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All Journal Explore: Jurnal Sistem Informasi dan Telematika (Telekomunikasi, Multimedia dan Informatika) Scan : Jurnal Teknologi Informasi dan Komunikasi Jurnal Informatika dan Teknik Elektro Terapan Jurnal IPTEK Jurnal Sistem Informasi dan Bisnis Cerdas JURNAL INSTEK (Informatika Sains dan Teknologi) Prosiding Seminar Nasional Sains dan Teknologi Terapan JURNAL TEKNOLOGI DAN OPEN SOURCE Data Science: Journal of Computing and Applied Informatics Jurdimas (Jurnal Pengabdian Kepada Masyarakat) Royal IJEEIT : International Journal of Electrical Engineering and Information Technology Applied Technology and Computing Science Journal Journal of Information Systems and Informatics Abdimas Universal bit-Tech Jurnal Teknologi Dan Sistem Informasi Bisnis Aviation Electronics, Information Technology, Telecommunications, Electricals, Controls (AVITEC) JATI (Jurnal Mahasiswa Teknik Informatika) International Journal of Advances in Data and Information Systems Jifosi Nusantara Science and Technology Proceedings KLIK: Kajian Ilmiah Informatika dan Komputer Jurnal Penelitian Inovatif Konstelasi: Konvergensi Teknologi dan Sistem Informasi PELS (Procedia of Engineering and Life Science) NUSANTARA: Jurnal Pengabdian Kepada Masyarakat Jurnal Teknik Mesin, Industri, Elektro dan Informatika Prosiding Seminar Nasional Rekayasa Teknologi Industri dan Informasi ReTII Jurnal Ilmiah Teknik Informatika dan Komunikasi Madani: Multidisciplinary Scientific Journal Scientica: Jurnal Ilmiah Sains dan Teknologi Student Research Journal Jurnal Informatika Polinema (JIP) Merkurius: Jurnal Riset Sistem Informasi dan Teknik Informatika Neptunus: Jurnal Ilmu Komputer dan Teknologi Informasi Jurnal ilmiah teknologi informasi Asia
Amalia Anjani Arifiyanti
Universitas Pembangunan Nasional “Veteran” Jawa Timur
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Population Density Cluster Analysis in DKI Jakarta Province Using K-Means Algorithm Amalia Anjani Arifiyanti; Farhan Setiyo Darusman; Brahmantio Widyo Trenggono
Journal of Information System and Informatics Vol 4 No 3 (2022): Journal of Information Systems and Informatics
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v4i3.315

Abstract

This study aims to analyze clusters based on the area and population density of the area and population density of the area in DKI Jakarta Province in 2015 using the data mining method by clustering as the first step in planning for population equality. The subject of analysis in this study is a village located in the province of DKI Jakarta which is recorded based on the area and population density in each sub-district until 2015 with several stages, namely data understanding, data processing or cleansing, cluster tendency assessment, clustering, cluster review. From this study, the results were obtained that the data tended to be clustered because the statistical value of Hopkins was close to the value of 0 and in VAT there was a vague picture of clusters that might be formed. Based on this, cluster creation is carried out using the K-Means Algorithm. Based on the results, there are 3 clusters formed, namely cluster 0 (not densely populated), cluster 1 (medium population density), and cluster 2 (densely populated). These results can be used as a basis for policy making in population management.
Design and Build a Customer Segmentation Website at the Hijabiken Online Store Oktania Purwaningrum; Amalia Anjani Arifiyanti; Dhian Satria Yudha Kartika
Procedia of Engineering and Life Science Vol 2 No 2 (2022): Proceedings of the 4th Seminar Nasional Sains 2022
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/pels.v2i2.1286

Abstract

Data can be processed to produce useful information for an organization/company. Example of transaction data that is processed to segment customers. Customer segmentation needs to be done so that sellers can find out market conditions and can be taken into consideration in developing marketing strategies. Customer segmentation can also make sellers know their customers well. Of course, customer segmentation needs to be done at the Hijabiken Online Store, this store sells Muslim products such as hijabs. Seeing the current conditions in the store, data storage is still manual which can be prone to damage and loss. Therefore, in this study, we will build a website that can store and process transaction data. Website design using DFD, CDM, PDM, and mockups. Segmentation is carried out using data mining science in the clustering process. Clustering is done with the K-Means algorithm and LRFM model. The results of testing every function of the website can be run properly.
Exploratory Data Analysis dalam Konteks Klasifikasi Data Mining Eka Dyar Wahyuni; Amalia Anjani Arifiyanti; Mashita Kustyani
Retii Prosiding Seminar Nasional ReTII Ke-14 2019
Publisher : Institut Teknologi Nasional Yogyakarta

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

Abstract

Each type of data has various forms and behaviors. Therefore, the process of data analysis cannot be standardized through a certain procedure. EDA is a data analysis approach that can be used in interpreting the information contained in data. EDA is flexible in adjusting data behavior and can be used for data observation through various points of view. This data analysis strategy can be used to complement the results of data mining classification analysis used to recognize data patterns. In this article it will be explained that EDA can help in enriching the results of data analysis and assist in the pre-processing stages of data mining classification. Data mining classification is done using the Naive Bayes Classifier algorithm and Logistic Regression.
Application of Augmented Reality in Food Ordering System Putu Anggi Suryantari; Rendi Panca Wijanarko; Seftin Fitri Ana Wati, S.Kom., M.Kom; Amalia Anjani Arifiyanti, S.Kom., M.Kom; Anita Wulansari, S.Kom., M.Kom; I Gusti Ayu Sri Deviyanti, ST., MT
IJEEIT : International Journal of Electrical Engineering and Information Technology Vol 6 No 1 (2023): March 2023
Publisher : NAROTAMA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29138/ijeeit.v6i1.2112

Abstract

Current digital trends put the need for information at the forefront, making information processingbetween authorities and organizations a priority. Information is a collection of data that has beenprocessed for use in future decision-making processes. When combined, they form an informationsystem. In the economic world, several food-related businesses have implemented informationsystems in their business fields related to data processing systems to carry out computerizedcommercial transactions. However, there are still many businesses that perform traditional serviceswith pencil and paper and have not been able to implement innovative ordering systems based ontechnological developments. One of the businesses experiencing this problem is Dapoer WidyaRestaurant. This study aims to form an ordering system with the PHP programming language and isdesigned using UML models and Augmented Reality (AR)-based menu innovations using Vuporia andUnity3D. System design is built by the SDLC (System Development Life Cycle) method. The result ofthis study is an ordering information system that includes table determination, integrated transactionreports for Dapoer Widya Restaurant staff, and AR-based menus that display 3D views of the menuserved.Keywords: ordering system, menu, augmented reality, SDLC
Asisten Virtual sebagai Pusat Layanan Informasi pada Perguruan Tinggi di Indonesia – A Systematic Literature Review Amalia Anjani Arifiyanti; Reisa Permatasari; Abdul Rezha Efrat Najaf
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 4 No. 2 (2023): Oktober 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v4i2.1222

Abstract

The ease of providing information services is one aspect of public services that must be fulfilled by higher education institutions. However, this requires quite a bit of resources to handle the large number of requests for information availability. Virtual assistants can be the answer to providing information easily and quickly. Virtual assistants have been widely used by various institutions to provide information services that are fast and can be accessed at any time. This study was conducted to study what types of methods and approaches can be applied to the development of virtual assistants in Indonesia. This study uses the Systematic Literature Review approach. A review was carried out on 13 selected articles that discussed the application of virtual assistants in higher education in Indonesia. As a result, virtual assistants can be applied in various forms with various development method approaches. In addition, it was also found that all academic service information provision and academic operational support owned by higher education institutions can be assisted by virtual assistants
Peramalan Jumlah Penderita Jenis Penyakit Utama Di Kota Surabaya Menggunakan Metode Autoregressive Integrated Moving Average (ARIMA) Tri Diana Rimadhani; Amalia Anjani Arifiyanti; Rizka Hadiwiyanti
Student Research Journal Vol. 1 No. 5 (2023): Oktober : Student Research Journal
Publisher : Sekolah Tinggi Ilmu Administrasi (STIA) Yappi Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/srjyappi.v1i5.612

Abstract

The decline in Covid-19 pandemic cases over the past few months before 2023 not only reduced Indonesia's challenges in dealing with other types of diseases. Surabaya city itself has health issues that need to be addressed, as indicated by an increase in several diseases in 2022. One attempt to handle disease cases is to predict the future case numbers to anticipate actions early on. By using data on the number of cases of Respiratory System Diseases during the year 2022, this data will be used to predict the number of cases in the coming months in 2023 by creating a variation of a univariate ARIMA forecasting model. Therefore, the research results show forecasted data that tend to increase when viewed from the analysis and the plotted graph of the forecast results.
ANALISIS SENTIMEN ULASAN PENGGUNA BSI MOBILE PADA GOOGLE PLAY DENGAN PENDEKATAN SUPERVISED LEARNING Amalia Anjani Arifiyanti; Nurisa Rahma Shantika; Anggy Oktaviana Syafira
Jurnal Informatika Polinema Vol. 9 No. 3 (2023): Vol 9 No 3 (2023)
Publisher : UPT P2M State Polytechnic of Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33795/jip.v9i3.1003

Abstract

Ulasan pengguna merupakan salah satu bentuk timbal balik dari pengguna yang sepatutnya dianalisis oleh pihak pengembang agar dapat digunakan sebagai dasar pengembangan aplikasi. Analisis sentimen dari ulasan pengguna dapat menjadi salah satu cara untuk mengetahui sentimen pengguna terhadap aplikasi. Analisis aplikasi m-banking Bank Syariah Indonesia yaitu BSI Mobile dilakukan dengan pendekatan klasifikasi dengan menggunakan supervised machine learning. Pada penelitian ini, model klasifikasi yang dibuat dengan algoritma Multinomial Naïve Bayes menghasilkan hasil evaluasi terbaik dengan nilai ROC area sebesar 0,84%. Hasil ini mengungguli hasil evaluasi SVM, Decision Trees, dan KNN. Namun sayangnya model klasifikasi yang dihasikan ini kurang mampu dalam memprediksi sentimen negatif sehingga ke depannya perlu peningkatan performa model klasifikasi untuk memperbaiki akurasi prediksi.
RANCANG BANGUN MULTI-PLATFORM MOBILE APPLICATION SISTEM INFORMASI PENDUKUNG PROGRAM MERDEKA BELAJAR Aghni Qisthina Al Rahma; Mohamad Irwan Afandi; Amalia Anjani Arifiyanti
Jurnal Informatika dan Teknik Elektro Terapan Vol 12, No 3 (2024)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jitet.v12i3.4753

Abstract

Aplikasi SILATURAHMI (Sistem Informasi Kolaborasi Terpadu Universitas, Pemerintah, Masyarakat, dan Industri) merupakan sistem informasi milik UPN ”Veteran” Jawa Timur yang dirancang untuk mengelola program MBKM dari pendaftaran hingga finalisasi penilaian konversi mata kuliah. Namun, sistem ini masih berbasis website yang dari awal dioptimasi untuk perangkat berbasis desktop. Pada perangkat berbasis mobile, sistem ini memiliki performa dan tampilan yang kurang baik sehingga muncul kebutuhan akan aplikasi berbasis mobile yang terpisah. Sistem informasi SILATURAHMI berbasis mobile dikembangkan dengan menerapkan metode Waterfall yang terdiri dari tahap communication, planning, modelling, construction, dan deployment dengan menggunakan framework flutter. Melalui metode ini, diharapkan sistem yang dihasilkan dapat  mempermudah pengguna, baik mahasiswa maupun dosen, dalam mengelola program MBKM melalui device berbasis mobile. Berdasarkan hasil pengujian yang dilakukan, Sistem Informasi SILATURAHMI berbasis mobile telah berhasil dijalankan di kedua sistem operasi yaitu AndroidOS dan iOS sesuai dengan proses bisnis yang telah direncanakan. Melalui sistem berbasis mobile ini dosen dan mahasiswa dapat lebih mudah dalam mengakses sistem informasi SILATURAHMI serta mengurangi kesalahan-kesalahan akibat tampilan dan performa yang kurang baik pada website
ANALISIS SENTIMEN ULASAN PENGGUNA ACCESS BY KAI MENGGUNAKAN METODE WORD2VEC DAN ALGORITMA SVM Ditha Lozera Devi; Amalia Anjani Arifiyanti; Seftin Fitri Ana Wati
Jurnal Informatika dan Teknik Elektro Terapan Vol 12, No 3 (2024)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jitet.v12i3.4892

Abstract

Beberapa ulasan dari pengguna KAI Access menyatakan sering terjadi gangguan pada saat pemesanan tiket. Hingga akhirnya pada tanggal 10 Agustus 2023 PT Kereta Api Indonesia melakukan peluncuran aplikasi Access by KAI sebagai bentuk upgrade dari aplikasi sebelumnya. Dengan adanya ulasan yang diberikan pengguna untuk aplikasi, perlu dilakukan analisis sentimen untuk melihat bagaimana pendapat dan reaksi pengguna dalam menggunakan aplikasi Access by KAI. Data ulasan pengguna diambil dari Google Play Store dan App Store. SEMMA dipilih sebagai metode pengembangan model data mining dengan tahapan dimulai dari Sample, Explore, Modify, Model, dan Assess. Analisis sentimen dilakukan dengan menggunakan metode Word2vec (CBOW dan Skip-gram) sebagai metode ekstraksi fitur dan 4 kernel SVM yang digunakan yaitu kernel linear, kernel polynomial, kernel RBF, dan kernel sigmoid. Hasil dari delapan skenario model klasifikasi yang dilakukan dengan menggabungkan metode Word2vec dan algoritma Support Vector Machine, dihasilkan satu skenario terbaik yaitu skenario model yang menggunakan algoritma SVM kernel RBF dengan metode Skip-Gram ditambah metode oversampling SMOTE dihasilkan nilai akurasi 81% dan nilai AUC sebesar 0.81.
Analisis Sentimen Pengguna Youtube Mengenai Analog Switch Off Menggunakan Word Embedding Dan Metode Long Short-Term Mochamad Suhri Ainur Rifky; Amalia Anjani Arifiyanti; Reisa Permatasari
Jurnal Teknik Mesin, Industri, Elektro dan Informatika Vol. 2 No. 3 (2023): September : JURNAL TEKNIK MESIN, INDUSTRI, ELEKTRO DAN INFORMATIKA
Publisher : Pusat Riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jtmei.v2i3.2273

Abstract

Analog Switch Off (ASO) or migration program from analog television to digital television is a program issued by the Ministry of Communication and Informatics in Indonesia. Some people provide different responses and opinions on YouTube comments about ASO. There are those who give positive or neutral comments. However, there were also those who gave negative comments. Sentiment analysis is a process that is carried out automatically in studying, retrieving, and processing textual data to obtain information and see responses or opinions about an issue or object towards positive, neutral or negative opinions. Thus sentiment analysis can be used as a reference in making organizational decisions, improving a service, or as a review of a product. Sentiment analysis was performed using word embedding with Word2Vec, and sentiment classification using the Long Short-Term Memory (LSTM) method. The results of the evaluation test are 92% accuracy, 92% precision, 92% recall, and 92% f1-score.
Co-Authors Abdul Rezha Efrat Najaf Achmad Fauzi Afandi, Mohamad Irwan Aghni Qisthina Al Rahma Agung Brastama Putra Agung Brastama Putra Akira Permata Ramadhani Al Rahma, Aghni Qisthina alathoillah, abdul hanif Ana Wati3, Seftin Fitri Ananda Lakunti A Andhyni, Cyntia Prisya Anggy Oktaviana Syafira Anita Wulansari Anita Wulansari, S.Kom., M.Kom Annisa Lusyani Zahra Anwar Sodik, Anwar Aprilia, Eka Fahira AryaRafa, Daud Audrey Septya Rosanti Bagus Utomo Basma Eno Ketherin Brahmantio Widyo Trenggono Brastama Putra, Agung Daniar, Ivan Faiz Devi, Ditha Lozera Dewi Safitri, Triyatul Dewi, Heni Lusiana Dharmawan, Ega Dhian Satria Yudha Kartika Diana Aqidatun Nisa Ditha Lozera Devi Eka Putri, Siti Oktavia Elfaretta, Syifa Saskia Fachrurrozy Nurqoulby Fandi, Rico Satria Farhan Setiyo Darusman Farhan Setiyo Darusman Fariska, Rahmah Putri Ferdiansyah, Rizky Fernaldy, Fabiyan Atha Fidyah Salsabila Putri Sillehu Firsttama, Risav Arrahman Fitri, Anindo Saka Hardiartama, Rendi I Gusti Ayu Sri Deviyanti Indira Setia Amalia Indra Fajar Novian Irwan Afandi, Mohamad Jannatuzzahra, Khoirunisa Ketherin, Basma Eno Kusumantara, Prisa Marga Kusumantara, Prisa Marga Luhur Indayanti Sugata, Tri M. Rizal Abdullah Rozi Mahanani, Anajeng Esri Edhi Marga Kusumantara, Prisa Marisca Amanda Hidayat Mashita Kustyani Maulana Arrasyid, Nizar Maulana Kharyska Abadi, Muhammad Mochamad Suhri Ainur Rifky Mochammad Fuad Pandji Mohamad Irwan Afandi Muhammad Burhanuddin F Narendra, Efriza Cahya Nilwanda, Leona Elsa Novian, Indra Fajar Nur Cahyo Wibowo Nur Rachman Nidhi Suryono, Muhammad Nurisa Rahma Shantika Nurjanti Takarini Oktania Purwaningrum Oktania Purwaningrum Oktania Purwaningrum Pandu Rizki Maulidiah Permatasari, Reisa Pradana, Rhendy May Putra, Satrio Honggonagoro Pramono Putri, Youlan Indira Putu Anggi Suryantari Rafi Purwa Syahputra Raihana Sakhi Aswanda Rendi Panca Wijanarko Rhendy May Pradana Rizka Hadiwiyanti Saka Fitri, Anindo Salma Nabila Seftin Fitri Ana Wati Sembilu, Nambi Sidhi Pamekas, Afu Solehudin Al Ayyubi Sudewantoro N M Sugata, Tri Luhur Indayanti Sulistyowati Sulistyowati Sulistyowati Sulistyowati Tri Diana Rimadhani Tri Luhur Indayanti Sugata Ubaidillah Fahmi, Rohmat Wahyuni, Eka Dyar Wati , Seftin Fitri Ana Wati, Seftin Fitri Ana Wibisono, Mahendra Priyo Wisnu Mukti Darwansah Yudha Yunanto Putra Yudha Yunanto Putra Zahra, Nabila Athifah