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Bulletin of Information Technology (BIT)
Published by Forum Kerjasama Pendidikan TInggi
ISSN : -     EISSN : 27220524     DOI : 10.47065/bit.v2i3.106
Core Subject : Science,
Computer Science & IT
Jurnal Bulletin of Information Technology (BIT) memuat tentang artikel hasil penelitian dan kajian konseptual bidang teknik informatika, ilmu komputer dan sistem informasi. Topik utama yang diterbitkan mencakup:berisi kajian ilmiah informatika tentang : Sistem Pendukung Keputusan Sistem Pakar Sistem Informasi, Kriptografi Pemodelan dan Simulasi Jaringan Komputer Komputasi Pengolahan Citra Dan lain-lain (topik lainnya yang berhubungan dengan teknologi informasi)
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 20 Documents
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Search results for , issue "Vol 5 No 4: Desember 2024" : 20 Documents clear
Sistem Cerdas Pengkategorian Surat Undangan Elektronik Tender Pekerjaan Dengan AutoML Kelly, Angel; Irsyad, Hafiz; Widiyanto, Eka Puji
Bulletin of Information Technology (BIT) Vol 5 No 4: Desember 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v5i4.1501

Abstract

Abstrak−Tender merupakan tawaran untuk mengajukan harga, memborong pekerjaan, atau menyediakan barang. Pengelompokan surat undangan elektronik tender pekerjaan merupakan proses penting dalam menentukan apakah tender tersebut termasuk kategori pekerjaan dalam suatu perusahaan. Dataset yang digunakan memiliki jumlah sebanyak 650 judul pekerjaan yang dibagi dengan rasio 80:20, data training sebesar 80% dan data testing sebesar 20%. Pengembangan perangkat lunka ini dilakukan untuk mengelompokan kategori surat undangan elektronik tender menggunakan algoritma AutoML AutoGluon. Hasil dari pengujian yang dilakukan menunjukkan akurasi terbaik yang dihasilkan pada pengujian skenario ketiga (presets High) dengan akurasi sebesar 81.53%, sedangkan skenario pertama (presets Medium) memberikan akurasi terendah sebesar 77.69%. Kata Kunci: AutoML, AutoGluon, Tender, Surat Undangan Elektronik
Penerapan Metode COCOSO dan TOPSIS untuk Pemilihan Lokasi Pembangunan Perumahan Kota Semarang Winarno, Edy; Dwi Cahyono, Taufiq
Bulletin of Information Technology (BIT) Vol 5 No 4: Desember 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v5i4.1567

Abstract

One of the important and complicated stages in the construction project development process is selecting the location to be built. Project success and customer satisfaction will be influenced by good location selection. It is very important to use a Decision Support System (DSS) to help make more organized and informed decisions in situations like this. This is an SPK proposal for a housing development location that combines the COCOSO (Combined Compromise Solution) and TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) methods. The COCOSO method, which considers several conflicting criteria, was used to resolve doubts and site selection problems. Additionally, locations are ranked using TOPSIS based on how close they are to the ideal solution. Identify important factors that influence location selection including accessibility, land prices, infrastructure, and environmental factors. Next, assessment and ranking are carried out using COCOSO to provide the best compromise solution, and the results are evaluated using TOPSIS to determine the best location. A fictional case study is used to test system performance. Potential housing location data is used as an example. The simulation results show that the proposed SPK can provide complete and reliable location recommendations for housing developers. COCOSO and TOPSIS integrated in this SPK help decision makers choose locations by considering trade-offs between various criteria and choosing the location closest to the best solution. This SPK can help developers make strategic decisions about housing development locations.
Penerapan Metode MOORA Untuk Menentukan Serangan Hama Dan Penyakit Tanaman Kakao Mulyani, Neni; Hutahaean, Jeperson; Aulia Putri Fahdrina, Jihan
Bulletin of Information Technology (BIT) Vol 5 No 4: Desember 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v5i4.1670

Abstract

− Lubuk Palas Village, precisely in the Banjar Village area, is one of the villages where most of the people make a living as farmers. One type of plantation crop that is cultivated in Lubuk Palas Village is cocoa. However, the productivity of cocoa plants is always decreasing, the problem is pests and diseases. So far, the farmers of Lubuk Palas Village are still using manual methods such as guessing in determining pests and diseases on the cocoa plant. This causes the results to be less accurate and take a long time to determine. Due to the absence of a system that can help farmers in Lubuk Palas Village in overcoming pest and disease attacks on cocoa plants quickly. Therefore, a decision support system is needed using the MOORA method with the calculation of the web-based MOORA method that can make it easier for cocoa farmers in Lubuk Palas Village to determine pest and disease attacks on cocoa plants quickly, and can overcome the losses caused by attacks by nuisance organisms. the cocoa plant. In this study using quantitative methods. The data sources used are based on interviews, questionnaires and observations. Based on the data analysis that has been carried out, it is concluded that fruit-sucking ladybugs (Helopeltis spp) are obtained with a weight value (0.42545616), and fruit rot disease (anthracnose) is obtained with a weight value (0.426163942), these pests and diseases often occur and detrimental to cocoa farmers in Lubuk Palas Village.
Pemanfaatan Data Mining Menggunakan Metode K-Means Untuk Analisa Komoditas Telur Ayam Faisal, Muhammad; Suharmanto; Wiranti Sri Utami; Pratiwi, Nila
Bulletin of Information Technology (BIT) Vol 5 No 4: Desember 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v5i4.1673

Abstract

Chicken eggs are a source of animal protein that taste delicious and have many benefits, especially in the culinary field or are one of the main ingredients in making cakes. Some animals, especially poultry, can produce eggs that can be bought and sold and consumed by humans, including chicken eggs, duck eggs, puyu eggs and goose eggs, but the most popular and frequently consumed by humans are chicken eggs. There are two types of chicken eggs, namely free-range chicken eggs (Buras) and free-range chicken eggs (Ras). Data on broiler egg commodities is recorded at the Central Statistics Agency (BPS) and this data can be used for research, especially in the field of data mining using the K-clustering method. The aim of the facility is to determine the commodity cluster for purebred chicken eggs in each province. The number of clusters obtained from 34 provinces was 8 clusters With a cluster percentage of 76,6%.
Implementasi Augmented Reality Stunting untuk Kader Aisyiyah Kota Cimahi Utomo, Suharjanto; Budiarto, Samsul; Iswanto, Iswanto; Ramdhani, Indiraki
Bulletin of Information Technology (BIT) Vol 5 No 4: Desember 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v5i4.1683

Abstract

The Regional Leadership of Aisyiyah Cimahi City has a new and excellent programme called “Cimahi City Zero Stunting to Welcome the Golden Generation” to assist the Cimahi government programme in reducing stunting rates. Aisyiyah stunting cadres in Cimahi city need to increase their capacity in understanding stunting, an approach with information technology is expected to be easier and more interesting. Augmented reality (AR) is a technology that combines the real world with digital or virtual elements generated, thus creating an interesting and interactive user experience. By implementing Augmented Reality in the form of Stunting education media, it is hoped that it will increase the understanding of Aisyiyah cadres in Cimahi city. The application developed can be run on an android phone so that it can be easily used by stunting cadres and the community.
Analisis Data Mining Pola Penggunaan Seluler dan Klasifikasi Perilaku Pengguna di Berbagai Perangkat Menggunakan Metode C4.5 Ernawati, Andi; Wahyuni, Sri
Bulletin of Information Technology (BIT) Vol 5 No 4: Desember 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v5i4.1689

Abstract

Along with the development of digital technology, the use of mobile devices is increasing rapidly and affects user behaviour in accessing information and interacting with digital applications. This research aims to analyse mobile device usage patterns and classify user behaviour across various devices by utilising the C4.5 data mining method. The data used in this study was obtained from the Kaggle.com platform which provides a dataset of mobile device usage patterns, including variables such as frequency of application use, duration of device use, and type of application accessed. The research stages include data collection, data pre-processing to ensure quality, and analysis using the C4.5 algorithm. The C4.5 algorithm was chosen due to its ability to build a decision tree model that can classify user behaviour with a good level of accuracy. The results of this study show that there are certain patterns in mobile device usage that can be linked to demographic characteristics and user preferences for device types and applications. The resulting decision tree model is able to classify user behaviour with an accuracy rate of 41.71%%, and shows that social media applications and streaming applications are the most frequently used categories on mobile devices. This research is expected to provide insights for app developers and digital marketers in understanding user behaviour and optimising mobile-based interaction strategies. In addition, the results of this study also contribute to the application of the C4.5 method for analysing mobile technology usage patterns in the context of big data. Keywords: Data Mining, C4.5, Mobile Usage Pattern, User Behaviour Classification,Rapidminer Decision Tree...
Analisis Sentimen Analisis Sentimen Publik Terhadap Pariwisata Aceh di Media Sosial X Menggunakan Algoritma Naive Bayes Classifier Yahya, Susilawati; Wahyuni , Sri
Bulletin of Information Technology (BIT) Vol 5 No 4: Desember 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v5i4.1700

Abstract

Aceh has been synonymous with negative perceptions among people outside the province. This is due to the prolonged armed conflict and the devastating tsunami in 2004. Despite these challenges, Aceh possesses abundant potential for tourism, including natural attractions, historical sites, cultural arts, and religious tourism. However, negative perceptions continue to influence tourists' decisions to visit Aceh. Therefore, this study aims to analyze public sentiment or public opinion towards Aceh's tourism using the Naive Bayes algorithm on the X (Twitter) social media platform. Data for this study was collected from tweets on X (Twitter) using the keyword "Aceh tourism" and then underwent several data pre-processing stages to improve data quality, including text cleaning, case folding, word normalization, tokenization, stop word removal, and stemming. Afterward, the Naive Bayes algorithm was applied to classify tweet sentiment into positive and negative categories. Model evaluation was conducted using a confusion matrix, accuracy, and classification report. The results showed that Naive Bayes performed well in classifying public sentiment with an accuracy of 81%. This analysis indicates that public perception towards Aceh's tourism has begun to shift positively, presenting a promising opportunity for the future development of Aceh's tourism sector.
Analisis Data Mining Dalam Pemilihan Smartphone dan Klasifikasi di Berbagai Perangkat Menggunakan Random Forest Aulia, Ananda; Wahyuni, Sri
Bulletin of Information Technology (BIT) Vol 5 No 4: Desember 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v5i4.1703

Abstract

Abstract− Smartphone technology continues to develop rapidly, driving the need for effective analysis methods to assist users in selecting devices that suit their needs. This research aims to implement data mining using the Random Forest method in the process of selecting smartphones and classifying devices based on their technical specifications. The Random Forest method was chosen because of its reliable ability to handle data with a large number of attributes, produce an accurate classification model, and minimize the risk of overfitting. The dataset used includes technical specifications of various smartphones, such as camera resolution, chipset, RAM capacity, screen resolution, and support for 4K video recording. The research process involved data collection, pre-processing to handle missing values ​​and data transformation, as well as model training using the Random Forest algorithm.  The research results show that the Random Forest method is able to classify devices with high accuracy, helping users determine smartphones that meet their criteria, such as support for 4K video recording and overall performance. Additionally, this research provides insight into the importance of certain attributes in smartphone selection. Thus, implementing data mining using Random Forest can be an effective solution in supporting data-based decision making in the field of consumer technology. Keywords: Data Mining, Random Forest, Smartphone, Classification, Technical Specifications
Optimasi Strategi Penjualan Am2000 Tirtamart Dengan Algoritma Apriori Untuk Mengidentifikasi Produk Favorit Pelanggan Sugito, Bambang; Wahyuni, Sri
Bulletin of Information Technology (BIT) Vol 5 No 4: Desember 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v5i4.1707

Abstract

The retail industry faces increasing competition, and to survive, companies need to understand customer purchasing behavior and optimize their sales strategies. One effective approach is the use of data mining to analyze sales data and identify purchasing patterns. This study aims to optimize the sales strategy of Toko AM2000 by applying the Apriori algorithm to identify the most popular products among customers. The data used includes sales transactions from January to September 2024, with a total of 1,000 transactions and 10 attributes. The results of the analysis using the Apriori algorithm show a significant association between the products "Water Softener" and "Filter Tank," although the support value obtained, which is 20.4%, does not meet the minimum support threshold of 30%. However, the confidence value of 80.6% indicates a high likelihood that customers who purchase "Water Softener" also buy "Filter Tank." This suggests that Toko AM2000 should focus its marketing strategies on promoting these two products. To improve the effectiveness of the analysis, it is recommended to lower the minimum support value, increase the number of transactions, and consider using other algorithms, such as K-means. This study provides valuable insights for business decision-making and the enhancement of Toko AM2000's marketing strategy.
Analysis Of Public Sentiment Towards The Corruption Eradication Commission On Twitter Nurhaliza Sofyan, Siti; Wahyuni, Sri
Bulletin of Information Technology (BIT) Vol 5 No 4: Desember 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v5i4.1711

Abstract

The Corruption Eradication Commission (KPK) is a state institution in Indonesia which was formed to eradicate corruption. The Corruption Eradication Committee (KPK) [1]has the main task of carrying out investigations, inquiries and prosecutions of criminal acts of corruption. This institution is independent and free from the influence of any power in carrying out its duties and authority [2]. This research explores the analysis of Indonesian people's sentiment towards the KPK in the current situation such as arrests for corruption and the policies and actions carried out by the KPK. Sentiment analysis used in the journal with data obtained from Twitter data and using Orange Data Mining, with multilingual sentiment analysis techniques to analyze Indonesian people's sentiment towards the KPK agency. The results of sentiment analysis are visualized through box plots and scatter plots, which aim to classify Twitter users based on their emotional responses. The findings of this research provide valuable insight into the landscape of sentiment surrounding the Corruption Eradication Commission's bicycles, as well as providing sustainable benefits and are expected to be used as material for evaluating the government's role. Data totaling 300 tweets were processed using text mining techniques in the Orange Data Mining application [3][4]. This technique consists of several stages of text processing, namely transformation, filtering, and tokenization. The text processing results are extracted via wordcloud to find out the features of words that are often discussed by the public. After that, sentiment analysis was carried out to determine public opinion regarding the KPK institution based on positive, negative and neutral categories [5], [6]

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