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Achmad Solichin
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Bit (Fakultas Teknologi Informasi Universitas Budi Luhur)
Published by Universitas Budi Luhur Jakarta
ISSN : 16939166     EISSN : 2685127X     DOI : http://dx.doi.org/10.36080/bit.v18i2.1618
Core Subject : Science, Engineering,
Computer Science & IT Electrical & Electronics Engineering
JURNAL BIT (Budi Luhur Information Technology) merupakan Jurnal yang diterbitkan oleh Fakultas Teknologi Informasi, Universitas Budi Luhur dengan jadwal publikasi dua kali dalam satu tahun (April dan September). Jurnal BIT bertujuan sebagai media pertukaran informasi, pengetahuan mengenai pengembangan dan ilmu komputer serta keterkaitan dengan disiplin ilmu lainnya. Fokus dan Ruang Lingkup pada Jurnal BIT: System Engineering, Expert System, Decision Support System, Data Mining, Artificial Intelligence (AI), Computer Network, Computer Engineering, Image Processing, Genetic Algorithm, Information System, Business Intelligence dan Knowledge Management, Database System, Big Data, Enterprise Computing, Robotic, Internet of Things, Data Science, dan Topik studi lain yang relevan
Arjuna Subject : Ilmu Komputer (semua kategori) - Sistem Informasi
Articles 13 Documents
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Search results for , issue "Vol 19, No 2 (2022): SEPTEMBER 2022" : 13 Documents clear
Cover Belakang Vol. 19 No. 2 Atik Ariesta
Bit (Fakultas Teknologi Informasi Universitas Budi Luhur) Vol 19, No 2 (2022): SEPTEMBER 2022
Publisher : Universitas Budi Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36080/bit.v19i2.2144

Abstract

Cover Belakang Vol. 19 No. 2
Penerapan Metode Algoritma Fisher Yates Shufle Pada Game Edukasi Ragam Budaya Berbasis Android Trisna Aditiya; Noni Juliasari; Pipin Farida Ariyani
Bit (Fakultas Teknologi Informasi Universitas Budi Luhur) Vol 19, No 2 (2022): SEPTEMBER 2022
Publisher : Universitas Budi Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36080/bit.v19i2.2135

Abstract

In this day and age, gaming has become a hobby for everyone. Starting from children, teenagers and adults. The use of educational games as learning media for the introduction of regional culture is considered suitable, because it can take advantage of developing technology. The way for children to get to know about the diversity of Indonesian culture is to play games with Indonesian cultural backgrounds. Therefore it is necessary to make educational game applications. Educational games about local wisdom were chosen so that children can still play while learning or getting to know food, house, and regional dances in Indonesia while still being able to play. This is considered effective in increasing children's knowledge about Indonesian culture without being forced to study. The game that will be made is not only an educational genre but also a quiz genre where the order of questions and the order of answers that appear will be randomized using the Fisher Yates Algorithm method. This Indonesian Cultural Variety educational game was developed using the Multimedia Development Life Cycle (MDLC) method which consists of six stages, namely concept, design, collecting material, assembly, testing and distribution. This Indonesian Cultural Variety educational game can be played on Android with a minimum of Android 6.0 software or commonly called marshmallow. Based on the results of tests involving 10 respondents, a good response was obtained because it got a percentage of 94.6%.
Peningkatan Akurasi Algoritma C4.5 Menggunakan Particle Swarm Optimization Untuk Mendeteksi Penyakit Diabetes I Gusti Bagus Ari Sidi Mantra Arsana; Ridowati Gunawan
Bit (Fakultas Teknologi Informasi Universitas Budi Luhur) Vol 19, No 2 (2022): SEPTEMBER 2022
Publisher : Universitas Budi Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36080/bit.v19i2.2044

Abstract

Diabetes is a disease that occurs due to an increase in blood sugar levels. Increased sugar levels can trigger death because they can cause damage to blood vessels, nerves, and other internal structures. To avoid bad consequences, it is important to predict whether a person has diabetes or not based on the information that each patient has. The method that can be used to predict whether someone has diabetes or not is a classification method. The C4.5 algorithm is one of the classification algorithms that can be used to predict diabetics. Although the C4.5 algorithm can be used to predict, getting a high accuracy value is also an important measurement. One thing that can be done to increase the accuracy value is to select the attribute that most influences a person to have diabetes or not. Feature selection greatly affects the accuracy of the C4.5 algorithm, particle swarm optimization is used as a feature selection method in this study. The purpose of this study is to increase the value of accuracy to predict whether someone has diabetes or not through feature selection using particle swarm optimization. The dataset used is the Pima Indian Diabetes Databases (PIDD) from the University of California Irvine (UCI) Machine Learning Repository. The results of the study show that feature selection using particle swarm optimization before using the C4.5 algorithm can increase accuracy by 6% from the previous accuracy value of 75%. The selected features are 4 attributes out of 9 attributes. The four attributes are Glucose, SkinThickness, BMI, and DiabetesPedigreeFunction. The results of feature selection using particle swarm optimization can increase the accuracy of predictions of whether someone suffering from diabetes or not.
Penerapan Algoritme Finite State Machine Pada Game "Si Jampang" Berbasis Android Ar-Rijalul Haq; Mardi Hardjianto
Bit (Fakultas Teknologi Informasi Universitas Budi Luhur) Vol 19, No 2 (2022): SEPTEMBER 2022
Publisher : Universitas Budi Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36080/bit.v19i2.2136

Abstract

The development of technology today is much faster than in previous years, the transformation of past technology into technology that is easier and faster, especially games. Game is a means of entertainment with the aim of having fun and filling spare time. Games can be a unique learning process for the community, because they will not only gain knowledge about folklore but they will also feel entertained. By making this game, it is hoped that it can help educate children to get to know and increase their knowledge about Indonesian folklore. Aside from being an entertainment medium to relieve fatigue or fill spare time, games can also be used as an attractive delivery medium for the younger generation, especially young people. This game is a door for the younger generation, especially young people, to get to know the character of warriors in Indonesia. The design of this android game entitled Si Jampang was made to provide an introduction to the character of Si Jampang and can provide entertainment to anyone who plays it. The development of foreign media and culture that has spread widely, it is feared that if the Si Jampang character is not maintained, then this one character will be forgotten. It is very unfortunate if the character of Si Jampang is swallowed up by the times, so precautions must be taken so that the character of Si Jampang is not completely forgotten. Namely by using the media game. For this reason, this android game was created as a problem solution for the author to be a deterrent so that this problem does not actually happen, but also can provide entertainment to users, so that they are interested in playing this android game. This game is a 2D game based on android. This game will be implemented by artificial intelligence using the Finite State Machine method. The method will regulate the behavior of the object when a change in the state or condition of the game occurs
Analisis Sentimen Kesehatan Mental Menggunakan K-Nearest Neighbors Pada Sosial Media Twitter Mahesworo Langgeng Wicaksono; Rusdah Rusdah; Diwi Apriana
Bit (Fakultas Teknologi Informasi Universitas Budi Luhur) Vol 19, No 2 (2022): SEPTEMBER 2022
Publisher : Universitas Budi Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36080/bit.v19i2.2042

Abstract

Mental health issues are still significant health problems in the modern world. Poor understanding, stigma, and low mental health awareness contribute to efforts to educate people about mental health. The issue of mental health is widely discussed on social media, one of which is Twitter. So it is necessary to analyze sentiment on mental health issues on Twitter. The dataset in this study uses community reviews on May 16, 2022, with the search word "Mental Health." The research method used in this study has several stages, such as processing data using the K-Nearest Neighbors algorithm by comparing the Support Vector Machine classification algorithm and Decision Tree Processing research data using Rapid Miner tools. The conclusion of this study is, based on experimental results with a dataset of 639 positive and 193 negative sentiment reviews. The results of modeling processing using the K-Nearest Neighbors algorithm obtained the best results when using the split data method 70:30 with k value at number 5, producing precision of 60.87% and recall of 44.03%, respectively, and accuracy of 58.39%.
Penerapan Metode Analytical Hierarchy Process Dalam Menentukan Teknisi Terbaik Pada PT. Sejahtera Buana Trada Nur Fahmi Azis; Hendri Irawan
Bit (Fakultas Teknologi Informasi Universitas Budi Luhur) Vol 19, No 2 (2022): SEPTEMBER 2022
Publisher : Universitas Budi Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36080/bit.v19i2.2137

Abstract

PT Sejahtera Buana Strada is the main Suzuki car dealer in Indonesia, which operates directly under the auspices of PT Suzuki Indomobil Sales as the ATPM (Single Agent for Brand Holders). Once in six months, the selection process for the best technicians is carried out. This mechanism aims to provide rewards and increase the motivation for the technicians' performance. However, the current approach is not optimal and has several obstacles. The problem faced is that the head of the workshop still takes a long time to determine the best technician. It is because the head of the workshop must analyze each technician's assessment form, which causes delays in submitting the best technician's report to the leader. In addition to other problems, the leadership is difficult to find out the history of the best technicians because the archives of the best technicians have not been stored properly. The decision support system was built to make it easier for the head of the workshop to make a decision. The system can decide by considering the criteria that the head of the workshop has determined. Therefore, a decision support system web-based application on PHP and MySQL as the database to solve this problem. This application uses the Analytical Hierarchy Process (AHP) method. The reason for using this method is because there is an eigenvector concept to carry out the priority ranking process for each criterion based on a pairwise comparison matrix. As a result, the process of assessing the best technicians can be carried out quickly, and leaders can review the history of the best technicians.
Analisis Sentimen Terhadap Pembelajaran Dosen Berdasarkan Data Kritik Saran Mahasiswa Menggunakan Metode Naive Bayes Noor Ferdyansyah; Achmad Solichin
Bit (Fakultas Teknologi Informasi Universitas Budi Luhur) Vol 19, No 2 (2022): SEPTEMBER 2022
Publisher : Universitas Budi Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36080/bit.v19i2.2041

Abstract

The quality of lecturers' teaching is the main key to the success of education at the University. By having lecturers who can provide good teaching, the seeds of nation-changing students can be created. To get lecturers who meet academic standards, of course, evaluation needs to be done. Therefore, Budi Luhur University always conducts questionnaires containing suggestion criticism forms that can be filled in by students. Completion of the suggestion criticism form is carried out for each group of courses at the end of the semester. Currently, the feedback data has not been used to analyze and evaluate the learning process. Therefore, in this research, sentiment analysis is carried out on the results of criticism suggestions that have been sent by students, to find out whether the criticism suggestions are positive, negative, or neutral. One of the sentiment analysis methods that can be used to solve opinion mining problems is the Naive Bayes Method. Data collected as many as 10,067 in the span of 1 semester, namely the odd semester of the 2021/2022 academic year. This suggestion criticism data is then preprocessed, and classified using the Naive Bayes method, testing is carried out using the Naive Bayes Classifier program which is made in the PHP programming language, then accuracy is obtained with the Naïve Bayes method in testing 60% - 40% getting an accuracy result of 83.92%, then in split data 70% - 30% getting an accuracy result of 83.26%, then for split data results 80% - 20% getting an accuracy result of 81.96%, obtained positive sentiment results as much as 2484, then negative sentiment as much as 152, and neutral sentiment as much as 267. This research aims to get sentiment results which are then expected to be used as a reference to improve the quality of teaching lecturers at the university and further evaluation.
Pengembangan Strategi Bisnis Melalui Business Model Canvas Dan Strategi Pemasaran Cv Sari Bumi Sakti Melalui Website Muhamad Ibrovic; Yudi Santoso; Nurwati Nurwati
Bit (Fakultas Teknologi Informasi Universitas Budi Luhur) Vol 19, No 2 (2022): SEPTEMBER 2022
Publisher : Universitas Budi Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36080/bit.v19i2.2017

Abstract

One of the promotion and marketing media that is currently developing is the website. The website is used to introduce what products are being sold. The website is also a means of communication between sellers and buyers. CV. Sari Bumi Sakti, which is engaged in producing therapeutic oils, uses offline sales by word of mouth and around the environment, so not many are familiar with therapeutic oils. Another problem is when data storage is still manual by writing sales results in books and staff taking turns so that when printing reports it confuses CV owners and takes a long time. Development of business strategy through the Business Model Canvas and CV Sari Bumi Sakti's marketing strategy through the website. The right solution is to compile a Business Model Canvas (BMC) to analyze each block in the BMC so that the problems and shortcomings of the running system are known that must be met in order to compete in the market. Marketing strategy development that has been carried out using social media as sales media is WhatsApp and Instagram. The purpose of this research is to make it easier for the owner to view sales reports, effective sales and sales targets. For this reason, an e-commerce website is designed that can promote therapeutic oil products and an e-commerce-based sales website that can store sales results and then facilitate online sales so that they achieve targets and print sales reports.
Perancangan Aplikasi Sistem Penggajian Karyawan Pada PT Immortal Cosmedika Indonesia Desti Chairunisa
Bit (Fakultas Teknologi Informasi Universitas Budi Luhur) Vol 19, No 2 (2022): SEPTEMBER 2022
Publisher : Universitas Budi Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36080/bit.v19i2.2138

Abstract

Payroll is considered a structure that plays an important role in various sectors with relevant data that it contributes. Meanwhile, the payroll system simplifies the process of collecting payroll data for employees. Currently, there are many applications that are being developed to help facilitate the calculation of employee payroll. Payroll applications make it easy to store and find the data needed. PT Immortal Cosmedika Indonesia has several problems, namely, the process of collecting employee data every month is still recorded in a special book and the submission of conventional payroll reports. The purpose of this study is to help the finance department of PT Immortal Cosmedika Indonesia reduce registration and payroll errors. This research uses the Research and Development (R&D) method with a data collection method which includes observation and interviews. This application was developed using Java Netbeans 8.2 and MySQL software as its database. The result of this research is that this application can be used to help facilitate and accelerate the work of the finance department of PT Immortal Cosmedika Indonesia in terms of employee data processing, employee salary processing, employee bonus processing and providing salary slips to employees without using paper as a printed medium. And make the stored reports in good condition and provide results quickly and accurately.
Penerapan Algoritma Random Forest Classifier Pada Sistem Deteksi Simbol Sistem Isyarat Bahasa Indonesia (SIBI) Prabandalu Enggar Wiraswendro; Hari Soetanto
Bit (Fakultas Teknologi Informasi Universitas Budi Luhur) Vol 19, No 2 (2022): SEPTEMBER 2022
Publisher : Universitas Budi Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36080/bit.v19i2.2043

Abstract

Sign language is a language that prioritizes body movements and facial expressions as symbols to communicate with each other. Deaf and speech-impaired groups are the main users of sign language. One type of sign language in Indonesia is SIBI (Indonesian Sign Language System). SIBI (Indonesian Sign Language System) is a form of spoken language that is converted into sign language. Sign language is not only used as a means of communication and interaction between deaf and mute people, but also with normal people. However, until now there is still a communication gap between people who are deaf or mute and normal people. Then made a system design that can detect the sign language symbol SIBI (Indonesian Sign Language System). This system is made using the Random Forest Classifier algorithm with the help of MediaPipe Holistic and OpenCV and is made using the Python programming language. In this study, a dataset was created which was limited to 10 (ten) classes of symbols representing words in the SIBI (Indonesian Sign System) with a total of 8734 data lines which were then pre-processed by dividing the dataset into 70% training data and 30% test data. This study contains stages such as making detection, creating datasets, training classification models, and testing. The test is carried out by calculating the accuracy using the Confusion Matrix and then getting the Accuracy rate of 98.6%, Precision of 98.6%, and Recall of 98.66%. With the creation of the SIBI (Indonesian Language Sign System) detection system, it is hoped that it can reduce the gap between people who are deaf or speech impaired and normal people in communicating. Contribute to knowledge about symbol detection in SIBI (Indonesian Sign System) using the Random Forest Classifier algorithm as well as MediaPipe Holistic and OpenCV. As well as preserving and popularizing SIBI (Indonesian Sign System) as a sign language in Indonesia.

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