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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 256 Documents
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Rancang Alat Pengukur Tinggi Badan Dengan Output Suara Berbasis Arduino Uno Yandri Lesmana Yandri Lesmana; Iwan Purnama; Rohani
Bulletin of Information Technology (BIT) Vol 4 No 2: Juni 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v4i2.697

Abstract

In every health test, of course, there is a measurement of height, so that a person's height can be measured, starting from the soles of the feet to the head, the height measuring device used is still manual, which uses a meter and the measurement process in done by someone to measure the height of someone who wants to know his height so that the results of these measurements require more time when the number of people measured is more than 20 people in other words the manual height meter is less effective when used during the recruitment period of new employees started. With these constraints, the authors created a tool that can measure height automatically by utilizing an Ultrasonic sensor as a measuring tool and an Arduino Uno microcontroller as a control center by displaying measurement results on a 16x2 LCD screen. In this result it can replace the manual height measuring device so that it helps the activities of workers in carrying out their noble duties to provide health services to the general public.
Pengembangan Game Puzzle Find Grass Menggunakan Algoritma Backtracking Yulyanto; Tito Sugiharto; Fikri Maudia Arsyad
Bulletin of Information Technology (BIT) Vol 4 No 2: Juni 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v4i2.703

Abstract

Game like a tools of entertainment that is enjoyed and played by many grups ranging from children. teenagers and adults. With the rapid development of technology, games are becoming more practical. For example, nowadays we no need to buy a games console like Playstation to play a games. One of the games that has a good impact to users is a game in the form of education, from the explanation above, idea arises to take research to make a game entitled “Find Grass” based on 3D perspective android. That the concept of each level of the game, user must direct or control the player, namely a rabbit looking for a grass to get to the final destination poin with limited time. In making this game requires a Backtracking Algorithm that can find the fastest path to get to a certain destination poin and later will be applied to the help system in the game. The system development method is GDLC (Game Development Life Cycle) which has stages such as initiation, pre-production , production, beta, release. For application design using UML (Unified Modeling Language ). In addition , the application to create games uses Unity 3D. The final result of the application created is a game that is compatible on smartphone devices with an android operating system at least 5.0 (Lollipop). This game has several menus including the main menu, stage menu consisting of 3 stage guide menu and exit menu.
Rancang Bangun Game Pembelajaran Operasi Dasar Matematika Menggunakan Algoritma Fisher Yattes Yulyanto; Andriasnyah; Nunu Nugraha
Bulletin of Information Technology (BIT) Vol 4 No 2: Juni 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v4i2.704

Abstract

One of the lessons regarding basic mathematical operations is found in 2nd grade material of SD Negeri 2 Randusari. In the learning process the teacher has not maximized in utilizing existing technology, especially since grade 2 elementary school. The students still tend to like to play and mathematics is considered a difficult subject. Therefore it is necessary to utilize media to be able to attract students' interest with the learning while playing method. one of them with game media. In this game the researcher applies the Fisher Yattes algorithm to each question that comes out so that students are not monotonous in playing it. The Game Development Life Cycle (GDLC) is a guideline that regulates the process of making this game with development stages including initiation, pre-production, production, alpha testing, beta testing and release. The results of the UAT test on 14 students where this game can be accepted by users by getting an average percentage value of 89.64%. In its application the Fisher Yattes algorithm succeeded in generating random values in the game and no similar questions came out repeatedly at the same level.
Rancang Bangun Aplikasi Pendataan Kendaraan Operasional Menggunakan Metode Prototipe Astri Aprilia Pratiwi; Muhammad Iqbal
Bulletin of Information Technology (BIT) Vol 4 No 2: Juni 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v4i2.714

Abstract

PT. HM Sampoerna Tbk is a leading tobacco company in Indonesia as well as an affiliate of the world's leading tobacco company, Philip Morris International, which has many operational vehicles to support the process of distributing their products but the process of managing operational vehicles for maintenance or repair is still not optimal. Operational vehicles that are poorly maintained can cause problems with the vehicle at any time, causing large losses for the company. Operational vehicle maintenance must be carried out regularly so that the company's operational activities are not disrupted and to keep the vehicle in good condition and primed for traveling to distribute the company's products. The author develops an operational vehicle data collection application using the prototype method, namely rapid software development to present an overview of existing ideas and problems and then obtain feedback from users so that prototypes can be repaired immediately. The application design uses DFD and ERD and the results obtained from this research are applications that can provide information about the history of operational vehicle repairs, remind operational vehicle data management staff to carry out periodic maintenance.
Optimasi Algoritma K- Nearest Neighbor Berbasis Particle Swarm Optimization Untuk Meningkatkan Kebutuhan Barang Taofik Safrudin; Gatot Tri Pranoto; Wahyu Hadikristanto
Bulletin of Information Technology (BIT) Vol 4 No 3: September 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v4i3.724

Abstract

Abstract− The application of the K-Nearest Neighbor algorithm can be implemented where the results also show a new insight, namely predicting the level of need. With a ratio of 90%:10%, where there are 50 data objects tested to predict the level of needs in 2 groups, namely low needs or high needs. The results of the model scenario show that there are 2 objects in the Low needs group and 1 object in the High needs group. In evaluating this model, it was obtained from 10 fold Cross Validation that the Accuracy value was 82%, then the Precision value was 87.50%, and the Recall value was 80%. By measuring the performance of the model with Cross Validation, the resulting accuracy has a standard value or standard deviation, which aims to see the distance between the average accuracy and the accuracy of each experiment. While the Test Results using PSO In the evaluation of this model, it is obtained from 10 fold Cross Validation the Accuracy value is 100%, then the Precision value is 100%, and the Recall value is 100%, the test results have increased significantly
Klasifikasi Kebutuhan Sparepart Dengan Algoritma K-Nearest Neighbor Untuk Meningkatkan Penjualan Sparepart Virza Putra Virza; Gatot Tri Pranot; Fibi Eko Putra
Bulletin of Information Technology (BIT) Vol 4 No 3: September 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v4i3.729

Abstract

Adequate supply of spare parts will be a supporting factor for consumer confidence in the company. The classification method approach can be applied in analyzing data to apply data mining with the classification method for spare parts needs generated by utilizing data testing consisting of 100 record datasets with a ratio of 90% training data (training data) and 10% test data (data testing). . Implementation of the K-Nearest Neighbor algorithm model on test data (data testing) of 100 data objects, obtaining results that show a new insight in the form of classification of low and high level needs based on 2 categories. No is a category of light needs, consisting of 89 data objects, the category Yes is a category of high needs. Performance evaluation and testing using the RapidMiner Sstudio application is able to provide optimal results with the scenarios that are modeled. This algorithm model has an Accuracy value of accuracy: 93.00% +/- 6.40% (micro average: 93.00%).
Pengelompokan Penerimaan Mahasiswa Baru Dengan Algoritma K-Means Untuk Meningkatkan Potensi Pemasaran Daniel Tambun Daniel; Sifa Fauziah; Muhtadhuddin Danny
Bulletin of Information Technology (BIT) Vol 4 No 3: September 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v4i3.732

Abstract

Utilization of the existing PMB dataset through the clustering method approach can be applied in analyzing the rate of acceptance of new students. The K-Medoid Cluster algorithm model that is applied has results that show a new insight, namely the grouping of new student acceptance rates based on 3 clusters, cluster 1 (C0) is a high level consisting of 49 data from 86 datasets tested and cluster 2 (C1) is a low level consisting of 11 data from 86 datasets tested and cluster 3 (C2) is a medium level consisting of 26 data from 86 datasets tested. The results of the Davies Bouldin Index or DBI value are based on the RapidMiner Studio application obtained from data testing, with a Davies-Bouldin Index evaluation value of 0.769. Keywords: Data Mining, K-Medoid Cluster, Klastrer, PMB
Prediksi Jumlah Kasus Klaim Indemnity Dengan Menggunakan Algoritma Regresi Linear Pada Asuransi Mandiri Inhealth Qori yumansyah Qori; Ahmad Turmudi Zy; Muhamad Fatchan
Bulletin of Information Technology (BIT) Vol 4 No 3: September 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v4i3.733

Abstract

Insurance is a type of financial institution that aims to provide guarantees to customers against risks that may occur in the future. In this study, by utilizing some data on indemnity claim cases on inhealth insurance through a prediction method approach and can be applied in analyzing data to make predictions of future insurance data based on the level of need. The prediction process of a simple Linear Regression algorithm can be implemented where the results also provide new insights for the prediction needs of claim data. Tests using rapidminer produce performance that is relevant to the scenario being modeled. The simple Linear Regression equation model after comparing the results of calculations manually and also with the Rapid Miner application generally shows the same data. The RMSE value is also obtained when evaluating the performance of the applied model, with an RMSE value of 0.273 with a standard deviation of +- 0.0.
Klasterisasi Stok Produk Retail Untuk Menetukan Pergerakan Kebutuhan Konsumen Dengan Algoritma K-Means Niko Suwaryo Niko; Arif Rahman; Dewi Marini Umi Atmaja; Amat Basri
Bulletin of Information Technology (BIT) Vol 4 No 3: September 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v4i3.736

Abstract

− Retail product clustering is a product arrangement that is adjusted to the flow of placement or this layout is more suitable for product placement according to standards. Utilization of existing data through the clustering method approach can be applied in analyzing product grouping of data on availability and inventory of goods in warehouses so that it can provide knowledge and information. The clustering method is processed using the K-Means algorithm, where the results also show a new insight, namely grouping products based on 3 clusters. Cluster 1 is a product category with low availability or Low, namely 939 out of 1000 availability categories based on the number of products tested, then cluster 2 is a product category with medium or Medium availability, namely 51 out of 1000 availability categories based on the number of products tested, and finally cluster 3 is a product category with fairly high availability or High, namely 10 out of 100 availability categories based on the number of products tested. Tests using Rapid Miner tools can also produce similar insights, namely that each cluster has cluster group members according to manual calculations such as Cluster_0 in Rapid Miner has 51 cluster members representing the Medium cluster, Cluster_1 has 939 cluster group members representing the Low cluster, and Cluster_2 has 10 cluster members corresponding to the cluster representation High.
Prediksi Penyakit Diabetes Untuk Pencegahan Dini Dengan Metode Regresi Linear Niko Suwaryo Niko; Arif Rahman; Dewi Marini Umi Atmaja; Amat Basri
Bulletin of Information Technology (BIT) Vol 4 No 3: September 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v4i3.739

Abstract

Estimation is a method in which we can estimate the population value by using the sample value and which can model an equation to calculate the estimate i.e. a linear regression algorithm attempts to model the relationship between two variables by fitting a linear equation to observe the data. The application of a simple Linear Regression algorithm model can be implemented well and is able to provide a new insight for the need for predictions about the condition of diabetes data quality in controlling sugar levels in the body. Predictions of diabetes in the future can be known through the use of datasets using a prediction method approach through structured stages in analyzing the data used to produce an RSME value when evaluating a model of 0.000 +/- 0.000. Performance testing of the models and algorithms used in the evaluation can produce a picture that is relevant to the scenario being modeled. The RMSE value is obtained when evaluating the model performance of 0.000 +/- 0.000 through the RapidMiner Studio application.

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