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ANALYTICAL HIERARCHY PROCESS DALAM PEMILIHAN KARYAWAN TERBAIK BERDASARKAN KUALITAS SUMBER DAYA MANUSIA
Get PDFContact Center PT. Bank HSBC Indonesia yang bergerak dalam bidang layanan informasi penggunaan kartu kredit, debit serta penjualan melalui telepon. Dimana saat ini Contact Center PT. Bank HSBC Indonesia khususnya dalam menentukan karyawan terbaik hanya menggunakan keputusan pimpinan yang dilihat dari hasil produktifitas saja tanpa mempertimbangkan yang lain. maka dari itu penulis ingin membangun sebuah sistem pendukung keputusan untuk pemilihan karyawan terbaik. Metode yang digunakan oleh penulis adalah Analytic Hierarchy Process (AHP) yang dapat membantu dalam mengambil keputusan secara tepat dan akurat. Hasil akhir yang diperoleh adalah terciptanya sistem pendukung keputusan pemilihan karyawan terbaik pada Contact Center PT. Bank HSBC Indonesia secara objektif. Yaitu dengan perhitungan menggunakan kriteria-kriteria seperti penjualan, kehadiran, kualitas pelayanan, tanggung jawab dan disiplin. Sistem ini dapat membantu bagian SDM dalam melakukan pemilihan karyawan terbaik dan karyawan dengan predikat terbaik memperoleh sertifikat penghargaan karyawan terbaik. Sistem pendukung keputusan pemilihan karyawan terbaik ini dapat dikembangkan seiring perkembangan kebutuhan penggunaan sehingga dapat meningkatkan kinerja sistem
PELATIHAN PEMBUATAN GOOGLE FORM BAGI JARINGAN PEMUDA DAN REMAJA MASJID INDONESIA (JPRMI)
Get PDFPandemi yang tak kunjung selesai memaksa setiap orang untuk senantiasa menjaga jarak antara individu yang satu dengan individu yang lain nya, hal ini amat sangat menyulitkan bagi remaja JPRMI dalam mengumpulkan informasi. Dengan adanya pelatihan peningkatkan keahlian dan keterampilan bagi para remaja JPRMI pada saat seperti diharapkan dapat membantu remaja JPRMI dalam mengumpulkan informasi yang mudah dengan cara yang efisien. Saat ini telah ada banyak software atau aplikasi yang dapat digunakan untuk mengumpulkan informasi tanpa harus mengumpulkan dan datang ke tempat pendata. Google sebagai perusahaan teknologi yang dikenal melalui produk-produknya menyediakan layanan informasi yang dapat diakses secara gratis oleh para penggunanya. Salah satu nya yaitu Google Form. Oleh karena itu, pemuda dan remaja JPRMI perlu memanfaatkan Google Form untuk membantu merencanakan acara, membuat kuisioner, form registrasi kegiatan pemuda dan remaja JPRMI secara online atau mengumpulkan informasi yang mudah dengan cara yang efisien. Pada kesempatan kali ini, Dosen-Dosen dari Universitas Nusa Mandiri memberikan pendampingan kepada Jaringan Pemuda Dan Remaja Masjid Indonesia (JPRMI) dalam penggunaan Google Form sebagai pendukung kegiatan yang dilakukan para remaja JPRMI. Hasil dari kegiatan pengabdian ini meningkatkan kemampuan remaja JPRMI dalam hal penggunaan google form. Sehingga hal tersbut memudahkan kegiatan mereka.
 
APPLICATION OF MACHINE LEARNING FOR BITCOIN EXCHANGE RATE PREDICTION AGAINST US DOLLAR
Get PDFPredicting a currency Exchange rate and performing analysis is an action to try to determine the price valuation of a currency or other financial instrument traded on an exchange platform. Bitcoin is a consensus network that enables new payment systems and fully digital money. Bitcoin is the first decentralized peer to peer payment network that is fully controlled by its users without any central authority or intermediary. From the user's point of view, Bitcoin is like cash in the internet world. Bitcoin can also be viewed as the most prominent triple bookkeeping system in existence today. The change in Bitcoin's behavior against the US dollar is influenced by many factors. Basic or economic factors that may be affected include inflation rates and money supply. In this study, data was collected by obtaining all data through the API provided by binance.com and labeled with the specified attribute. The modeling is done by using the rapidminer application. The process begins by taking training data that has been provided previously. The next stage is the data testing process, all operators that have been previously determined are connected and tested using the Linear Regression operator. The purpose of testing this data is to predict stock prices from the testing data that has been made by the Split Data operator, which is 19% of the total data that has been prepared
PENINGKATAN MUTU KUALITAS PENGURUS YAYASAN KOPIA RAYA INSANI DALAM PROSES ADMINISTRASI DENGAN PELATIHAN MICROSOFT OFFICE
Get PDFSalah satu manfaat dalam kegiatan pengabdian kepada masyarakat adalah berupaya dalam meningkatkan mutu atau kualitas sumber daya manusia dalam aspek pengetahuan, peningkatan wawasan serta keterampilan yang dimiliki dan diimplementasikan oleh para akademisi perguruan tinggi. Hal ini pun sebagai salah satu perwujudan tridharma yang ikut aktif dalam mewujudkan kepedulian terhadap kesejahteraan masyarakat luas. Adapun pada impelementasinya, kemajuan teknologi informasi merupakan salah satu sumber yang berperan penting dalam beberapa kegiatan pengabdian masyarakat, diantaranya teknologi berperan dalam menunjang bidang ekonomi, bidang pendidikan ataupun bidang lainnya. Selain untuk menunjang kegiatan tersebut, teknologi informasi juga dapat menunjang dalam menyelesaikan persoalan administrasi. Adapun kegiatan Pengabdian kepada masyarakat ini secara khusus ditujukan kepada pengurus Yayasan Kopia Raya Insani, hal ini dilakukan karena adanya keterbatasan wawasan terkait penggunaan sarana dalam proses administrasi. Pada dasarnya, terdapat beberapa aplikasi yang dapat digunakan dalam proses administrasi, salah satu perangkat lunak yang dapat digunakan untuk menunjang persoalan tersebut adalah Microsoft Word, Microsoft Excel dan Microsoft Power Point. Namun banyak fitur yang yang dimiliki perangkat lunak Microsoft Word, Microsoft Excel dan Microsoft Power Point yang masih kurang familiar di sebagian pengguna, terutama oleh para pengurus Yayasan Kopia Raya Insani. Adapun solusi yang akan kami berikan yaitu dengan diadakannya pelatihan penggunaan Microsoft Office sebagai sarana penunjang dalam proses administrasi pengurus Yayasan Kopia Raya Insani dengan tujuan para pengurus dapat mengerti tata kelola yang lebih baik dalam proses administrasi dengan memanfaatkan beberapa perangkat lunak yang tersedia dalam Microsoft Office
IDENTIFICATION OF BACTERIAL SPOT DISEASES ON PAPRIKA LEAVES USING CNN AND TRANSFER LEARNING
Get PDFPaprika, often called bell peppers, is a plant with the Latin name Capsicum annuum var. gross. Paprika in Indonesia has a high selling value, so the opportunity for cultivating the paprika plant itself is enormous. However, the cultivation of this plant cannot be separated from the threat of disease that can affect the yield of paprika. Bacterial spot is one of them, and it is a disease that is very dangerous for paprika plants because the disease infects all parts of the plant. In this case, early detection is needed to carry out appropriate treatment to minimize the effects caused by bacterial spots. Detection of bacterial spots on paprika can be done by direct observation or conducting laboratory tests, but this requires people who have the appropriate knowledge and experience. Based on the above problems, the identification system can be an option in identifying bacterial spot disease in paprika. This research chose the Convolutional Neural Network (CNN) algorithm in the identification system. Because CNN is one of the algorithms that can receive output in the form of an image which is very suitable for the case of bacterial spots on peppers, this research dataset is divided into healthy leaves and leaves infected with bacterial spots. In this study, the implementation of CNN with transfer learning obtained results from a test accuracy of 90%, training accuracy 97% with a loss of 8.5%, validation accuracy of 97.5% with a loss of 6.9%
SENTIMENT ANALYSIS ON TWITTER SOCIAL MEDIA ACCOUNTS: SHOPEECARE USING NAIVE BAYES, ADABOOST, AND SVM(EVOLUTION) ALGORITHM COMPARATIVE METHODS
No full textThe growth of Indonesian e-commerce is increasing along with the growth of internet use in Indonesia. In 2015, there were 92 million internet users in Indonesia. One of the popular online shopping platforms in Indonesia is Shopee. One of the services to see the response and reporting of problems from users, including shopeecare. shopeecare was created on the social media platform twitter to help facilitate communication between customers. with the amount of customer enthusiasm in tweeting and Retweeting existing content, we decided to research about Sentiment analysis on twitter social media accounts: Shopeecare uses the SMOTE NB, ADboost, and SVM comparison methods. From the data, the comparison results from the test experiments used the Smote + Naive Bayes, Smote + Naive Bayes + Adaboost, and Smote + SVM models. It is known that the Accuracy, Precision, AUC values of the Smote + SVM algorithm are higher than other algorithms, namely Accuracy 76.24%, Precision 75.65%, AUC 0.822. From the results of the algorithm comparison, it shows that the algorithm in determining the sentiment of the complaint and not complaint analysis is better than other algorithms
EARLY WARNING SYSTEM FOR FLOOD IN GUNUNGSARI DISTRICT BASED ON IOT WITH TELEGRAM BOT AS A WARNING MESSAGE SENDER
Get PDFEntering the rainy season with a high level of rainfall will have an impact on vulnerability to floods that will hit a number of areas in various parts of Indonesia. As is often the case in the Gunungsari Sub-district, West Lombok Regency, heavy rains that come early with high intensity for several days often occur, which causes flood disasters and the absence of an automatic system or tool that can detect flooding in the area so that people around the difficulty of detecting floods that come early and cause many people to lose their homes and property due to the flood disaster. The purpose of this study is to provide information related to signs before a flood disaster using the Raspberry Pi 4 as the main tool and the Hc-SR04 ultrasonic sensor as a tool for measuring the distance of an object, where this system can monitor the water level of the river, then disseminate information. related to the water level periodically via Telegram. The test results of the detection sensor system show that the level of accuracy in reading the water level with an average error of 0.48%, indicates that this IoT system has good accuracy.
 
COMPARISON OF PORTERS STEMMING ALGORITHM AND NAZIEF & ADRIANI'S STEMMING ALGORITHM IN DETERMINING INDONESIAN LANGUAGE LEARNING MODULES
Get PDFOne of the methods used to improve the performance of text summarization to obtain complete information in a learning module is by transforming the words in a module into basic words or, in other words, through a steaming process. The steaming process in Indonesian language texts is more complicated/complex because there are word affixes that must be removed to get the root word (root word) of a word, so this research will compare the two stemming algorithms of Porter and stemming Nazief & Adriani in the learning module at Mataram University of Technology. The test results of the Nazief & Adriani stemming algorithm on an average process duration of 51.8 seconds with an average accuracy of 74.175%. In Porter's Algorithm, the average processing time is 16.875 seconds, with an accuracy of 73.225%
COLLABORATION OF ANALYTIC HIERARCHY PROCESS AND SIMPLE ADDITIVE WEIGHTING METHOD TO DETERMINE EMPLOYEE SALARY BONUS
Get PDFImproving the quality of employee performance, a company needs motivation in the form of giving employee bonuses. Bonuses are additional wages given to employees for achieving the best work that has been done in a period. The environmental service of Sragen has implemented a bonus for its employees, however, the bonus has not been assessed based on supporting criteria so that it is not considered objective. This research was made to be able to help determine employee bonuses more objectively by using several criteria that became the basis for giving bonuses. The criteria used are cooperation, behavior, attendance, performance, service and adaptation. The Analytic Hierarchy Process (AHP) and Simple Additive Weighting (SAW) methods are used in this study so that the bonus calculation can be more objective. The results of the weights from the AHP will be used as a reference for the calculation of SAW. The decision support system is developed using Java programming. The system created can produce recommendations for the amount of bonuses received by each employee.
Keywords: AHP method, SAW method, Employee Salary Bonus
Intisari— Dalam meningkatkan kualitas kinerja karyawan suatu perusahaan atau instansi perlu adanya motivasi berupa pemberian bonus karyawan. Bonus upah atau gaji merupakan upah tambahan yang diberikan kepada karyawan atas pencapaian pekerjaan terbaik yang telah dilakukan dalam suatu periode. Dinas Lingkungan Hidup Sragen sudah menerapkan pemberian bonus bagi karyawannya, hanya saja pemberian bonus tersebut belum menggunakan penilaian berdasarkan kriteria-kriteria penunjang sehingga dirasa belum obyektif. Kriteria yang digunakan dalam penelitian ini antara lain kerjasama, perilaku, absensi, kinerja, pelayanan dan adaptasi. Penelitian ini dibuat dengan tujuan untuk dapat membantu menentukan bonus karyawan dengan lebih obyektif yaitu menggunakan beberapa kriteria yang menjadi dasar pemberian bonus. Metode Analytic Hierarchy Process (AHP) dan Simple Additive Weighting (SAW) digunakan dalam penelitian ini agar perhitungan bonus dapat lebih obyektif. Hasil bobot dari AHP akan dijadikan acuan untuk perhitungan SAW. Sistem pendukung keputusan dibuat menggunakan pemrograman Java. Sistem yang dibuat dapat menghasilkan rekomendasi besaran bonus gaji yang diterima masing-masing karyawan.
Kata Kunci: metode AHP, metode SAW, bonus karyawan
APPLICATION OF DECISION TREE AND NAIVE BAYES ON STUDENT PERFORMANCE DATASET
Get PDFStudent performance is the ability of students to deal with the entire academic series taken during school. Student performance produces two labels, namely successful and unsuccessful students. Successful students can graduate with excellent, excellent, and suitable performance labels. At the same time, students who have a label on average are students who get poor performance. Measurement of student performance is needed for every educational institution to take strategic steps to improve student performance. This study aimed to obtain a data mining method that worked well on student performance datasets. In this study, student performance datasets were processed, which had 11 indicators with one result label. Student performance datasets are processed using data mining methods, namely decision tree and nave Bayes, while the tool used for dataset processing is WEKA. The research results from processing student performance datasets obtained that the accuracy value for the decision tree method was 94.3132%, and the accuracy produced by the naive Bayes method was 84.8052%