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All Journal Information Technology and Telematics Dinamik Jurnal Ilmiah Dinamika Teknik Elkom: Jurnal Elektronika dan Komputer Scientific Journal of Informatics Jurnal Ilmiah Giga Proceeding SENDI_U Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) JURNAL MEDIA INFORMATIKA BUDIDARMA CogITo Smart Journal JURNAL INSTEK (Informatika Sains dan Teknologi) Jurnal Teknik Informatika UNIKA Santo Thomas Jurnal Teknologi Sistem Informasi dan Aplikasi IKRA-ITH ABDIMAS J-SAKTI (Jurnal Sains Komputer dan Informatika) JURIKOM (Jurnal Riset Komputer) Jurnal Informasi dan Komputer JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Building of Informatics, Technology and Science Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi JURNAL MAHAJANA INFORMASI Jurnal Abdimas Mandiri Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) JATI (Jurnal Mahasiswa Teknik Informatika) Journal of Computer System and Informatics (JoSYC) Jurnal Pengabdian kepada Masyarakat J-SAKTI (Jurnal Sains Komputer dan Informatika) Jurnal Teknik Informatika Unika Santo Thomas (JTIUST) Jurnal Pengabdian Masyarakat Intimas (Jurnal INTIMAS): Inovasi Teknologi Informasi Dan Komputer Untuk Masyarakat Jurnal Pengabdian Pada Masyarakat Jurnal Kabar Masyarakat SmartComp Fundamentum: Jurnal Pengabdian Multidisiplin Servis : Jurnal Pengabdian dan Layanan kepada Masyarakat Andan Jejama: Indonesian Journal Of Community Engagement
Veronica Lusiana
Universitas Stikubank (UNISBANK) Semarang
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Penentuan Klustering Indeks Pembangunan Manusia Provinsi Jawa Tengah dengan Metode K-Means Berbasis Web Aryasatya, Rakryan; Lusiana, Veronica
Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 8 No 1 (2024): JANUARY-MARCH 2024
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jtik.v8i1.1403

Abstract

The Human Development Index uses a data clustering algorithm, namely the K-Means algorithm, which is the simplest clustering algorithm compared to other algorithms. This algorithm is one of the most important algorithms in data mining. K-Means divides the data and then groups it into several similar clusters and separates each cluster based on the differences between each cluster. The aim of this research is to design and implement the Human Development Index for Central Java Province using a web-based k-means clustering algorithm. This research is a qualitative research in the field of electrical engineering, especially in the field of software. This research was conducted by analyzing data using the K-Means Clustering Algorithm for the Human Development Index. The implementation of the k-means clustering algorithm into the clustering system provides effective data grouping classification results and the process of each centroid distance rotation literacy, the determination of cluster points is formed, human data as a reference object saves more time when clustering the Human Development Index. The application of this clustering results in more flexible information that can be accessed at any time by users who are given access rights to utilize the data. The application of the K-Means Clustering Algorithm to obtain the results of the Human Development Index requires an information system implementation to form four clusters
Pengaruh Peningkatan Kualitas Citra Menggunakan Modifikasi Kontras Pada Kompresi Data RLE Lusiana, Veronica; Al Amin, Imam Husni; Sutanto, Felix Andreas
Building of Informatics, Technology and Science (BITS) Vol 4 No 1 (2022): June 2022
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (600.757 KB) | DOI: 10.47065/bits.v4i1.1646

Abstract

Data compression is needed so that the need for storage media and data transfer time becomes more efficient. This study compressed image data using the Run-Length Encoding (RLE) method. The test data is the original image (gray scale) and the image results of improving image quality (image enhancement) using contrast modification. Modification of contrast using contrast stretching methods. Through experiments wanting to know the extent to which the RLE method works less effectively for images with complex color intensity. The image of contrast modification results has a more complex color intensity or more varied pixel value. Obtained the number of pairs (p, q) RLE in the image of contrast modification results is less than the original image, with the pair ratio (p, q) RLE ranges from 0.64% to 1.59%. Although this image has a more varied pixel value than its original image, it can produce a compression ratio of the number of pairs (p, q) RLE.
Pendampingan Digital Marketing Produk UMKM Desa Manggihan Kabupaten Semarang Budi Hartono; Veronica Lusiana; Kristiawan Nugroho; Mohammad Riza Radyanto
Jurnal Kabar Masyarakat Vol. 2 No. 1 (2024): Februari : JURNAL KABAR MASYARAKAT
Publisher : Institut Teknologi dan Bisnis Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54066/jkb.v2i1.1634

Abstract

Located in Getasan subdistrict, Semarang district, Manggihan village has 506 families. Most of the population works as farmers, cattle breeders and entrepreneurs. The problem faced is that micro, small and medium enterprises (MSMEs) cannot market their products widely. The superior products are mushroom chips, onion crackers and processed catfish. Marketing of these products experienced a decline in turnover during the Covid 19 Pandemic. The solution to this problem is to provide MSME partners who are affected by the pandemic through digital marketing assistance. Empowerment through this assistance involves various elements: academics (Lecturers, Unisbank Semarang Students), government (Semarang Village and Regency Government), business (farmers, MSMEs, digital marketing providers). The method used to solve this problem uses business assistance through digital marketing training with social media, creating market place accounts, logo branding and etiquette. The output target that partner MSMEs want to achieve is helping increase turnover through post-pandemic digital marketing and strengthening product branding and expanding markets
Pengaruh Ekstraksi Fitur Tekstur Pada Hasil Klastering Data Citra Buah Menggunakan Metode K-Means Cluster Lusiana, Veronica; Al Amin, Imam Husni; Hartono, Budi
Journal of Computer System and Informatics (JoSYC) Vol 5 No 4 (2024): August 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v5i4.5770

Abstract

Penelitian ini bertujuan untuk menganalisis pengaruh ekstraksi fitur tekstur menggunakan metode grey level co-occurence matrix (GLCM) dan local binary pattern (LBP) pada hasil klastering data citra. Ekstraksi fitur tekstur dilakukan pada data uji 30 citra buah matang dan citra buah busuk. Melalui percobaan diperoleh hasil metode ekstraksi fitur LBP dapat menaikan nilai fitur kontras dan menurunkan nilai fitur korelasi. Pada fitur energi, dengan atau tanpa LBP maka perbedaan nilai fitur ini tidak terlalu jauh. Metode GLCM dan LBP berpengaruh pada hasil klastering data citra menggunakan k-means clustering. Data uji tanpa ekstraksi tekstur LBP, diperoleh dua alternatif hasil. Alternatif pertama, anggota klaster 1 yaitu 24 data dan klaster 2 yaitu 6 data. Alternatif kedua, anggota klaster 1 yaitu 22 data dan klaster 2 yaitu 8 data. Pada data uji dengan ekstraksi tekstur LBP, diperoleh tiga alternatif hasil. Alternatif pertama, anggota klaster 1 yaitu 23 data dan klaster 2 yaitu 7 data. Alternatif kedua, anggota klaster 1 yaitu 17 data dan klaster 2 yaitu 13 data. Alternatif ketiga, anggota klaster 1 dan klaster 2 masing-masing 15 data.
Penerapan K-Means Clustering Untuk Mengelompokkan Data Transaksi Penjualan (Studi Kasus pada Wijaya Hijab) Widyawati, Lanjar; Lusiana, Veronica
Jutisi : Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Vol 12, No 3: Desember 2023
Publisher : STMIK Banjarbaru

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35889/jutisi.v12i3.1386

Abstract

UKM Wijaya Hijab Outfit is a shop engaged in Muslim fashion. The problem that occurs in this shop is the difficulty in supplying product stock that is in high demand, quite attractive, and less desirable by consumers. To prevent product shortages and excess stock, a system is needed to classify products using the K-Means Clustering Algorithm into 3 groups, namely highly desirable, moderately desirable, and less desirable. The data used in this study are sales transaction data for 12 months, out of 38 products processed using RapidMiner Software, there is 1 product that is a member of cluster 1 with the most interested category, 2 products of cluster member 2 categories of sufficient interest, and 35 products of cluster 3 members who are less fans. The expected objective of this research is to determine the stock of products so that excess and shortage of product stock does not occur. So that the inventory of goods can be controlled and can help improve stock management improvements and sales strategies at the store.Keywords: Clustering; K-Means Algorithm; Stock Management; Sales Transaction Data AbstrakUKM Wijaya Hijab Outfit merupakan sebuah toko yang bergerak dibidang fashion muslim. Permasalahan yang terjadi pada toko ini yaitu kesulitan dalam persediaan stok produk yang sangat diminati, cukup diminati, dan kurang diminati oleh konsumen. Untuk mencegah kekurangan dan kelebihan stok produk maka dibutuhkan sistem untuk mengelompokkan produk menggunakan Algoritma K-Means Clustering menjadi 3 kelompok yaitu sangat diminati, cukup diminati, dan kurang diminati. Data yang digunakan pada penelitian ini yaitu data transaksi penjualan selama 12 Bulan dari 38 produk yang diolah menggnakan Software Rapid Miner terdapat 1 produk yang menjadi anggota cluster 1 dengan kategori peminat terbanyak, 2 produk anggota cluster 2 kategori cukup peminatnya, dan 35 produk anggota cluster 3 yang kurang peminatnya. Tujuan yang diharapkan dari penelitian ini adalah untuk menentukan penyetokan produk agar tidak terjadi kelebihan dan kekurangan stok produk. Sehingga persediaan stok barang dapat terkontrol dan dapat membantu memperbaiki peningkatan manajemen stok dan strategi penjualan pada toko. 
Uji akurasi Metode KNN dan Citra HSI dalam Mengklasifikasi Batik Solo Berdasarkan Motif Setiaji, Isnan; Lusiana, Veronica
Jutisi : Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Vol 12, No 3: Desember 2023
Publisher : STMIK Banjarbaru

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35889/jutisi.v12i3.1377

Abstract

Batik is an Indonesian national artwork made with special techniques. Batik patterns contain meanings and philosophies from various customs and cultures that developed in Indonesia, and each region in Indonesia has different styles and characteristics due to the variety of batik motifs and colors. Therefore, digital images can be used as a first step in identifying Solo batik motifs because image processing is a highly developed research. Starting with the detection process on items, grouping items, and determining the right type of batik motif. this classification process using the KNN (K-Nearest Neighbor) method is converted to an HSI (Hue, Saturation, Intensity) image making it easier for image extraction. This research uses 50 training data and 25 test data, consisting of 10 Sidomukti batik data, 10 Parang batik data, 10 Kawung batik data, 10 Truntum batik data, 10 Satrio Manah batik data, the final result with testing and calculation of accuracy using the KNN algorithm is 80%.Keywords: K-Nearest Neighbor; Hue-Saturation-Intensity; Classification; Solo Batik AbstrakBatik adalah karya seni nasional Indonesia yang dibuat dengan teknik khusus. Corak-corak batik mengandung makna dan filosofi dari berbagai adat istiadat dan budaya yang berkembang di Indonesia, dan setiap daerah di Indonesia memiliki gaya dan ciri khas yang berbeda. karena beragamnya motif dan warna batik. Oleh karena itu, gambar digital dapat digunakan sebagai langkah awal dalam mengidentifikasi motif batik Solo karena proses pengolahan gambar adalah penelitian yang sangat berkembang. Dimulai dengan proses deteksi pada item, pengelompokan item, dan menentukan jenis motif batik yang tepat. proses klasifikasi ini menggunakan metode KNN (K-Nearest Neighbor) dikonversi ke citra HSI (Hue, Saturation, Intensity) sehingga memudahkan untuk ekstraksi citra. Penelitian ini menggunakan 50 data latih dan 25 data uji, terdiri dari 10 data batik Sidomukti, 10 data batik Parang, 10 data batik Kawung, 10 data batik Truntum, 10 data batik Satrio Manah, hasil akhir dengan pengujian dan perhitungan akurasi menggunakan algoritme KNN sebesar 80%. 
Rekayasa Ulang Proses Bisnis Kelompok Tani Parijotho Muria Kudus Melalui Penerapan Mesin Pengering Cerdas Riza Radyanto, Mohammad; Ma’sum, Muhammad Ali; Lusiana, Veronica
Jurnal Abdimas Mandiri Vol. 8 No. 3
Publisher : UNIVERSITAS INDO GLOBAL MANDIRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36982/jam.v8i3.4618

Abstract

Desa Colo Kecamatan Dawe Kabupaten Kudus merupakan sentra budidaya tanaman Parijoto (Medinella Speciosa Blume) buah endemik yang banyak tumbuh di lereng Gunung Muria pada ketingggian 900-1200 mdpl. Mitra pengabdian adalah Kelompok Tani Parijotho Muria Kudus yang membudidayakan buah parijoto hingga pengolahan hasil panen. Dalam proses produksi dan budi dayanya kelompok ini dihadapkan pada permasalahan rendahnya produktivitas pengolahan hasil panen dan keseragaman mutu produk yang tidak sama karena belum memiliki standar mutu. Hal tersebut disebabkan karena alat produksi dan pemrosesannya masih menggunakan cara yang sederhana dan manual karena keterbatasan sumber daya. Metode kegiatan pengabdian yang dilakukan adalah rekayasa ulang proses bisnis dalam bentuk diseminasi hasil penelitian dosen berupa pemanfaatan alat produksi cerdas berbasis Internet of Things (IoT) salah satunya adalah mesin pengering buah parijoto yang menggunakan sistem arduino dengan tujuan agar petani meningkatkan produktivitasnya dalam mengolah hasil panen. Selain itu, melalui kegiatan pelatihan dan sosialisasi pentingnya pemanfaatan teknologi cerdas dalam proses pengolahan hasil panen, paska pengabdian masyarakat petani memiliki peningkatan level keberdayaan mitra dari sisi aspek produksi, manajemen dan sosial kemasyarakatan berupa meningkatnya pengetahuan dan ketrampilan. Penerapan teknologi cerdas pada alat produksi memberikan dampak signifikan berupa: pemanfaatan alat pengering berteknologi IoT, terjadi kenaikan pasokan bahan baku dari semula 50% menjadi 70 %, produktivitas meningkat dari 10 liter per hari menjadi 15 liter per hari. Hasil dari kegiatan pengabdian ini berimplikasi pada peningkatan produktivitas dan mutu produk hasil panen melalui standarisasi mutu dan proses produksi.
Peningkatan Akurasi Temu Kembali Citra Berbasis Konten dengan Modifikasi Kontras Histogram Equalization dan Fast Fourier Transform Hartono, Budi; Lusiana, Veronica; Eniyati, Sri
Building of Informatics, Technology and Science (BITS) Vol 6 No 3 (2024): December 2024
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v6i3.6418

Abstract

Image retrieval is a way to search for images in an image database based on the content or contents of the image or Content-Based Image Retrieval (CBIR). This study aims to develop a retrieval system using Fast Fourier Transform (FFT) for image texture feature extraction. The test image and image database consist of four Batik motif textures—contrast modification using Histogram Equalization. The level of similarity between the test image and the image database is calculated using Manhattan Distance. The study results show a difference in the accuracy of the retrieval results between images without and with contrast modification. In images with contrast modification, the accuracy of the search results increases by 71.4%. System performance is evaluated based on the level of accuracy calculated using the Precision, Recall, and F1-score values. Further research is still needed to test the accuracy of image retrieval results, especially in pre-processing image textures with other batik motifs.
Perluasan Pemasaran melalui Literasi Aplikasi Shopee bagi UMKM Paguyuban Lentera Mranggen Demak Supriyanto, Edy; Lestariningsih, Endang; Murti, Hari; Redjeki, Rara Sriartati; Handoko, Widiyanto Tri; Ardhianto, Eka; Soelistijadi, R.; Wismarini, Theresia Dwiati; Wahyudi, Eko Nur; Lusiana, Veronica
Jurnal Pengabdian Pada Masyarakat Vol 9 No 4 (2024): Jurnal Pengabdian Pada Masyarakat
Publisher : Universitas Mathla'ul Anwar Banten

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30653/jppm.v9i4.989

Abstract

Pelaku usaha UMKM adalah kelompok penting yang menggerakkan perekonomian mikro dimasyarakat. Paguyuban UMKM Lentera yang terletak di Mranggen Demak, sebelah timur pinggir kota Semarang, juga perlu mendapatkan perhatian untuk meningkatkan kemampuan pengelolaan dan pendapatan. Hal ini dilihat dari maraknya pembukaan minimarket yang tumbuh dibanyak area penduduk. Permasalahan yang dihadapai saat ini dalah area pemasaran yang terbatas dan jumlah pendapatan yang saat ini stagnan dan cenderung menurun. Solusi yang ditawarkan atas permasalahan adalah adanya ekspansi pasar melalui pembukaan toko online. Pelaksanaan kegiatan ini menggunakan teknik Participatoty Action Research (PAR) dengan bentuk seminar, pelatihan, dan pendampingan. Hasil yang diperoleh adalah meningkatnya pemahaman anggota UMKM Lentera terhadap manfaat, resiko penggunaan toko online, serta keberhasilan para anggota UMKM Lentera untuk membuka toko online sebesar 64,28% dari jumlah peserta keseluruhuan. Toko online yang dimiliki perserta lengkap dengan foto produk dan harga yang siap bersaing. Sebagai bentuk refleksi perlua danya pendampingan dan kegiatan secara berlanjut untuk meningkatkan pemasaran dari berbagai aspek. MSME entrepreneurs are an important group that drives the micro-economy into society. The Lentera MSME Association, which is located on Mranggen Demak, eastern of the edge of Semarang city, also needs attention to improve management capabilities and income. This can be seen from the widespread opening of minimarkets which are growing in many populated areas. The problems currently faced are the limited marketing area and the amount of income which is currently stagnant and tends to decrease. The solution offered to the problem is market expansion through opening an online shop. The implementation of this activity uses Participatory Action Research (PAR) techniques in the form of seminars, training and mentoring. The results obtained were an increase in the understanding of MSME Lentera members regarding the benefits, risks of using online shops, as well as the success of MSME Lentera members in opening online shops amounting to 64.28% of the total number of participants. The online shop owned by participants is complete with product photos and prices that are ready to compete. As a form of reflection on the need for ongoing assistance and activities to improve marketing in various aspects.
Deteksi Jenis Sayuran dengan Tensorflow Dengan Metode Convolutional Neural Network Hidayat, Agung Rizqi; Lusiana, Veronica
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 6, No 2 (2022): EDISI SEPTEMBER
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v6i2.512

Abstract

Vegetables are food ingredients of plant origin that have a high water content, vegetables can be consumed fresh or processed into a dish. The diversity of vegetables in the world causes many classification processes for vegetables. Such as classification based on cultivation method, edible organs, botanical classification and classification based on growing conditions. In this study, a dataset of 17 types of vegetables and 2,550 images of vegetables were used. The vegetable species classification process uses the Convolutional Neural Network (CNN) algorithm because it has good ability in classifying image objects. The trial process was carried out using five smartphones with an Android-based operating system. The process of designing this android-based application uses the python programming language with the Tensor flow module for the testing and training process of data. The final result of the accuracy test on vegetables resulted in an average accuracy of recognizing the types of vegetables by 70% with one of the results of the classification test on vegetables producing the highest accuracy rate of 86%.
Co-Authors Adi Nugroho, Hermawan Aisyah Nur Ramadhayani Alfian, Riyan Antono Adhi ARIFUDIN, WAHYU Aryasatya, Rakryan budi hartono Budi Hartono Budi Hartono Deva Ega Marinda Dewi Handayani Untari Ningsih Dian Kristiawan Nugroho Dimas Wahyu Edy Supriyanto Edy Winarno Eka Ardhianto Eko Nur Wahyudi Endang Lestariningsih Febriana, Trissa Noor Aulia Felix Andreas Sutanto Hari Murti Hartono, Budi Hartono, Budi Hidayat, Agung Rizqi Ilham Ramadhan, Hafidh Imam Husni Al Amin Iskandar Zulkarnein Jefri Alfa Razak Krisna Aditya Pratama Kristianto, Teguh Ma’sum, Muhammad Ali Miftah Khul Janah Muhammad Muslimin Ningsih, Dewi Handayani .U Oka Rosalin, Agnes Pusdita, Tistantia R. Soelistijadi Radyanto, Mohammad Riza Ramadhani, Insan Rara Sri Artati Redjeki Ratnaduhita, Aurellia Razak, Jeffri Alfa Rina Candra Noor Santi Sariyun Naja Anwar Setiaji, Isnan Sri Eniyati Sri Wahyuni Sumarno, Davis Danendra Tahta Febri P, Gilar Taufan Maynard Prananda Sancaka1 Teguh Khristianto Umi Kholifah Wahyu Priyo Atmaja WAHYU PRIYO ATMAJA Widiyanto Tri Handoko Widyawati, Lanjar Wismarini, Th Dwiati Wiwien Hadikurniawati Wulan Nur Afifah, Wulan Nur Zulkarnein, Iskandar