Bulletin of Information Technology (BIT)
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)
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<![CDATA[Perancangan Game Sederhana Perancangan Game Sederhana Menggunakan Scratch Programming Sebagai Media Pembelajaran Visual Bagi Anak Usia Dini ]]>
<![CDATA[Yunus Yunus Anis]]>;
<![CDATA[Artin Bayu Mukti]]>;
<![CDATA[Sri Mulyani]]>
<![CDATA[ Bulletin of Information Technology (BIT) Vol 4 No 3: September 2023 ]]>
Publisher : <![CDATA[Forum Kerjasama Pendidikan Tinggi (FKPT) ]]>
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DOI: 10.47065/bit.v4i3.769
<![CDATA[This study aims to design a simple game using Scratch Programming as a visual programming language learning media for early childhood. This article describes the implementation stages of game design and the evaluation of learning media carried out. The literature review reviews the advantages of Scratch Programming as a learning medium for children and previous related research. In the implementation of game design, game concepts are designed using Scratch Programming, and simple game examples are generated. Evaluation of learning media is carried out to collect evaluation data from participants using relevant methods. The results of the evaluation of learning media and the discussion of research findings provide information about the effectiveness of game design using Scratch Programming. The results of this study indicate that designing simple games using Scratch Programming can be an interesting and effective learning medium for young children in learning visual programming languages. The implication of this research is further development in game design and the use of visual programming languages in early childhood education. Suggestions for further research are to involve more participants and explore more complex programming concepts.]]>
<![CDATA[Media Pembelajaran Syariat Islam Pada Anak Usia Dini Berbasis Android ]]>
<![CDATA[Ghifron Akhiru Syahroni]]>;
<![CDATA[Shinta Esabella]]>;
<![CDATA[Eri Sasmita Susanto]]>
<![CDATA[ Bulletin of Information Technology (BIT) Vol 4 No 3: September 2023 ]]>
Publisher : <![CDATA[Forum Kerjasama Pendidikan Tinggi (FKPT) ]]>
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DOI: 10.47065/bit.v4i3.791
<![CDATA[Limited facilities and low learning media infrastructure are two of the causes of the low quality of Indonesian education. This applies to children at TPQ Al-Ikhsan Dusun Boak Dalam, where learning methods still use books and whiteboards, which are relatively boring for children, and some material is still very difficult to understand. This disrupts the learning process. Then a solution is needed to answer this problem, namely by having an Android-based learning media application that includes Islamic law material for children. This study aims to develop an Android-based application that is specifically designed for learning media for Islamic law in early childhood at TPQ Al-Ikhsan Dusun Boak Dalam so that it makes it easier for children to understand learning material. The resultstugas of this study are in the form of an Android-based prototype of Islamic Shari'a learning media applications in early childhood that can help children understand learning material.]]>
<![CDATA[Analisis Gempa Bumi Di Indonesia Dengan Metode Clustering ]]>
<![CDATA[Arji Prasetio]]>;
<![CDATA[M. Makmun Effendi]]>;
<![CDATA[M. Najamuddin Dwi M]]>
<![CDATA[ Bulletin of Information Technology (BIT) Vol 4 No 3: September 2023 ]]>
Publisher : <![CDATA[Forum Kerjasama Pendidikan Tinggi (FKPT) ]]>
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DOI: 10.47065/bit.v4i3.820
<![CDATA[Indonesia is known as an archipelagic country because it consists of thousands of islands stretching from Sabang in the west to Merauke in the east. Testing earthquake data using the K-Means algorithm, where the results also show a new insight, namely the grouping of earthquake-prone areas in Indonesia based on 3 clusters. Cluster 1 is a category of areas with a relatively low level of earthquake-prone areas in Indonesia, namely 209 out of 1113 categories of the number of cases based on the area tested, then cluster 2 is a category of areas with a moderate level of earthquake-prone areas in Indonesia, namely 863 out of 1113 the category of the number of cases based on the area tested, and finally cluster 3 is the category of area with a high level of earthquake-prone areas in Indonesia, namely 41 out of 1113 categories of the number of cases based on the area tested. Tests using the earthquake clustering method with the K-Means algorithm can produce clusters that have cluster group members according to manual calculations such as Cluster_0 in Rapid Miner has 209 cluster members representing the Low cluster, Cluster_1 has 863 cluster group members representing the Medium cluster, and Cluster_2 has 41 cluster members corresponding to the cluster representation High.]]>
<![CDATA[Rancang Bangun Robot Pengantar Obat dan Makanan Pasien Berbasis Internet of Things ]]>
<![CDATA[Edy Sopyan]]>;
<![CDATA[Dedi Suarna]]>;
<![CDATA[Muhammad Harun Ashar]]>;
<![CDATA[Mustakim]]>
<![CDATA[ Bulletin of Information Technology (BIT) Vol 4 No 3: September 2023 ]]>
Publisher : <![CDATA[Forum Kerjasama Pendidikan Tinggi (FKPT) ]]>
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DOI: 10.47065/bit.v4i3.839
<![CDATA[The rapid development of technology today, especially in the field of information technology, requires everyone to be able to follow it so as not to be left behind by other developing countries, especially regarding the use of technology. The goal to be achieved from this research is to design a robot that can ease the work of medical personnel, especially in delivering medicine and food to patients so that they no longer need to deliver it manually, just use a robot controlled by an application. The research method used is the waterfall method. Robot testing is done by testing the control distance to find out how far the robot can be controlled. This robot consists of 3 layers and has 4 wheels. The working system of this robot is controlled by 4 buttons namely forward, backward, left and right by the user through a control application. The command is sent to the NodeMcu Esp8266 which is then forwarded to the Motor Driver L298n as the overall voltage of the system is made to work properly.]]>
<![CDATA[Pengelompokan Untuk Penjualan Obat Dengan Menggunakan Algoritma K-Means ]]>
<![CDATA[Holwati]]>;
<![CDATA[Edi Widodo]]>;
<![CDATA[Wahyu Hadikristanto]]>
<![CDATA[ Bulletin of Information Technology (BIT) Vol 4 No 3: September 2023 ]]>
Publisher : <![CDATA[Forum Kerjasama Pendidikan Tinggi (FKPT) ]]>
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DOI: 10.47065/bit.v4i3.848
<![CDATA[Drug grouping is an arrangement that adjusts to the flow of placement or drug layout is more suitable for standard processes. Utilization of existing data through the clustering method approach can be applied to analyze in grouping drug data on data availability and inventory in warehouses so as to provide knowledge and information. The clustering method is processed using the K-Means algorithm where the results also show a new knowledge, namely the grouping of drug data based on 2 clusters. Cluster 1 is a high need category with availability of 71 out of 100 availability categories based on the amount of drug data tested, then cluster 2 is a drug category with moderate or low availability, namely 29 out of 100 availability categories based on the number of drug data tested. Tests using Rapid Miner tools can also produce similar insights, namely each cluster has cluster group members according to manual calculations such as Cluster_0 in Rapid Miner has 72 cluster members representing the Medium cluster, Cluster_1 has 72 cluster group members as high cluster representations, and Cluster_2 has 3 cluster members corresponding to low representation.]]>
<![CDATA[Pemetaan Tingkat Kriminalitas di Indonesia: Analisis Spasial dengan Pendekatan SIG pada Tingkat Provinsi ]]>
<![CDATA[Ronal Watrianthos]]>;
<![CDATA[Sudi Suryadi]]>;
<![CDATA[Kusmanto]]>;
<![CDATA[Samsir Samsir]]>
<![CDATA[ Bulletin of Information Technology (BIT) Vol 4 No 3: September 2023 ]]>
Publisher : <![CDATA[Forum Kerjasama Pendidikan Tinggi (FKPT) ]]>
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DOI: 10.47065/bit.v4i3.861
<![CDATA[Indonesia memiliki Indeks Pembangunan Manusia yang rendah, yang menunjukkan bahwa masih ada pekerjaan yang harus dilakukan untuk meningkatkan kualitas hidup dan kesehatan masyarakatnya. Selain itu, Indonesia menghadapi banyak masalah sosioekonomi, termasuk populasi yang berlebihan, kemiskinan, tingkat pengangguran yang tinggi, dan sistem pendidikan yang buruk. Masalah-masalah ini dapat memengaruhi masyarakat, termasuk meningkatkan kejahatan. Banyak indikator yang umum digunakan dalam bidang statistik kriminal untuk mengukur kejahatan dari perspektif yang luas dan untuk menilai tingkat keparahannya. Tujuan dari penelitian ini adalah untuk menggambarkan distribusi tingkat kejahatan secara keseluruhan di antara provinsi-provinsi Indonesia, dengan penekanan khusus pada Sumatra dan Jawa. Studi ini menggunakan data dari Badan Pusat Statistik dari tahun 2010 hingga 2020 tentang jumlah kejahatan yang dilaporkan oleh petugas polisi regional. Objek yang diamati di masing-masing provinsi dikelompokkan ke dalam kelompok yang saling terkait menggunakan teknik pembelajaran tidak terbimbing dengan algoritma klasifikasi K-Means. Hasil menunjukkan bahwa antara tahun 2010 dan 2020, provinsi Bengkulu, Kepulauan Bangka Belitung, dan Banten memiliki tingkat kejahatan terendah dibandingkan provinsi lain di Sumatra dan Jawa. Hasil ini menunjukkan bahwa ketiga provinsi ini mungkin memiliki kemampuan yang lebih baik untuk mengatasi masalah sosioekonomi yang diketahui berkontribusi pada kejahatan.]]>
<![CDATA[Distribusi Spasial Unmet Need Pelayanan Kesehatan dengan Algoritma K-Means untuk Pemetaan Provinsi di Indonesia ]]>
<![CDATA[Kusmanto]]>;
<![CDATA[Samsir Samsir]]>;
<![CDATA[Ronal Watrianthos]]>;
<![CDATA[Sudi Suryadi]]>
<![CDATA[ Bulletin of Information Technology (BIT) Vol 4 No 3: September 2023 ]]>
Publisher : <![CDATA[Forum Kerjasama Pendidikan Tinggi (FKPT) ]]>
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DOI: 10.47065/bit.v4i3.862
<![CDATA[Pemetaan spasial terhadap kebutuhan pelayanan kesehatan yang belum terpenuhi (unmet need) penting dilakukan untuk mengenali wilayah yang memerlukan prioritas intervensi guna meningkatkan akses dan kualitas layanan kesehatan. Penelitian ini bertujuan memetakan tingkat unmet need pelayanan kesehatan di 34 provinsi Indonesia tahun 2015-2022 dengan algoritma klasterisasi K-Means. Data unmet need dianalisis dan dievaluasi menggunakan Indeks Davies-Bouldin untuk menentukan jumlah klaster optimal. Hasil analisis menunjukkan 3 klaster provinsi optimal berdasarkan tingkat unmet need. Klaster 1 (DKI Jakarta, Bali, Papua) memiliki rata-rata unmet need terendah 2,47%. Klaster 2 (sebagian provinsi di Jawa dan Kalimantan) memiliki rata-rata unmet need sedang 5,46%. Klaster 3 (sebagian besar provinsi di luar Jawa) merupakan kelompok dengan unmet need tertinggi rata-rata 7,35%. Secara spasial, provinsi di luar Jawa cenderung berada di klaster dengan unmet need tinggi, sejalan dengan tantangan aksesibilitas pelayanan kesehatan. Hasil pemetaan K-Means ini dapat menjadi acuan dalam merumuskan rekomendasi peningkatan akses dan kualitas layanan kesehatan di provinsi-provinsi prioritas berdasarkan tingkat unmet need.]]>
<![CDATA[The Expert System of Determining the Type of Malaria by using Dempster-Shafer Method ]]>
<![CDATA[Ronal Maruli Marusaha]]>;
<![CDATA[Dian Noviandri]]>;
<![CDATA[Andre Hasudungan Lubis]]>
<![CDATA[ Bulletin of Information Technology (BIT) Vol 4 No 3: September 2023 ]]>
Publisher : <![CDATA[Forum Kerjasama Pendidikan Tinggi (FKPT) ]]>
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DOI: 10.47065/bit.v4i3.887
<![CDATA[Malaria is the most dominant disease in Asia and Africa and may become a life-threatening disease for it suffers. The types of malaria such as Plasmodium Vivax, Plasmodium Ovale, Plasmodium Malariae, and Plasmodium Falciparum are mostly infected people around the world. These types of malaria have certain symptoms that drives difficulties for some patients to confirm which malaria that their infected. A clinical testing and medical diagnostic assessments may be performed to determine the types of malaria, but utilizing a system also brings some benefits for rural areas which lack of medical facilities. The study develops a system by implementing the Dempster Shafer method to determine types of malaria. We collected the knowledge from the experts including 18 possible symptoms along with the density value. This paper present 5 cases of sufferers and provide the system result with the possibilities of malaria types. The result pointed out a various percentage of malaria types that may infected to the patients.]]>
<![CDATA[Perbandingan Algoritma Extreme Learning Machine dan Multilayer Perceptron Dalam Prediksi Mahasiswa Drop Out ]]>
<![CDATA[Muhammad Ibnu Saad Saad]]>
<![CDATA[ Bulletin of Information Technology (BIT) Vol 4 No 3: September 2023 ]]>
Publisher : <![CDATA[Forum Kerjasama Pendidikan Tinggi (FKPT) ]]>
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DOI: 10.47065/bit.v4i3.890
<![CDATA[Determined by the university concerned. The high number of drop out students at tertiary institutions can be minimized by policies from tertiary institutions to direct and prevent students from dropping out that detecting at-risk students in the early stages of education is very important to do to keep students from dropping out. The purpose of this study is to classify and compare the Extreme Learning Machine and Multilater Perceptron algorithms in predicting student drop out. This study uses two algorithms, namely Extreme Learning Machine and Multilater Perceptron which are feedforward artificial neural network learning methods. The data used is 110 data according to the number of students from class 2012 to 2018. The data is taken from the Doctor of Education Management academic information system. In this case how to predict student drop out using the variables Gender, Working Status, Family Status, Age, Semester 3 GPA, Comprehensive Examination, Dissertation Progress, and Publications. The results of the Extreme Learning Machine classification based on a ratio of 80:20 get an accuracy of 95% with a hidden layer of 20 and a Mean Squared Error value of 0.369. Whereas the Multilater Perceptron with the same ratio gets 91% accuracy. From the two models used, it shows that the two artificial neural network algorithms can produce good performance in predicting drop out students.]]>
<![CDATA[Memprediksi Kualitas Produk Inspeksi Dalam Meminimalisasi Resiko Produk Ng Meggunakan Algoritma Regresi Linier ]]>
<![CDATA[Dini Rahayu]]>;
<![CDATA[Aris Gunaryati]]>
<![CDATA[ Bulletin of Information Technology (BIT) Vol 4 No 3: September 2023 ]]>
Publisher : <![CDATA[Forum Kerjasama Pendidikan Tinggi (FKPT) ]]>
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DOI: 10.47065/bit.v4i3.894
<![CDATA[Predicting the product is a form of analyzing data, predicting the product is an important factor that determines the smooth running of the product. Utilization of product and defect data can be used in carrying out the process of data mining and modeling stages to predict the number of product defects at one time. The application of the simple Linear Regression algorithm equation model can be implemented where the results also provide a new insight for the prediction needs of the number of product defects. The simple Linear Regression equation model after comparison with actual calculation results (observations) and also with the Rapid Miner application in general shows similar results. Evaluation and testing of the RMSE value was also obtained when evaluating the applied linear regression model, with an RMSE value of 0.984 with a standard deviation of +- 0.0]]>
