Garuda - Garba Rujukan Digital

STRATEGI PEMASARAN PRODUK INDUSTRI KREATIF MENGGUNAKAN ALGORITMA K-MEANS CLUSTERING BERBASIS PARTICLE SWARM OPTIMIZATION Oding Herdiana; Shanti Maulani; Eryan Ahmad Firdaus
NUANSA INFORMATIKA Vol 15, No 2 (2021)
Publisher : FKOM UNIKU

The existence of abundant UMKM data sources can be used to dig up information. Classification is one of the techniques to explore hidden data owned by data mining. Data mining classification methods, one of which is the Support Vector Machine (SVM) algorithm. The SVM algorithm has proven better results than the KKN, Decision Tree and Linear Regression algorithms. In the classification process, the accuracy and time efficiency results obtained are very important. So optimization is needed in order to increase accuracy and time efficiency during the classification process. The optimization of the SVM algorithm was carried out using the K-Means algorithm for the clustering and continuous process on UMKM data and the feature selection process using Particle Swarm Optimization (PSO). This paper aims to optimize the accuracy of the data in the form of type of business, business and turnover. From the results of the discussion of the SVM method using K-Means and PSO, it gives an average accuracy of 55% but 0.12% lower than SVM just using PSO. Keywords: UMKM, Clustering, K-Means, SVM, PSO

Perencanaan Business Intelligence untuk Strategi Pengembangan Produk Unggulan UMKM Oding Herdiana; Syti Sarah Maesaroh; Alifia Fatimatun Nazya
Jurnal Teknologi Informatika dan Komputer Vol 8, No 2 (2022): Jurnal Teknologi Informatika dan Komputer
Publisher : Universitas Mohammad Husni Thamrin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37012/jtik.v8i2.1142

Pengembangan Usaha Mikro Kecil dan Menengah (UMKM) merupakan upaya yang dilakukan pemerintah, dunia usaha, dan masyarakat untuk memberdayakan UMKM melalui pemberian fasilitas, bimbingan, pendampingan dan meningkatkan kemampuan daya saing UMKM. Upaya pengembangan UMKM melalui akselerasi produk unggulan agar masuk pasar digital terus ditingkatkan oleh pemerintah. Pelaku bisnis yang sukses biasanya dijelaskan dengan omset yang tinggi. Namun, jika pengusaha tidak dapat mengelola inventaris barang, memperkirakan produksi, dan membeli secara cepat dan akurat akan mengakibatkan produk kehabisan stok atau terjual pada waktu yang salah. Proses bisnis yang dilakukan UMKM perlu direncanakan dengan baik, mulai dari pemasaran produk, mengelola keuangan, merekrut karyawan, membeli bahan baku, dan mengelola produksi. Penelitian ini menggunakan metode penelitian development reserarch, dengan metode pengembangan sistem business intelligence Larissa T.moss. Penelitian ini merancang sistem Business Intelligence dengan memanfaatkan data UMKM Kota Tasikmalaya untuk strategi pengembangan produk unggulan menggunakan mockup prototype. Penelitian ini menghasilkan sebuah rancangan dashboard business intelligence bagi Dinas UMKM yang menampilkan profil bisnis berupa informasi status badan usaha, pengusaha UMKM per jenis kelamin dan rata-rata pendapatan. Sistem ini juga dirancang untuk kebutuhan pelaku UMKM berupa dashboarad business intelligence yang dapat mengetahui pendapatan sesuai dengan waktu, mengetahui trend produk yang paling banyak diminati, akses pembiayaan, dan dapat memprediksi penjualan produk.

Marketing Risk Management and Mapping Based on Geographic Information System in The Micro, Small, and Medium Enterprise in Tasikmalaya City Syti Sarah Maesaroh; Ardli Swardana; Asep Nuryadin; Oding Herdiana; Risma Rahatuningtyas
Jurnal Ilmiah Manajemen dan Bisnis Vol 8, No 3 (2022): Jurnal Ilmiah Manajemen dan Bisnis
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/jimb.v8i3.15796

The current COVID-19 pandemic has greatly impacted the economic sector, especially Micro, Small, and Medium Enterprises (MSMEs). Restrictions on physical mobility hinder the marketing of MSMEs’ products, which is usually carried out directly. This is one of the important risks to be studied in depth. The purpose of this study is to determine the management system and mapping of marketing risks in MSMEs in Tasikmalaya City. The research method used in this study was descriptive quantitative. Data were collected through a closed questionnaire that was given to MSMEs. The obtained data were processed through a risk management system approach and then mapped using a Geographical Information System (GIS). The results showed that the highest marketing risks for MSMEs in Tasikmalaya City are increasingly fierce business competition, nonoptimal internet usage, and limited marketing coverage. Geographically, the level of marketing risks of MSMEs in Tasikmalaya City is in the medium category. Geographical marketing risk mapping can determine the most appropriate recommendations to deal with various risks faced according to regional characteristics.

The Evaluation of User Experience UPI Digital Business Website with Usability Testing Method and System Usability Scale Moch Gan-gan Sidiq; Rangga Gelar Guntara; Oding Herdiana
Indonesian Journal of Digital Business Vol 4, No 1 (2024): Indonesian Journal of Digital Business
Publisher : Universitas Pendidikan Indonesia (UPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17509/ijdb.v4i1.59589

The UPI Digital Business website, which has a domain at https://bisnisDigital.upi, is the official website of the Digital Business study program at Universitas Pendidikan Indonesia. According to the results of observing similarweb.com visitor traffic data, there are interesting findings related to the high bounce rate on the website, which is 71.35%. Likewise, from the results of informal observations of the closest website users, namely UPI Digital Business students, it was found that there were still complaints, one of which was difficulty finding some of the information needed because of the confusing navigation structure. The developer has never evaluated the experience of using the website, so it is not yet known how and how well the website can be used by current users. The research focuses on evaluating user experience in terms of ease of use by conducting usability testing and SUS tests with three aspects of ISO 9421-11 usability, namely effectivity, efficiency, and satisfaction. The result is that effectivity gets a grade “ Bad” with score of 60%, efficiency gets a score of 38%, and satisfaction gets a score of 33 out of 100.

Pengaruh Pemasaran Media Sosial terhadap Keterlibatan Pelanggan (Survei pada Pengguna Halodoc di Indonesia) Alif Ridha Ramadhani; Mochamad Ardan Fauzi; Muhammad Mufti Abdullah; Syti Sarah Maesaroh; Oding Herdiana
Jurnal Teknologi Terpadu Vol. 9 No. 1 (2023): Juli, 2023
Publisher : LPPM STT Terpadu Nurul Fikri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54914/jtt.v9i1.622

This study was conducted to obtain information about the magnitude of the influence of social media marketing on customer engagement. Social media marketing (X) is the independent variable, and customer engagement (Y) is the dependent variable in this study. Followers on the Halodoc Instagram account were selected to be the population in this study, and the sample was taken randomly (simple random sampling), with 120 respondents successfully obtained. The SEM method is used to analyze data with the help of IBM SPSS AMOS 21 software for Windows in the data processing. The results of data processing illustrate that there is an influence of social media marketing on customer involvement of (0.931) with a p-value (0.002) <0.05. Artificial Intelligence-Analitycs for social media is a tool for efforts to increase the competitiveness of official Instagram managers for a business against competitors owned by analyzing content optimization through various services in the form of statistics and metrics from Artificial Intelligence-Analitycs providers, which are generally website-based. The author's recommendation for Halodoc is to increase closeness with customers so that their bonds become stronger through planning content that is useful for the community and packaged attractively. Later it is hoped that there will be more user-generated content or posting word-of-mouth recommendation comments from customers to other customers.

Perencanaan Business Intelligence untuk Strategi Pengembangan Produk Unggulan Menggunakan Algoritma Support Vector Machine Oding Herdiana
Jurnal Informatika Vol 2 No 2 (2023): Jurnal Informatika
Publisher : LPPM Universitas Nias Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57094/ji.v2i2.1088

The government continues to encourage the government to accelerate Small and Medium Enterprises (SMEs) flagship products to enter the digital market, because the current digitalization of SMEs cannot be ignored, SMEs must be able to change their business to the digital realm. The strategy for developing superior SME products needs to be well planned, because a good and measurable strategy is very important for policy making. Development uses an approach that emphasizes that the driving force of development is commodities that are considered to be superior, both at the domestic, national and international levels. Superior products that have quality and are needed by customers require the right selection process, so we need a method to produce this information. Business Intelligence (BI) is a global term for all processes, techniques, and tools that support business decision making based on information technology. The strategy for developing superior products for SME products uses the criteria of production data, income, and SME respondent data in determining the priority list. A good product assessment based on priority can be done by BI using the classification method with the Support Vector Machine (SVM) algorithm. The research method carried out for planning the development of superior products for MSMEs in Tasikmalaya City is a research development research. To complete the classification of the right superior product development strategy, then Support Vector Machine algorithm can be used with test results using the Confusion Matrix with an average accuracy of 97%.

Pengaplikasian Literasi Wirausaha Digital Yang Mendorong Tumbuhnya Motivasi Pengembangan Usaha Santanamekar Kabupaten Tasikmalaya Adi Prehanto; Btari Mariska Purwaamijaya; Oding Herdiana; Muhammad Dzikri Ar Ridlo; Adam Hermawan; Alifia Fatimatun Nazya
Jurnal Pengabdian Nasional (JPN) Indonesia Vol. 5 No. 1 (2024): Januari
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Indonesia Banda Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jpni.v5i1.525

The industrial revolution 4.0 has brought many developments, the era of automation has been implemented in several sectors to make activities more effective and artificial intelligence is the driving force in this era, which promises many conveniences in various fields. Based on the results of research entitled "Perceptions and Prospective Analysis of Artificial Intelligence and its impact on Human Resources in the Indonesian Industry 4.0," Human Resources in Industry is a crucial variable in changes in Indonesia's movement to prepare for industry 4.0. Industry 4.0 can be interpreted as an industrial era in which all entities or devices within it are made able to communicate with each other in real time at any time by utilizing internet technology, in order to achieve the goal of creating new value or optimizing existing value from every process in the industry. . The results of the pre-test and post-test on 8 respondents showed an increase after the pre-test of 87.5%, which was dominated by housewives in the digital entrepreneurship strategy workshop. Based on the results of 2 studies, it was found that there is a need for training that can apply digital technology to help them professionally by adapting to the demands of industry 4.0 and the role of university teaching staff to engage with the community in empowerment who have experience not only as academics, but also as practitioners who have pedagogical, professional and social competency abilities so that they attract more interest.

Pengaruh Pemasaran Media Sosial terhadap Keterlibatan Pelanggan (Survei pada Pengguna Halodoc di Indonesia) Ramadhani, Alif Ridha; Fauzi , Mochamad Ardan; Abdullah, Muhammad Mufti; Maesaroh, Syti Sarah; Herdiana, Oding
Jurnal Teknologi Terpadu Vol 9 No 1 (2023): Juli, 2023
Publisher : LPPM STT Terpadu Nurul Fikri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54914/jtt.v9i1.622

This study was conducted to obtain information about the magnitude of the influence of social media marketing on customer engagement. Social media marketing (X) is the independent variable, and customer engagement (Y) is the dependent variable in this study. Followers on the Halodoc Instagram account were selected to be the population in this study, and the sample was taken randomly (simple random sampling), with 120 respondents successfully obtained. The SEM method is used to analyze data with the help of IBM SPSS AMOS 21 software for Windows in the data processing. The results of data processing illustrate that there is an influence of social media marketing on customer involvement of (0.931) with a p-value (0.002) <0.05. Artificial Intelligence-Analitycs for social media is a tool for efforts to increase the competitiveness of official Instagram managers for a business against competitors owned by analyzing content optimization through various services in the form of statistics and metrics from Artificial Intelligence-Analitycs providers, which are generally website-based. The author's recommendation for Halodoc is to increase closeness with customers so that their bonds become stronger through planning content that is useful for the community and packaged attractively. Later it is hoped that there will be more user-generated content or posting word-of-mouth recommendation comments from customers to other customers.

Analysis of Information Security Awareness of E-Commerce Users Among Micro Small Medium Enterprises Muttaqin, Irham Khairul; Maesaroh, Syti Sarah; Herdiana, Oding
Jurnal Teknologi Informasi dan Pendidikan Vol. 17 No. 1 (2024): Jurnal Teknologi Informasi dan Pendidikan
Publisher : Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/jtip.v17i1.802

Information security is vital in today's digital era. Micro small medium enterprises are always required to survive with the unfavorable conditions. Through e-commerce, businesses can be helped to sell their products widely. Carelessness in managing information in e-commerce applications by business owners can cause great losses. In this article, the information security awareness of MSMEs will be analyzed using the Knowledge Attitude Behaviour method developed by Kruger-Kearney. The sample of respondents was taken using a purposive sampling technique where the criteria for respondents were categorized micro small medium enterprises owners and using e- commerce applications to sell their products. This article succeeded in analyzing, that the awareness of business owners was in a good category. The resulting score is 93 and is considered a high value. There are several factors that cause the high awareness score obtained, one of which is the training held by the state-owned creative house. This article can be developed for further research.

Sentiment Analysis For User Review Classification On Jenius Application Using Naive Bayes Algorithm Based On Particle Swarm Optimization Fitriani, Vivi Indah; Herdiana, Oding; Guntara, Rangga Gelar
Indonesian Journal of Digital Business Vol 4, No 2 (2024): Indonesian Journal of Digital Business
Publisher : Universitas Pendidikan Indonesia (UPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17509/ijdb.v4i2.59529

The rapid development of information technology and communication has facilitated various aspects of life, including the banking sector. Jenius is one of the digital banking applications that has been downloaded by five million users and continues to grow. With the increasing number of users, there is a growing number of opinions written about their experiences using the application, making it difficult to identify reviews through manual monitoring without textual data processing. This study aims to classify user reviews of the Jenius application on Google Playstore using the Naive Bayes algorithm and Particle Swarm Optimization feature selection. The data used consists of 3047 user reviews of the Jenius application collected from January 16, 2022 to April 13, 2023 and will be divided into two classes, namely positive and negative sentiment. This study also compares the Naive Bayes algorithm using PSO feature selection and without using PSO feature selection. The test results of the two methods indicate that the PSO feature selection with 800 iterations proves to be effective in optimizing the performance of the Naive Bayes algorithm model with an accuracy of 98.50%, precision of 97.81%, recall of 99.36%, and F1-score of 98.58%. Meanwhile, the performance level of the Naive Bayes algorithm without using PSO feature selection is lower with an accuracy of 96.68%, precision of 94.83%, recall of 99.04%, and F1-score of 96.88%.

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