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All Journal Jurnal technoscientia Jurnal Informatika dan Teknik Elektro Terapan Information System for Educators and Professionals : Journal of Information System Informatics for Educators and Professional : Journal of Informatics Information Management For Educators And Professionals (IMBI) JITK (Jurnal Ilmu Pengetahuan dan Komputer) KOPERTIP: Jurnal Ilmiah Manajemen Informatika dan Komputer JURNAL ILMIAH INFORMATIKA Pelita : Jurnal Penelitian dan Karya Ilmiah JURIKOM (Jurnal Riset Komputer) Jurnal Informasi dan Komputer JOURNAL INFORMATICS, SCIENCE & TECHNOLOGY Jurnal Tekno Kompak Jurnal ICT : Information Communication & Technology Jurnal Manajemen Komunikasi Jurnal Informatika dan Rekayasa Perangkat Lunak JURSIMA (Jurnal Sistem Informasi dan Manajemen) JATI (Jurnal Mahasiswa Teknik Informatika) E-Link: Jurnal Teknik Elektro dan Informatika Journal of Computer System and Informatics (JoSYC) Jurnal Sistem Komputer dan Informatika (JSON) MEANS (Media Informasi Analisa dan Sistem) JURNAL TEKNOLOGI TECHNOSCIENTIA Jurnal Informatika Terpadu Prosiding Seminar Nasional Sisfotek (Sistem Informasi dan Teknologi Informasi) Journal of Artificial Intelligence and Engineering Applications (JAIEA) Jurnal Informatika dan Teknologi Informasi INFORMATION SYSTEM FOR EDUCATORS AND PROFESSIONALS : Journal of Information System TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi JURSIMA Jurnal Teknologi Ilmu Komputer AMMA : Jurnal Pengabdian Masyarakat Jurnal Informatika Polinema (JIP) Jurnal Sistem Informasi dan Manajemen Jurnal Ilmiah Betrik : Besemah Teknologi Informasi dan Komputer Jurnal Ilmiah Sistem Informasi Informasi interaktif : jurnal informatika dan teknologi informasi
Gifthera Dwilestari
STMIK IKMI Cirebon
Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Nursing Social Sciences Other

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MENINGKATKAN EFISIENSI PEMETAAN DAN PERENCANAAN DI KABUPATEN CIREBON MENGGUNAKAN SISTEM INFORMASI GEOSPASIAL Khoirul Huda, Muhammad; Faqih, Ahmad; Dwilestari, Gifthera
Jurnal Informatika dan Teknik Elektro Terapan Vol. 13 No. 2 (2025)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jitet.v13i2.6184

Abstract

Pengembangan geoportal berbasis website untuk Kabupaten Cirebon bertujuan untuk meningkatkan layanan pemerintah dan memperbaiki akses terhadap data geospasial untuk perencanaan pembangunan. Penelitian ini menjelaskan efisiensi Sistem Informasi Geografis (SIG) dalam mengelola data geografis dan membandingkannya dengan sistem sebelumnya.  Metodologi yang digunakan meliputi, analisis pengembangan, desain, implementasi, serta pengujian dan evaluasi dengan menggunakan model ADDIE . Aplikasi ini dikembangkan menggunakan UML dan flowchart untuk memastikan proses yang terstruktur. Data dikumpulkan melalui observasi berani dan survei untuk menilai reaksi pengguna terhadap antarmuka dan fitur sistem. Hasil penelitian menunjukkan bahwa SIG baru lebih efisien, sederhana, dan cepat dibandingkan sistem sebelumnya, dengan rata-rata penilaian pengguna sebesar 4,8625.  Kesimpulannya, SIG ini meningkatkan efisiensi pengelolaan data spasial di Kabupaten Cirebon dan mendukung pengambilan keputusan yang lebih akurat dalam perencanaan pembangunan berkelanjutan. Abstrak. Pengembangan geoportal berbasis website untuk Kabupaten Cirebon bertujuan untuk meningkatkan layanan pemerintah dan memperbaiki akses terhadap data geospasial untuk perencanaan pembangunan. Penelitian ini menjelaskan efisiensi Sistem Informasi Geografis (SIG) dalam mengelola data geografis dan membandingkannya dengan sistem sebelumnya. Metodologi yang digunakan meliputi, analisis pengembangan, desain, implementasi, serta pengujian dan evaluasi dengan menggunakan model ADDIE . Aplikasi ini dikembangkan menggunakan UML dan flowchart untuk memastikan proses yang terstruktur. Data dikumpulkan melalui observasi berani dan survei untuk menilai reaksi pengguna terhadap antarmuka dan fitur sistem. Hasil penelitian menunjukkan bahwa SIG baru lebih efisien, sederhana, dan cepat dibandingkan sistem sebelumnya, dengan rata-rata penilaian pengguna sebesar 4,8625. Kesimpulannya, SIG ini meningkatkan efisiensi pengelolaan data spasial di Kabupaten Cirebon dan mendukung pengambilan keputusan yang lebih akurat dalam perencanaan pembangunan berkelanjutan.
KOMPARASI ALGORITMA REGRESI LINEAR DAN BACKPROPAGATION NEURAL NETWORK PADA SISTEM PREDIKSI HARGA SAHAM BERBASIS WEBSITE Setiawan, Riyan; Purnamasari, Ade Irma; Ali, Irfan; Rohmat, Cep Lukman; Dwilestari, Gifthera
Jurnal Informatika dan Teknik Elektro Terapan Vol. 14 No. 1 (2026)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jitet.v14i1.8468

Abstract

Penelitian ini bertujuan untuk membandingkan performa algoritma Regresi Linear dan Backpropagation Neural Network dalam memprediksi harga saham PT Astra Agro Lestari serta mengimplementasikannya ke dalam sistem prediksi berbasis web. Data historis saham dari Kaggle digunakan dengan variabel previous, high, low sebagai input dan close sebagai target. Pengembangan sistem menggunakan model Waterfall melalui tahapan analisis kebutuhan, desain, implementasi, pengujian, dan analisis komparatif. Pelatihan model dilakukan menggunakan Scikit-learn untuk Regresi Linear dan TensorFlow/Keras untuk Backpropagation Neural Network, dengan preprocessing MinMaxScaler dan pembagian data latih dan uji sebesar 80:20. Evaluasi model menggunakan Root Mean Squared Error (RMSE) dan Mean Absolute Error (MAE). Hasil pengujian menunjukkan BPNN lebih akurat dengan RMSE 26.81 dan MAE 19.01, dibandingkan Regresi Linear dengan RMSE 45.11 dan MAE 29.56. Sistem web berhasil menampilkan prediksi otomatis, grafik komparatif, dan evaluasi error secara real-time.
Evaluasi Pembelajaran AR Sejarah Berbasis SUS, UEQ, TAM Rudi Kurniawan; Dadang Sudrajat; Kaslani; Gifthera Dwilestari; Sandy Eka Permana
Prosiding SISFOTEK Vol 9 No 1 (2025): SISFOTEK IX 2025
Publisher : Ikatan Ahli Informatika Indonesia

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

Abstract

History education in secondary schools still faces challenges in presenting material that attracts the digital generation’s attention. The Bandung Lautan Api event, a topic rich in local and national values, is often taught using conventional methods that limit student engagement and motivation. This study evaluates the feasibility of Augmented Reality (AR)-based learning media to enhance students’ historical literacy on the Bandung Lautan Api topic. A quantitative approach was applied using three integrated evaluation models: the System Usability Scale (SUS), User Experience Questionnaire (UEQ), and Technology Acceptance Model (TAM), involving 100 respondents comprising high school teachers and students. The results indicate that the AR media demonstrates excellent usability (SUS = 87.69), a highly positive user experience across all UEQ dimensions (highest attractiveness = 2.12), and strong technology acceptance (PU = 5.87; PEOU = 5.69; BI = 6.18). Both teachers and students shared consistent perceptions. These findings confirm that the AR media is feasible and capable of creating immersive and interactive learning experiences. Theoretically, this research enriches AR-based learning evaluation literature, while practically, it provides a ready-to-adopt model for integrating AR into history education.
Prediksi Dinamis Harga Tiket Penerbangan Pesawat Menggunakan Algoritma Regresi Linier Berganda Zacky Muhammad Dinata; Khaerul Anam; Puji Pramudya Marta; Gifthera Dwilestari
Prosiding SISFOTEK Vol 9 No 1 (2025): SISFOTEK IX 2025
Publisher : Ikatan Ahli Informatika Indonesia

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

Abstract

This study aims to develop a dynamic prediction model for airline ticket prices using the Multiple Linear Regression algorithm. The research utilizes the public dataset Flight Price Prediction from Kaggle, which originally contained 116,464 rows and 12 columns. After data cleaning by removing missing values (dropna()) and non-predictive columns (such as Flight_ID), the final dataset used for analysis consisted of 116,463 rows and 10 columns. Data preprocessing included handling missing data, encoding categorical variables, feature engineering, standardization, and multicollinearity testing using the Variance Inflation Factor (VIF). The MLR model achieved an R² of 0.882, MAE of 4573.37, and RMSE of 7797.53, indicating strong predictive performance for a linear model. The most influential factors were airline type, service class, number of stops, duration, and booking lead time. Full-service airlines such as Vistara and Air India tend to have higher ticket prices, while early bookings and economy class tickets significantly lower prices. The findings confirm that MLR remains a reliable baseline for interpretable, efficient, and explainable price forecasting systems. Future research may combine MLR with non-linear algorithms (e.g., Random Forest or Neural Network) to enhance accuracy. This study contributes to integrating data science into predictive information systems for dynamic airline pricing and decision support optimization.
MOTIF PENGGUNAAN APLIKASI MEDIA SOSIAL BIGO LIVE DI KALANGAN MAHASISWA JURUSAN ILMU KOMUNIKASI UNIVERSITAS TELKOM Dwilestari, Gifthera; Ali, Dini Salmiyah Fithrah
Manajemen Komunikasi Vol 3, No 1 (2018): Accredited by Republic Indonesia Ministry of Research, Technology, and Higher Ed
Publisher : Faculty of Communication Sciences Universitas Padjadjaran

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (271.79 KB) | DOI: 10.24198/jmk.v3i1.12901

Abstract

Pengguna internet di Indonesia cukup tinggi diantara negara lainnya khususnya diantara negara-negara Asia Tenggara lainnya.Hampir seluruh pengguna internet di Indonesia adalah pengguna aktif sosial media.Salah satu aplikasi media sosial yang sedang tren saat ini adalah Bigo Live.Bigo Live merupakan aplikasi live video streaming, dimana penggunanya bisa berinteraksi secara realtime.Popularitas Bigo Live di kalangan pengguna media sosial cukup tinggi karena pada 6 bulan pertama sejak waktu rilisnya, aplikasi tersebut telah menduduki urutan ke-10 pada Top Charts untuk aplikasi gratis di Google Play Store dan urutan ke-4 Top Charts untuk aplikasi gratis kategori sosial.  Keunikan Bigo Live lainnya yaitu Bigo Live memiliki nilai ekonomi dengan adanya sistem poin yang biasa disebut beans yang dapat ditukarkan dengan uang tunai apabila telah mencapai minimal 6.700 beans. Tujuan dilakukannya penelitian ini adalah menemukan motif yang mendorong penggunaan media sosial Bigo Live oleh mahasiswa jurusan Ilmu Komunikasi di Universitas Telkom. Penelitian ini dilakukan dengan menggunakan metode kualitatif kepada empat orang informan. Dari hasil penelitian ditemukan bahwa motif yang mendorong penggunaan media sosial Bigo Live oleh mahasiswa jurusan Ilmu Komunikasi Universitas Telkom ini relevan dengan teori motif penggunaan media yang diungkapkan oleh McQuail yaitu, motif informasi, motif identitas diri, motif integrasi dan interaksi sosial dan motif hiburan. Namun keempat motif tersebut tidak semuanya dimiliki informan, motif yang paling sering ditemukan adalah  motif informasi, interaksi dan hiburan.
Analisis Sentimen Ulasan Pengguna Aplikasi E-Commerce Toco Menggunakan Algoritma Naive Bayes Purnamasari, Adinda; Astuti, Rini; Anam, Khaerul; Gifthera Dwilestari; Mulyawan
Jurnal Ilmiah Sistem Informasi (JISI) Vol. 5 No. 1 (2026): MARET
Publisher : Universitas Muhammadiyah Metro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24127/jisi.v5i1.10627

Abstract

This study aims to analyze the sentiment of user reviews of the Toco e-commerce application using the Naïve Bayes Multinomial algorithm. The dataset consists of 1425 reviews with an unbalanced distribution between positive and negative classes. Review data was collected from the Google Play Store platform, then processed automatically through the stages of case folding, normalization, stopword removal, and stemming. Modeling was carried out by dividing the data into training and test data, and classifying sentiment using the Naïve Bayes approach. From the evaluation results, the model's accuracy in sentiment classification reached 88%, with higher performance achieved in the majority class (positive) compared to the minority class (negative), as reflected in the low precision and recall values. This study emphasizes the need to handle unbalanced data so that the analysis results reflect the diverse perceptions of users. This research provides a baseline for sentiment analysis for local e-commerce applications and contributes to the development of automated analytics systems to support decision-making in the Indonesian e-commerce industry.
Klasifikasi Kondisi Gizi Bayi Bawah Lima Tahun Pada Posyandu Melati Dengan Menggunakan Algoritma Decision Tree Ahmad Zam Zami; Odi Nurdiawan; Gifthera Dwilestari
Jurnal Sistem Komputer dan Informatika (JSON) Vol. 3 No. 3 (2022): Maret 2022
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v3i3.3892

Abstract

One of the health problems in Cirebon is about nutritional status. This happens because the increase and decrease in the number of children under five who experience nutritional status problems each year is uncertain. Toddlers are a group of people who are vulnerable to nutrition. The incidence of malnutrition if not addressed will cause a bad impact for toddlers. The impacts include death and chronic infection. Early detection of undernourished children (malnutrition and malnutrition) can be done with an examination of weight for age (W/U) to monitor the child's weight, the parameters used to calculate the nutritional status of toddlers include age, weight and height/length. To classify the nutritional status of children under five, a knowledge or scientific study is needed that can classify data based on the data from measurements and weighing. This study uses 8 criteria, namely Name, Address, Mother's Name, Gender, Age, Weight, Height, Status Classification. The accuracy results obtained are 98.86% with details, namely the Prediction Results of Malnutrition and it turns out that the True Malnutrition is 13 data. Poor Nutrition Prediction Results and turns out to be True Normal by 1 Data. Normal Prediction Results and it turns out to be True Malnutrition is 1 Data. Normal Prediction Results and turns out to be True Normal of 161 data. The results of the classification of infant levels based on age, infants aged 0 months to 10 months had normal nutrition, while infants aged 10 months to 19.5 months were prone to malnutrition for infants, and those aged more than 19.5 months had poor nutrition. normal.
KLASIFIKASI KELAYAKAN PENERIMA BANTUAN SEMBAKO MENGGUNAKAN METODE DECISION TREE Rizaldy, Farhan; Suprapti, Tati; Dwilestari, Gifthera
PELITA JURNAL PENELITIAN DAN KARYA ILMIAH Vol 25 No 2 (2025): Pelita : Jurnal Penelitian dan Karya Ilmiah [Juli - Desember]
Publisher : UNIVERSITAS ISLAM SYEKH - YUSUF TANGERANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33592/pelita.v25i2.5159

Abstract

The K-Means method is one of the Data Mining methods that is widely used in clustering research. Based on the results of research that has been conducted to build a process model for Poverty Data Clustering Analysis Using the K-Means Method Approach in Teluk Agung Village, Indramayu District, Indramayu Regency, can use RapidMiner tools by creating operators and processing parameters used for clustering the P3KE class category. The operators used in this study are Read Excel, Set Role, Select Attributes, Replace Missing Values, Nominal to Numerical, Multiply, Clustering (K-Means) and Performance operators. The operators used are 8 operators by applying the stages of Knowledge Discovery in Database (KDD). This research will apply the Davies Bouldin Index (DBI) as a way of optimising the number of clusters to group data, from the best cluster value experiment, the closest to 0 is K9 with a DBI value of -2.257, from this we can conclude that approximately 43 items from clusters 2 - 10 are included in the P3KE category, and other than the 43 items can be interpreted as still not included in the P3KE category.
Jurnal Klasifikasi KLASIFIKASI KELAYAKAN PENERIMA BANTUAN SEMBAKO MENGGUNAKAN METODE DECISION TREE Rizaldy, Farhan; Suprapti, Tati; Dwilestari, Gifthera
PELITA JURNAL PENELITIAN DAN KARYA ILMIAH Vol 25 No 2 (2025): Pelita : Jurnal Penelitian dan Karya Ilmiah [Juli - Desember]
Publisher : UNIVERSITAS ISLAM SYEKH - YUSUF TANGERANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33592/pelita.v25i2.5162

Abstract

Poverty is one of the fundamental problems that is of concern to governments in all countries.  An important aspect to support poverty alleviation strategies is the availability of accurate and targeted poverty data. Staple food is the nine basic needs of Indonesian people, including food or drinks used in daily life. On this basis, the government often organizes basic food assistance programs for those in need. classification is one of the most commonly used prediction techniques to predict new labels or categories based on experience gained from known data. The main purpose of classification is to understand patterns or relationships between input and output variables, so that you can take appropriate decisions or actions based on the available information. Based on the results of the analysis and implementation of the Decision Tree Algorithm for classification of eligibility for basic food aid recipients in the Teluk Agung Village area, Indramayu District, Indramayu Regency, it can be concluded that the model developed has a very high level of accuracy, namely 94.83%. This model has proven effective in classifying various categories that are worthy of receiving assistance, starting from class 1, 2, 3 and not worthy of receiving assistance. The factors used in this model, such as monthly income, have been processed well through stages in the Knowledge Discovery in Databases (KDD) framework, resulting in a reliable classification. With high accuracy and performance, it is hoped that this model can be implemented practically to support decision making in mitigating the risk of non-delivery of basic food aid in the Teluk Agung Village area, Indramayu District, Indramayu Regency.
Co-Authors Abdul Ajiz Abdul Ajiz, Abdul Abdul Rauf Chaerudin Abdullah Syafii Abdullah Syafii Aby Febrian Ade Irma Purnamasari Ade Irma Purnamasari Ade Rizki Rinaldi Agis Maulana Robani Agung Nugraha agus bahtiar Ahmad Faqih Ahmad Faqih Ahmad Rifa'i Ahmad Zam Zami Aldiani, Dea Alia Cahyani, Cica Alibasyah, Aziz Ananda Rafly Andi Suandi Anita Nur Kirana Anwar Musaddad Apriliyani, Ela Arif Rinaldi Dikananda Arifin, Bagas Adam Athhar Hafizha Luthfi Auliya Bagas Al Haddad Bambang Siswoyo Basysyar, Fadhil Muhammad Caswadi, Caswadi Chaerudin, Chaerudin Cindyk Irawanto Dadang Sudrajat Dea Miftahul Huda Dessy Angelina Destriyanah, Riska Dian Ade Kurnia Dias Bayu Saputra Dienwati Nuris, Nisa Dienwati, Nisa Dikananda, Arif Rinaldi Dikananda, Fatihanursari Dzaffa 'Ulhaq Edi Tohidi Edi Tohidi Eka Permana, Sandy Fadhil Muhammad Basysyar Fadhil Muhammad Basysyar Fajar Fauzan, Muhammad Fajria, Azzahra Moudy Fasa, Saefullah Fathurrohman Fathurrohman Fatihanursari Dikananda Faujia, Agnes Fithrah Ali, Dini Salmiyah Fuadi Ahmad, Cecep Hamonangan, Ryan Haris Abdul Hadi Herdiana, Rulli Hermawan, Bagus Hermawan, Muhammad Andi Hilya Ashfia Nabila Himawan, Irvan Hira Wahyuni Azizah Hoeriah, Dede Hoerunnisa, Anis Iin Iin Solihin Iis Riyana Irfan Ali Irfan Ali Irfan Ali, Irfan Irma Agustina Irma Purnamasari, Ade Irvan Himawan Jayawarsa, A.A. Ketut Karimah, Ayu Kaslani Kencana, Junaedi Surya Khaerul Anam Khoirul Huda, Muhammad Kokom Komariyah Lestari, Anjar Ayuning Martanto . Mar’atun Sholihah, Oliffia Maulana Sidiq, Cecep Mochamad Aditya Sunaryo Muhammad Abdurohman Muhammad Basysyar, Fadhil Mulyawan Mulyawan, Mulyawan Musliyadi, Mar'i Nana Suarna Nana Suarna Nana Suarna Narasati, Riri Narasati Nining R Nining Rahaningsih Nisa Dieanwati Nuris Nur Amalia Nur Kirana, Anita Nuraini, Asyifa Nurhakim, Bani Nurul Aini, Yuli Nurwahidah, Dalilah Odi Nurdiawan Odi Nurdiawan Permana, Sandy Eka Pratama, Denni Prihartono, Willy Puji Pramudya Marta Purnamasari, Ade Irma Purnamasari, Adinda Puspita Maulana Arumsari R, Nining Raditya Danar Dana Raena Agustin Laeliyah Rahaditya Dasuki Ramdhan, Dadan Ramiro Firjatullah, Federicko Ranu Husna Rini Astuti Rizaldy, Farhan Rizqy, Muhammad Enricco Rohmat, Cep Lukman Rosmeri Manurung, Agnes Rudi Kurniawan Saeful Anwar Saeful, Agung Saefullah Fasa Saepu Qirom, Dani Saepudin, Asep Saepul Hadi Sagita, Ayu Salsabila, Putri Sandy Eka Permana Septiana, Angga Setiawan, Riyan Sri Suwartini Suandi, Andi Suarna, Nana Subhiyanto, Fajar Sunana, Heliyanti Suryani Dewi, Ike Susana, Heliyanti Syafi'i Syafi'i Syafi'i, Syafi'i Tati Suprapti Tohidi, Edi Tuti Hartati Umi Hayati Vibrianti, Vera Wahyudin, Edi Yubi Aqsho Ramadhan Zacky Muhammad Dinata