. This reduces the time it takes to order food or products and avoids human error in ordering. Based on the results of the recapitulation of the 6 test criteria that have been carried out, the results of the number of answers from respondents are obtained which have a value of 100% in accordance with testing system functionality using blackbox testing. The results of processing respondent response data based on ISO 25010 aspects of Performance Efficiency, Operability Aspects, and Functional Efficiency Aspects obtained a total score of 85.47%. Based on this, the ISO 25010 prototype is very good for ordering systems using Web-Based Quick Response Code (QR Code) and First in First out (FIFO) Technology.
Sistem Pendukung Keputusan Pemilihan Jasa Travel Menggunakan Metode Multi Attribute Utility Theory Pasha, Donaya
Jurnal Ilmiah Computer Science Vol. 2 No. 2 (2024): Volume 2 Number 2 January 2024
Publisher : PT. SNN MEDIA TECH PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58602/jics.v2i2.23

Abstract

Decision Support System (DSS) is an information system designed to assist decision makers in the process of data analysis and evaluation of alternatives to achieve certain goals. This study aims to determine travel services using the Multi Attribute Utility Theory method so that the results of recommendations can be input for users in selecting existing travel services. With this decision support system, it is expected that the process of selecting travel services will not only be more efficient but also provide a more satisfying travel experience for customers. The final ranking results were ranked 1st with a value of 0.678062574 obtained by Travel E, rank 2nd with a value of 0.459657989 obtained by Travel D, and rank 3rd with a value of 0.42685178 obtained by Travel C.
Analisis Sentimen Pengunaaan Aplikasi Kinemaster Menggunakan Metode Naive Bayes Kevin, Kevin; Enjeli, Margareta; Wijaya, Andri
Jurnal Ilmiah Computer Science Vol. 2 No. 2 (2024): Volume 2 Number 2 January 2024
Publisher : PT. SNN MEDIA TECH PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58602/jics.v2i2.24

Abstract

Penelitian ini bertujuan untuk menganalisis sentimen terkait penggunaan aplikasi Kinemaster dengan menggunakan metode Naive Bayes. Fokus utama adalah memahami sentimen pengguna yang terungkap dari ulasan dan umpan balik terkait Kinemaster, sebuah aplikasi penyunting video yang populer. Tujuan utama adalah menerapkan teknik machine learning, khususnya klasifikasi Naive Bayes, untuk mengidentifikasi dan mengelompokkan sentimen yang terungkap dalam ulasan pengguna. Metodologi penelitian ini melibatkan pengumpulan dataset yang signifikan berupa ulasan dan umpan balik yang dihasilkan oleh pengguna terkait aplikasi Kinemaster dari berbagai platform online. Untuk mempersiapkan dataset untuk analisis, teknik preprocessing diterapkan guna membersihkan dan mempersiapkan data. Selain itu, algoritma Naive Bayes digunakan untuk mengklasifikasikan sentimen yang terungkap dalam ulasan Google Play Store sebagai positif, negatif, atau netral. Ulasan di Google Play Store terus bertambah dari hari ke hari. Oleh karena itu, perlu dilakukan analisis terhadap ulasan-ulasan tersebut melalui analisis sentimen terhadap ulasan-ulasan KineMaster. Langkah pertama dalam analisis sentimen adalah observasi, preprocessing, yaitu proses tokenisasi, stopword removal, dan stemming. Data dibagi menjadi dua bagian, yaitu data latih dan data uji, dengan perbandingan 80:20. Algoritma yang digunakan adalah Naive Bayes classifier yang memiliki akurasi 85%, presisi 82%, recall 74% dan f1 score 78%.
Analisis Perbandingan SAW, WP dan TOPSIS Untuk Rekomendasi Restoran Sabandar, Vederico Pitsalitz; Wahyudi, Agung Deni
Jurnal Ilmiah Computer Science Vol. 2 No. 2 (2024): Volume 2 Number 2 January 2024
Publisher : PT. SNN MEDIA TECH PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58602/jics.v2i2.25

Abstract

Choosing the right restaurant for your food is a decision that can affect your overall culinary experience. In this study, the data used is data from TripAdvisor in the form of ratings and ratings of restaurants in Lampung. The data taken is the top 5 ranking data in tripadvisor which will be an analysis in providing restaurant recommendations based on the rating data on the website. The ranking results using the SAW method Rank 1 was obtained by Square Restaurant with a final score of 0.895. The ranking results using the WP Rank 1 method were obtained by Square Restaurant with a final score of 0.203427. The ranking results using the TOPSIS method Rank 1 were obtained by Pempek 123 with a final value of 0.580511982. The results of a comparative analysis of SAW, WP, or TOPSIS depend on the complexity of the decision, user preferences, and the specific characteristics of the decision-making problem at hand. SAW lends itself to simple decision, WP provides greater flexibility on weight handling, and TOPSIS can provide more in-depth analysis by considering both positive and negative ideal matrices.
Sistem Pendukung Keputusan Penentuan Kinerja Sales Terbaik Menggunakan Kombinasi Grey Relational Analysis dan Pembobotan Rank Sum Citra, Puspa; Sriyasa, I Wayan; Santoso, Heri Bambang
Jurnal Ilmiah Computer Science Vol. 2 No. 2 (2024): Volume 2 Number 2 January 2024
Publisher : PT. SNN MEDIA TECH PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58602/jics.v2i2.26

Abstract

The best sales performance is one of the key elements in the business world that not only reflects the ability of individuals or sales teams to achieve sales targets, but also becomes a key pillar in the growth and success of the company. The problem in choosing the best sales performance is that there is no decision support system model in choosing the best sales performance. The purpose of this study is to determine the best sales performance by applying the GRA method and rank sum weighting in the assessment of existing sales performance, so that the results of the sales performance appraisal will be a recommendation for companies in determining the best sales performance. The ranking results showed the highest value of 0.1309 obtained by sales Hadi for rank 1, the next highest value of 0.0941 obtained by sales Arini for rank 2, the next highest value of 0.0777 obtained by sales Cindy for rank 3.

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