Implementation Of Data Mining On Telkom Customer Data Using The K-Nearest Neigbor Method To Predict Service Status: Implementasi Data Mining Pada Data Pelanggan Telkom Menggunakan Metode K-Nearest Neigbor Untuk Memprediksi Status Pelayanan

The use of the internet makes it easier for people to get information. The large number of wifi users resulted in an increase in Telkom Indonesia. This impact resulted in frequent delays in the service process. The purpose of this study is to classify service status as normal or abnormal. This study implements the k-nearest neighbor classification method. The data used is Telkom customer data of 15,113 (May to June 2018), dataset of 100 data. The input consists of 60% training data and 40% testing data. Weka processes calculations and displays classification results in the form of normal or abnormal. In Weka, the correctness prediction is 92.5%, the error prediction is 7.5%. In manual calculations, the correctness prediction is 98%, the error prediction is 3%. From the results of calculations using KNN, the highest results were obtained using manual with truth level of 98%, error rate of 3%

SISTEM INFORMASI PENGELOLAAN DAN PERENCANAAN BELANJA UNTUK CUSTOMER TOKO KELONTONG BERBASIS ANDROID

Saat ini teknologi berbasis mobile berkembang sangat pesat, sehingga menyebabkan perubahan besar pada bidang usaha jual beli. Dengan adanya hal tersebut persaingan bisnis menjadi sangat ketat, terlebih lagi bagi pelaku usaha mikro (khususnya pemilik toko kelontong) yang saat ini belum banyak memanfaatkan teknologi untuk menjalankan usahanya. Penelitian ini dilaksanakan pada toko kelontong yang berada di desa Suko Sidoarjo. Metode penelitian yang digunakan dalam penelitian ini terdiri dari pengumpulan data, analisa masalah, perancangan sistem, dan pembuatan sistem. Dengan adanya penelitian ini diharapkan menghasilkan sistem informasi berbasis android untuk customer toko kelontong, sehingga dapat meningkatkan penjualan toko kelontong dan dapat bersaing dengan toko modern dalam segi fasilitas, kesetaraan harga, dan pelayanan yang mudah dan cepat

SISTEM PAKAR DIAGNOSA DINI PENYAKIT GIGI DAN MULUT

Gigi dan mulut adalah organ organ tubuh yang ada pada wajah .keduanya sangatlah vital keberadaannya oleh karenanya kesehatan kedua organ ini sangatlah penting . pada umumnya orang sangat menyepelekan masalah kesehatan sekitar mulut , karena mungkin mereka lebih mementingkan kesehatan organ-organ tubuh lainnya, yang di anggap lebih penting. Padahal penyakit yang menyerang gigi dan mulut dapat menimbulkan masalah yang berarti bagi kesehatan lainnya . contoh : masalah penampilan atau masalah di organ tubuh lainnya Bahkan berawal dari penyakit inilah akan timbul penyakit penyakit yang membahayakan dan menyerang anggota tubuh lainnya. Sistem pakar merupakan teori untuk mengatasi dalam ketidakpastian. Sejumlah teori telah ditemukan untuk menyelesaikan ketidakpastian, termasuk diantaranya probabilitas klasik (classicalprobability), probabilitas Bayes (Bayesianprobability), teori Hartley berdasarkan himpunan klasik (Hartleytheorybasedon classicalsets), teori Shannon berdasarkan pada probabilitas (Shannontheorybasedon probability), teori Dempster-Shafer (Dempster- Shafer theory), teori fuzzyZadeh (Zadehísfuzzy theory) dan faktor kepastian (certainty factor). Berdasarkan uraian diatas penulis tertarik untuk menyusun penelitian dengan judul ―Diagnosa Dini Penyakit Gigi dan Mulut Dengan Menggunakan Metode Dempster Shafer”. Penelitian ini berisi tentang deteksi awal penyakit Gigi dan Mulut yang dapat digunakan oleh dokter maupun masyarakat umum dalam mendiagnosa dini penyakit Gigi dan Mulut dimana saja dan kapan saja. Hasil penelitian ini memperlihatkan nilai Demster Shafer berada pada kisaran 0 sampai dengan 1, jika keluaran Demster Shafer mendekati 1, maka kepastiannya mendekati benar. Keyword : Gigi dan Mulut, Demster Shafer, sistem paka

Penerapan Bot Telegram untuk Sistem Monitoring Jaringan Intranet Daerah di Instansi Pemerintahan

Currently, the internet has become a basic need in the process of providing information and knowledge. Public, government and private services compete with each other in the use of information technology, which is expected to support employee performance and service. Therefore, human resources are needed who not only master material aspects, but also have adequate capacity and ability to apply and develop information in all fields. The use of this monitoring system is very necessary for the sidoarjo communicarions and information services departement and institutions that operate in the network sector and also have a fairly broad and complex customer coverage. Problems that often occur are slow internet connections, broken network cables, damaged network devices, etc. At that time, a network monitoring system was needed as a system that could detect when the network connection was lost. The research method used in this research is experimentation, namely a category of research that aims to find the cause and effect situation of a phenomenon. Therefore, this research is to investigate cause and effect, in accordance with previous conditions. From the results of the tests carried out, Mikrotik succeeded in sending notification messages in real time to the Telegram bot, with an average response time of 1 second in each condition. Router and Telegram will detect and send real-time message notifications to administrators if the internet connection status changes from off to active or vice vers

Sistem Informasi Manajemen Layanan Jasa Asosiasi Konstruksi

The rapid development improvement in Indonesia has had an excessive influential impact in the construction service business sector. Thus, it is necessary to have a construction service management information system. The construction association considers that the management information system needs developing in line with the soaring demand for construction. The aim of this research is to develop a service management information system in construction associations for better performance. The method used in this study is a case or field research, with data collection through observation, interviews, and literature study. The results obtained from the development of a construction service management information system can assist in data processing of Membership Cards (KTA) and Business Entity Certificates (SBU). With this system, it can also help process data more effectively and more efficientl

WISATA ALAM DIGITAL DI KOTA KEDIRI MENGGUNAKAN AUGMENTED REALITY

Augmented Reality merupakan salah satu bentuk dari teknologi baru yang menggabungkan antara dunia realita dan dunia maya secara nyata. Augmented Reality berperan penting sebagai media perantara untuk memberikan sejumlah informasi yang lebih mudah dipahami oleh pengguna. Aplikasi bernama NaturalAR merupakan sebuah teknologi Augmented Realty yang dikembangkan untuk media promosi objek wisata alam di Kota Kediri. Tujuannya adalah meningkatkan pengalaman interaktif wisatawan dan memberikan informasi mengenai wisata alam di Kota Kediri. Model 3 Dimensi yang digunakan pada aplikasi NaturalAR berupa sejumlah objek wisata alam. Konsep NaturalAR dapat diterapkan dengan menggunakan media berupa peta sebagai penanda untuk menampilkan Model 3 Dimensi. Pengembangan NaturalAR dibuat dengan menggunakan salah satu metode dari SDLC (System Development Life Cycle) yaitu metode waterfall dan software Unity3D sebagai alat untuk pembuatan aplikasi. Bahasa bahasa pemrograman yang digunakan adalah C#. Dalam melakukan konfigurasinya, NaturalAR menggunakan Vuforia sebagai aset untuk membuat, menyimpan, dan mengatur data yang dibutuhkan pada pengembangan aplikasi Augmeted Reality

IMPLEMENTASI METODE KLASIFIKASI DENGAN ALGORITMA SUPPORT VECTOR MACHINE KERNEL GAUSSIAN RBF UNTUK PREDIKSI PARTISIPASI PEMILU TERHADAP DEMOGRAFI KOTA SURABAYA

Pemilu ialah proses mencari kekosongan kursi pemerintahan melalui pemilihan oleh warga negara indonesia sesuai dengan ketentuan yang telah ditetapkan. Faktor penting dari kesuksesan terselanggaranya Pemilu ialah partisipasi masyarakat. Partisipasi masyarakat dalam ajang politik dapat dijadikan tolak ukur kesuksesan kegiatan Pemilu serta bisa dinilai untuk evaluasi dan kontrol masyarakat terhadap kinerja eksekutif dan legislatif. Faktor lain yang menunjang kesuksesan Pemilu juga dapat dilihat dari pemerataan pembangunan serta pemberdayaan masyarakat. Penelitian bertujuan untuk mengtahui tingkat partispasi masyarakat Kota Surabya dalam upaya pemerataan sosialisasi Pemilu. Metode yang diterapkan pada penelitian yakni metode klasifikasi menggunakan algortma Support Vector Machine dengan kernel RBF. Data yang dipergunakan yakni data demografi berasal dari laman website resmi BPS Kota Surabaya serta data rekapitulasi pemilu 2019 berasal dari laman website resmi KPU Kota Surabaya. Implementasi SVM menggunakan bahasa pemrograman python dengan hasil pengujian mendapatkan nilai akurasi terbaik dari rasio perbandingan training 80% serta testing 20% yakni 67,91%, serta mendapatkan nilai AUC yakni 0,68

Aplikasi IT Support Work Orders Berbasis Web Dalam Rangka Menuju Sidoarjo Smart City

One important aspect in supporting the smart city concept is adequate information technology infrastructure. The Sidoarjo district government has made many innovations in making this happen, one of which is the construction of an intranet and internet network using fiber optics which is centered in the Data Center and managed by the Sidoarjo District Communication and Information Center. As a work unit in the field of ICT infrastructure and security at the Sidoarjo Regency Diskominfo, it is responsible for serving reports from the OPD (Regional Apparatus Organization) regarding intranet and internet network problems in the Sidoarjo regency environment. However, the reporting system used is still very simple and manual. The aim of this research is to design and build a web-based system that functions as a complaint, documenting work, and reporting handling related to intranet and internet network problems at the OPD in Sidoarjo Regency. In collecting data, this research used qualitative methods. Meanwhile, system development uses the System Development Life Cycle (SDLC) method with waterfall model, and uses Unified Modeling Language (UML) and Entity Relationship Diagram (ERD) as system modeling. This application was built using PHP with the CodeIgniter framework and MySQL. The results of this research show that the system makes it easier for related parties to make complaints, document work, and report handling

Unplag Demographic Attribute Selection Model For Prediction Of Election Participation Using Decision Tree

Implementing a democratic general election is expected to produce people's representatives who can channel the people's aspirations. Demographic data is information that discusses a group of people with several related attributes and involves many factors. In this study, we will relate the relationship between the implementation of elections and the condition of demographic data with a benchmark for the form of public participation in the election. By utilizing 2019 election data and Bangkalan Regency demographic data from the Central Statistics Agency (BPS), it is expected to determine the relationship between the two conditions of the dataset on the form of public participation at the polling station (TPS) level. By starting with the Preprocessing step, it implement a classification method with the Decision Tree (DT) algorithm to predict community presence at the polling station level. There are three versions of the dataset that will be used in modeling, namely initial data that has not been selected for attributes (version 1), data that has been chosen using correlation�based attribute selection (version 2), and data that has been selected using chi�square attributes ( version 3). The results show version 1 with a prediction of 81%, followed by version 2 with a prediction of 81%, and the last is version 3 with a prediction of 70%. The detachment model's formation with the selection attribute has a different impact, and the relationship between the election dataset and demographics has a significant effect, as indicated by the prediction results of version 2

UNPLAG INFLUENCE OF DEMOGRAPHICS FOR PREDICTION OF ELECTION PARTICIPATION USING LOGISTIC REGRESSION ALGORITHM

Indonesia is a democratic country for General Elections (Election) which are carried out directly, freely, confidentially, honestly, and fairly. Several stages of the election, among others, begin with compiling a permanent voter list (DPT), determination of polling stations (TPS), and recapitulating election results. Various factors, including the demographic factor, can affect citizen participation in the general election. Demographic data covers Energy, Geographic, Education, Health, Population, Economy, Communication, and Transportation factors. This study tries to combine election data with demographic data taken from the official website of the Central Statistics Agency (BPS) of Mojokerto Regency and data on the results of the 2019 Election calculations taken from the official website of the General Election Commission (KPU) of Mojokerto Regency. Preprocessing steps are data cleaning, data integration, and correlation attributes for a more optimal presentation of the dataset and the distribution of four split datasets (training data and testing data) to find the best results. Implementation of classification method with Logistic Regression (LR) algorithm to predict community participation at the TPS level. From the test results of four split datasets, the highest predictive value was 64.80% in composition 3 with a ratio of 80:20, where 127 data were labeled low, and 291 data were labeled high