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Implementasi Algoritma Knuth Morris Pratt Dalam Pencocokan String Pada Kamus Indonesia–Korea Rakhmat Kurniawan R; Aidil Halim Lubis; Siti Ayu Hadisa
Jurnal Sistem Komputer dan Informatika (JSON) Vol 5, No 1 (2023): September 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v5i1.6149

Currently, South Korean culture is very popular with many Indonesians, and the rapid development of Korean culture in Indonesia is currently very widespread and very popular. Many Indonesians even learn Korean to keep up with current trends, but due to the different structure of the language, learning Korean becomes more difficult for most people. The dictionary is an effective guide for translating foreign languages/terms. Conceptually, dictionaries are arranged alphabetically, along with explanations of definitions, uses or translations. This is also required for Indonesian to Hangul Korean translation. Many Indonesian-Korean dictionaries are currently published in printed form, but it is still difficult to use because users have to look up the meanings manually. We need practical and effective new media such as smartphone media. There are many algorithmic methods that can be used to create dictionary applications, one of which is using the Knuth Morris Pratt (KMP) algorithm. With this algorithm, every text to be translated is checked for word search and then a match is found with the appropriate word from the desired word. In this study, the final results of the study found differences in the use of the word hangul in formal and informal forms. In this study, the authors tested the application of the algorithm on an Android-based Indonesian-Korean dictionary application.

Protoype Sistem Penyiram Lahan Perkebunan Kangkung Otomatis Berbasis Internet of Things dengan Logika Fuzzy Sugeno Ismail Mahfuddin; Rakmat Kurniawan R; Aidil Halim Lubis
Journal of Computer System and Informatics (JoSYC) Vol 4 No 2 (2023): Februari 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v4i2.2668

Watering is one of the jobs that are routinely carried out in plant maintenance which usually causes various problems. One of them is the absence of the same measure of water quantity when watering will result in the plants being treated can experience excess or lack of water, causing the plants to dry out or rot and die. So we need a tool that can help in terms of watering plants. The internet of things-based automatic watering machine for water spinach plantations is expected to be a system to assist farmers in watering especially kale that can detect moisture in the soil and temperature around the land and has scheduling options, automatic fuzzy and manual that can be controlled via the android application. which has been designed and can work based on the selected option. This tool is made using the Sugeno fuzzy logic method because this method is suitable for use in making decisions to find the values of humidity and temperature that fluctuate and are less certain. Based on the results of the study, the average percentage difference in the humidity sensor is 0.016 % and the accuracy (accuracy) on the humidity sensor circuit is 99.98%, while the percentage difference in the temperature sensor is 0.02% and the accuracy (accuracy) on the LM35 temperature sensor circuit is 99.99%.

IMPLEMENTASI METODE FUZZY LOGIC SUGENO DAN BACKWARD CHAINING DALAM SISTEM PAKAR MENDIAGNOSIS PENYAKIT PERIODONTITIS TERHADAP PEROKOK AKTIF Ilka Zufria; Aidil Halim Lubis; Sarmila Sarmila
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol 7, No 2 (2024): May 2024
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v7i2.1834

Abstract: Dental and oral health is sometimes a priority for some people, even though dental and oral diseases have a serious impact on general health, because the teeth and mouth are places where germs and bacteria enter so that they are likely to interfere with the health of other organs of the body. Periodontitis is a gum disease caused by bacteria that damages the supporting tissues of the teeth and causes tooth loss. This disease can be avoided if you come to the dentist early. However, the problem that often occurs is that many people only start treatment after periodontitis reaches a chronic stage, so an approach is needed that can assist people in diagnosing periodontitis early, quickly and accurately. An expert system is a system that seeks to implement human knowledge on computers so that computers can solve problems as experts do. Fuzzy Logic Sugeno and Backward Chaining methods are used for calculations because these methods can solve the hypothesis of a problem by measuring one's beliefs. The results of this study are an expert system that can have an output in the form of the name of the disease periodontitis and the degree of certainty of the user's disease. Keywords: expert system, fuzzy logic sugeno, backward chaining, periodontitis Abstrak: Kesehatan gigi dan mulut terkadang memang merupakan prioritas ke sekian bagi beberapa orang, padahal sebenarnya penyakit gigi dan mulut berdampak serius bagi kesehatan secara umum, sebab gigi dan mulut merupakan tempat masuknya kuman dan bakteri sehingga kemungkinan besar dapat mengganggu kesehatan organ tubuh lainnya. Penyakit Periodontitis adalah penyakit gusi yang disebabkan oleh bakteri yang merusak jaringan penunjang gigi dan meyebabkan kehilangan gigi. Penyakit tersebut bisa dihindari apabila datang ke dokter gigi lebih awal. Akan tetapi permasalahan yang sering terjadi adalah banyak masyarakat yang baru mulai berobat setelah penyakit periodontitis mencapai tahap kronis, sehingga diperlukan sebuah pendekatan yang dapat membantu masyarakat dalam mendiagnosis penyakit periodontitis secara dini, cepat dan akurat. Sistem pakar merupakan sistem yang berusaha mengimplementasikan pengetahuan manusia pada komputer agar komputer bisa menyelesaikan masalah sebagaimana yang dilakukan oleh para ahli. Metode Fuzzy Logic Sugeno dan Backward Chaining digunakan untuk perhitungan dikarenakan metode tersebut dapat menyelesaikan ketidakpastian terhadap suatu masalah dengan mengukur keyakinan seseorang. Hasil dari penelitian ini adalah sebuah sistem pakar yang dapat memiliki keluaran berupa nama penyakit periodontitis dan tingkat kepastian terhadap penyakit yang diderita pengguna. Kata kunci: sistem pakar, fuzzy logic sugeno, backward chaining, periodontitis

Implementasi Algoritma Knuth Morris Pratt Dalam Pencocokan String Pada Kamus Indonesiaâ€“Korea Rakhmat Kurniawan R; Aidil Halim Lubis; Siti Ayu Hadisa
Jurnal Sistem Komputer dan Informatika (JSON) Vol. 5 No. 1 (2023): September 2023
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v5i1.6149

Currently, South Korean culture is very popular with many Indonesians, and the rapid development of Korean culture in Indonesia is currently very widespread and very popular. Many Indonesians even learn Korean to keep up with current trends, but due to the different structure of the language, learning Korean becomes more difficult for most people. The dictionary is an effective guide for translating foreign languages/terms. Conceptually, dictionaries are arranged alphabetically, along with explanations of definitions, uses or translations. This is also required for Indonesian to Hangul Korean translation. Many Indonesian-Korean dictionaries are currently published in printed form, but it is still difficult to use because users have to look up the meanings manually. We need practical and effective new media such as smartphone media. There are many algorithmic methods that can be used to create dictionary applications, one of which is using the Knuth Morris Pratt (KMP) algorithm. With this algorithm, every text to be translated is checked for word search and then a match is found with the appropriate word from the desired word. In this study, the final results of the study found differences in the use of the word hangul in formal and informal forms. In this study, the authors tested the application of the algorithm on an Android-based Indonesian-Korean dictionary application.

Klasifikasi Tingkat Kepuasan Pengguna Produk Body Care Menggunakan Algoritma Decision Tree Nur Jannah Hasibuan; Aidil Halim Lubis
Bulletin of Computer Science Research Vol. 6 No. 4 (2026): June 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v6i4.1110

The increasing competition in the body care industry encourages companies to understand customer satisfaction as a basis for improving product quality and service performance. However, analyzing user satisfaction often produces complex data that are difficult to process manually. This study aims to apply the Decision Tree algorithm to classify the satisfaction levels of body care product users based on user characteristics and product evaluations. The research data were collected through questionnaires distributed to 250 respondents, including attributes such as gender, age, frequency of use, product quality, price, service quality, and satisfaction level as the target variable. The research stages consisted of data preprocessing, attribute selection, data transformation, splitting data into training and testing datasets, and building a classification model using the Decision Tree algorithm. Model evaluation was carried out using a confusion matrix with accuracy, precision, recall, and F1-score metrics. The results showed that the model was able to classify user satisfaction into four categories: very satisfied, satisfied, fairly satisfied, and dissatisfied, with an accuracy of 58%, precision of 57%, recall of 57%, and F1-score of 57%. This study contributes to the implementation of data mining for customer satisfaction analysis in the body care industry and helps companies identify dominant factors influencing user satisfaction, particularly product quality and service quality. In addition, the findings are expected to serve as a reference for developing customer satisfaction analysis systems based on data mining in the beauty and body care industry.

Klasifikasi Persepsi Publik Terhadap Perang Dagang Amerika Serikat Menggunakan Algoritma Naïve Bayes Classifier Bunga Nurul Manisa; Aidil Halim Lubis
Bulletin of Computer Science Research Vol. 6 No. 4 (2026): June 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v6i4.1112

The import tariff policy implemented by the President of the United States on April 2, 2025 triggered tensions in global trade and provoked various public reactions. Differences in public perceptions of the policy generated diverse opinions, including support, criticism, and neutral responses, making sentiment analysis necessary to understand public opinion trends more systematically. This study aims to classify public perceptions of the U.S. trade war through sentiment analysis of Twitter data using the Naïve Bayes Classifier (NBC) algorithm. The dataset consists of 2,000 tweets collected using the keywords “trade war” and “import tariff increase” during April 3–30, 2025. Six preprocessing stages were applied: cleaning, case folding, tokenizing, slangword normalization, stopword removal, and stemming to improve data quality and consistency. Automatic labeling was conducted using a lexicon-based method with the InSet dictionary, yielding sentiment distributions of 83.5% negative, 12.8% positive, and 3.8% neutral. Feature representation was performed using TF-IDF, followed by an 80:20 train-test split. To address class imbalance, the Synthetic Minority Over-sampling Technique (SMOTE) was applied. Experimental results show that the NBC model without SMOTE achieved an accuracy of 83.5% but exhibited bias toward the majority class. After applying SMOTE, the dataset became balanced with 1,335 samples per class. Although overall accuracy decreased to 76%, the Macro F1-Score improved from 0.30 to 0.45, indicating improved model performance in handling multi-class classification more fairly. Additionally, the model achieved a recall of 43% for the positive class and 13% for the neutral class, providing a more representative evaluation of public sentiment toward the U.S. trade war issue.

Penerapan Naive Bayes untuk Klasifikasi Opini Fans Manchester United pada Media Sosial Muhammad Luthfi Lubis; Aidil Halim Lubis
TIN: Terapan Informatika Nusantara Vol 7 No 2 (2026): July 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v7i2.10724

This study examines the application of the Naïve Bayes algorithm to classify the opinions of Manchester United fans in Indonesian-language comments on YouTube. The diverse linguistic forms found in the comments such as slang, abbreviations, jokes, and sarcasm make manual analysis inefficient and potentially subjective. Data was collected from eight YouTube videos using the YouTube Data API v3 and stored in a MySQL database. Of the 4,886 comments obtained, 1,962 were identified as being in Indonesian. A total of 1,000 comments were used as ground truth, consisting of 400 positive, 300 negative, and 300 neutral comments. The data was divided into 80% training data and 20% test data using a stratified split. The processing stages included text preprocessing, TF-IDF weighting, Naïve Bayes classification, and evaluation using a confusion matrix, accuracy, precision, recall, and F1-score. The test results yielded an accuracy of 92.50%, a macro precision of 92.81%, a macro recall of 92.36%, and a macro F1-score of 92.57%. Of the 1,944 comments successfully classified, positive sentiment dominated at 47.58%, followed by negative at 28.34% and neutral at 24.07%. The web-based system, built using Laravel, PHP, and MySQL, is capable of integrating the processes of data extraction, labeling, classification, evaluation, and result visualization.

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