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All Journal J@TI (TEKNIK INDUSTRI) JURNAL SISTEM INFORMASI BISNIS Jurnal Rekayasa Sistem Industri Jurnal Teknologi dan Manajemen Informatika SPEKTRUM INDUSTRI PROSIDING SEMINAR NASIONAL CENDEKIAWAN JOIV : International Journal on Informatics Visualization Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal Sistem dan Manajemen Industri RABIT: Jurnal Teknologi dan Sistem Informasi Univrab Journal of Information Technology and Computer Science (JOINTECS) INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi JURNAL MEDIA INFORMATIKA BUDIDARMA SMARTICS Journal Indonesian Journal of Artificial Intelligence and Data Mining JKTP: Jurnal Kajian Teknologi Pendidikan Dinamisia: Jurnal Pengabdian Kepada Masyarakat Jurnal Sisfokom (Sistem Informasi dan Komputer) Prosiding Seminar Nasional Pakar Jurnal Teknologi Sistem Informasi dan Aplikasi Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) JUSIM (Jurnal Sistem Informasi Musirawas) ACADEMICS IN ACTION Journal of Community Empowerment Jurnal Sistem Teknik Industri Jurnal Aplikasi Dan Inovasi Ipteks SOLIDITAS Mulia International Journal in Science and Technical Journal of Industrial Engineering Zonasi: Jurnal Sistem Informasi International Journal of Industrial Research and Applied Engineering JOURNAL OF INFORMATION SYSTEM MANAGEMENT (JOISM) Teknika IDEAS: Journal of Management & Technology Malcom: Indonesian Journal of Machine Learning and Computer Science The Indonesian Journal of Computer Science INOVTEK Polbeng - Seri Informatika Widya Teknik
Anastasia Lidya Maukar
Universitas Presiden
Humanities Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics Mechanical Engineering Social Sciences Transportation Other

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ANALISA DAN DESAIN SISTEM INFORMASI KEUANGAN STUDI KASUS PENDIDIKAN GURU RAUDHATUL ATHFAL (PGRA) Pramudita, Krisna Eka; Vitianingsih, Anik Vega; Kacung, Slamet; Maukar, Anastasia Lidya; Wati, Seftin Fitri Ana
JUSIM (Jurnal Sistem Informasi Musirawas) Vol 9 No 1 (2024): JUSIM : Jurnal Sistem Informasi Musi Rawas JUNI
Publisher : LPPM UNIVERSITAS BINA INSAN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32767/jusim.v9i1.2246

Abstract

Kesulitan dalam pembuatan laporan keuangan terkait dengan pengelolaan laporan keuangan yang masih banyak dilakukan menggunakan Gmail atau WhatsApp, selanjutnya rincian laporan keuangan tersebut akan dibuat salinan untuk diarsipkan menggunakan Microsoft office Excel. Penelitian ini menghasilkan rancangan sistem informasi keuangan untuk Lembaga Pendidikan Guru Raudhatul Athfal (PGRA). Sistem akan mampu menampilkan informasi keuangan dalam bentuk laporan, mengelola dan mengelompokkan pemasukan dan pengeluaran berdasarkan sumber, tanggal, dan waktu, serta menampilkan persentase hasil analisis kondisi keuuangann antara pemasukan dan pengeluaran. Model pengembangan perangkat lunak dengan pendekatan waterfall yang mencakup langkah-langkah analisis kebutuhan, desainn spesifikasi, implementasi, pengujiann, dan pemeliharaan. Sistem ini akan membantu lembaga dalam pembuatan, pengiriman laporan keuangan, dan arus kas, Hasil penelitian ini mampu membantu dalam keberlanjutan operasional sekolah, menjaga transparansi dan keakuratan manajemen keuangan.
Pengembangan Aplikasi Game Edukasi Sejarah Sunan Kalijaga Berbasis Android Vitianingsih, Anik Vega; Firmansyah, Anggi; Maukar, Anastasia Lidya; Choiron, Achmad; Cahyono, Dwi
JKTP: Jurnal Kajian Teknologi Pendidikan Vol 6, No 1 (2023)
Publisher : Universitas Negeri Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17977/um038v6i12023p001

Abstract

Historical education is essential in forming human character because it is the basis for forming a sense of nationalism. Along with the development of technology, learning models are also affected. Learning can be facilitated through learning sources other than educators, thereby changing the role of educators in learning and adapting learning to current developments. One of the learning resources is game technology. Game applications can be a learning medium because of their visual and interactive nature. Packing history learning into an educational game application might be an alternative source of learning that is interesting and not monotonous. The purpose of this research is developing education media as an Android-based historical learning tool by packaging the historical learning of the story of Sunan Kalijaga in the form of a game application. The results of the black box, white box trials that went well, and the feasibility test that was carried out on 15 respondents, 93% stated that the material presented was appropriate so that it can be concluded that the game application is suitable for use as an alternative media for mobile learning by teachers and students with an assessment feature using an Android smartphone.AbstrakPendidikan sejarah sangat penting dalam proses pembentukan karakter manusia karena merupakan dasar dari pembentukkan rasa nasionalisme. Seiring dengan berkembangnya teknologi, Pembelajaran pun ikut terpengaruhi. Pembelajaran dapat dipermudah melalui sumber pembelajaran selain pendidik, sehingga menggubah peran pendidik dalam pembelajaran dan menyesuaikan pembelajaran dengan perkembangan zaman saat ini. Salah satu sumber pembelajaran itu adalah teknologi game. Aplikasi game dapat menjadi media pembelajaran karena sifatnya yang visual dan interaktif. Mengemas pembelajaran sejarah kedalam sebuah aplikasi game edukasi mungkin bisa menjadi salah satu alternatif sumber pembelajaran yang menarik dan tidak monoton. Tujuan dari penelitian ini adalah membuat aplikasi game “Lokajaya Sang Kalijaga” sebagai sarana pembelajaran sejarah berbasis Andoid dengan mengemas pembelajaran sejarah kisah Sunan Kalijaga ke dalam bentuk aplikasi game. Hasil dari uji coba black box, white box yang berjalan baik serta uji kelayakan yang telah dilakukan pada 15 responden, 93% menyatakan materi yang dibawakan telah sesuai sehingga dapat disimpulkan aplikasi game layak dipergunakan sebagai media alternatif pembelajaran secara mobile oleh guru dan murid dengan fitur penilaian menggunakan smartphone Android.
Sistem Rekomendasi Pemilihan Komponen Komputer Menggunakan Metode AHP dan Profile Matching Salmanarrizqie, Ageng; Vitianingsih, Anik Vega; Kristyawan, Yudi; Maukar, Anastasia Lidya; Marisa, Fitri
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 8, No 3 (2024): Juli 2024
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v8i3.7643

Abstract

Computers have become one of the technological tools that play a crucial role in enhancing society's productivity. Therefore, many desktop computer users assemble their own computers to achieve computer performance according to their preferences or needs. However, some people lack information about the variations, specifications, and capabilities of each computer component to be assembled. This research offers a recommendation system that is part of a decision support system (DSS) to assist users in providing recommendations for computer components that are being sought and needed based on brand, price, and specifications using the Analytic Hierarchy Process (AHP) and Profile Matching methods. Parameters are based on the processor, motherboard, graphics card (VGA), storage, RAM, power supply, and casing with priority categories based on specifications, price, and brand. Data weighting is done using the Analytic Hierarchy Process (AHP) method, while the Profile Matching method is used for ranking the weighting results. The research results show an accuracy rate of 60% using the Profile Matching method, while the AHP method achieves an accuracy rate of 57%.
Forecasting Model of Indonesia's Oil & Gas and Non-Oil & Gas Export Value using Var and LSTM Methods Rijal, Khaidar Ahsanur; Vitianingsih, Anik Vega; Kristyawan, Yudi; Maukar, Anastasia Lidya; Wati, Seftin Fitri Ana
Jurnal Teknologi dan Manajemen Informatika Vol. 10 No. 1 (2024): Juni 2024
Publisher : Universitas Merdeka Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26905/jtmi.v10i1.13127

Abstract

As a country with abundant natural resources in the form of mineral and non-mineral products, Indonesia is characterized by its ability to fulfill domestic and foreign needs through export activities categorized into two commodities: oil and gas and non-oil and gas. Export activities are an indicator of the country's economic growth that often fluctuates in value, and these conditions are fundamentally caused by a decrease in production quantity and the instability of the global economic climate. The strategy to overcome these problems is to create a forecasting model. This research aims to develop a forecasting model using time series analysis methods, including vector autoregressive (VAR) and long short-term memory (LSTM) methods based on oil and non-oil and gas value parameters. The results of the Granger causality test stated that the values of oil and gas and non-oil and gas affect each other. The VAR model with the optimum lag produced by the Akaike Information Criterion (AIC) test obtained an accuracy value of MAPE oil & gas and non-oil and gas of 18.4% and 32.1%, respectively. LSTM generates the best model with a MAPE value of 6,23% for oil & gas and 8,18% for non-oil and gas.
Proposed Business Expansion of Yatai Tori using Constraint Management Mohamad Toha; Adi Saptari; Anastasia Lidya Maukar
JIE Scientific Journal on Research and Application of Industrial System Vol 9, No 1 (2024)
Publisher : President University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33021/jie.v9i1.4983

Abstract

Yatai Tori management expects the business to double in size from its current condition while facing a minimal market growth of 3.7%. In the Market sector, performance needs to be perfect: tasty menu, Friendly Service, Clean and Attractive tools, Fast responses from the servants, and Clear and easy access to information on social media. In terms of the physical sector, the space of Yatai Tori is sufficient to handle 40 clients per day, which is double the existing performance of 15 customers per day. It should add one person to balance the workload of an employee. Following the Policy sector, management should implement employee compensation to motivate workers to increase performance. And management should find a good supplier to make the minimum possible food cost, increase the favourite menu stock, and decrease the favourite lees menu to control the capacity of Yatai Tori. To elevate the limitation, an investment of Rp. 370.000.000 and a total working capital of Rp. 30.000.000 is required, yielding an internal rate of return of 23.36%.
Sentiment Analysis of Brand Ambassador Influence on Product Buyer Interest Using KNN and SVM Putri, Natasya Kurnia; Vitianingsih, Anik Vega; Kacung, Slamet; Maukar, Anastasia Lidya; Yasin, Verdi
Indonesian Journal of Artificial Intelligence and Data Mining Vol 7, No 2 (2024): September 2024
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/ijaidm.v7i2.29469

Abstract

In the dynamic marketing, companies usually use strategies involving celebrities or influencers to promote their products or brands. The currently popular strategy is using Korean boy bands as brand ambassadors. This collaboration certainly gets a lot of opinion responses through tweets on X app social media. This research aims to analyze sentiment to determine how the product buyer's interest responds to brand suitability, brand image management, and the influence of issues that arise in this collaboration. The research stages consist of data collection, pre-processing, labeling, weighting, and classification with K-Nearest Neighbor and Support Vector Machine and performance evaluation using a confusion matrix. The dataset used was 696 tweets taken using web scrapping techniques. This research uses the Lexicon-based method to divide the dataset into positive, negative, and neutral classes. The SVM method shows superior test results by achieving an accuracy rate of 83.34% compared to the KNN method, which produces an accuracy value of 71.2% in its calculations
Sistem Rekomendasi Pemilihan Komponen Komputer Menggunakan Metode AHP dan Profile Matching Salmanarrizqie, Ageng; Vitianingsih, Anik Vega; Kristyawan, Yudi; Maukar, Anastasia Lidya; Marisa, Fitri
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 8, No 3 (2024): Juli 2024
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v8i3.7643

Abstract

Computers have become one of the technological tools that play a crucial role in enhancing society's productivity. Therefore, many desktop computer users assemble their own computers to achieve computer performance according to their preferences or needs. However, some people lack information about the variations, specifications, and capabilities of each computer component to be assembled. This research offers a recommendation system that is part of a decision support system (DSS) to assist users in providing recommendations for computer components that are being sought and needed based on brand, price, and specifications using the Analytic Hierarchy Process (AHP) and Profile Matching methods. Parameters are based on the processor, motherboard, graphics card (VGA), storage, RAM, power supply, and casing with priority categories based on specifications, price, and brand. Data weighting is done using the Analytic Hierarchy Process (AHP) method, while the Profile Matching method is used for ranking the weighting results. The research results show an accuracy rate of 60% using the Profile Matching method, while the AHP method achieves an accuracy rate of 57%.
Analisis Sistem Pembelajaran Daring Berbasis Gamification Collaboration untuk Mendukung Merdeka Belajar Menggunakan Octalysis Framework Maukar, Anastasia Lidya; Vitianingsih, Anik Vega; Marisa, Fitri; Pramudita, Atanasia; Putri, Jessica Ananda; Pramisela, Intan Yosa
Jurnal Teknologi dan Manajemen Informatika Vol. 8 No. 2 (2022): Desember 2022
Publisher : Universitas Merdeka Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26905/jtmi.v8i2.7855

Abstract

The COVID-19 pandemic has had a major impact on many things. Education, which is one of the important aspects in supporting human life, also felt the impact of the pandemic. Based on Circular Letter Number 4 of 2020 concerning the Implementation of Education Policies during the emergency period of the spread of COVID-19, the government has a policy that face-to-face education is not allowed to be carried out. Therefore, the world of education began to implement distance learning or e-Learning.  In addition to how to teach and learn, there are other things that need to be considered for the success of the process. Another thing is student learning motivation. Changes in the teaching and learning process also have an impact on student learning motivation. In this study, a questionnaire has been distributed to find out the core drive of student learning motivation. Based on a questionnaire that has been filled out by 167 respondents, the core drive that influences students' learning motivation is at a high level. This indicates that the level of student learning motivation during the COVID-19 pandemic is still high.
Penerapan Algoritma Klasifikasi pada Machine Learning untuk Deteksi Phishing: Application of Classification Algorithms in Machine Learning for Phishing Detection Fauzan, Rizky; Vitianingsih, Anik Vega; Cahyono, Dwi; Maukar, Anastasia Lidya; Suprio, Yoyon Arie Budi
MALCOM: Indonesian Journal of Machine Learning and Computer Science Vol. 5 No. 2 (2025): MALCOM April 2025
Publisher : Institut Riset dan Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57152/malcom.v5i2.1968

Abstract

Phishing merupakan salah satu bentuk kejahatan siber yang bertujuan mencuri informasi sensitif melalui metode penipuan, seperti situs web palsu yang menyerupai halaman resmi. Maka diperlukan sistem deteksi yang lebih akurat dan efisien untuk mengidentifikasi ancaman ini. Penelitian ini bertujuan untuk menganalisis penerapan algoritma klasifikasi dalam machine learning guna mendeteksi URL phishing. Algoritma yang digunakan dalam penelitian ini adalah Naïve Bayes, Random Forest, dan Decision Tree, yang diterapkan pada dataset yang dikumpulkan dari berbagai sumber. Dataset ini dianalisis menggunakan fitur berbasis Term Frequency - Inverse Document Frequency (TF-IDF) serta fitur numerik, seperti panjang URL, jumlah angka, karakter khusus, dan keberadaan kata kunci yang sering ditemukan dalam situs phishing. Evaluasi model dilakukan menggunakan metrik akurasi, precision, recall, dan F1-score untuk mengukur efektivitas sistem deteksi yang dikembangkan. Hasil eksperimen menunjukkan bahwa model Random Forest memiliki performa terbaik dengan akurasi mencapai 97,2%, diikuti oleh Decision Tree (96,3%), sementara Naïve Bayes memiliki akurasi lebih rendah (85,3%). Model Random Forest juga memiliki keseimbangan yang baik antara precision dan recall, sehingga lebih andal dalam mendeteksi URL phishing. Penggunaan algoritma Machine Learning terbukti dapat meningkatkan efektivitas deteksi phishing secara signifikan.
Sentiment Analysis On Tripadvisor Travel Agent Using Random Forest, Support Vector Machines, and Naïve Bayes Methods Fauzi, Ariq Ammar; Vitianingsih, Anik Vega; Kacung, Slamet; Maukar, Anastasia Lidya; Wati, Seftin Fiti Ana
Teknika Vol. 14 No. 1 (2025): March 2025
Publisher : Center for Research and Community Service, Institut Informatika Indonesia (IKADO) Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34148/teknika.v14i1.1198

Abstract

TripAdvisor faces problems in improving the quality of service on its application, namely the presence of unexpected or non-functional features, which can affect the user experience and reduce trust in the application.  This research aims to develop an application capable of performing sentiment analysis on TripAdvisor application user reviews on the Google Play Store with negative, positive, and neutral classifications using the Random Forest (RF), Support Vector Machine (SVM), and Naïve Bayes (NB). The RF method was chosen in this study because of its ability to handle large and complex data very accurately, while SVM is able to classify data on a large scale and is resistant to overfitting, while NB is able to classify text with clear probabilities. The Lexicon-based method as data labelling. The results of sentiment analysis from 1500 reviews with web scrapping show the classification of positive, negative, and neutral sentiments of 48, 726, and 646 data, respectively. Model performance in RF, SVM, and NB testing gets an accuracy value of 94%, 93.6%, and 77.8%, respectively. The RF model produces the best accuracy compared to other methods. The RF model produces the best accuracy compared to other methods. The results of sentiment analysis from 1500 user reviews allow developers to identify features that are often criticized or do not function properly in their application services.
Co-Authors Abdul Rezha Efrat Najaf Achmad Aziz Wahdana Achmad Choiron Adi Saptari Agus Sasmito Agustinus Noertjahyana Ahmad Yanu Rokhim Ana Wati, Seftin Fitri Anang Aris Widodo Andira Andira Andira Andira Andira Andira Andira Taslim Andira, Andira ANGGI FIRMANSYAH Anik Vega Vitianingsih Anik Vega Vitianingsih Anik Vega Vitianingsih Anik Vega Vitianingsih Anik Yuesti Apri Junaidi, Apri Arie Restu Wardhani Arrosyadi, Laesa Qotrun Nada Arthur Silitonga Athina Sakina Ratum Avania Shinta Aziiza, Arizia Aulia Azzahra, Morra Fatya Gisna Nourielda Bella Chelsea Berliana Burhan Primanintyo Cahyono, Cahyono Kaelan Cakranegara, Pandu Adi Carolena Setephany Christian Setiadi Ciswondo Ciswondo Dewa Anggara Kesuma Dian Retno Sari Dewi DWI CAHYONO Fauzan, Rizky Fauzi, Ariq Ammar Fawaidul Badri Firmansyah, Deden Fitri Marisa Fitri Marisa Fitri Marisa Fitri Marissa Fitri, Anindo Saka Gita Indah Marthasari Gunawan Hamidan, Rusdi Handini, Mia Hanum, Dinda Latifah Haryanto, Kurniawan Wahyu Hashim, Ummi Rabah Helmi Indra Purnomo Hermansyah, David Herwan Yusmira Hikmawati, Nina Kurnia Husri Sidi Ineu Widaningsig Sosodoro Ineu Widaningsih Ineu Widaningsih Sosodoro Ineu Widaningsih Sosodoro Ineu Widaningsih Sosodoro, Ineu Widaningsih Intan Puspita Pribadi Intan Yosa Pramisela Jack Febrian Rusdi Jazid Rizkon Jean Hillary P Korua Jenifer Cafriaty Johan Krisnanto Runtuk Johan Runtuk Julius Mulyono Kamalrudin, Massila Kresna Arief Nugraha Krismantoro, Putu Gede Ari KRISTIAWAN KRISTIAWAN Luqman Hakim Mardiana Andarwati MARIFANI FITRI ARISA Mashudi Mashudi Maulidiana, Putri Dwi Rahayu Maurits Walalayo Mieke Wijayanti Minggow, Lingua Franca Septha Mochammad Syaiful Riza Mohamad Toha Mohd Syaiful Rizal Mucalinda Rupasari Mucalinda Rupasari Muhammad Afra Irwansyah Muzaki, Mochammad Rizki Niken Titi Pratitis Nurhaba Djiha Octa Wendy Tanurahardja Oktafamero, Yomara Oktavia Sunny Pamudi Pamudi, Pamudi Pangestu, Resza Adistya Pramisela, Intan Yosa Pramudita, Atanasia Pramudita, Krisna Eka Puspitarini*, Erri Wahyu Puspitarini, Erri Wahyu Putri, Jessica Ananda Putri, Natasya Kurnia Rachmad Ary Ramadhan Rahardiyanto, Panca Ramadhan, Rachmad Ary Rendy - Rhiza Adiprabowo Rhiza Adiprabowo, Rhiza Richki Hardi Rijal, Khaidar Ahsanur Rivaldo Tito Lamberto Da Silva Rusdi Hamidan Rusdi, Jack Febrian Salmanarrizqie, Ageng Seftin Fitri Ana Wati Shofa Ramadhina Sigit Sigalayan Siti Hajar Binti Mohtar Slamet . Slamet Kacung, Slamet Slamet Riyadi, Slamet Riyadi Stefanus Setiady SUMARDI Susilo, Yunus Sutrisno Sutrisno Syahroni Wahyu Iriananda, Syahroni Wahyu Tantyo Edo Wicaksana TEGUH ARIFIANTO, TEGUH Tubagus Mohammad Akhriza Uda, Tonich Ullum, Choirul Voni Anggraeni Suwito Putri Wati, Seftin Fiti Ana Wati, Seftin Fitri Ana Widiya Nur Permata Wijiono, Aditya Kusuma Yana Hendriana Yasin, Verdi Yoyon Arie Budi Suprio Yudi Kristyawan, Yudi Yunus Susilo Yustian Zandroto, Yosefin Yuniati Zangana, Hewa Majeed