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Jurnal Informatika dan Rekayasa Perangkat Lunak
Published by Universitas Wahid Hasyim Semarang
ISSN : 26562855     EISSN : 26855518     DOI : http://dx.doi.org/10.36499/jinrpl
Core Subject : Science,
Computer Science & IT
Journal of Informatics and Software Engineering accepts scientific articles in the focus of Informatics. The scope can be: Software Engineering, Information Systems, Artificial Intelligence, Computer Based Learning, Computer Networking and Data Communication, and Multimedia.
Arjuna Subject : Ilmu Komputer (semua kategori) - Perangkat Lunak
Articles 222 Documents
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Analisis Sentimen Pengguna Youtube terhadap Polemik Pelarangan Tiktok Shop menggunakan Algoritma Naive Bayes Muhamad farhan Tholhah hidayat; Martanto Martanto; Umi Hayati
Jurnal Informatika dan Rekayasa Perangkat Lunak Vol 6, No 1 (2024): Maret
Publisher : Universitas Wahid Hasyim

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36499/jinrpl.v6i1.10313

Abstract

Youtube and TikTok are creative platforms for creating videos and interacting with users. In addition to its function as a creative platform, TikTok Shop has recently emerged as a new breakthrough in the world of e-commerce because it can combine social media and e-commerce in one platform. TikTok Shop has become controversial as it disrupts micro, small, and medium-sized enterprises (MSMEs). Due to this controversy, the Indonesian government, through the Ministry of Home Affairs under the instruction of the President of Indonesia, has officially prohibited the use of TikTok as an e-commerce platform and limited it to only being a social media or social commerce application, leading to controversy turning into polemics. This has elicited various reactions from TikTok users, MSMEs, the general public, sellers, and TikTok Shop customers. Therefore, a method is needed to classify reviews automatically by conducting sentiment analysis. In this study, 4403 comment data from one CNN YouTube content titled 'TikTok Shop Banned? Ministry of Cooperatives and SMEs: If Not Regulated, Our MSMEs Could Collapse' were collected. This research applied the naïve Bayes algorithm with a qualitative and quantitative integration method and used the Knowledge Discovery in Databases (KDD) approach and confusion matrix evaluation. The data were divided into training and test sets using four schemes: first scheme 90-10, second scheme 80-20, third scheme 70-30, and fourth scheme 60-40. After evaluating the third scheme with a 70-30% data split, it achieved the best accuracy with a 94% accuracy rate of the test data in the naïve Bayes confusion matrix, which is the percentage of successfully predicted data. Furthermore, the Recall value was 96%, Precision 98%, and F1-Score 96%. This indicates that the model has a high level of accuracy for all training and test data.
Rancang Bangun Sistem Informasi Penyewaan Perlengkapan Pernikahan Berbasis Web pada CV. Ria Dewangga Imam Wibowo; Ardian Fachreza
Jurnal Informatika dan Rekayasa Perangkat Lunak Vol 5, No 2 (2023): September
Publisher : Universitas Wahid Hasyim

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36499/jinrpl.v5i2.7989

Abstract

Currently, with the development of information technology, it makes it easier for all industrial sectors, including the rental of wedding instruments. CV. Ria Dewangga Gubug is a company that rents out wedding party equipment. Information media facilities that are still not widespread and rental transactions that are still simple make company information less known to many people. Therefore, it is necessary to have an information system that provides all information and rental transactions that can be reached by the wider community. From the description above, the author is interested in creating a web-based information system design for wedding equipment rental using the waterfall system development method. It is hoped that this system can assist the company in processing customer data, transaction data. In addition, it makes it easier for the public to obtain information and in rental transactions.
Klasifikasi Algoritma KNN dalam menentukan Penerima Bantuan Langsung Tunai Ryan Hamonangan; Risa Komala Sari; Saeful Anwar; Tuti Hartati
Jurnal Informatika dan Rekayasa Perangkat Lunak Vol 6, No 1 (2024): Maret
Publisher : Universitas Wahid Hasyim

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36499/jinrpl.v6i1.10298

Abstract

Poverty is a condition where an individual or a group experiences economic incapacity to meet their basic needs, and this study involves broader aspects than just expenditures. The focus of this research is on Ciherang and Ciaro Villages, located in the Nagreg Subdistrict, Bandung Regency, which are areas with significant levels of poverty. This research responds to poverty issues by utilizing the K-Nearest Neighbor (KNN) Algorithm in the data mining classification process. KNN considers the proximity of a new object to its nearest neighbors, and as a supervised learning algorithm, KNN requires target information or classes in the analyzed dataset. The aim of this research is to provide information regarding the classification of recipients of Direct Cash Assistance (BLT) in Ciherang and Ciaro Villages. The research results present data on criteria for determining whether recipients are considered eligible or ineligible for BLT, with an accuracy rate reaching 81.56%. Additionally, the performance of this algorithm is demonstrated through true recall values for both eligible and ineligible recipients, with recall for true ineligible recipients at 88.43%, recall for true eligible recipients at 74.80%, precision for eligible recipients at 86.79%, and precision for ineligible recipients at 77.54%. These findings provide a basis for more accurate decision-making in determining BLT recipients in both villages. This can contribute to the design of more targeted and effective social policies in reducing the impact of poverty, providing in-depth insights into the characteristics of BLT recipients, and demonstrating the relevance and efficiency of the KNN algorithm in addressing complex social issues.
Analisis Clustering Data Anak Balita di Posyandu Kampung Sukarame Menggunakan Algoritma K-Means Mira Miranda; Nining Rahaningsih; Raditya Danar Dana
Jurnal Informatika dan Rekayasa Perangkat Lunak Vol 6, No 1 (2024): Maret
Publisher : Universitas Wahid Hasyim

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36499/jinrpl.v6i1.10256

Abstract

Nutrition has a very important role in maintaining the health of the human body, especially in children and toddlers. The current level of health of toddlers and children is still a challenge in every region. Balance in nutritional consumption has a significant impact on children's growth and development phases, increasing their learning capacity, and making a positive contribution to their future. Currently, the problem at the Mulus Rahayu posyandu Kp. Sukarame, Cileunyi Kulon Village, Bandung Regency is that there are still many parents who do not understand the importance of balanced nutrition for toddlers. Some toddlers are known to experience malnutrition problems, while others are obese. However, no attempt has been made to group data based on the nutritional value characteristics of toddlers using the K-Means Clustering algorithm, based on height, weight and age of toddlers. To categorize into groups such as good nutrition and poor nutrition. Through the application of the K-Means algorithm, it is possible to group the nutritional values of toddlers more symmetrically, providing a basis for earlier prevention efforts by posyandu cadres in handling problems of good nutrition and malnutrition. In this research, the methods applied include literature study and observation. The results of this research are able to categorize the nutritional value of toddlers as a whole, providing a basis for initial preventive steps that can be taken by posyandu cadres in dealing with good and poor nutrition of toddlers.
Aplikasi Electronic Customer Relationship Management (E-CRM) untuk Meningkatkan Layanan Orang Tua pada Madrasah Aliyah Al-Falah Fadil Muhammad Zuhri; Safitri Juanita
Jurnal Informatika dan Rekayasa Perangkat Lunak Vol 6, No 1 (2024): Maret
Publisher : Universitas Wahid Hasyim

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36499/jinrpl.v6i1.9439

Abstract

Competition between private schools in New Student Admissions (PSB) requires the right strategy, namely implementing Electronic Customer Relationship Management (E-CRM). Madrasah Aliyah (MA) Al-Falah is currently having a problem with decreasing the number of prospective new students (CSB) during the pandemic because the CSB registration process is carried out offline, and brochures are distributed when CSB comes to school. Apart from that, there is no media for alumni to provide positive reviews or for students' parents to give criticism and suggestions. Therefore, this research contributes to designing an E-CRM application to increase the number of CSB and student-parent services at MA Al-Falah. This research aims to simplify the CSB admission process by implementing two stages of CRM, namely acquiring and retaining, to increase the loyalty of parents so that their children return to school at MA Al-Falah and provide solutions in terms of school promotions, alumni reviews, and criticism of suggestions from students' parents. The method used in this research is qualitative research with descriptive analysis and the Waterfall system development method. This research concludes that the E-CRM application at MA Al-Falah helps make the PSB process easier because it features a registration form, registration fee information and discount coupons. The E-CRM system can also increase the loyalty of students' parents because it has a suggestion and criticism feature.
Penerapan Data Mining dengan Metode Clustering untuk menentukan Strategi Peningkatan Penjualan Berdasarkan Data Transaksi Muhamad Sulaiman; Riandy Yudistira; Riri Narasati; Ruli Herdiana
Jurnal Informatika dan Rekayasa Perangkat Lunak Vol 6, No 1 (2024): Maret
Publisher : Universitas Wahid Hasyim

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36499/jinrpl.v6i1.10329

Abstract

Improving marketing strategies in mini markets by applying the clustering method as the basis of the approach. By using the K-Means cluster algorithm on data on the number of transactions and total sales, this research aims to identify groups of customers who have similar purchasing patterns. This clustering is the basis for formulating a more targeted and efficient marketing strategy. The K-Means approach is used to group customers into segments that have similarities in transaction behavior. The results of this clustering are then used to develop more personalized marketing strategies, understand the unique needs of each customer group, and increase the effectiveness of marketing efforts. This research involves collecting data on the number of transactions and total sales from mini markets during a certain time period. The data is then analyzed using the K-Means algorithm to produce customer segments that have similar characteristics. The results of this analysis resulted in 4 clusters being formed, consisting of cluster 0, cluster 1, cluster 2, cluster 3 consisting of 7303 data that had gone through the preprocessing stage, divided into cluster 0 including low clusters and cluster 1 including high clusters and clusters 2 and 3 including Meanwhile, from these results, strategies can be concluded that can be implemented to improve minimarket performance by identifying these results.
Aplikasi Pengacakan Soal Ujian Online M.Syaifuddin Zuhri; Agung Riyantomo
Jurnal Informatika dan Rekayasa Perangkat Lunak Vol 5, No 2 (2023): September
Publisher : Universitas Wahid Hasyim

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36499/jinrpl.v5i2.9146

Abstract

The exam process, which is still manual or uses paper and writing instruments, has many weaknesses, including the duplication and distribution of question papers that require money and are not guaranteed to be safe, the use of unlimited answer sheet paper, the inaccuracy in the time of execution and collection of exam answers, examination of answer sheets. which takes quite a long time and cheating will also occur when working on exam questions because students can share answers to other students because the exam questions given are the same. This study aims to build applications for randomizing online exam questions that can facilitate the process of scoring or evaluating exam results and can avoid cheating that occurs when working on exam questions. The application of randomization of online exam questions can be used for the process of randomizing online exam questions so that online exams can avoid cheating and facilitate the assessment results or exam scores. The total score of the online exam scores is calculated using the formula for the number of correct / number of questions * 100.
Analisis Pola Pembelian Makanan dan Minuman di Kedai Distrik Menggunakan Algoritma Fp-Growth Tiana Dewi; Rini Astuti; Yudhistira Arie Wijaya
Jurnal Informatika dan Rekayasa Perangkat Lunak Vol 6, No 1 (2024): Maret
Publisher : Universitas Wahid Hasyim

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36499/jinrpl.v6i1.10303

Abstract

District Kedai is one of the many shops in Cirebon district, located on Jl. Raya Kalikoa, District. Kedawung, Cirebon Regency, West Java which operates in the food and beverage sector. Every day, sales transactions occur at the District Store. Sometimes consumers don't just buy one food or drink, but two or more foods or drinks in one transaction. Transaction recording is still limited to archives and has not been utilized, only left to accumulate by the District Store so that it does not provide information for the Store. Transaction data is also related to shopping patterns which can be used to determine the results of sales of goods in order to maximize sales to meet buyers' needs, therefore it is very important to know the purchasing patterns frequently made by Kedai District customers in order to develop strategies and increase sales. The aim of this research is to find out what the support and confidence values are to get an association to occur using the Association Rules method and the FP-Growth Algorithm. To find out consumer shopping patterns and find out how often item combinations appear in the sales data, the FP-Growth algorithm is an alternative algorithm that can be used to determine the data set that appears most often (frequent item set) in a data set. Therefore, this research will involve the process of collecting and processing data on food and drink purchase transactions that occurred at Kedai District during the period 1-31 October totaling 2,360 transactions. Next, the FP-Growth algorithm is used to identify purchasing patterns that have significant value and tend to repeat themselves. By conducting frequent itemsets using association rule techniques, and determining the support value and confident value to find out how often relationships appear between itemsets. Therefore, based on the final results obtained from this research, the relationship pattern generated from District Store transaction data with a minimum (support 0.7825) and (confidence 0.8) produces 1 rule. If a customer buys Grilled Sausage, they will buy Sate Suki with a support value of 0.161% and a confidence of 0.806%.
Menentukan Nilai Gizi pada Balita Menggunakan Algoritma Support Vektor Machine (SVM) di Posyandu Kelurahan Ciherang Silvia Dini Widianti; Rini Astuti; Fadhil Muhamad Basysyar
Jurnal Informatika dan Rekayasa Perangkat Lunak Vol 6, No 1 (2024): Maret
Publisher : Universitas Wahid Hasyim

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36499/jinrpl.v6i1.10274

Abstract

Determining nutritional status in toddlers is based on age, weight and height. The process is still done manually, resulting in the resulting data being less relevant. This research serves to provide information about determining the nutritional status of toddlers so that the community and officers at Posyandu Ciherang Village. The problem of this study is to determine the growth and development of nutritional status in toddlers at Posyandu Ciherang Village. Data obtained from Posyandu at the village level whose activities are carried out once a month by cadres under the technical guidance of the puskesmas. Based on the existing problems, a system for determining the nutritional status of toddlers is needed to make it easier to get the right results. The method to be used is Support Vector Marchine (SVM) which is a method of classifying data and providing a basis for early preventive action in overcoming nutritional problems in toddlers. The purpose of this study is to determine the nutritional status of toddlers there are 3 criteria needed, namely the age of toddlers, weight and height. The Support Vector Marchine (SVM) algorithm is considered more optimal because it is able to analyze the best results. The results of this study are expected to provide better insight into determining nutritional values in toddlers. Based on the results show True Less (TK) on pred.NORMAL is 31 records classified as malnutrition and True Normal (TN) on pred.NORMAL is 267 records classified as normal nutrition with the smallest result of class recall 76.52% and the smallest result of class precision 76.52%. From these results it can be concluded that the accuracy rate with the Support Vector Marchine (SVM) algorithm is 85.58%.
Implementasi Steganografi Metode Least Significant Bit (LSB) untuk Menyembunyikan File Pesan dalam Gambar Muhammad Naim Al Jumah; Sarimuddin Sarimuddin
Jurnal Informatika dan Rekayasa Perangkat Lunak Vol 6, No 1 (2024): Maret
Publisher : Universitas Wahid Hasyim

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36499/jinrpl.v6i1.10143

Abstract

Ease of image manipulation is not something difficult. Images become a more effective communication medium for society. The development of software for image manipulation, increasing crime such as phishing and bullying in cyberspace. The Least Significant Bit method is a steganography method that can be used to encrypt or hide messages in images. Hiding information in various media files such as images is done to maintain the confidentiality of the messages sent. This research implements the Least Significant Bit (LSB) method to hide a message file in an image. This research carries out encryption and description of the message to be sent by inserting a file into the image. This research will also carry out a testing process for the stego image. From the results of tests that have been carried out by carrying out three processes of sending stego image files via copying files with a flash disk, email and sending via WhatsApp with a document model, the results obtained are that stego image files can still be extracted data to get messages that have been encrypted in the image, However, when the stego image file is sent via WhatsApp using the image sending method, the stego image cannot be extracted. This happens because there has been a change in the extension of the file downloaded from WhatsApp. This is also influenced by data changes in the form of file compression from the WhatsApp application. Where every file sent via the WhatsApp application will experience file compression so that data changes will occur

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