Claim Missing Document
Check
Articles

Found 39 Documents
Search

PERANCANGAN UI/UX APLIKASI DESTINASI WISATA BERBASIS WEB MENGGUNAKAN METODE HUMAN CENTERED DESIGN Nurdiana Handayani; Fandhilah Fandhilah; Hendra Mayatopani
JOISIE (Journal Of Information Systems And Informatics Engineering) Vol 7 No 1 (2023)
Publisher : Institut Bisnis dan Teknologi Pelita Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35145/joisie.v7i1.2907

Abstract

Muhammadiyah Travel sebagai penyedia jasa destinasi wisata yang masih menggunakan media sosial dalam mempromosikan paket-paket wisata dan layanan lainnya. Seiring dengan perkembangan teknologi yang banyak memberikan kemudahan untuk mendapatkan informasi dengan cepat dan mudah dari mana saja dan kapan saja. Muhammadiyah Travel membutuhkan perancangan aplikasi dengan desain user interface dan user experience yang dapat membantu kebutuhan pengguna sehingga dapat memberikan kemudahan pengguna dalam memahami aplikasi. Penelitian ini menggunakan metode human centered design, melakukan pendekatan design dengan proses informasi dari pengguna (inspiration, ideation dan implementation), yang fokus pada pengguna aplikasi dan kebutuhannya. Hasil penelitian ini menghasilkan desain atau mockup aplikasi berbasis web yang dapat diterima dan memenuhi kebutuhan pengguna. Pada hasil pengujian desain diperoleh nilai efektifitas sebesar 92% dan nilai efisiensi 15,25 detik hal ini menunjukkan bahwa desain tampilan interface yang dihasilkan adalah tampilan sederhana yang mudah dimengerti oleh pengguna serta desain efisien yang dapat diterima oleh pengguna.
CLASSIFICATION OF VEHICLE TYPES USING BACKPROPAGATION NEURAL NETWORKS WITH METRIC AND ECCENTRICITY PARAMETERS Hendra Mayatopani; Rohmat Indra Borman; Wahyu Tisno Atmojo; Arisantoso Arisantoso
Jurnal Riset Informatika Vol. 4 No. 1 (2021): December 2021
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (758.834 KB) | DOI: 10.34288/jri.v4i1.139

Abstract

One of the efforts to break down traffic jams is to establish special lanes that can be passed by two, four, or more wheeled vehicles. By being able to recognize the type of vehicle can reduce congestion. Citran based vehicle classification helps in providing information about the vehicle type. This study aims to classify the type of vehicle using a backpropagation neural network algorithm. The vehicle image can be recognized based on its shape, then the backpropagation neural network algorithm will be supported by metric and eccentricity parameters to perform feature extraction. Then from the results of feature extraction with metric parameters and eccentricity, the object will be classified using a backpropagation neural network algorithm. The test results show an accuracy of 87.5%. This shows the algorithm can perform classification well.
Analisis Sentiment Review Kepuasan Pengguna Wi-Fi First Media di Twitter March Vircan Karuna; Hendra Mayatopani
Journal of Management and Bussines (JOMB) Vol 5 No 2 (2023): Journal of Management and Bussines (JOMB)
Publisher : IPM2KPE

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31539/jomb.v5i2.8301

Abstract

Technology in the current era has developed greatly in society. The internet helps people search for information or communicate with each other. There is one internet provider that provides internet services, namely "First Media". This provider also has a service account on Twitter with the name @FirstMediaCares which aims to provide feedback from customers who use services at this provider. So the aim of this research is to be able to analyze sentiment in feedback or tweets provided by customers or consumers. There was 845 data pulled from the account from August to September. Then it is processed again to become 310 valid data that can be used for analysis. The algorithm used is Naïve Bayes, which is a classification method that can determine probability based on past experience. Keywords: User Satisfaction, Review Sentiment, Wi-Fi First Media
Multi-criteria decision making using weighted aggregated sum product assessment in corn seed selection system Hendra Mayatopani
Jurnal Teknik Informatika C.I.T Medicom Vol 15 No 1 (2023): March: Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/cit.Vol15.2023.302.pp21-31

Abstract

Corn is one of the seven national strategic commodities developed by the government. The role of corn in the national industry is so great that the process of cross-breeding is often carried out in order to obtain superior varieties. Given the important role of corn in Indonesian agriculture, it is normal for corn seeds to be scattered in the market. For this reason, corn farmers or someone who wants to grow corn must be careful to choose the right corn seeds for their needs and what they want. This study aims to implement the Multi-Criteria Decision Making (MCDM) approach with Weighted Aggregated Sum Product Assessment (WASPAS) on a corn seed selection decision support system, in order to obtain the best alternative according to the needs of several alternatives and certain criteria. The WASPAS method is able to solve multi-criteria problems by optimizing the assessment for selecting the highest and lowest values to get the best alternative. The DSS developed is based on a website, with the main features including managing criteria and weight data, alternative data, conducting alternative assessments, calculating processes using the WASPAS method and displaying the best alternative in the form of ranking. In addition, the developed system produces valid WASPAS method calculations, because the results are in accordance with manual calculations. Based on the tests carried out with the black-box testing approach, it shows that the system built has been running well.
ANALISIS SISTEM PENJUALAN DAN CUSTOMER RELATIONSHIP MANAGEMENT (CRM) PADA APLIKASI SHOPEE Damayanti, Helen Agustin Puspa; Kurniawan, Heri; Mayatopani, Hendra
IDEALIS : InDonEsiA journaL Information System Vol 6 No 2 (2023): Jurnal IDEALIS Juli 2023
Publisher : Universitas Budi Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36080/idealis.v6i2.3014

Abstract

E-Commerce merupakan transaksi bisnis yang meliputi transfer maupun serah terima kepemilikan hak atas suatu barang atau jasa dengan menggunakan internet. Transaksi bisnis yang dimaksud meliputi pembelian dan penjualan barang serta jasa melalui internet. Shopee berfokus kepada sistem penjualan dan Customer Relationship Management (CRM) untuk meningkatkan kualitas perusahaan dalam bersaing dengan aplikasi e-commerce besar lainnya. Shopee Indonesia telah menerapkan strategi CRM ini di salah satu platform yaitu jejaring sosial Instagram. Hal ini dilakukan oleh Shopee dengan tujuan untuk meningkatkan loyalitas pelanggan. Metode yang digunakan adalah Observasi, Kuesioner, dan Studi Literatur serta menggunakan tool Microsoft Visio 2019 dalam membantu teknik analisis data. Hasil yang didapatkan dari penelitian ini adalah sistem penjualan dan penerapan CRM aplikasi Shopee saat ini berdampak positif untuk perusahaan dalam menjangkau lebih banyak userbaru serta meningkatkan loyalitas user, berdampak positif juga untuk userdalam memperluas usaha nya serta terjadinya peningkatan penjualan produk melalui online.
Analasis User Experience pada Sistem Informasi Akademik Universitas Pradita dengan Metode Heuristic Evaluation (HE) Christopher, Christopher; Mayatopani, Hendra
Jurnal Teknoinfo Vol 18, No 1 (2024): Januari
Publisher : Universitas Teknokrat Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33365/jti.v18i1.3505

Abstract

Sistem Informasi Akademik adalah sebuah sistem yang dirancang untuk memudahkan proses pengolahan data, administrasi, dan pelaporan yang terkait dengan aspek akademik baik di lingkungan sekolah, universitas dan Lembaga Pendidikan lainnya. Universitas Pradita mempunyai Sistem Informasi Akademik berbasis web yang digunakan oleh mahasiswanya yang memiliki beberapa fitur seperti pengisian kartu rencana studi, jadwal pembelajaran, absensi, laporan nilai semester, dan berbagai fitur akademik lainnya. Dalam penelitian ini memiliki tujuan untuk menganalisis User Experience atau pengalaman pengguna dalam menggunakan Sistem Informasi Akademik Universitas Pradita dengan menggunakan metode Heuristic Evaluation (HE). Untuk mengetahui penilaian Sistem Informasi Akademik, akan digunakan Google Form dalam membuat kuosioner yang akan dibagikan kepada responden dalam menilai dan memberi masukkan. Responden merupakan mahasiswa Universitas Pradita yang masih aktif menggunakan Sistem Informasi Akademik Universitas Pradita. Hasil dari analisis yang telah dilakukan akan memperoleh hasil akhir berupa masukan atau pendapat dari analis yang dapat digunakan untuk memberikan solusi perbaikan terhadap Sistem Informasi Akademik Universitas Pradita. Solusi yang diberikan akan memperbaiki keefektifan dan ketepatan dalam penggunaan Sistem Informasi Akademik Universitas Pradita dalam memudahkan jalannya proses akademik bagi mahasiswa Universitas Pradita.
Perancangan Strategi Pemasaran Digital Untuk Meningkatkan Penjualan Bibit Anggur Pada Rumah Peng'Angguran Mayatopani, Hendra; Gupita Sari, Marchelia; Audrey, Kelly Kirsten; Tanuwijaya, Piter; Rico, Rico; Wendy, Wendy
Prosiding Konferensi Nasional Pengabdian Kepada Masyarakat dan Corporate Social Responsibility (PKM-CSR) Vol 6 (2023): INOVASI PERGURUAN TINGGI & PERAN DUNIA INDUSTRI DALAM PENGUATAN EKOSISTEM DIGITAL & EK
Publisher : Asosiasi Sinergi Pengabdi dan Pemberdaya Indonesia (ASPPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37695/pkmcsr.v6i0.1986

Abstract

Rumah Peng’Angguran adalah pusat dari komunitas pecinta anggur di Tangerang yang telah berdiri sejak tahun 2022. Awal memperkenalkan Rumah Peng'angguran' kepada masyarakat dengan dilakukannya strategi pemasaran secara konvensional, mengenai hal ini perkembangan teknologi yang kian berkembangan sehingga jika dilakukan dengan melakukan cara tersebut kurang menfasilitasi kebutuhan dan ini tidak akan mampu mencapai target secara menyeluruh dalam memberikan sebuah informasi yang ada di Rumah Peng’Angguran. Dalam beberapa tahun terakhir, kemajuan teknologi dan popularitas internet telah mengubah cara orang mencari informasi. Platform-platform daring seperti situs web, media sosial, dan aplikasi. Penentuan strategi pemasaran yang efektif dan efisien untuk meningkatkan jumlah penjualan bibit anggur pada Rumah Peng’Angguran menjadi tantangan yang penting dalam menambah eksposur kepada pasar yang cukup kompetitif. E-flyer, website dan forum komunitas kelompok tani anggur menjadi strategi pemasaran yang mengundang banyak eksposur dari masyarakat. Target jangkauan eksposur melalui digital ini se-Indonesia maupun luar negeri untuk perkembangan Rumah Peng’Angguran yang lebih besar lagi. Tahapan metode yang digunakan dengan cara pengumpulan informasi dengan wawancara dan survei lapangan dengan memperhatikan kemampuan sumber daya manusia yang tersedia di Rumah Peng’Angguran kota Tangerang. Hasil dari perencanaan dan perancangan strategi pemasaran digital memudahkan kegiatan dalam hal kegiatan promosi, penjualan dan terjalinnya silahturahmi kelompok tani anggur pada Rumah Peng’Angguran.
Implementation of ANN and GARCH for Stock Price Forecasting Mayatopani, Hendra
Journal of Applied Data Sciences Vol 2, No 4: DECEMBER 2021
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v2i4.41

Abstract

For simulating intricate goalfunctions, neural networks are a technology that is employed in artificial intelligence. The usage of artificial neural networks is becoming more popular.(ANNs) to certain sorts of tasks, for example learning to comprehend complicated sensor data collected in the real world, is one of the most effective methods of learning approaches available. The usage of time series models in financial time series prediction has grown significantly over the past decade, and their relevance in this area continues to expand. To be more specific, the goal of this research is to determine whether neural networks have the ability to predict financial time series in general, or, more specifically, whether they have the ability to predict future patterns i The stock market in the United States is characterized by the European Union, and Brazil, among other things. They are compared to a well-known forecasting approach, generalized autoregressive conditional heteroskedasticity, in this research, and their accuracy is shown to be superior (GARCH). Aside from that, the optimal network design for each data sample is developed for each data sample. According to this article, ANNs are capable of forecasting the stock markets under examination, and their resilience may be increased by varying the network topology utilized to construct them. Aside from that, the results of this research demonstrate that ANNs outperform GARCH models in terms of efficiency of statistical performance.
ANDROID-BASED UTILITY FACILITY MAINTENANCE APPLICATION USING DYNAMIC SYSTEM DEVELOPMENT METHODOLOGY (DSDM) Edison Siregar, Master; Mayatopani, Hendra; Kurniawan, Rido Dwi; Prathama, Dhion Angga
Jurnal Teknik Informatika (Jutif) Vol. 5 No. 4 (2024): JUTIF Volume 5, Number 4, August 2024 - SENIKO
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2024.5.4.2371

Abstract

In the ever-evolving digital era, the maintenance of utility facilities is becoming increasingly important to ensure smooth operations and services. Utility facilities include critical infrastructure such as waterways, electricity, and communication networks that must be properly maintained to maintain their function and reliability. The main contribution of this research is the application of DSDM in the development of related applications to improve the maintenance efficiency of utility facilities. organizational challenges faced in managing maintenance processes effectively, including untimely reporting issues, poor coordination, and lack of integration with company systems. To address this issue, this paper presents the development of an Android-based application designed to streamline and improve the maintenance process of utility facilities. The application leverages the Dynamic Systems Development Methodology (DSDM), known for its iterative and incremental approach, to ensure on-time delivery and adaptability to changing needs. The main goal of the app is to provide facility managers and maintenance personnel with a comprehensive solution through features such as real-time reporting, maintenance scheduling, and task management. By implementing DSDM in the context of utility maintenance, application users can be actively involved in the entire development process, allowing for rapid adaptation to changing needs The results of the development of this application are expected to improve the maintenance management of utility facilities efficiently, encourage preventive maintenance, and optimize the performance of these vital infrastructures.
Sentiment Analysis of Indonesian Society Toward the Launch of iPhone 16 Using Naive Bayes, Random Forest, and KNN Algorithms Christopher Ezra Manurung; Hendra Mayatopani
Jurnal Komputer, Informasi dan Teknologi Vol. 5 No. 1 (2025): Juni
Publisher : Penerbit Jurnal Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53697/jkomitek.v5i1.2219

Abstract

The development of smartphone technology, especially involving global brands like Apple, always attracts the attention of the world, including Indonesia. Every time Apple launches a new product, the public's response, particularly in Indonesia, often appears in the form of tweets on the social media platform Twitter, now known as X, which can be analyzed to reflect public views. This phenomenon presents an opportunity to understand how products are received in today's market. The dataset used in this study was obtained from tweets or comments from the Indonesian public between October and November 2024. The study found that 51.49% of the tweets fell into the positive sentiment category, 28.15% were neutral, and 20.35% were negative. Accuracy evaluation using three algorithms showed that Random Forest had the highest accuracy at 72.4%, followed by KNN with an accuracy of 66.9%, and Naïve Bayes with an accuracy of 66.3%. The results of this study indicate that the majority of the Indonesian public showed a positive sentiment toward the launch of the iPhone 16, reflecting high enthusiasm for the product. Furthermore, the Random Forest algorithm proved to be more effective in sentiment classification  compared to KNN and Naïve Bayes, with higher accuracy.