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All Journal Informatika Mulawarman: Jurnal Ilmiah Ilmu Komputer Sinkron : Jurnal dan Penelitian Teknik Informatika SemanTIK : Teknik Informasi JURNAL MEDIA INFORMATIKA BUDIDARMA Indonesian Journal of Artificial Intelligence and Data Mining INOVTEK Polbeng - Seri Informatika EKONOMIS : Journal of Economics and Business IKRA-ITH Informatika : Jurnal Komputer dan Informatika Jurnal Sisfokom (Sistem Informasi dan Komputer) Jurnal Teknologi Sistem Informasi dan Aplikasi Informatik : Jurnal Ilmu Komputer SEINASI-KESI Jurnal Riset Informatika JURNAL MANAJEMEN BISNIS JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Jurnal Teknologi Informasi dan Pendidikan Journal Cerita: Creative Education of Research in Information Technology and Artificial Informatics Jurnal Kajian Manajemen dan Wirausaha Idealis : Indonesia Journal Information System SKANIKA: Sistem Komputer dan Teknik Informatika Jurnal Teknik Informatika (JUTIF) Jurnal Pendidikan dan Teknologi Indonesia Kresna: Jurnal Riset dan Pengabdian Masyarakat Bit (Fakultas Teknologi Informasi Universitas Budi Luhur) Jurnal Sisfotek Global Prosiding Seminar Nasional Sisfotek (Sistem Informasi dan Teknologi Informasi) Jurnal Ticom: Technology of Information and Communication Telematika MKOM SmartComp Jurnal Ticom: Technology of Information and Communication Teknologi : Jurnal Ilmiah Sistem Informasi
Deni Mahdiana
Program Studi Sistem Informasi, Fakultas Teknologi Informasi, Universitas Budi Luhur
Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Social Sciences

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Desain E-Commerce Wahib Collection Dengan Business Model Canvas Untuk Meningkatkan Penjualan Manda, Seftifin Ratna; Ariesta, Atik; Mahdiana, Deni; Hin, Lauw Li; Ratna Kusumawardani
Jurnal Ticom: Technology of Information and Communication Vol 11 No 3 (2023): Jurnal Ticom-Mei 2023
Publisher : Asosiasi Pendidikan Tinggi Informatika dan Komputer Provinsi DKI Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70309/ticom.v11i3.97

Abstract

Perkembangan teknologi sekarang sangatlah pesat, salah satunya adalah internet. Internet menjadi topik utama dikalangan masyarakat sekarang, dengan adanya internet orangorang mampu melakukan berbagai aktivitas seperti jual beli barang secara online. Jaman sekarang jual beli sangat mudah dengan adanya model bisnis yang sangat popular yakni ecommerce jadi pelanggan tidak harus datang ke toko untuk transaksi pembelian. Toko Wahib Collection merupakan toko yang bergerak dibidang penjualan pakaian. Produk yang dijual berbagai macam pakaian seperti daster, pakaian wanita, kaos,celana, jaket. Toko Wahib Collection berdiri sejak tahun 2000 usaha milik keluarga dan diturunkan pada anak-anaknya. TokoWahib Collection terdapat permasalahan yakni toko Wahib Collection memasarkan produknya hanya membuka lapak tokodi pasar saja dengan jangkauan pemasaran hanya di sekitar toko, pencatatan pada toko masih dilakukan secara manual sehingga pencatatan tidak sesuai, terjadi penurunan penjualan dikarenakan pandemi Covid-19 menerapkan social distancing dan orang-orang harus menaati protokol kesehatan dan menghindari kerumunan sehingga pasar menjadi sepi. Hal inilah yang menjadi latar belakang untuk memanfaatkan e-commerce sebagai platform penjualan dan pembelian secara online. Tujuan dari penelitian ini adalah agar jangkauan pemasaran semakin luas, pencatatan data akan tersimpan dengan baik pada website, dan penjualan dapat dilakukan secara online. Adapun metodologi yang digunakan yaitu wawancara, Analisis dokumen dan studi literatur dengan pengembangan sistemnya menggunakan Rapid Application Development (RAD). sehingga terbentuknya suatu sistem informasi penjualan menggunakan Content Management System (CMS) Wordpress. Business Model Canvas (BMC) digunakan untuk menentukan model bisnis yang diusulkan berdasarkanmodel bisnis yang sedang berjalan. Hasil penelitian ini pelanggan dapat melakukan pembelian secara online dengan menggunakan website tidak harus datang ke toko dan pencatatan pada toko sudah terkomputerisasi
SYSTEMATIC LITERATURE REVIEW OF THE CLASS IMBALANCE CHALLENGES IN MACHINE LEARNING Rifqi Fitriadi; Deni Mahdiana
Jurnal Teknik Informatika (Jutif) Vol. 4 No. 5 (2023): JUTIF Volume 4, Number 5, October 2023
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2023.4.5.970

Abstract

The significant growth of data poses its own challenges, both in terms of storing, managing, and analyzing the available data. Untreated and unanalyzed data can only provide limited benefits to its owner. In many cases, the data we analyze is imbalanced. An example of natural data imbalance is in detecting financial fraud, where the number of non-fraudulent transactions is usually much higher than fraudulent ones. This imbalance issue can affect the accuracy and performance of machine learning classification models. Many machine learning classification models tend to learn more general patterns in the majority class. As a result, the model may overlook patterns that exist in the minority class. Various research has been conducted to address the problem of imbalanced data. The objective of this systematic literature review is to provide the latest developments regarding the cases, methods used, and evaluation techniques in handling imbalanced data. This research successfully identifies new methods and is expected to provide more choices for researchers so that imbalanced data can be properly handled, and classification models can produce unbiased, accurate, and consistent results.
SYSTEMATIC LITERATURE REVIEW APPLICATION OF METHODS IN INFORMATION SYSTEMS DEVELOPMENT Gita Cahyani, Annisa Putri; Mahdiana, Deni
Jurnal Teknik Informatika (Jutif) Vol. 5 No. 4 (2024): JUTIF Volume 5, Number 4, August 2024
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2024.5.4.1954

Abstract

In today's rapidly changing digital age, information system development is critical to the growth and success of organizations and businesses. It is critical to select the appropriate system development method because it can impact many aspects of the system, including efficiency, dependability, and alignment with organizational requirements. Businesses or organizations may struggle to determine the best approach based on their project environment and specific requirements. The goal of this study is to gain a better understanding of the various approaches to systems development and how they work. In information systems, each system development technique's complexity and effectiveness will be investigated using a qualitative approach in conjunction with descriptive analysis. A better understanding of the features and benefits of each method, such as agile, waterfall, Rapid Application Development (RAD) and others, will be enable organizations to make more precise and goal-driven decisions. Furthermore, this study will look at previous research on a variety of topics and discussions, such as information system design and the practical application of cutting-edge software. Determine trends, best practices, and issues that have emerged during the development of current information systems. One of the motivations for this research is the growing complexity of project environments, as well as the need for dependable and efficient systems. Learning more about systems development techniques can assist organizations and businesses in lowering project risks, increasing efficiency, and identifying solutions that better meet their business goals. The waterfall method is most popular because it provides more control over the system development process.
IMPLEMENTATION OF DEEP LEARNING MODELS IN HATE SPEECH DETECTION ON TWITTER USING AN NATURAL LANGUAGE PROCESSING APPROACH Arifin, Muhammad; Mahdiana, Deni
Jurnal Teknik Informatika (Jutif) Vol. 5 No. 5 (2024): JUTIF Volume 5, Number 5, Oktober 2024
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2024.5.5.2043

Abstract

In the digital era, the misuse of the freedom to communicate on the internet often leads to problems such as the spread of hate speech, which can harm individuals based on race, religion, and other characteristics. This issue requires effective solutions for content moderation, particularly on social media platforms like Twitter. This research develops a deep learning model utilizing Natural Language Processing (NLP) to detect hate speech and aims to improve existing content moderation mechanisms. The methods used include data collection, preprocessing through techniques such as case folding, tokenization, lemmatization, and model creation using TensorFlow Extended (TFX) involving embedding, dense, and global pooling layers. The model is trained to optimize accuracy by minimizing the loss function and closely monitoring evaluation metrics. The results show that this model achieves a prediction accuracy of 84%, an AUC value of 0.796, and a binary accuracy of 76%. The conclusion of this research is that the use of deep learning and NLP in detecting hate speech offers a highly potential approach to enhancing digital content moderation, providing a solution that is not only efficient but also accurate.
SYSTEMATIC LITERATURE REVIEW ON THE APPLICATION OF UI/UX DESIGN METHODS IN SYSTEM DEVELOPMENT Ramadani, Romi; Mahdiana, Deni
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.2024.5.4.2073

Abstract

In the current modern digital era, system development is undoubtedly rapid and massive, especially across various sectors such as healthcare, business, and public services. In system development, many aspects are considered, one of which is the appearance of the user interface. Interface design becomes an intriguing aspect and has an influence on system or application development. System development surely involves user interface and user experience aspects as part of the human-computer interaction (HCI) discipline. This research aims to identify research opportunities in UI/UX aspects in system development, with data obtained from relevant journals spanning from 2019 to 2024 as a representation of the latest study on UI/UX design research. This study utilizes the Systematic Literature Review (SLR) method. The results of this research provide a systematic literature review of existing studies on UI/UX design. This research can benefit the HCI community by applying methods in UI/UX design in system development to shape the direction of future research.
Optimizing Change Management Using the Analytical Hierarchy Process Method: Analysis with Super Decisions Software Ken Putri, Lulasnov Viola Prameswari; Mahdiana, Deni
JURNAL SISFOTEK GLOBAL Vol 14, No 2 (2024): JURNAL SISFOTEK GLOBAL
Publisher : Institut Teknologi dan Bisnis Bina Sarana Global

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38101/sisfotek.v14i2.15661

Abstract

A major challenge in change management lies in selecting unbiased policy alternatives that promote effective decision-making. To overcome this obstacle, this research utilizes Super Decisions software to perform AHP calculations and assess various change management policies. The methodology used includes identifying key criteria affecting change management, structuring the problem into an AHP hierarchy, collecting data through expert surveys or interviews, and analyzing the data using Super Decisions software to determine the criteria weights and optimal policy alternatives. The study revealed that improving Standard Operating Procedures (SOPs) emerged as the most optimal policy alternative. The implementation of AHP demonstrated its ability to provide a systematic and unbiased framework, assisting top management in strategic decision-making. Overall, this study underscores the value of AHP in reducing bias and informing sound change management policies. The study recommends continued adoption and adjustment of the AHP method to suit organizational needs.
Comparative Analysis of Logistic Regression, SVM, Xgboost, and Random Forest Algorithms for Diabetes Classification Hidayat, Rahmat; Mahdiana, Deni; Fergina, Anggun
Jurnal Teknologi Sistem Informasi dan Aplikasi Vol. 7 No. 1 (2024): Jurnal Teknologi Sistem Informasi dan Aplikasi
Publisher : Program Studi Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/jtsi.v7i1.38258

Abstract

Diabetes is a disease that can attack anyone, where this disease occurs because there is excessive sugar content in the human body. Therefore, prevention of diabetes is necessary so that preventive measures can be given as early as possible. In this research, a classification process will be carried out using the Random Forest algorithm, Support Vector Classification and XGBoost. This research will use a dataset which consists of 768 total data with a distribution of non-diabetic data of 500 and a distribution of diabetes data of 268. For the classification results after testing, the results were that classification using random forest obtained a testing accuracy of 79.22%, with using support vector classification gets a testing accuracy of 76.62%, using XGBoost gets a testing accuracy of 79.22% using Logistic Regression gets a testing accuracy of 80.52%. The best classification value is obtained when using the Logistic Regression algorithm, namely with a precision of 79.00%, recall of 77.00% and F1-Score of 78.00%.
PENERAPAN ALGORITMA K-MEANS UNTUK KLASTERISASI INDEKS STANDAR PENCEMARAN UDARA Mahendrasyah, Ihjal; Diana, Anita; Rusdah; Mahdiana, Deni
TEKNOLOGI: Jurnal Ilmiah Sistem Informasi Vol 14 No 2 (2024): July
Publisher : Universitas Pesantren Tinggi Darul 'Ulum (Unipdu) Jombang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26594/teknologi.v14i2.4088

Abstract

Lingkungan merupakan satu ruang utuh yang berisi semua benda, daya, keadaan, serta makhluk hidup di dalamnya, termasuk juga manusia dan perilakunya yang mempengaruhi alam. Penting untuk menjaga lingkungan agar tidak timbul pencemaran yang dapat menciptakan kondisi yang tidak sehat. Pengelompokkan pencemaran lingkungan dapat mempermudah pemerintah dalam pertimbangan wilayah mana saja yang memerlukan atensi lebih dalam penegakkan perlindungan dan pengelolaan lingkungan hidup. Pengelompokan yang digunakan menggunakan algoritma K-Means Clustering yang dapat mengelompokkan data ke dalam kelompok yang sama dan data yang berbeda ke dalam kelompok yang berbeda. Klasterisasi dilakukan terhadap data indeks standar pencemaran udara provinsi DKI Jakarta berdasarkan parameter pencemaran udara. Sehingga dapat diketahui informasi mengenai kualitas udara terutama di wilayah provinsi DKI Jakarta. Data yang digunakan adalah data tahun 2021 dan diperoleh dari situs resmi Jakarta Open Data. Dataset berisi 365 hari pemantauan kualitas udara tahun 2021 serta parameter pencemaran udara seperti pm10, pm25, so2, co, 03, dan n02. Data yang telah diperoleh kemudian diolah dengan tools RapidMiner menggunakan Algoritma K-Means Clustering dalam 3 cluster, diketahui hasil klasterisasi yaitu kategori kualitas udara sehat pada cluster 0 terdiri dari 39 hari, kategori kualitas udara sedang pada cluster 1 yang terdiri dari 128 hari, dan kategori kualitas udara tidak sehat pada cluster 2 yang terdiri dari 198 hari. Sehingga dapat diketahui hasil klasterisasi dengan Algoritma K-Means terhadap kualitas udara di Provinsi DKI Jakarta tahun 2021 cenderung berada di kategori tidak sehat. Hasil klasterisasi ini diharapkan dapat menjadi masukan bagi pemerintah dalam upaya penanganan daerah yang mengalami pencemaran lingkungan.
The Effect of Using Decision Support System on Company Benefits at PT Mitra Integrasi Informatika (Case Study on Employees of The IT Deplover Section) A Djafar, Muhammad Agung; Mahdiana, Deni
Ekonomis: Journal of Economics and Business Vol 9, No 1 (2025): Maret
Publisher : Universitas Batanghari Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33087/ekonomis.v9i1.1928

Abstract

In the era of digitalization, companies are required to operate in tandem with technological developments and are faced with rapid changes in consumption patterns from consumers. One sign of change in the competitive arena is the shift from bureaucratic organizations to organizational forms that are sensitive to vertical, horizontal, and external challenges and opportunities. Companies are currently being helped by the development of management information systems that make it easier to process information into strategic decisions, including the Decision Support System. In organizational benefits, there are three main constructs that may be affected: effective decisions, competitive advantage, and stakeholder satisfaction. Penuli uses the SPSS 23.0 for Windows program in processing data and an analytical framework to evaluate the use of the Decision Support System on company benefits at PT Mitra Integrasi Informatika. Based on the results of the simple linear regression test analysis, the results obtained are the magnitude of the partial relationship of the decision support system. The magnitude of the partial relationship of the decision support system (X) to the benefits of the company (Y) is 5,863 with a p-value of 0.000 <alpha 0.05, stating that Ho is rejected, which means that there is a partial positive influence relationship from the decision support system (X) on company benefits (Y).
Penerapan Algoritma K-Nearest Neighbor pada Twitter untuk Analisis Sentimen Masyarakat Terhadap Larangan Mudik 2021 Lestari, Diah Ayu; Mahdiana, Deni
Informatik : Jurnal Ilmu Komputer Vol 17 No 2 (2021): Agustus 2021
Publisher : Fakultas Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52958/iftk.v17i2.3629

Abstract

Media sosial Twitter merupakan media yang banyak digunakan oleh masyarakat dalam menyampaikan sebuah opini yang sedang hangat dibahas. Kebijakan larangan mudik yang diterapkan oleh pemerintah saat ini belum diketahui opini atau pendapat masyarakat terhadap pelaksanaan larangan mudik 2021 ini, sehingga pemerintah kesulitan dalam mengevaluasi kebijakan larangan mudik tersebut. Penelitian ini akan melakukan analisis sentimen menggunakan algoritma K-Nearest Neighbor (K-NN) dan menerapkan metodologi Cross-Industry Standard Process for Data Mining (CRIPS-DM). Pada penelitian ini data bersih yang digunakan berjumlah 4.799 tweet, yang diambil dari media sosial twitter pada 04 April 2021 – 17 Mei 2021 dengan sentimen positif berjumlah 834 tweet dan 3.965 tweet sentimen negatif. Penelitian ini menghasilkan bahwa K-NN dapat diimplementasikan dengan baik dikarenakan mencapai nilai akurasi sebesar 86.67 % dengan nilai recall 39.52 %, precision 70.97 % dan spencificity sebesar 96.60%  menggunakan split data perbandingan 80 untuk data training dan 20 untuk data testing dengan nilai k=3. Sehingga dapat dikatakan bahwa algoritma K-NN dapat mengklasifikasikan data secara benar dan baik.
Co-Authors A Djafar, Muhammad Agung Abdurrahman, Faris Nur Achmad Fauzi adang badru jaman,anggun fergina, adang badru jaman,anggun fergina Ade Davy Wiranata Ade Setiadi Adi Saputra, Yulian Adiputra, Januar Ahadti Puspa Sari Airlambang, Dwiki Akhmad Wijaya Kusuma Amalia Khairunisa Andhika Arethuza Ari Anita Diana Arif Rahman Arifin Istighfari Zahro Atik Ariesta auddie mahlyda Bagas Wahyu Putratama Bayu Aji Susilo Brury Trya Sartana Chairul Kahfi Dahlia Mariyam Ohorella Daniel Iskandar Dedy Mirwansyah Devit Setiono Diah Ayu Lestari, Diah Ayu Diana Putri djuan narita Dzakiyyah, Syifa Ghina Erly Krisnanik Fahlevi, Noval Febriansyah Ramadhan Gita Cahyani, Annisa Putri Haderiansyah Haderiansyah Hasibuan, Tuhfatul Habibah Hikmah, Maulida Irgi Arifal Nulhakim janah purwanti Jejen Jaenudin Jumaryadi, Yuwan Ken Putri, Lulasnov Viola Prameswari Khafistia Hayyu Kharmytan, Yan Baktra Kraugusteeliana Kraugusteeliana Kusumawardhany, Nidya Kusumo Adi Lauw Li Hin Leonardus Adityo Toto Pratomo Maemunah Maemunah Mahendrasyah, Ihjal Manarul Haikal Casandy Manda, Seftifin Ratna Maulana, Hanif Mirza Sutrisno Mohammad Aldinugroho Abdullah Muhammad Abduh Khairullah Muhammad Arifin Mutia Hasanah Nurramdhani, Helena Purwo Setyo Aji putri yani, putri Putri, Jasmin Maula Rahmat Hidayat Ramadani, Romi Ratna Kusumawardani Ratna Kusumawardani Renaldi Setiawan Putra Rifqi Fitriadi Riskiyono, Fajar Rusdah Rusdah Rusdah Sarastuti, Elina Seftifin Ratna Manda Solehan Solehan Sri Devi Yulita Sugiarto S Supardi Supardi Syahid, Achyar Jhonathan Syifa Aryanti Tjahjanto, Tjahjanto Wiguna, Kevin Zahran, Aziz