DETEKSI KERUSAKAN HANDPHONE SAMSUNG MELALUI SISTEM PAKAR MENGGUNAKAN KOMBINASI ALGORITMA K-NEAREST NEIGHBOR DENGAN CASE BASED REASONING

Berdasaarkan hasil observasi yang dilakukan dilapangan, diperoleh bahwa kurangnya tenaga ahli yang dapat memperbaiki kerusakan pada handphone terutama handphone samsung dan banyaknya masyarakat awam yang kurang mengetahui gejala-gejala kerusakan handphone samsung, maka perlu adanya suatu teknologi informasi yang dapat membantu masyarakat awam dalam mengatasi kerusakan handphone tersebut.dalam penelitian ini menggunakan pendekatan sistem pakar dengan metode Kombinasi Algoritma K-Nearest Neighbor  Dengan Case Based Reasoning, menggunakan bahasa pemrograman Visual Studio. Adapun tujuan penelitian ini yaitu : membuat sistem pakar untuk mengidentifikasi kerusakan dan solusi perbaikan handphone Samsung dengan kombinasi metode Case Based Reasoning dan algoritma K Nearest Neighbo, mnunjukkan tingkat akurasi dari penerapan metode Case Based Reasoning dengan kombinasi algoritma K Nearest Neighbor pada sistem pakar deteksi kerusakan handphone Samsung. Hasil dari penelitian ini masyarakat awam dapat mengetahui jenis kerusakan handphone Samsung tanpa harus berkunjung ke service cente, mengetahui seberapa besar tingkat akurasi yang dihasilkan dari kombinasi metode Case Based Reasoning dan K-Nearest Neighbor

The Implementation of Top-Down Approach Method on Redesign of LAN Harvani Hotel Palembang

In this research, the object was taken from one of the hotels in Palembang, namely Harvani Hotel Palembang. This hotel is one of the hotels in South Sumatra Province, where this hotel has 4 floors. Harvani Hotel Palembang has a Local Area Network (LAN) which consists of several computers. LAN is very important to be applied to Harvani Hotel Palembang in order to support administrative work processes (management of hotel data, employee data, guest data to financial data) and guest needs (internet usage in every room of the Hotel which is one of the services provided by Harvani Hotel Palembang). However, the LAN owned by the Harvani Hotel Palembang still has disadvantages, such as LAN still cannot reach every hotel room on the 2nd floor. In addition, the administration side also faces obstacles because each floor of the Harvani Hotel Palembang has its own administrative section and then at the end of each work shift, reports from each administrative section are submitted to the administrative department on the 1st floor using external storage media. Therefore, it is necessary to redesign the Harvani Hotel Palembang LAN by applying the Top-Down Approach Method. The results of LAN redesign in this research will be displayed using Cisco Packet Tracer simulator software, where from the simulation results it can be seen that the new design of the Harvani LAN Hotel Palembang has connected the entire computer of each room and every floor of the Hotel. Therefore, if the results of this simulation are applied to Harvani Hotel Palembang, then the administrative work process can be managed directly because all data has been stored on the database server. In addition, this new LAN design has also reached all guest rooms of Harvani Hotel Palembang, so guests can access the internet in their respective rooms more comfortable.In this research, the object was taken from one of the hotels in Palembang, namely Harvani Hotel Palembang. This hotel is one of the hotels in South Sumatra Province, where this hotel has 4 floors. Harvani Hotel Palembang has a Local Area Network (LAN) which consists of several computers. LAN is very important to be applied to Harvani Hotel Palembang in order to support administrative work processes (management of hotel data, employee data, guest data to financial data) and guest needs (internet usage in every room of the Hotel which is one of the services provided by Harvani Hotel Palembang). However, the LAN owned by the Harvani Hotel Palembang still has disadvantages, such as LAN still cannot reach every hotel room on the 2nd floor. In addition, the administration side also faces obstacles because each floor of the Harvani Hotel Palembang has its own administrative section and then at the end of each work shift, reports from each administrative section are submitted to the administrative department on the 1st floor using external storage media. Therefore, it is necessary to redesign the Harvani Hotel Palembang LAN by applying the Top-Down Approach Method. The results of LAN redesign in this research will be displayed using Cisco Packet Tracer simulator software, where from the simulation results it can be seen that the new design of the Harvani LAN Hotel Palembang has connected the entire computer of each room and every floor of the Hotel. Therefore, if the results of this simulation are applied to Harvani Hotel Palembang, then the administrative work process can be managed directly because all data has been stored on the database server. In addition, this new LAN design has also reached all guest rooms of Harvani Hotel Palembang, so guests can access the internet in their respective rooms more comfortable

Enhancing Promotional Strategy Mapping Using the K-Means Clustering Algorithm to Raise Sales

To enhance sales, organizations must improve the alignment of their promotional tactics. Enterprises have the ability to promote their goods in locations where there is demand for them. Facilitating the delivery of the goods would enhance the ease with which clients can carry out their purchases and sales transactions. A corporation's ability to strategically allocate its goods enables it to expand its operations. Prospective clients have a greater array of choices at their disposal than the total number of enterprises operating within the same sector. This is accomplished by using a diverse range of promotional media to enhance the sales of products and services. Optimizing promotional strategies is the first and critical stage in presenting items to clients, as it directly impacts the benefits that the firm will get. So far, the sales process has not been affected by the promotional method. The objective of this research was to use the K-Means Clustering algorithm in a data mining procedure to optimize the categorization of customer data, CRISP-DM is used for the purpose of comprehending and preparing data, constructing models, evaluating them, and deploying them. The CRISP-DM method is employed specifically for the construction of clusters. A non-hierarchical clustering technique called K-Means divides data into many groups according on how similar they are. The program facilitates the determination of appropriate location mapping for promotional purposes. The study results may serve as a foundation for decision-making in order to maximize promotional techniques, using the generated clusters

PERSEBARAN LOKASI PRAKTEK BIDAN MELALUI PENERAPAN SISTEM INFORMASI GEOGRAFIS MENGGUNAKAN METODE CLUSTERING

Distribution of midwife practice pomegranate (quality of service) in Cirebon is difficult to know where the location of the practice because of the vast area of Cirebon. Then, the number of pregnant women who are less get help quickly (giving birth without medical assistance) because of ignorance location midwife practice pomegranate (quality of service) nearby. And the number of midwives pomegranate (quality of service) has not cooperated with the insurance BPJS to perform payment transactions. This study uses a clustering method, which can segment data clustering method, which is used to facilitate information retrieval midwife pomegranate (quality of service). Clustering methods have representation stage pattern, the selection traits or characteristics, pattern proximity, distance measurement, data obtained from IBI (Indonesian Midwives Association) and the tools used: phpMyAdmin, notepad ++, xampp, GoogleMapApi, Dreamwaver. This system can be expected to map the location of the practice of midwives pomegranate (quality of service) in the district of Cirebon, can find the nearest location midwife pomegranate (quality of service), can find pomegranate midwives who work with BPJS to perform payment transactions. Then, hopefully it can help people in handling pregnant women rapidly. And, is expected to reduce maternal and child mortality

Sentiment Analysis of the Public Towards the Kanjuruhan Tragedy with the Support Vector Machine Method

A tragedy occurred in the Indonesian football world during the Arema vs. Persebaya match on October 1, 2022, resulting in the loss of approximately 714 lives, including 131 fatalities and 583 injuries. The tragedy is believed to have been caused by tear gas in the spectator stands and the closure of exits at the Kanjuruhan stadium. This event sparked a diverse range of public responses on social media, which can be analyzed through sentiment analysis. In this study, we employed the Support Vector Machine (SVM) algorithm, known for its speed and accuracy in text classification, to process and analyze tweets from October 1 to 31, 2022, as well as YouTube comments related to the Kanjuruhan tragedy from October 1 to November 20, 2022. Among the different SVM kernels, the RBF kernel exhibited the highest accuracy, precision, recall, and F1 scores, reaching 76.40%, 75.74%, 76.40%, and 75.18% respectively, when predicting data with three labels. Furthermore, the RBF kernel showed the best performance for data with two labels, achieving the highest accuracy, precision, recall, and F1-Score, which increased to 81.54%, 81.56%, 81.54%, and 81.56%, respectively

SISTEM INFORMASI REPORTING CURICULUM VITAE KARYAWAN MENGGUNAKAN METODE RAPID APPLICATION DEVELOPMENT BERBASIS WEBSITE DI PT. PINS INDONESIA

PT. PINS Indonesia merupakan sebuah perusahaan yang bergerak dibidang internet of things dengan kantor cabang yang tersebar dibeberapa kota besar di Indonesia. pengolahaan data karyawan dari PT. PINS Indonesia masih belum maksimal dikarenakan belum terdapat sebuah sistem informasi pelaporan curriculum vitae yang digunakan untuk divisi Human Capital guna mempermudah proses pencarian dan pencetakan data diri karyawan yang akan melakukan proses kenaikkan jabatan dan pengangkatan karyawan tetap. Oleh karena itu dibutuhkan sebuah sistem informasi reporting curriculum vitae yang berfungsi sebagai sebuah sistem yang dapat mempercepat proses pencarian data serta pencetakkan dokumen curriculum vitae karyawan PT. PINS Indonesia. Dalam proses pengembangan sistem informasi ini, penulis menggunakan metode Rapid Application Development (RAD). Pertimbangan penulis dalam memilih metode RAD dikarenakan pada proses pengembangan menggunakan metode RAD dapat dilakukan dengan cepat dan tepat diterapkan pada studi kasus sistem informasi reporting curriculum vitae yang tidak memiliki sistem yang kompleks sehingga proses pengembangan dapat dilakukan dengan waktu yang singka

PERANCANGAN APLIKASI ANDROID IDENTIFIKASI TANDA TANGAN MENGGUNAKAN MULTI LAYER PERCEPTRON

Sering terjadinya suatu kasus pemalsuan tanda tangan disebabkan karena metode yang digunakan untuk mengidentifikasi tanda tangan masih kurang baik dan tidak akurat. Hal ini dikarenakan identifikasi tanda tangan kebanyakan masih dilakukan dengan cara melihat langsung tanda tangan, beserta nama pemilik tanda tangan yang tercantum di bagian bawah tanda tangan pada sebuah dokumen. Mengidentifikasi tanda tangan dengan cara manual tentu memiliki banyak kelemahan seperti ketelitian dan ketepatan saat identifikasi yang kurang absah, sehingga pemalsuan tanda tangan sangat mungkin terjadi. Penelitian ini menggunakan metode Artificial Neural Network yang akan diterapkan pada aplikasi identifikasi tanda tangan. Neural Network merupakan metode yang dapat mendeteksi pola rumit dan tidak mengikuti seragkaian instruksi yang diberikan peneliti. Namun metode ini mampu belajar dengan sendirinya saat menghadapi permasalahan. Metode ini memiliki kelebihan yaitu kemampuan untuk memodelkan fungsi linear, komputasi paralel, dan mempunyai sifat mentolerir kesalahan (fault tolerance). Penelitian ini diharapkan dapat membantu suatu lembaga, baik itu lembaga pemerintahan maupun lembaga swasta dalam mengidentifikasi pemilik dari suatu tanda tangan yang ada pada dokumen-dokumen penting seperti dokumen pencairan dana dan dokumen surat-menyurat. Sehingga kasus pemalsuan tanda tangan dapat diminimalisir. Selain hal tersebut dalam penelitian ini juga diharapkan agar nantinya sistem identifikasi tanda tangan dapat diterapkan pada suatu lembaga atau instansi

PENINGKATAN JUMLAH PENDAFTAR PENERIMAAN SISWA BARU MELALUI PENERAPAN BISNIS INTELEGENT DENGAN TEKNIK OLAP ( ONLINE ANALYCTICAL PROCESS )

Penerimaan Jumlah pendaftar siswa baru PSB di SMK Islam Annur Losari selama 5 periode terakhir mengalami  pasang surut yang signifikan, dikarenakan daya saing antar sekolah yang semakin tinggi. Keadaan saat ini, pemerintah menerapkan aturan yang sulit dalam meningkatkan kualitas pendidikan di Indonesia dengan kurikulum 2013 ( KURTILAS ) khususnya di wilayah Brebes, Selain hal tersebut, khususnya Sekolah Menengah Kejuruan saling meningkatkan kualitas pendidikan salah satunya adalah pembenahan sarana dan prasarana dalam meningkatkan jumlah pendaftar mahasiswa baru. Penelitian ini akan menggunakan teknik OLAP ( Online Analyctical Processing ) yang didalamnya terdapat tahapan dalam menyelesaikan kasus ini, seperti Analysis Services Project, Integration Service Project, dan Reporting Service Project, Dalam membangun Aplikasi Bisnis Intelijen, Alat bantu yang digunakan adalah POWER OLAP Versi 14, data yang digunakan dari penelitian ini adalah data set ( data warehouse ) penerimaan siswa baru angkatan tahun 2010 – 2015 pada SMK Islam Annur Losari. Penelitian ini diharapakan menghasilkan prediksi atau analisa sementara untuk meningkatkan jumlah pendaftar guna mempermudah pihak SMK Islam Annur Losari  dalam menganalisis perkembangan data Penerimaan Siswa Baru (PSB) dan mengetahui data informasi yang akurat, dan dengan hasil prediksi ini diharapkan pula dapat meningkatkan persentasi jumlah pendaftar penerimaan siswa baru di SMK Islam Annur Losari. Kata kunci: Bisnis Intelijen, KTSP, Kurtilas OLAP, Power OLAP, Warehous

Kombinasi Single Linkage Dengan K-Means Clustering Untuk Pengelompokan Wilayah Desa Kabupaten Pemalang

K-Means is very dependent on determining the center cluster initial which has an impact on the quality  of clusters resulting, in addition to determining the center of cluster the number of k that will be used it can also affect the quality of the cluster from the method K-Means. Poverty is mostly experienced by rural communities, this can be seen from the lack of existing facilities to serve the interests of the community in various fields. To avoid the imbalance that occurs, a development plan is needed in accordance with the characteristics of the welfare of the people in the region. Therefore, we need an effort to group villages so that policy making is right on target. One of the algorithms clustering that is commonly used is the K-Means algorithm because it is quite simple, easy to implement, and has the ability to group large data groups very quickly. However, the K-Means algorithm has a weakness in determining the center cluster initial given. Initialization of centers cluster randomly may result in formation clusters changing (inconsistent). For this reason, the K-Means method needs to be combined with the hierarchical method in determining the center cluster initial. This combination method is called Hierarchical K-Means which is a combination of methods hierarchical and partitioning, where the process is hierarchical used to find the initial center initialization cluster and the process partitioning to get the cluster optimal. The hierarchical method used in this study is the method single linkage. Based on the method Elbow , the recommended amount of k for this study is k = 4.The combination of the single linkage and k-means algorithms with k = 4 in this study results in avalue silhouette coefficient of 0.685 which is a feasible or appropriate cluster category, while the evaluation measurement by Davies The Boulldin Index yielded a value of 0.577.

Prediksi Penyakit Ginjal Kronis Menggunakan Hibrid Jaringan Saraf Tiruan Backpropagation dengan Particle Swarm Optimization

The number of Chronic Kidney Disease patient increased year by year while it doesn’t following by sufficient human resources and infrastructure needs the information of Chronic Kidney Disease patient prediction. Prediction of Chronic Kidney Disease patient is necessary to be done as an anticipation for preparing the better human resources and infrastructure that will effect to patient survival rate. In this study, backpropagation artificial neural network and particle swarm optimization combination used to predict the number of Chronic Kidney Disease patient. Artificial Neural Network has the ability in time series data prediction, such as the number of Chronic Kidney Disease year by year. But, backpropagation artificial neural network has a weakness in weight inisialization which taken unoptimally that could cause bad convergence speed. Particle swarm optimization will resolve the backpropagation artificial neural network weakness by weights optimization that will used in backpropagation artificial neural network. The Artificial Neural Network and Particle Swarm Optimization have several parameters, such as the number of hidden layer neuron, learning rate, and swarm. This research is using RSUD Banyumas Chronic Kidney Disease patient data in 2011 until 2020. Matlab R2019a used in this research as a software to predict chronic kidney disease patient data. The test results shows the prediction accuracy based on Mean Squared Error value is 0,0370 using 12-16-1 artificial neural network architecture, 0.005 learning rate, 1250 epochs and 50 swarm