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All Journal International Journal of Electrical and Computer Engineering IAES International Journal of Artificial Intelligence (IJ-AI) IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Dinamik Seminar Nasional Aplikasi Teknologi Informasi (SNATI) JURNAL SISTEM INFORMASI BISNIS Jurnal Sistem Komputer JSI: Jurnal Sistem Informasi (E-Journal) Prosiding SNATIF Jurnal Teknologi Informasi dan Ilmu Komputer Scientific Journal of Informatics Journal of Information Systems Engineering and Business Intelligence Khazanah Informatika: Jurnal Ilmu Komputer dan Informatika JOIV : International Journal on Informatics Visualization Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) International Journal of Artificial Intelligence Research INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi JURNAL MEDIA INFORMATIKA BUDIDARMA Desimal: Jurnal Matematika INOVTEK Polbeng - Seri Informatika BAREKENG: Jurnal Ilmu Matematika dan Terapan International Journal on Emerging Mathematics Education Jurnal ULTIMA InfoSys MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Jurnal Teknologi Sistem Informasi dan Aplikasi Journal of Information Technology and Computer Engineering J-SAKTI (Jurnal Sains Komputer dan Informatika) Aptisi Transactions on Management JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Aptisi Transactions on Technopreneurship (ATT) EDUKATIF : JURNAL ILMU PENDIDIKAN Building of Informatics, Technology and Science Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Progresif: Jurnal Ilmiah Komputer Journal of Information Systems and Informatics KAIBON ABHINAYA : JURNAL PENGABDIAN MASYARAKAT Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) ICIT (Innovative Creative and Information Technology) Journal Computer Science and Information Technologies Jurnal Bumigora Information Technology (BITe) Aiti: Jurnal Teknologi Informasi Jurnal Teknik Informatika (JUTIF) ADI Bisnis Digital Interdisiplin (ABDI Jurnal) IAIC Transactions on Sustainable Digital Innovation (ITSDI) JOINTER : Journal of Informatics Engineering International Journal of Engineering, Science and Information Technology Advance Sustainable Science, Engineering and Technology (ASSET) Journal of Information Technology (JIfoTech) J-SAKTI (Jurnal Sains Komputer dan Informatika) Jurnal Nasional Teknik Elektro dan Teknologi Informasi Jurnal Pengabdian Papua Jurnal Ilmiah Sains Magistrorum et Scholarium: Jurnal Pengabdian Masyarakat JEECS (Journal of Electrical Engineering and Computer Sciences) Metris: Jurnal Sains dan Teknologi Midang Scientific Journal of Informatics Advance Sustainable Science, Engineering and Technology (ASSET) International Journal of Information Technology and Business INOVTEK Polbeng - Seri Informatika JuTISI (Jurnal Teknik Informatika dan Sistem Informasi) Jurnal DIMASTIK International Journal of Marketing and Digital Creative (IJMADIC)
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Analisis Sentimen Komentar Konsumen Industri Jamu di Media Sosial menggunakan Artificial Neural Network dan K-Nearest Neighbor Kurniawan, Daniel; Purnomo, Hindriyanto Dwi; Iriani, Ade
Jurnal Sistem Informasi Bisnis Vol 14, No 3 (2024): Volume 14 Nomor 3 Tahun 2024
Publisher : Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21456/vol14iss3pp210-223

Abstract

Phytopharmaceutical plants have become one of the main commodities contributing significantly to the economy through their use in the pharmaceutical, cosmetic, and health industries. However, behind this economic potential, traditional herbal medicine businesses often face challenges, particularly in promotion and brand identity. Social media platforms like Instagram have now introduced unique features to support business and marketing, primarily by providing in-depth information about herbal products and offering opportunities for businesses to receive feedback from consumers. Comments on social media are valuable but often unstructured; hence, sentiment analysis is necessary to organize and categorize this data. By combining comment data with information from Google Trends, cause-and-effect relationships from comments during specific periods can be identified using path analysis. This research aims to analyze consumer comments on the Sidomuncul company's Instagram platform, with the hope of benefiting the company and advancing herbal medicine products. The methods used in this study include Artificial Neural Network (ANN) and K-nearest neighbor (KNN) to classify comments into positive, negative, and neutral categories. Both methods show satisfactory results in classification, with an average accuracy of 0.887 for ANN and 0.874 for KNN. However, the ROC curve for the KNN model indicates a relatively low AUC value in classifying negative comments, at 0.598.
Analysis Of Library Visitors' Interest Using Factor Analysis And Discriminant Analysis Hery Santono; Eko Sediyono; Hindriyanto Dwi Purnomo
INOVTEK Polbeng - Seri Informatika Vol. 10 No. 1 (2025): March
Publisher : P3M Politeknik Negeri Bengkalis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35314/g3vb2a79

Abstract

The relevance of libraries as learning centers, gathering places for the scientific community, and access points for resources not always available online underscores the importance of understanding the factors that influence library visitor interest. This study aims to analyze the factors impacting visitor interest using Factor Analysis and Discriminant Analysis. The key factors explored include service quality, comfort of facilities, quality of book collections, access to digital technology, and frequency of visits. Data was collected through surveys conducted with 500 library visitors across five different locations over a three-month period. Factor Analysis revealed that comfort factors and access to technology were the most significant variables influencing visitor interest, accounting for 65% of the variance in visitor behavior. Discriminant Analysis further classified visitors into high and low interest groups, showing that library facilities were the primary differentiator between these two groups. The study found that visitors with high interest were more likely to be influenced by the library's physical comfort and technology access, while those with low interest were less engaged with the library's services. This research provides valuable insights for library managers to enhance services, optimize library environments, and incorporate technological advancements to increase visitor engagement. It also contributes to the theoretical understanding of library management by identifying key factors that affect visitor interest, which can inform future strategies in the field. However, this study is limited by its cross-sectional nature, and the results may not be generalizable to other regions or visitor demographics. Future research could explore longitudinal data to assess how visitor preferences evolve over time.
Consumer Behavior Analysis using Apriori Algorithm Safitri, Adila; Purnomo, Hindriyanto Dwi
International Journal of Information Technology and Business Vol. 1 No. 2 (2019): April: International Journal of Information Techonology and Business
Publisher : Universitas Kristen Satya Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Along with the development of the era, also followed by growth and also the birth of many companies in the field of goods and services, where each company always strives as much as possible to obtain and maintain market share. This can make competition tight, especially for business people, especially those that occur in digital printing companies owned by Abadi Digital Printing, Salatiga. Because this printing company is still a new company, it requires a lot of research on consumer purchasing patterns to increase sales and marketing strategies so as not to be rivaled by other printing that has been longer, the following analysis uses apriori algorithms with RapidMiner tools. By using a support value of 0,025 and confidence of 0,6, the results are that the items often purchased by consumers are standing banner with x banner. From these results it can be used as a promotional event, deal packages, etc to increase consumer attractiveness.
Utilization of Optical Character Recognition Technology in Reading Identity Cards Hendradito Dwi Aprillian; Hindriyanto Dwi Purnomo; Hari Purwanto
International Journal of Information Technology and Business Vol. 4 No. 2 (2022): April: International Journal of Information Technology and Business
Publisher : Universitas Kristen Satya Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24246/ijiteb.422022.38-46

Abstract

Along with the times, the world of banking is also required to have growth in providing services to the public. The world of banking itself has a significant contribution in daily life. However, some deficiencies that arise due to the application of the procedures used are still often encountered. This situation can be seen from the number of customer self-registration data that is still done manually. Optical Character Recognition (OCR) technology on Citizenship Cards can be used to get the results of accuracy and speed and get the best reading results. The purpose of this study was to use Optical Character Recognition (OCR) technology in reading the Identity Card (KTP). The readings from OCR can be used to compare the size of the original, medium, and small images in color and grayscale images, so that the best results can be found in the processing of personal data on Identity Cards with Optical Character Recognition (OCR). This study resulted in the accuracy of reading grayscale Identity Card (KTP) data more accurately. Where the amount of 86.32% for the accuracy of the colored Identity Card (KTP) and 88.58% for the accuracy of the grayscale Identity Card (KTP).
PENGENALAN GAME EDUKASI BAGI SISWA TK KRISTEN 1 SATYA WACANA SALATIGA USIA 5-6 TAHUN Anton Hermawan; Nataliani, Yessica; Hindriyanto Dwi Purnomo; Christianto, Erwien; Atik Setyanti, Angela; Yulia, Hanita; Krismiyati; Juliastomo Gundo, Adriyanto; Wellem, Theophilus; Hendry
Jurnal DIMASTIK Vol. 3 No. 2 (2025): Juli
Publisher : Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/dimastik.v3i2.12302

Abstract

Kemajuan teknologi informasi dan komunikasi menuntut adanya adaptasi dalam dunia pendidikan, termasuk pada jenjang pendidikan anak usia dini. Pengenalan teknologi sejak dini menjadi langkah strategis dalam membentuk kesiapan anak menghadapi era digital. Kegiatan pengabdian ini bertujuan untuk mengenalkan teknologi, khususnya komputer, kepada siswa Taman Kanak-kanak (TK) melalui game edukasi berbasis online. Kegiatan dilaksanakan secara luring di TK Kristen 1 Satya Wacana, Salatiga, dengan melibatkan siswa berusia 5–6 tahun. Metode pelatihan dilakukan dalam beberapa sesi, mencakup pengenalan bagian-bagian komputer, penggunaan mouse, serta pelatihan melalui game edukasi seperti pengenalan huruf, angka, bentuk geometri, dan jenis-jenis kendaraan. Hasil evaluasi menunjukkan bahwa siswa menunjukkan antusiasme tinggi selama pelatihan, serta mulai mengenal komputer sebagai media pembelajaran alternatif selain perangkat yang biasa digunakan di rumah seperti handphone dan tablet. Kegiatan ini membuktikan bahwa pendekatan belajar sambil bermain dengan teknologi dapat meningkatkan minat belajar dan keterampilan dasar siswa dalam menggunakan komputer.
Comparison of K-Means & K-Means++ Clustering Models using Singular Value Decomposition (SVD) in Menu Engineering Setiyawati, Nina; Bangkalang, Dwi Hosanna; Purnomo, Hindriyanto Dwi
JOIV : International Journal on Informatics Visualization Vol 7, No 3 (2023)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.7.3.1053

Abstract

The menu is one of the most fundamental aspects of business continuity in the culinary industry. One of the tools that can be used for menu analysis is menu engineering. Menu engineering is an analytical tool that assists restaurants, companies, and small and medium-sized enterprises (SMEs) in assessing and making decisions on marketing strategies, menu design, and sales so that it can produce maximum profit. In this study, several menu engineering models were proposed, and the performance of these models was analyzed. This study used a dataset from the Point of Sales (POS) application in an SME engaged in the culinary field. This research consists of three stages. First, pre-processing the data, comparing the models, and evaluating the models using the Davies Bouldin index. At the model comparison stage, four models are being compared: K-Means, K-Means++, K-Means using Singular Value Decomposition (SVD), and K-Means++ using SVD. SVD is used in the dataset transformation process. K-Means and K-Means++ algorithms are used for grouping menu items. The experiments show that the K-Means++ model with SVD produced the most optimal cluster in this research. The model produced an average cluster distance value of 0.002; the smallest Davies-Bouldin Index (DBI) value is 0.141. Therefore, using the K-Means++ model with SVD in menu engineering analysis produces clusters containing menu items with high similarity and significant distance between groups. The results obtained from the proposed model can be used as a basis for strategic decision-making of managing price, marketing strategy, etc., for SMEs, especially in the culinary business.
Analisis Pemetaan Jaringan Komunikasi Karyawan Menggunakan Social Network Analysis pada Perusahaan Multifinance Zusrony, Edwin; Purnomo, Hindriyanto Dwi; Prasetyo, Sri Yulianto Joko
INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi Vol 3 No 2 (2019): Vol. 3 No. 2 Agustus 2019
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (627.187 KB) | DOI: 10.29407/intensif.v3i2.12786

Abstract

Business development in the financial services sector improved competition among companies to give the best service to their customers. Having reliable services with a good communication network in the organization is the critical success of the company. This study aims to find the actors or people who influence organizations through formal and informal communication networks using Social Network Analysis (SNA). Information on casual and formal communication networks can be used by the HR department to measure the level of the social relationship of all employees that can improve their performance in the company. The author researched PT. BFI Salatiga. The results showed that tissue density was below 50% so that relationships were considered weak. The most dominant actor in degree centrality, closeness centrality, and betweenness centrality is the actor id#24 and id#29 from the collection division, actor id#27 from the operation division and actor id#30 from the credit division.
Utilization of Social Network Analysis (SNA) in Knowledge Sharing in College Nurrokhman, Nurrokhman; Dwi Purnomo, Hindriyanto; Dwi Hartomo, Kristoko
INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi Vol 4 No 2 (2020): August 2020
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (709.035 KB) | DOI: 10.29407/intensif.v4i2.14460

Abstract

Campus competition in Central Java creates superior and empowered human resources to make XYZ campus optimize the Knowledge Sharing process. In optimizing the Knowledge Sharing process on the XYZ campus through interaction and communication between students in the study program. This study aims to identify the Knowledge Sharing collaboration of students on the XYZ campus in three study programs with 100 respondents using the Social Network Analysis (SNA) method. The parameters used in this study include density, degree centrality, closeness centrality, betweenness centrality, and clicks (subgroups). Based on the analysis of the results obtained by the level of density level of 4.7% or weak ties because under 50%. Actor 98 has the highest degree of centrality with outdegree value 32 and indegree 7, while actor 65, which has the highest closeness centrality with inCloseness value 16,952 and outCloseness value 1,020. Actor 15 also has the highest centrality betweenness with an amount of Betweenness 2750,148 and nBetweenness 28,346. In this study, it can be concluded that there is collaboration in the Knowledge Sharing of students on the XYZ campus from each divided into three study programs, namely, informatics engineering, accounting computerization, and graphic design.
Sentiment Analysis of e-Government Service Using the Naive Bayes Algorithm Winny purbaratri; Hindriyanto Dwi Purnomo; Danny Manongga; Iwan Setyawan; Hendry Hendry
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 23 No. 2 (2024)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v23i2.3272

Abstract

E-Government which involves the use of communication and information technology to provide Public services have three obstacles. One of these obstacles is the implementation of e-Government by autonomous regional governments is still carried out individually. Apart from that, implementing the website regions are also not supported by efficient management systems and work processes, this is partly the case This is largely due to the lack of preparation of regulations, procedures and limited resources man. Apart from that, many local governments consider implementing e-Government only involves developing local government websites. More precisely, the implementation of e-Government It is only limited to the maturity stage and ignores the three other important stages that need to be completed. The aim of this research is to determine the level of public approval for government application services. This research uses the Naive Bayes Classifier approach as the methodology. The data sources used in this research consist of user reviews and comments obtained from Google Play Store. The results of this investigation produce a level of precision The highest is achieving a score of 83%. Additionally it shows an accuracy rate of 83%,levelcompleteness is 100%, and F-measure is 90.7%.
INTEGRASI ALGORITMA APRIORI DAN K-MEANS DALAM ANALISIS POLA PEMBELIAN UNTUK MENINGKATKAN STRATEGI PEMASARAN Putri, Violita Eka; Purnomo, Hindriyanto Dwi
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 10, No 1 (2025)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v10i1.5768

Abstract

UMKM pada bidang usaha kuliner sedang mengalami peningkatan yang signifikan sehingga muncul persaingan dalam dunia bisnis yang semakin tidak terelakkan. Selain itu, kebiasaan pelanggan dalam melakukan pembelian yang membutuhkan waktu lama menjadi perhatian khusus bagi pemilik bisnis Premium Salad.co untuk dapat membuat penawaran produk yang lebih sesuai dengan keinginan pelanggann. Oleh karena itu, penelitian ini bertujuan untuk membentuk sebuah strategi pemasaran dalam bentuk rekomendasi paket menu atau dapat juga digunakan sebagai paket bundling produk dengan memperhatikkan produk apa saja yang memiliki frekuensi penjualan yang sering dibeli secara bersamaan oleh pelanggan, hal ini bertujuan untuk meningkatkan daya tarik pelanggan. pada saat memilih dan membeli produk, meningkatkan keuntungan penjualan, pemerataan penjualan produk, sekaligus inovasi baru untuk mengimbangi adanya persaingan bisnis kuliner. Data transaksi yang sebelumnya tidak dimanfaatkan secara optimal oleh Premium Salad.co kini dapat dimanfaatkan untuk mencari pengetahuan lebih dalam mengenai gambaran penjualan produk yang terjadi secara keseluruhan dengan bantuan data mining. Pada penelitian ini metode data mining yang digunakan yaitu clustering dan aturan asosiasi. Algoritma k-means berperan untuk mengelompokkan data dalam 4 cluster dengan nilai uji validitas Davies Bouldin Index (DBI) sebesar 0,465. Algoritma apriori berpartisipasi dalam pencarian aturan asosiasi pada cluster. Tujuan dari penggabungan dua metode ini agar menghasilkan aturan asosiasi yang lebih variatif dan lebih sesuai dengan penyelesaian masalah yang dibutuhkan. Dengan menetapkan dukungan minimum sebesar 0,01 dan kepercayaan minimum sebesar 0,5. Pada cluster 0 dengan dataset 321 transaksi menghasilkan 1 aturan dengan tingkat kepercayaan tertinggi sebesar 75%. Cluster 3 dengan dataset paling kecil yaitu 127 transaksi mampu menghasilkan sejumlah 16 aturan dengan tingkat kepercayaan tertinggi mencapai 100%.
Co-Authors Ade Iriani Adi Nugroho Adimas Tristan Nagara Hartono Adriyanto Juliastomo Gundo Agung Wibowo Agus Priyadi Ahmad Bayu Yadila Andre Kurniawan Andreas A. Sukmana Andrew Aquila Chrisanto Pabendon Andry Ananda Putra Tanggu Mara Andry Tanggu Mara Angela Atik Setiyanti Anton Hermawan Anton Hermawan Anwar, Muchamad Taufiq April Firman Daru April Lia Hananto Aris Puji Widodo Aris Tri Joko Harjanto Arseta, Gama Astawa, I Wayan Aswin Dew Atik Setyanti, Angela Atmoko Nugroho Aziz Jihadian Barid Azzahra Nurwanda Bandung Pernama Baun, Sindy Cristine Bayangkariwati Tacoh, Yuliana Tien Betty E. Kristiani Budhi Kristianto Budi Kristianto Budi Kristianto, Budi C. Leuwol, Sylvie Cahyaningtyas, Christyan Cahyo Dimas K Chandra Halim Chandra, Dian W. Charitas Fibriani Christyan Cahyaningtyas Daniel Kurniawan Daniel Kurniawan Daniel Yeri Kristiyanto Danny Manongga Danu Satria Wiratama Deden Rustiana Dedy Prasetya Kristiadi Didit Budi Nugroho Dody Agung Saputro Dwi Hosanna Bangkalang Edwin Zusrony Eka Purnama Harahap Eko Sediyono Eliansion Ivan eremia Silvester Sutoyo Erwien Christianto Evang Mailoa Evangs Mailoa Fajar Rahmat Faudisyah, Alfendio Alif Fauzi Ahmad Muda Feibe Lawalata Florentina Tatrin Kurniati Galih Putra Cesna Giner Maslebu Gladis Tri Enggiel Griya Jitri Pabutungan Gudiato, Candra Hanita Yulia Hanna Arini Parhusip Hari Purwanto Hendra Kusumah Hendra Waskita Hendradito Dwi Aprillian Hendro Steven Tampake Hendry Hendry Hendry Heni Pujiastuti Hermanto Abraham, Rendy Heru Riza Chakim Hery Santono Hery Santono HR. Wibi Bagas N Hsin Rau Huda, Baenil Hui-Ming Wee Irdha Yunianto Irwan Sembiring Istiarsi Saptuti Sri Kawuryan Istiarsih Saputri Sri Kawuryan Iwan Setiawan Iwan Setyawan Janinda Puspita Anidya Jihot Lumban Gaol Joanito Agili Lopo Jonas, Dendy Juliastomo Gundo, Adriyanto Kainama, Marchel Devid Karema Sarajar, Dewita Kho, Delvian Christoper Krismiyati Kristoko Dwi Hartomo Lea Klarisa Lumban Gaol, Jihot Markus Permadi Mau, Stevanus Dwi Istiavan Maya Sari Mellyuga Errol Wicaksono Merryana Lestari Mira Mira Mira Muhammad Aufal Muhammad Rizky Pribadi Nadya Octavianna Lompoliuw Nahak, Yosef Jeffri Silvanus Nahusona, Ferry Nanle, Zeze Nina Rahayu Nina Setiyawati Ninda Lutfiani Ninda Lutfiani Nurrokhman, Nurrokhman Nyree Ani Oliver Sauntos Permadi, Markus Picauly, Irma Amy Pratyaksa Ocsa Nugraha Saian Priatna , Wowon Purwanto - Purwanto Putri, Violita Eka Radius Tanone Ramos Somya Raynaldo Raynaldo Raynaldo Raynaldo, Raynaldo Richard William Kho Riko Yudistira Robert William Ruhulessin Rufina Rahma Ajeng Setyaningsih Saekoko, Agatha Marilin Safitri, Adila Sakalessy, Afelia Jozalin Elisa Sampoerno Santoso, Fian Julio Santoso, Fian Yulio Santoso, Joseph Teguh Setiyaji, Akhfan Setyanti, Angela Atik Sri Kasmiyati Sri Kawuryan, Istiarsi Saptuti Sri Sri Yulianto Joko Prasetyo Sugiman, Marcelino Maxwell Sutarto Wijono Syahrul Mu’Arif Wahid Syamsul Arifin Tad Gonsalves Tad Gonsalves Teguh I. Bayu Teguh Indra Bayu Teguh Wahyono Theopillus J. H. Wellem Tio Nurtino Tirsa Ninia Lina Tri Wahyuningsih Trivena Andriani Tukino, Tukino Tumbade, Marcho Oknivan Tungady, Cornelius Arvel Pratama Untung Rahardja Utama, Deffa Ferdian Alif Valentino Kevin Sitanayah Que Vinsensius Wijaya Walangara Nau, Novriest Umbu Wibowo, Mars Caroline Widyarini, Liza Wilujeng Ayu Nawang Sari Winny purbaratri Wisnu Wibisono, Indra Wiwien Hadikurniawati Yerik Afrianto Singgalen Yessica Nataliani Yos Richard Beeh Yudistira, Riko Yuli Agung Suprabowo, Gunawan Yusuf, Natasya Aprila Zakaria, Noor Azura