Julia: Jurnal Ilmu Komputer An Nuur

IMPLEMENTASI ALGORITMA FP-GROWTH UNTUK REKOMENDASI PRODUK DI TOKO LM MART

2024-01-04T19:10:35+07:00

LM Mart is one of the BumDesa shop businesses located on Jl Raya Purwodadi-Semarang Km.13, Godong sub-district, Grobogan Regency. The products sold include various basic food items (nine basic commodities) for general community needs. Data is stored in the LM Mart store database. One of them is increasing transaction data. With the increasing volume of data at LM Mart, the analyst's function of analyzing data manually must be replaced by computer-based applications. The problem with the LM Mart Store is that traders lack the ability to observe consumers' desires and needs, which of course will have an impact on increasing product sales. Besides that, sales transaction data, if processed, can produce useful information which can become a sales strategy to improve marketing. The FP-Growth algorithm will be used for the association approach in this research. The FP-Growth algorithm is a development of the apriori algorithm, it corrects the shortcomings of the apriori algorithm. To obtain a frequent item set, the a priori algorithm must generate candidates. From the research results, calculations using RapidMiner with a Support value of 30% and a Confidance value of 80% with transaction data of 800 records produced 36 rules.

ANALISIS SENTIMEN PADA TWITTER TENTANG ISU PERILAKU ANTISOSIAL DENGAN ALGORITMA NAÏVE BAYES

2024-01-06T10:39:02+07:00

In 2023, around 78.19% of the 275.77% or 215.63 million Indonesian population will be connected to the internet, with positive impacts such as fast communication, entertainment and new knowledge. The internet makes non-cash transactions easier and has negative impacts such as addiction and antisocial behavior such as indifference to people around you. Teenagers often access social media, especially Twitter, to express opinions and vent both positive and negative. Sentiment analysis is used to determine opinions about antisocial behavior on Twitter by using text mining techniques to analyze teenagers' opinions. Naive Bayes and SVM algorithms are used in sentiment analysis on the Twitter dataset to analyze antisocial behavior. Actions to evaluate the Naive Bayes algorithm in assessing antisocial behavior sentiments had the best accuracy results of 59.71% with k=7 without n-grams. The Naïve Bayes algorithm with k=5 and n-gram n=2 has the best precision of 33.76% and the best recall of 33.45%. Future research can try to use other classification algorithms such as KNN, SVM, etc. To find the best accuracy of the antisocial behavior dataset.

Keywords: Internet; Twitter; antisocial behaviour; Sentiment analysis;

PREDIKSI TINGKAT KELULUSAN MAHASISWA S1 UNIVERSITAS AN NUUR DENGAN METODE DECISION TREE C4.5

2024-04-14T22:52:41+07:00

One of the private universities in Purwodadi is An Nuur Purwodadi University. Many students have graduated from An Nuur Purwodadi University, but there are some students who did not graduate on time. This poses a problem and raises a significant question as to why these students did not graduate on time. A decision tree is a suitable data mining method for this research because it has the advantage of identifying and summarizing patterns in the data. The Decision Tree algorithm has an accuracy of 96.25%. The recall values for each class are 97.37% for the "Late" class and 95.00% for the "On-Time" class. Meanwhile, the precision values for each class are 94.87% for the "Late" class and 97.44% for the "On-Time" class

ANALYSIS OF SENTIMENT ON TEACHER MARKETPLACE ISSUES USING THE LEXICON AND K-NEAREST NEIGHBOR ALGORITHMS

2024-05-15T14:34:05+07:00

The advancement of social media makes it easier for users to express opinions. Twitter has become one of the media that is loved by internet users, users can freely express their thoughts or opinions, apart from that they can also express everything that is being experienced. The busy issue of the Teacher Marketplace initiated by the Minister of Education, Nadiem Makarim, has invited many comments from internet users. Twitter users' tendencies in posting content can be determined by analyzing sentiment. In this research, the Lexicon and K-Nearest Neighbor (KNN) methods are proposed to analyze sentiment towards the education minister's discourse on Twitter social media on the topic of Teacher Marketplace Issue Sentiment by classifying it into positive, neutral and negative. The results of this research show that the accuracy value obtained was 91.70%, precision 90.51%, recall 71.95%. By carrying out this sentiment analysis, it is hoped that the problems contained in the Marketplace Guru topic controversy can be identified, used as input and consideration for further research.

IMPLEMENTASI ALGORITMA APRIORI UNTUK MENCARI POLA TRANSAKSI PENJUALAN PADA TOKO PERTANIAN TOKO BIDSALTANI

2024-05-22T10:27:47+07:00

Progress in the industrial sector is currently growing rapidly, especially in medium and upper-class businesses, especially in agricultural shop businesses. Agricultural shops are one of the medium-sized businesses where competition is quite tight, this can be seen from the high consumer demand for fertilizer and agricultural equipment.With the high demand of consumers for agricultural needs as well as intense competition, agricultural shop companies must further improve their business performance in order to be able to face the problems that occur.Bidsal Tani is one of the many agricultural shops in Purwodadi District that sells agricultural necessities, such as chemical fertilizer, compost, plant seeds and all other agricultural necessities, it can be seen that to make a profit as expected.The a priori algorithm is a market basket analysis algorithm used to produce association rules. Association rules can be used to find relationships or cause and effect. The results of the research are that the products frequently purchased by consumers are PHONSKA, NPA, ZA, FASTAC, KOGE, UREA, GANDASIL, FLORAN, SP36, TSP, WUXAL, BAYFOLAN, BLOPATEK, KCL, HYDRASIL AND DECIS products.