Penerapan Micorosoft Excel Pada Metode Kuantitatif Bisnis Dengan Analytical Hierarchy Process (Proses Analitis Hierarkis)

Pengamatan mendasar tentang sifat manusia, pemikiran analitik, dan pengukuran membawa pada pengembangan suatu model yang berguna untuk memecahkan persoalan secara kuantitatif. Analytical Hierarchy Process (AHP) merupakan suatu model yang luwes yang mampu memberikan kesempatan bagi perorangan atau kelompok untuk membangun gagasan-gagasan dan mendefinisikan persoalan dengan cara membuat asumsi mereka masing-masing dan memperoleh pemecahan yang diinginkan darinya. Proses ini juga memungkinkan orang menguji kepekaan hasilnya terhadap Perubahan informasi. Beberapa keuntungan penggunaan metode AHP adalah kesatuan, kompleksitas, saling ketergantungan, penyusunan hierarki, pengukuran, konsistensi, síntesis, tawar menawar, penilaian dan konsensus serta pengulangan proses. AHP merupakan salah satu tools dalam pemecahan masalah yang bersifat strategis, dalam hal ini digunakan software Microsoft Excel. Kata Kunci : AHP, kuantitatif, hierarki, excelBasic research about human characteristic, especially in analythical thinking and measurement bring to a model that usefull for solving quatitativ problems. Analytical Heararchy Proces (AHP) is a model that flexibly can give the opportunity for individual or community to build the idea and define a problem with their assumption. This process also suitable for someone to give a test in regards to sensitivity of information change. Some benefits of AHP are: integrity, complexity, inter dependency, hierarchy position of information, consistency, synthesis, bargaining, checking and consensus, and process iterative. AHP is a tool for solving strategic problem that using Microsoft Excel in this paper

Prototype Mesin Presensi Berbasis E-mail Pada SMP Assyairiyah Attahiriyah Jakarta

This research discusses the design of E-mail-based Presence Machine Prototype in Assyairiyah Attahiriyah Junior High School Jakarta which aims to information for parents and schools who have difficulty monitoring student attendance at school, thus helping to manage student presence data more effectively and efficiently. The system development method used is the Prototype method. Data obtained by conducting interviews and direct observation of spaciousness to get right data as needed. The results of this research are hardware and software, in the process of making hardware using NodeMCU, LCD 16x2, Buzzer and Fingerprint Sensor and the software uses the PHP programming language with MySql database. The presence of the Presence Machine Prototype becomes a means for parents and schools to process and get information related to student attendance in schools effectively and efficiently.   Keywords: Presence Machine, Presence, Prototype, NodeMCU.   Abstrak   Penelitian ini membahas perancangan Prototype Mesin Presensi Berbasis E-mail yang bertujuan sebagai sarana informasi bagi orang tua maupun pihak sekolah yang kesulitan memonitoring kehadiran siswa disekolah, sehingga membantu pengelolaan data presensi siswa menjadi lebih efektif dan efisien. Metode pengembangan sistem yang digunakan adalah metode prototype. Data diperoleh dengan melakukan wawancara serta observasi langsung kelapangan guna mendapat data yang akurat sesuai yang dibutuhkan.  Hasil penelitian ini berupa hardware dan software, dalam proses pembuatan hardware menggunakan NodeMCU, LCD 16x2, Buzzer dan Sensor Fingerprint serta softwarenya menggunakan bahasa pemrograman PHP dengan database MySql. Adanya Prototype Mesin Presensi ini menjadi sarana bagi orang tua dan sekolah untuk mengolah dan mendapatkan informasi terkait presensi siswa disekolah dengan efektif dan efisien.   Kata Kunci: Mesin Presensi, Presensi, Prototype, NodeMCU

Learning Vector Quantization, Hebbian Learning, and Self-Organizing Map for Classification

Deep Learning has been rapidly developed. Almost all proposed methods already have very high accuracy. Most of these methods still use techniques from the past with some modifications to adapt to existing modules. Sometimes it is necessary to understand past methods to produce new methods. Therefore, this research examines past models that have the potential to improve the performance of existing deep learning models. The methods to be examined include Learning Vector Quantization (LVQ), Hebbian learning, and Self-Organizing Map (SOM). The iris dataset available on Scikit-learn (SKlearn) is used here for testing in cases of supervised learning and unsupervised learning (especially SOM). The results show that LVQ has a good accuracy of 93%, while Hebbian learning has an accuracy of 56%. SOM fluctuates between 88% and 93%. Although the accuracy of SOM does not exceed LVQ, this model does not require labels in its training process

Sistem Informasi Praktek Kerja Industri pada SMK Taruna Bangsa Bekasi

Industry Work Practice or commonly called the Job Training (PKL) is an activity that mustbe followed by every vocational students during school as a form of implementation of science or asan addition to an insight into the working world they will face in the future. Most vocational schoolhave more than one competence program and consists of several classes. Of course, there is thetask of separate schools in distributing each student to carry out industry work practice as a whole.Related division in charge is also required to present the data and information needs in order toreduce confusion as in the submission process. Information system of industry work practice neededto improve the performance of the school in distributing and processing data and information. Thissystem is developed using waterfall method. This method provides an approach of software workflowsequentially form analyzing, designing, coding, testing and supporting. Result of this system cancertainly help the activities of industrial work practice for each data and information are well integratedto facilitate each student to get information and the school process data from the process submission,industrial work practice until the report

Prediksi Kelas Jamak dengan Deep Learning Berbasis Graphics Processing Units

For the first time, machine learning did the classical classification process using two classes (bi-class) such as class -1 and class +1, 0 and 1, or the form of categories such as true and false. Famous methods used are Artificial Neural Networks (ANN) and Support Vector Machine (SVM). The current development was a problem with more than two classes, known as multi-class classes. For SVM sometimes the plural classes are overcome by doing a gradual process like a decision tree (DT) method. Meanwhile, ANN has experienced rapid development and is currently being developed with a large number of layers with the new activation functions, i.e. the rectified linear units (ReLu), and the probabilistic-based activation, i.e. softmax, including its optimizer methods (adam, sgd, and others). Then the term changed to Deep Learning (DL). This study aimed to compare two well-known methods (DL and SVM) in classifying multiple classes. The number of DL layers was six with the neuron composition are 128, 64, 32, 8, 4, and 3, while SVM uses a radial kernel base function with gamma and c respectively 0.7 and 5. Besides, this study intends to compare the use of the Graphics Processing Unit (GPU) available on Google Interactive Notebook (Google Colab), an online Python language programming application. The results showed that DL accuracy outperformed SVM but required large computational resources, with the accuracy for DL and SVM are 99% and 98%, respectively. However, the use of the GPU can overcome these problems and is proven to increase the speed of the process as much as 47 times. Keywords: Artificial Neural Networks, Graphics Processing Unit, Google Interactive Notebook, Rectified Linear units, Support Vector Machine. Abstrak Di awal perkembangannya mesin pembelajaran melakukan proses klasikfikasi menggunakan dua kelas (bi-class) misalnya kelas -1 dan kelas +1, 0 dan 1, atau bentuk kategori seperti benar dan salah. Metode terkenal yang digunakan adalah Jaringan Syaraf Tiruan (JST) dan Support Vector Machine (SVM). Perkembangan selanjutnya adalah problem dengan kelas yang lebih dari dua kelas, dikenal dengan istilah kelas jamak (multi-class). Untuk SVM terkadang kelas jamak diatasi dengan melakukan proses berjenjang mirip pohon keputusan (decision tree). Sementara itu JST telah mengalami perkembangan yang pesat dan saat ini sudah dikembangkan dengan jumlah layer yang banyak disertai dengan fungsi-fungsi aktivasi terkini seperti rectified linear unit (ReLu), dan softmax yang berbasis probabilistik, termasuk juga metode-metode optimizernya (adam, sgd, dan lain-lain). Kemudian istilahnya berubah menjadi Deep Learning (DL). Penelitian ini mencoba membandingkan dua metode terkenal (DL dan SVM) dalam melakukan klasifikasi kelas jamak. Jumlah layer DL sebanyak enam dengan masing-masing neuron sebesar 128, 64, 32, 8, 4, dan 3, sementara SVM menggunakan kernel radial basis function dengan gamma dan c berturut-turut 0.7 dan 5. Selain itu penelitian ini bermaksud membandingkan penggunaan Graphics Processing Unit (GPU) yang tersedia di Google Interactive Notebook (Google Colab), sebuah aplikasi online pemrograman bahasa Python. Hasil penelitian menunjukan akurasi DL unggul tipis dibanding SVM namun memerlukan sumber daya komputasi yang besar masing-masing dengan akurasi 99% dan 98%. Namun penggunaan GPU mampu mengatasi permasalahan tersebut dan terbukti meningkatkan kecepatan proses sebanyak 47 kali. Kata kunci: Jaringan Syaraf Tiruan, Graphics Processing Unit, Google Interactive Notebook, Rectified Linear units, Support Vector Machine

Animasi Interaktif Pengenalan Flora Dan Fauna Di Indonesia Pada SD 03 Cakung Jakarta Timur

Abstract   In the city, elementary-school children are less familiar with flora and fauna. An animation application was proposed to assist them in learning flora and fauna as well as to help teachers and parents in teaching elementary-school children to understand the flora and fauna. Data were collected from various sources and the software to build such applications was prepared, i.e. Adobe Flash. To develop the application, a life cycle method was used, including: concept, design, material collecting, assembly, testing, and distribution. Testing results showed that the proposed application can be used as an additional learning material and help students to understand a subject more easily. In addition, teaching flora and fauna for children in Indonesia needs a strategy through additional facility in the class. To attract attention, it is necessary to create a class situation that makes children motivated to learn as well as the use of aids or media when the teacher is teaching. Also, the rapid advances in technology, especially information technology, encourage people to develop learning media that can be used anytime and anywhere outside the classroom. The proposed application was called Interactive Animation of Introduction to Flora and Fauna in Indonesia, and was implemented in SD 03 Cakung, East Jakarta, Indonesia.   Keywords: Interactive animation, Flora, Fauna, Instructional Media.   Abstrak   Sekarang ini, anak SD kurang begitu mengenal flora dan fauna. Animasi ini diharapakan mampu membantu mereka dalam mencari informasi flora dan fauna. Animasi ini dapat membantu masyarakat terutama orang tua dan guru SD bisa mengajarkan kepada anak-anak mereka untuk lebih mengenal flora dan fauna. Pengumpulan data dari informasi flora dan fauna dari berbagai sumber perlu dilakukan, serta menyiapkan software yang dibutuhkan untuk membangun aplikasi. Langkah berikutnya yaitu membangun aplikasi dengan adobe flash sebagai media pembuatannya. Dalam pembuatan animasi ini digunakan metode multimedia development life cycle, terdapat tahapan-tahapan meliputi concept, design, material collecting, assembly, testing, dan distribution dalam pembentukan kerangka pemikiran dalam multimedia development life cycle. Berdasarkan hasil uji aplikasi pada siswa Selain itu multimedia pembelajaran ini juga dapat membantu guru menyampaikan materi pengenalan hewan dengan lebih mudah. Mempelajari flora dan fauna di Indonesia perlu adanya cara atau strategi yang dapat memudahkan anak-anak dalam belajar. Untuk menarik perhatian, perlu diciptakan situasi kelas yang membuat anak-anak termotivasi untuk belajar. Salah satu caranya adalah dengan penggunaan alat bantu mengajar atau media ketika guru mengajar. Maka hasil dari penelitiran ini adalah sebuah program “Animasi Interaktif Pengenalan Flora Dan Fauna Di Indonesia Pada SD 03 Cakung Jakarta TImur Dengan Metode Multimedia Development Life Cycle”.   Kata kunci: Animasi Interaktif, Flora, Fauna, Media Pembelajaran

Efektifitas Pembatasan Sosial Berskala Besar (PSBB) di Kota Bekasi Dalam Mengatasi COVID-19 dengan Model Susceptible-Infected-Recovered (SIR)

To overcome the COVID-19 outbreak, the government did not carry out the lockdown policy (regional quarantine policy) but implemented the Large-Scale Social Restrictions (PSBB) policy. Starting from the capital city of Jakarta, this policy was followed by other regions. Bekasi City as a buffer zone of Jakarta immediately implemented the PSBB policy since this area is close to Jakarta and is feared to be affected by the Jakarta region which is a red zone with almost half of Indonesian COVID-19 cases are in the Jakarta area. Many people do not agree with the PSBB, but in order to keep the economic growth as well as to overcome the outbreak, the government does not adopt a regional quarantine policy. To determine the effectiveness of PSBB in the city of Bekasi, this study tried to use the Susceptible-Infected-Recovered (SIR) model to measure the spread rate of COVID-19. The results showed a decrease in the number of infected cases with beta and gamma were 0.071 and 0.05, respectively, and the epidemic was predicted to end in June 2020. Keywords: coronavirus, epidemic, pandemic, regional quarantine policy, Bekasi City   Abstrak Dalam mengatasi wabah COVID-19, pemerintah tidak melakukan karantina wilayah (lock down) tetapi menggunakan kebijakan Pembatasan Sosial Berskala Besar (PSBB). Dimulai dari ibukota Jakarta, kebijakan ini diikuti oleh wilayah lainnya. Kota Bekasi sebagai wilayah penyangga Jakarta segera menerapkan kebijakan PSBB mengingat wilayah ini berdekatan dengan Jakarta dan dikhawatirkan terpengaruh dengan kota Jakarta yang merupakan zona merah dengan hampir separuh kasus COVID-19 ada di wilayah Jakarta. Banyak pihak yang mendukung dan juga kurang setuju dengan PSBB, namun agar perekonomian tetap berjalan dan wabah dapat diatasi, pemerintah tidak mengambil kebijakan karantina wilayah. Untuk mengetahui efektifitas PSBB di kota Bekasi, penelitian ini mencoba menggunakan model Susceptible-Infected-Recoverd (SIR) untuk mengukur laju penyebaran COVID-19. Hasilnya menunjukan adanya laju penurunan kasus terinfeksi dengan beta dan gamma beruturut-turut sebesar 0,071 dan 0,05 dan diprediksi akan berakhir di bulan Juni 2020. Kata kunci: virus corona, epidemik, pandemik, karantina wilayah, Bekasi Cit

Web-Based Mail Search Using the Levenshtein Distance Algorithm

The use of information technology in filing letters has been widely applied, especially in government institutions. In the Administrative Affairs of the Police Information Technology Bureau, the archiving of incoming and outgoing letters is still done manually, by utilizing records in a large agenda book and stored in a large folder. The absence of a system capable of assisting mail processing causes work to be inefficient, especially in terms of searching for letters. The purpose of this research is to produce a website that can help search letters by applying the Levenshtein Distance Algorithm. The design begins with needs analysis, design, implementation, verification (system testing), operation and maintenance. A website that can search letters by applying the Levenshtein Distance Algorithm was generated. This website is very helpful in the process of searching for letters to the Administrative Affairs of the Police Information Technology Bureau

Algoritma Hungarian Dalam Menentukan Pembagian Tugas Sebagai Manajemen Jurnal Pada Open Journal System (OJS)

Abstrak: Saat ini penerapan dan penggunaan open journal system (OJS) di berbagai perguruan tinggi untuk mendukung peningkatan publikasi ilmiah semakin gencar dilakukan. Aplikasi bersifat Open source ini digunakan dalam rangka membantu pengelola jurnal ilmiah dalam penerbitan online. Pengelolaan jurnal ilmiah yang sering disebut manajemen jurnal memiliki sepuluh (10) peran/tugas yang perlu disediakan. Dalam penelitian ini hanya akan dibahas tujuh (7) peran yang penting antara lain: penulis, editor layout, proofreader, manager jurnal, reviewer, editor dan copyeditor. Metode penelitian yang digunakan adalah metode penugasan dengan algoritma Hungarian. Penelitian ini menggunakan software Excel QM V5.2 dan QM for Windows V5 dan hasilnya adalah dua solusi optimal berupa formasi penugasan dengan total waktu proses yang sama (24 jam). Walaupun formasi penugasan yang diperoleh berbeda, ada beberapa karyawan yang memiliki peran yang sama dalam dua formasi penugasan yang dihasilkan.   Kata kunci: algoritma hungarian, excel QM V5.2, open journal system, manajemen jurnal, QM for Windows V5   Abstract: Many universities have implemented Open journal system (OJS) to increase the publication performance. Such an Open source system can help journal staff in online publishing. There are ten tasks in journal management, but in this paper seven tasks are discussed, namely: writer, layout editor, proofreader, journal manager, reviewer, editor, and copy-editor. Hungarian algorithm was used as a task method of research methodology. This research used two applications (Excel QM and QM for Windows V5) and created two different task formations with the same time allocation (24 hours). Although different formations results, some staffs had the same task for both formation.   Keywords: excel QM V5.2, hungarian algorithm, journal management, open journal system, QM for Windows V

Sistem Informasi Panduan Trayek Angkutan Umum Berbasis Mobile Smartphone Pada Dinas Perhubungan Jakarta

Public transport is an integral part of the city's transportation system and is a component whose role is very significant, because the condition of the poor public transport system will cause a decline in the effectiveness and efficiency of public transport itself. Smartphone users or the public can use and take advantage of its mobile devices to be able to search for information about public transportation route and location of the place to be searched. Mobile applications natively public transportation route system is based on the PhoneGap framework and use GoogleMaps asan interface map, the language he uses is HTML5, Javascript, JQuery Mobile. Algorithm method used is the method dijstra, dijkstra method can be used to determine the fastest path from a node. These properties can be applied to determine the trajectory path of nearby public transportation.The accuracy of the reading position ( Location Base Services ) on the map approximately 97 % of the radius of a meter scale map. The accuracy depends on GPS devices and mobile handsets speed internet bandwidth