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A IMPLEMENTASI TERM FREQUENCY – INVERSE DOCUMENT FREQUENCY (TF-IDF) DAN VECTOR SPACE MODEL (VSM) UNTUK PENCARIAN BERITA BAHASA INDONESIA Wiyanto W; Wowon Priatna; Jumi Saroh Hidayat
Jurnal Pelita Teknologi Vol 14 No 2 (2019): Pelita Teknologi: Jurnal Ilmiah Informatika, Arsitektur dan Lingkungan
Publisher : DPPM Universitas Pelita Bangsa

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Abstract

A search engine that already exists and widely used today can be provide the result of information very much, so it takes time to sort through the information in need. The research with the title "The “implementation term frequency-inverse document frequency (TF-IDF) and vector space model (VSM) to search a news of Indonesian language” have a purpose to develop the method of quick search uses TF-IDF method and vector space model. There are two main processes in the search system of news that are indexing and retrieval. The process of indexing is a process to give assessment to the words on document, the method of assessment in this research uses an assessment of method TF-IDF. The process of retrieval is a process of calculating the slope of the query against the document, the calculation of the similarity using concept vector space model by finding the value of cosine similarity. Based on the analysis and implementation in the build of search system in the news. The quick method of search can be built using vector space model. The system build by this method of vector is able to display a results of search that relevant accordance with the query in the user input. Keywords: term frequency - inverse document frequency, vector space model, search a news of Indonesian language, indexing, retrieval.
Media Pembelajaran 35 Sirah Shahabiyah Berbasis Android Wiyanto Wiyanto
STRING (Satuan Tulisan Riset dan Inovasi Teknologi) Vol 3, No 1 (2018)
Publisher : Universitas Indraprasta PGRI Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (807.087 KB) | DOI: 10.30998/string.v3i1.2726

Abstract

The rapid development in the telecommunications and digital world today makes android-based mobile devices basic needs for many people. The devices have even provided various kinds of learning media for the community. Further, even though the devices are easily to apply as learning media, they have not been a priority for Muslims in improving their knowledge, such as Sirah Shahabiyah (the journey of a female companion of the Prophet Muhammad). Due to the community’s little interests in learning Sirah Shahabiyah, it is necessary to create a learning application that allows the user and the community to easily learn it. The methods used to collect the data of this research are field study, literature review and previous literature review. The system is developed using a prototype system development method consisting of the stages of planning, analysis, design and implementation and is designed using Unified Modeling Language (UML). The result of this research is a learning application in the form of android-based Sirah Shahabiyah, by which the user and the community can easily learn Sirah Sahabiyah, facilitating pleasant and effective learning activities.
Implementasi E-Voting Pilkades Ciantra Berbasis Web Dengan Menggunakan Sensor Sidik Jari Wiyanto Wiyanto
Jurnal SIGMA Vol 12 No 4 (2021): Desember 2021
Publisher : Teknik Informatika, Universitas Pelita Bangsa

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Abstract

Indonesia is a democratic country in which elections for President, Governor, Regent, and Village Heads are still conducted conventionally, where there are still many shortcomings, including the problem of sending ballot logistics, old calculations and inaccurate population data with voters. who do not get their voting rights so that it is less effective in its implementation. To overcome this, especially in the selection of the Village Head, in this study a web-based electronic voting system (e-Voting) was made using a fingerprint sensor that aims to collect voters' data so that voters get their voting rights and their voting rights cannot be used by other citizens. The method used in developing this application is the waterfall method which includes the stages of needs analysis, system design, coding and testing, testing and maintenance. The result of this research is an up to date e-Voting system for counting votes, so as to minimize fraud occurring at the time of village head election. So the conclusion obtained from this study that web-based e-Voting using a fingerprint sensor can produce a quick election winner decision because it does not require tiered and accurate vote counting because citizens who choose according to the data registered. Keywords: e-Voting, fingerprint, Waterfall, PHP, Website
ANALISA TINGKAT KEPUASAN PELANGGAN TERHADAP PELAYANAN PERUSAHAAN OTOBUS XYZ MENGGUNAKAN METODE NAÏVE BAYES Wiyanto W; Tri Ngudi; Asep Saefulloh
Jurnal Pelita Teknologi Vol 15 No 1 (2020): Pelita Teknologi: Jurnal Ilmiah Informatika, Arsitektur dan Lingkungan
Publisher : DPPM Universitas Pelita Bangsa

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Abstract

The inter-city public transport competition between provinces encourages otobus companies to require maximum service quality for customer satisfaction. PO. XYZ is one of the otobus companies that is interested in the people of Central Java and East Java in general to the capital city of Jakarta and surrounding areas, but the level of customer satisfaction for the services provided has not been well predicted. Therefore we need an analysis of the level of satisfaction with the services provided. From these considerations, the authors use the Naïve Bayes method to analyze customer satisfaction with customer satisfaction PO. XYZ. The test uses Rapidminer 9.1, and is implemented into a web-based system to make it easier to determine the level of customer satisfaction. Based on the results of the analysis obtained in the research conducted applying the Naïve Bayes method for prediction of customer satisfaction with services from PO. XYZ It can be concluded that, the Naïve Bayes Method is used by using training data to obtain the probability of each criterion for different classes, then the values ​​of these criteria can be optimized to predict new customer satisfaction, namely by testing the data. From the results of tests that have been done, get a high level of accuracy that is equal to 94.00%. Keywords: Customer Satisfaction, Data Mining, Naïve Bayes, Data Training, Data Testing, Rapidminer.
SISTEM PENDUKUNG KEPUTUSAN PENENTUAN DEPARTEMEN TERBAIK DALAM PROGRAM 5R MENGGUNAKAN METODE AHP Wiyanto W
Jurnal Pelita Teknologi Vol 14 No 1 (2019): Pelita Teknologi: Jurnal Ilmiah Informatika, Arsitektur dan Lingkungan
Publisher : DPPM Universitas Pelita Bangsa

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Abstract

The implementation of a quality management system is inseparable from the work culture of the company concerned. The better the work culture of the organization, the more effective the ISO 9001 quality management system is implemented. As with the health and safety management system or commonly called OHSAS 18001 K3 management, and the ISO 14001 environmental management system it cannot be separated from the application of work culture 5R. If the implementation of the 5R culture goes well, the quality management system, K3 system and environmental management system will certainly have a good effect on its implementation. PT. Kayu Permata has a 5R program which is held regularly every Friday of the week. In the process of determining the best department, it can also be done using a decision support system by calculating the Analytical Hierarchy Process (AHP) method so that selection can be done quickly, precisely and accurately. Keywords: 5R Program,K3 System, AHP Method, ISO.
IMPLEMENTASI SISTEM PENDUKUNG KEPUTUSAN UNTUK MEMPREDIKSI KARYAWAN TELADAN MENGGUNAKAN METODE NAIVE BAYES Wiyanto Wiyanto; Fazri Muharam Anwar
Jurnal SIGMA Vol 10 No 1 (2019): September 2019
Publisher : Teknik Informatika, Universitas Pelita Bangsa

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Abstract

Every company always makes an assessment of its employees, but in this company it is still subjective in assessing it so that research is carried out aimed at predicting exemplary employees by implementing a decision support system to obtain objective predictions of exemplary employees with the Naive Bayes method using the absent, skill, kaizen assessment parameters teamwork and this parameter to get the criteria for exemplary employee status, good employees and poor employees. In this study using 100 training data and a test data was made with the criteria for absent value, skill, kaizen, teamwork by producing a prediction of the status of exemplary employees because it has the highest value with a value of 0.013 while for good employees 0 and poor employees is 0. Support system the decision to predict this exemplary employee using the Naive Bayes algorithm method can make it easier to obtain predictions of exemplary employees. Keywords: Decision Support System, Naive Bayes Method, Web Based
Sentiment Analysis Pemutusan Hubungan Kerja Akibat Pandemi Covid-19 Menggunakan Algoritma NaïveBayes Dan PSO Wiyanto Wiyanto; Zulita Setyaningsih
Jurnal Sisfokom (Sistem Informasi dan Komputer) Vol 10, No 3 (2021): NOVEMBER
Publisher : ISB Atma Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32736/sisfokom.v10i3.1299

Abstract

The Pandemic Covid-19  in Indonesia in 2020 had an impact on Termination of Employment (PHK), this has received various public opinions on social media. At a time when the poverty rate is high and unemployment increases every year, it becomes a factor of public disapproval of Termination of Employment (PHK). It is necessary to classify public opinion into a negative opinion or a positive opinion on this issue. The purpose of this study is to analyze the sentiment towards layoffs to determine negative or positive opinions using the Naïve Bayes algorithm by adding feature selection. The research stages consist of data collection, text preprocessing, feature selection, and application of algorithms. The testing process in this study uses the Rapid Miner application. The test results in this study using the Naive Bayes Algorithm, the accuracy value is 93.57% and for addition to the Naïve Bayes + PSO feature selection, the accuracy value is 93.71%. The best accuracy value in sentiment analysis of layoffs in the covid-19 pandemic is the addition of the PSO feature selection in the Naïve Bayes Algorithm, which is 0.14% better.
Implementasi Sistem Rekam Medis Pasien Menggunakan Pendekatan Customer Relationship Management (CRM) Wiyanto Wiyanto; Fajar Butsianto; Karsito Karsito
Jurnal Sisfokom (Sistem Informasi dan Komputer) Vol 7, No 2 (2018): September
Publisher : ISB Atma Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (893.01 KB) | DOI: 10.32736/sisfokom.v7i2.558

Abstract

Information technology is rapidly developed in this century that impact to various aspects of the organization really need information technology to support the performance and everyday business processes. In health services, information technology is required to process and storage the patient medical records, so that the patient's medical record is well preserved, and competitive advantage can be obtained between patient and polyclinic. The application of Customer Relationship Management (CRM) approach can be developed by implementing information system of medical record history to get new patient and retain existing patient, improving relationship with patient and maintaining patient loyalty as well as supporting the company/organization to provide excellent service to customers in real time through the advantage of information technology. The aims of this research are to understand patient medical record by CRM approach and Unified Modeling Language (UML) for system design, system validation using Forum Group Discussion (FGD), and using software testing Model ISO 9126. The result of this research are Medical Record History Information System and the result of system validation with FGD is 100% accepted, the result of system test using Model ISO 9126 is good with success rate 82,86%, so it can give contribution to polyclinic.
Penerapan Sistem Pakar Berbasis Android Dengan Metode Decision Tree Untuk Memprediksi Postpartum Haemorrhage Pada Wanita Hamil Wiyanto W; Mutiara Ihdina Maulida; Sifa Fauziah
Jurnal Pelita Teknologi Vol 16 No 1 (2021): Pelita Teknologi: Jurnal Ilmiah Informatika, Arsitektur dan Lingkungan
Publisher : DPPM Universitas Pelita Bangsa

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Abstract

Postpartum haemorrhage factor is a contributor to the Maternal Mortality Rate (MMR) 19.7% in the range 12.9 - 28.9 with 480,000 deaths worldwide and 479,000 from developing countries such as Indonesia. In Indonesia the MMR is 305/100,000 Live Births (LB) of the Millennium Development Goals (MDGs) target of only 102/100,000 LB. To achieve the MDGs target, the MMR needs to be lowered, then formulated the problem of how to make an Android-based expert system using the decision tree method so that it can predict Postpartum Haemorrhage from an early age. With the aim of being able to produce an Android-based expert system to predict Postpartum Haemorrhage, so that cases of death caused by Postpartum Haemorrhage receive medical attention from an early age. The expert system makes predictions from logic in an Android-based program using the SDLC structured design system design method and a parallel development model. This logic has gone through the process of classifying a dataset using the Decision Tree method manually and using Rapid Miner. The Decision Tree logic produces three statements of PPH, NO PPH and Potential PPH which are entered using the Java programming language on Android to become an expert system. Pregnant women with predicted PPH and Potential PPH from the expert system can consult a doctor to get the medical personnel they need early to prevent maternal death caused by Postpartum Haemorrhage.
Penerapan Algoritma Naive Bayes Untuk Pemilihan Keluarga Yang Membutuhkan Bantuan Dalam Program Keluarga Harapan (Pkh) (Studi Kasus Di Desa Karang Asih, Cikarang Utara) Wiyanto Wiyanto; Saana Atmaja
Jurnal SIGMA Vol 9 No 1 (2018): Volume 9 Nomor 1 September 2018
Publisher : Teknik Informatika, Universitas Pelita Bangsa

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Abstract

Abstraksi Program keluarga harapan adalah sebuah program pemerintah yg bertujuan untuk meringankan beban keluarga miskin atau hampir miskin dalam hal pangan, dalam implementasinya penerima bantuan ini masih belum optimal dikarenakan masih banyak penerima program keluarga harapan yang belum tepat sasaran. Desa Karang Asih yang terletak di Cikarang Utara, menjadi obyek penelitian ini, dengan penduduk Desa Karang Asih yang terletak di Cikarang Utara dapat dijadikan model, dengan penduduk sebanyak 60.543 jiwa, dimana hampir 9% atau 5.448 jiwa pada kondisi dibawah harapan hidup atau RTSM (Rumah Tangga Sangat Tidak Mampu) yang membutuhkan ulurantangan pemerintah agar anak anak usia sekolah tidak putus sekolah. Data mining dapat dipakai untuk mempermudah mengatasi masalah yang belum optimal maka metode klasifikasi mampu menemukan model yang membedakan konsep atau kelas data dengan tujuan untuk dapat memperkirakan kelas-kelas dari suatu objek yang labelnya tidak diketahui oleh sebab itu, Algoritma Naive Bayes dapat memprediksi peluang dimasa depan berdasarkan pengalaman dimasa sebelumnya. Penelitian ini mengambil data sebanyak 70 data dan sebuah data uji dengan menggunakan 6 kriteria yaitu : Status PKH, Jumlah tanggungan, Kepala rumah tangga, Kondisi rumah, Jumlah penghasilan, dan Status pemilik rumah. Dari hasil pengujian sebanyak 70 sampel menunjukan 3,5% tidak layak menerima program keluarga harapan Kata kunci: Program Keluarga Harapan, Algoritma Naive Bayes