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SKANIKA: Sistem Komputer dan Teknik Informatika
Published by Universitas Budi Luhur Jakarta
ISSN : -     EISSN : 27214788     DOI : 10.36080
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Engineering
SKANIKA: Sistem Komputer dan Teknik Informatika adalah media publikasi online hasil penelitian yang diterbitkan oleh Program Studi Sistem komputer dan Teknik Informatika, Fakultas Teknologi Informasi, Universitas Budi Luhur. Scope atau Topik Jurnal: Kriptografi, Steganografi, Sistem Pakar / Artificial Intelligence , Sistem Penunjang Keputusan, Bioinformatika, Kecerdasan Komputasional, Semantics Web dan Ontologies, Data Mining,Text Mining,Natural Language Processing, Pengelolaan Citra Digital, Otomasi Berbasis Sensor, Wireless Sensor Network, Network Management dan Maintenance, Sistem Operasi, Sosial Network Analysis, Security, Augmented Reality, Game Development, Virtual Reality, Webservice / API, Internet of Things (IoT)
Arjuna Subject : Ilmu Komputer (semua kategori) - Aplikasi Ilmu Komputer
Articles 340 Documents
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TEKNOLOGI PROCESS AWARE INFORMATION SYSTEM (PAIS) MANAJEMEN EKSTRAKURIKULER UNTUK OTOMASI PEMANTAUAN KEGIATAN Munna, Daurin Nabilatul; Prasetyo, Gigih Agung; Maghfira, Aulia Ilmi; Yaqin, Muhammad Ainul
SKANIKA: Sistem Komputer dan Teknik Informatika Vol 7 No 1 (2024): Jurnal SKANIKA Januari 2024
Publisher : Universitas Budi Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36080/skanika.v7i1.3116

Abstract

Education in Indonesia, including in Malang City, has seen rapid development in recent decades. Extracurricular activities, as an integral part of education, offer students opportunities to develop skills, talents, and interests beyond the main curriculum. However, the current management of extracurricular activities is still manual and inefficient. To address this issue, we propose the implementation of a Process-Aware Information System (PAIS) to automate the monitoring of extracurricular activities. This system involves input such as school data, student data, and extracurricular data. The outputs include reports on extracurricular activities, student talents and interests, and school achievements. The process includes student registration for extracurricular activities, validation by administrators, activity scheduling, attendance monitoring, and reporting. This system is expected to efficiently and accurately monitor these activities. Through the PAIS workflow, we ensure more efficient and real-time management and monitoring of extracurricular activities. This system assists in improving extracurricular management, data accuracy, better decision-making, and time savings.
KLASIFIKASI TEKS ULASAN APLIKASI NETFLIX PADA GOOGLE PLAY STORE MENGGUNAKAN ALGORITMA NAÏVE BAYES DAN SVM Khoirunnisaa, Nabiilah; Nabila Nastiti Kesuma, Kaylista; Setiawan, Septhiyanthi; Yunizar Pratama Yusuf, Ajif
SKANIKA: Sistem Komputer dan Teknik Informatika Vol 7 No 1 (2024): Jurnal SKANIKA Januari 2024
Publisher : Universitas Budi Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36080/skanika.v7i1.3138

Abstract

Netflix is a subscription streaming platform that presents various shows, such as TV series, documentaries, and films, connected to a device connected to the internet. One of the most popular sites for streaming videos is Netflix, throughout the world and is now starting to apply data analysis and machine learning technology to improve its user services. Through the Google Play Store, users can submit various reviews about the Netflix application. It is possible to extract significant hidden information from this vast quantity of review data that is helpful for assessing an application's quality. Therefore this research aims to classify text reviews of the Netflix application by comparing the two algorithms applied, that is, Support Vector Machine (SVM) and Naive Bayes. With the aim of finding out which algorithm performs better in terms of accuracy. The dataset was obtained through the Google Play Store and applied to the scraping method, totaling 1000 reviews, and processed utilizing the Python programming language. Then the Netflix application review data that was obtained was divided into 70% train data and 30% test data. 82% of the accuracy results were obtained using the Naive Bayes approach., while the support vector machine (SVM) yielded 85% accuracy. It therefore demonstrates that support vector machines (SVM) are no more successful than the outcomes of applying the Naive Bayes method. (SVM).
RANCANGAN CHATBOT REKOMENDASI COFFEE SHOP JABODETABEK DENGAN MENGGUNAKAN DIALOGFLOW NATURAL LANGUAGE PROCESSING Syahrani, Gina; Sevira, Silviana; Yunizar Pratama Yusuf, Ajif
SKANIKA: Sistem Komputer dan Teknik Informatika Vol 7 No 1 (2024): Jurnal SKANIKA Januari 2024
Publisher : Universitas Budi Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36080/skanika.v7i1.3139

Abstract

Public interest in coffee culture is increasing, especially in the JABODETABEK area. Some ways to get information about finding recommendations for coffee shops that are tiring through social media platforms, asking peers, advertisements and others still feel less effective and efficient. Utilization of chatbot technology and Natural Language Processing as an effective solution in providing coffee shop recommendations to users. This research aims to design and implement a chatbot that has the ability to deliver coffee shop recommendations based on user preferences. This chatbot is applied with Dialogflow which is able to connect to the Telegram platform. Dialogflow is used to process user input in the form of natural language and provide additional information such as location, opening hours, prices, menus, and social media to communicate to the coffee shop. Chatbot is a practical way for Telegram users to communicate information quickly. The expected result of this coffee shop recommendation chatbot system using Dialogflow NLP is to be able to provide useful and relevant recommendations to users, with the potential to promote coffee culture in the Jabodetabek area.
CHATBOT BERBASIS NLP UNTUK REKOMENDASI PRODUK SKINCARE LOKAL PADA TELEGRAM Agustin, Syafira Cessa; Syafina, Prilia Hashifah; Rachmatin, Nida; Pratama Yusuf, Ajif Yunizar
SKANIKA: Sistem Komputer dan Teknik Informatika Vol 7 No 1 (2024): Jurnal SKANIKA Januari 2024
Publisher : Universitas Budi Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36080/skanika.v7i1.3141

Abstract

This research applies a Natural Language Processing (NLP)-based chatbot to provide recommendations for local skincare products. Telegram, as a widely used communication platform, is an ideal medium to present this innovative solution to consumers looking for appropriate skincare products. The chatbot is designed to understand the user's needs regarding skin type, and skin concerns. By utilizing artificial intelligence, the chatbot can provide personalized recommendations of suitable local skincare products, improving consumers' access to product information and facilitating the process of selecting the right product. This research is expected to make chatbot an effective tool in finding skincare products that suit the skin, as well as increasing consumer participation in supporting the local skincare industry through instant messaging platform, telegram.
PENGEMBANGAN GAME EDUKASI PENDIDIKAN AGAMA BUDDHA BERBASIS PROGRESSIVE WEB APPS DENGAN MODEL GAMIFIKASI DAN GDLC Wahyu, Sawali; Gotama, Jeskel Fornardi
SKANIKA: Sistem Komputer dan Teknik Informatika Vol 7 No 1 (2024): Jurnal SKANIKA Januari 2024
Publisher : Universitas Budi Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36080/skanika.v7i1.3145

Abstract

The use of technology to support people's daily activities has become something normal and usual, positive things that can be accepted and utilized by the community, but negative things must be overcome by applying basic education from an early age, namely to children. Religion is part of the spiritual education implemented in schools, in this case Buddhist Religious Education. The problems and application of these solutions can be presented in the form of non-formal education, namely through Buddhist Sunday School with the implementation of interactive and interesting learning that applies information technology in the form of web-based educational games. The research methodology used is the Game Development Lifecycle (GDLC) which contains a guide to the stages for building a game. The gamification model is used as a learning method by utilizing elements in the game to motivate children to achieve a target achievement. To maximize the performance of the game, Progressive Web Apps is applied to make the application performance better. This research produces a web-based game application that will help Sunday school children access Buddhist Education learning materials by motivating learners. The game was tested using the System Usability Scale method which resulted in a test score of 86 including an A or Excellent rating. As well as the results of UAT (User Acceptance Testing) testing at the beta stage with the results shown with the lowest score being 3 (Agree) and the highest score being 4 (Strongly Agree), thus there is no difficulty in using the educational game because it has clear features and is easy to use.
MODEL PENILAIAN ESAI OTOMATIS MENGGUNAKAN ALGORITMA RABIN-KARP, DICE COEFFICIENT SIMILARITY DAN SYNONYM RECOGNITION STUDI KASUS PADA UNIVERSITAS BUDI LUHUR Saputro, Heru; Budiyanto, Utomo
SKANIKA: Sistem Komputer dan Teknik Informatika Vol 7 No 1 (2024): Jurnal SKANIKA Januari 2024
Publisher : Universitas Budi Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36080/skanika.v7i1.3146

Abstract

The exam is one way to find out the results of students' material understanding abilities from the teaching and learning process taught by educators. In general, the exam system itself has several types of questions, namely multiple choice questions and essays. Implementation of automatic exam assessment is generally only a multiple-choice exam on the e-learning page. One of them is that Budi Luhur University in conducting student exam assessments in the form of multiple choice questions already has an automatic scoring system on the e-learning page. However, there is no automatic system for assessing essays. So for the assessment of essay questions, Budi Luhur University lecturers are still correcting them manually. From the manual essay scoring system it takes quite a long time and is less effective. Based on this background, it is necessary to have a website-based automatic essay assessment system that can assist Budi Luhur University lecturers in assessing student learning outcomes. The method proposed in this study is to use the Rabin-Karp Algorithm, Dice Coefficient Similarity and Synonym Recognition. This study aims to create an automatic essay scoring system that can assist Budi Luhur University lecturers in correcting student learning outcomes. This system can produce the highest accuracy percentage of student grade correction results and is close to the lecturer's manual assessment with an accuracy value of 93.75%.
RANCANG BANGUN PEMILAH SAMPAH ORGANIK DAN NON ORGANIK BERBASIS MOBILE DI MEDANG LESTARI Maulana, Rizky Akbar; Windarto, Windarto
SKANIKA: Sistem Komputer dan Teknik Informatika Vol 7 No 1 (2024): Jurnal SKANIKA Januari 2024
Publisher : Universitas Budi Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36080/skanika.v7i1.3147

Abstract

The trash bins in RT 01/08 currently have only one container, causing organic and non-organic waste to mix. This situation has led to environmental issues in RT 01/08, making the surroundings unpleasant and emitting a strong odour due to the accumulation of mixed waste. The negative impacts of this mixed waste, we can be reduced by separating the trash according to its respective categories when disposing of it. With the advancements in the era of globalization and information technology, especially in the field of microcontrollers and sensors, there have been significant improvements in human life. The emergence of various new technologies can aid human activities and also have a positive impact on environmental cleanliness. The purpose of this research is to develop an automated trash bin that can sort organic and non-organic waste based on mobile technology. By doing so, it can reduce the mixing of different types of waste in the environment, and users can control the opening and closing of the trash bin. The prototyping method tested has proven to work well as desired. This prototyping method involves designing a system and device that can automatically sort different types of waste, producing separate outputs for organic and non-organic waste. Ultrasonic sensors are used to detect the proximity of users, while capacitive and infrared proximity sensors are used to differentiate between organic and non-organic waste. The testing results of the automated trash bin showed that the ultrasonic sensor effectively detects the proximity of users, enabling the trash bin lid to open and close automatically. In distinguishing organic from non-organic waste, the capacitive proximity sensor can detect organic waste such as vegetable scraps, fruit peels, and leaves. Meanwhile, the infrared proximity sensor can detect non- organic waste such as plastic bottles and foot wrappers. However, both proximity sensors experienced a delay in detecting waste, taking approximately 1-3 seconds. Furthermore, the testing results also had a positive impact on the community, raising awareness among people about the importance of disposing of waste according to its respective categories.
CHATBOT DENGAN ALGORITMA MULTILAYER PERCEPTRON SEBAGAI LAYANAN INFORMASI SEKRETARIAT FAKULTAS TEKNOLOGI INFORMASI UNIVERSITAS BUDI LUHUR Maulidia, Mia; Syafrullah, Mohammad
SKANIKA: Sistem Komputer dan Teknik Informatika Vol 7 No 1 (2024): Jurnal SKANIKA Januari 2024
Publisher : Universitas Budi Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36080/skanika.v7i1.3148

Abstract

Information service centers are very important today, with the existence of information service centers many people are helped in conveying and receiving the information needed, including in the world of higher education, information about academics is needed in teaching and learning activities in lectures. Although to get general information related to current teaching and learning activities at the Faculty of Information Technology at Budi Luhur University can be accessed through the website, supervisors and social media. But the problem now is to get information from supervisors who sometimes take too long to respond to students or even miss not responding. One way to overcome this problem is to create a chatbot system as an information service at the Faculty of Information Technology at Budi Luhur University using a natural language Natural Language Processing (NLP) approach with the Neural Network method and Multilayer Perceptron algorithm and extraction features using the binary Bag of words method by matching and giving a value of 1 to each question that is used as a token at the appropriate preprocessing stage on The train data and assigns a value of 0 to each toen that does not match the token on the train data. As well as using datasets saved in JSON format. Based on the model that has been trained to obtain accuracy and loss results with an accuracy value = 1,000 and a loss value = 0.0117, it can be concluded that the trained model is a good model.
PENERAPAN DATA MINING UNTUK KLASTERISASI TINGKAT KEMISKINAN BERDASARKAN DATA TERPADU KESEJAHTERAAN SOSIAL (DTKS) Zuhendra, Muhammad Ihza; Hidayat, Rahmad; Hendrawaty, Hendrawaty
SKANIKA: Sistem Komputer dan Teknik Informatika Vol 7 No 1 (2024): Jurnal SKANIKA Januari 2024
Publisher : Universitas Budi Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36080/skanika.v7i1.3149

Abstract

The level of poverty serves as a significant indicator influencing a nation's well-being. Poverty can arise from various factors, such as limited job opportunities resulting in insufficient income to cover living expenses, substantial family responsibilities, and more. In this context, the government plays a role by providing assistance, such as social aid programs. One step in providing this assistance involves individuals being registered as participants in the Unified Social Welfare Data (Data Terpadu Kesejahteraan Sosial or DTKS). Becoming a DTKS participant requires meeting the criteria categorizing someone as extremely poor, which is generally determined by the Minister of Social Affairs' Decision No. 146/HUK/2013 on the criteria for registered individuals in extreme poverty.This consideration can serve as a guideline in determining the socioeconomic status of community groups within a region. However, on a larger scale, classifying communities based on poverty levels can be a complex and time-consuming task. K-Means clustering is one of several non-hierarchical data clustering methods that work by partitioning existing data into one or more clusters or groups. This clustering can be applied to categorize a large dataset to enhance the accuracy of the information obtained, such as assessing the poverty level in a specific area. The objective of this research is to develop an application that facilitates the categorization of communities in analyzing the progression of poverty rates in a region based on predefined criteria. This aids the government and other stakeholders in understanding poverty distribution better, identifying high-risk groups, and designing targeted and effective social aid programs or policies. The outcomes of this research showcase visualizations depicting the percentage composition of each group within a dataset. The presented data visualizations can also be customized based on categories such as the number of clusters, regions, years, and more.
IMPLEMENTASI RAPIDMINER UNTUK MENENTUKAN SISWA UNGGULAN MENGGUNAKAN METODE K-MEANS Wahyudi, Nabella Rosyefa; Rahmawati, Yunianita; Supriyanto, Supriyanto
SKANIKA: Sistem Komputer dan Teknik Informatika Vol 7 No 2 (2024): Jurnal SKANIKA Juli 2024
Publisher : Universitas Budi Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36080/skanika.v7i2.3173

Abstract

This research aims to apply the K-Means Method and RapidMiner in identifying superior students based on the scores of Mathematics, Science, and Social Studies subjects at SMP Negeri 11 Sampit. With a dataset consisting of 24 attributes and 31 student data, the K-Means Method successfully clusters students based on the similarity of the grades the students obtained. The model evaluation results show that the best cluster value is 2 clusters. The use of the K-Means Method in this study is a solution to the difficulty in determining superior students at SMP Negeri 11 Sampit because students' abilities tend to be balanced in each semester. This research provides insight that the K-Means Method is effective in determining superior students and can be a useful tool in educational evaluation.

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