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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Jurnal Informatika dan Teknik Elektro Terapan Journal of Information Systems Engineering and Business Intelligence Jurnal Informatika Jurnal CoreIT Jurnal Komputer Terapan JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Anterior Jurnal Technologia: Jurnal Ilmiah Jurnal Teknologi Informasi dan Terapan (J-TIT) Jurnal Teknologi Informasi : Jurnal Keilmuan dan Aplikasi Bidang Teknik Informatika JATI (Jurnal Mahasiswa Teknik Informatika) Journal Of Information And Technology Unimor (JITU) Jurnal Saintekom : Sains, Teknologi, Komputer dan Manajemen Konstelasi: Konvergensi Teknologi dan Sistem Informasi Jurnal Atma Inovasia JOINTECOMS (Journal of Information Technology and Computer Science) Teknomatika: Jurnal Informatika dan Komputer Diteksi : Jurnal Pengabdian Kepada Masyarakat
Nova Noor Kamala Sari
Universitas Palangka Raya
Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Environmental Science Languange, Linguistic, Communication & Media Library & Information Science Medicine & Pharmacology Social Sciences Other

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Rancang Bangun Aplikasi Angkotkita Menggunakan Location Based Service Dengan Metode Haversine Berbasis Android Imamsyah, Rasyid Noor; Sari, Nova Noor Kamala; Lestari, Ariesta
Journal of Information Technology and Computer Science Vol. 3 No. 1 (2023): JOINTECOMS : Journal of Information Technology and Computer Science
Publisher : Universitas Palangka Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47111/jointecoms.v3i1.10796

Abstract

One of the problems that are often encountered by city transport passengers is the uncertainty that there will be city transportation that will pass through the passenger's location and uncertainty regarding the number of passengers in the city transportation. Meanwhile, the problem for city transportation drivers is the uncertainty of the location of passengers who will order city transportation and the location of passengers who are scattered, making the driver have to stop several times even though the location between passengers and others is not too far away. This study aims to create a city transportation service application using a location based service (LBS) with the haversine method. The research methodology used is extreme programming which has four stages, namely planning, design, coding, and testing. The results of the study are the AngkotKita Application for passengers and the AngkotKita Application for drivers. Applications for passengers provide information about the route from the passenger's starting point to the nearest bus stop, information on city transportation that will pass the bus stop, detailed information on passenger orders both ongoing and completed, and promo information and news. Applications for drivers provide information in the form of being able to see bus stops containing passengers, user profile information, driver's incoming and outgoing QR Code information, information on ongoing and completed orders.
Rancang Bangun Prototype Monitoring Banjir Berbasis Website Anorgi, Andrew; Saragih, Agus Sehatman; Sari, Nova Noor Kamala
Journal of Information Technology and Computer Science Vol. 3 No. 2 (2023): JOINTECOMS : Journal of Information Technology and Computer Science
Publisher : Universitas Palangka Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47111/jointecoms.v3i2.10819

Abstract

Indonesia usually has certain areas where flooding occurs in different locations that can be flooded by rainfall that falls then will flow through the upstream of the river or the end of the river path where the water will pass and collect to a place where the water can accommodate is no longer available. again wasted water that there is no drain line. Based on these problems, a website-based flood monitoring prototype system is needed by adding the following functions IoT (Internet of Things) which can monitor floods about the condition of the water level graph on the website that can be seen by officers. This study uses an experimental method that was developed based on the needs of the research. In hardware system design used is microcontroller NodeMCU ESP8266 as system control. An ultrasonic sensor for water level and an anemometer to determine the current speed determines the water level in the box. Based on the research that has been carried out, the conclusion is that the system can predict when a flood will occur in the next few hours when water enters the box and the website graph appears. After the water is full it will send a notification via telegram bot to the owner of the officer within 3 minutes.
Rancang Bangun Sistem Enterprise Resource Planning Construction Sebagai Solusi Manajemen Proyek Konstruksi Yudhistira, Aditya Septian; Sari, Nova Noor Kamala; Priskila, Ressa
Journal of Information Technology and Computer Science Vol. 3 No. 2 (2023): JOINTECOMS : Journal of Information Technology and Computer Science
Publisher : Universitas Palangka Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47111/jointecoms.v3i2.10821

Abstract

Construction management is a professional service that uses special project management techniques to oversee the course of construction projects from the initiation stage to project closure. Enterprise Resource Planning (ERP) is an information technology solution that enables businesses and their suppliers to manage large projects effectively and efficiently throughout the project life cycle. Proper utilization of internal and external resources is very important if a construction company wants to make the best business decisions, maximize business goals, and survive in a competitive environment, it requires a system that can integrate various business functions and resources, especially those related to project procedures. Thus, a system Enterprise Resource Planning Construction System as a Construction Management Solution is designed. This system was developed using the waterfall software development methodology, which consists of four stages. Among other things, analyzing and defining features, constraints and system objectives, conducting system design to form a system architecture based on predetermined requirements using UML, implementing and unit testing and performing system integration and testing. The result of this research is an Enterprise Resource Planning Construction system that integrates Invoicing, Customer Relationship Management, Sales, Purchase, Inventory, Human Resource and Project modules. So that this system can be an alternative construction project management solution for managing construction projects online.
PENERAPAN METODE HYBRID-BASED RECOMMENDATION PADA SISTEM REKOMENDASI LAPTOP: Implementation of Hybrid-Based Recommendation Method in a Laptop Recommendation System Sari, Nova Noor Kamala; Christian , Efrans; Alparez Rati , Rizky
Jurnal Teknologi Informasi: Jurnal Keilmuan dan Aplikasi Bidang Teknik Informatika Vol. 19 No. 1 (2025): Jurnal Teknologi Informasi : Jurnal Keilmuan dan Aplikasi Bidang Teknik Inform
Publisher : Universitas Palangka Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47111/jti.v19i1.22585

Abstract

Recommendation systems play a crucial role in helping users choose complex and diverse products, such as laptops, which have numerous and varied technical attributes. This research aims to implement a Hybrid-Based Recommendation method that combines Content-Based Filtering (CBF) and Collaborative Filtering (CF). CBF is implemented using TF-IDF Vectorization and cosine similarity to recommend laptops based on technical attribute similarity. Concurrently, CF uses Singular Value Decomposition (SVD) to predict user preferences based on rating history. A Cascade Hybrid strategy is applied by filtering initial candidates from CBF and then re-ranking them using rating predictions from CF. The dataset comprises laptop data and user ratings obtained from Kaggle. Evaluation is performed using the NDCG metric to measure the relevance order of recommendations and MAPE to assess prediction accuracy. The research results indicate that this hybrid system is capable of generating relevant and personalized recommendations, with an NDCG value of 0.9838 and a MAPE value of 27.94%. The study concludes that the integration of CBF and CF through a hybrid approach effectively produces relevant and effective recommendations. For future development, exploring other hybrid methods, parameter optimization, and direct user testing are suggested.
Optimized ensemble framework for predicting hydroponic stock and sales using machine learning Pranatawijaya, Viktor Handrianus; Priskila, Ressa; Putra, Putu Bagus Adidyana Anugrah; Sari, Nova Noor Kamala; Christian, Efrans; Geges, Septian; Kristianti, Novera
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 14, No 5: October 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v14.i5.pp3879-3886

Abstract

The increasing global demand for food necessitates the adoption of sustainable agricultural practices. Hydroponic farming, while efficient in resource utilization, faces challenges in accurately predicting stock levels and sales due to dynamic, ever-changing factors. This research presents an optimized ensemble framework for forecasting hydroponic stock levels and sales by integrating linear regression (LR), random forest (RF), and XGBoost, further enhanced through an evolutionary algorithm (EA). The proposed framework is evaluated using root mean square error (RMSE) and mean absolute error (MAE), demonstrating significant accuracy improvements over individual models. The ensemble model achieves an RMSE reduction of 43.82% for stock prediction and 55.3% for sales forecasting compared to the best-performing individual model. Additionally, local interpretable model-agnostic explanations (LIME) are employed to offer stakeholders clear insights into decision-making processes, such as identifying "number of harvested crops" and "sales data" as key drivers of prediction outcomes. This framework supports sustainable development goals (SDGs) 9.3, 12.3, and 12.C by promoting resource efficiency, reducing food waste, and improving small-scale farmer market access. Future research will explore real-time data integration for dynamic adaptation and further model enhancements.
IMPLEMENTASI CONTENT-BASED FILTERING MENGGUNAKAN TF-IDF AND COSINE SIMILARITY UNTUK SISTEM REKOMENDASI RESEP MASAKAN Priskila, Ressa; Nova Noor Kamala Sari; Putu Bagus Adidyana Anugrah Putra
Jurnal Teknologi Informasi: Jurnal Keilmuan dan Aplikasi Bidang Teknik Informatika Vol. 18 No. 1 (2024): Jurnal Teknologi Informasi : Jurnal Keilmuan dan Aplikasi Bidang Teknik Inform
Publisher : Universitas Palangka Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47111/jti.v18i1.12543

Abstract

Many housewives are still confused about what dishes they will cook with existing food ingredients. Most housewives get recipe ideas from the website. Recipes from the website have the advantage of being easily accessible, but the disadvantages are sometimes troublesome for users because they have to choose a recipe from which site because there are many sites that contain the same recipe, and most of the recipe websites on the internet do not have a feature to search recipes based on the ingredients they have. The aim of this research is to implement a content-based filtering method using TF-IDF and cosine similarity for a recipe recommendation system. The TF-IDF and cosine similarity models are used to find similarity values between material data in the database and the query entered by the user in the search form. The sample data used in this research is 30 recipe data points taken from the website makapahariini.com. As a result, this system displays recipe recommendations that match the query of ingredients inputted by the user on the search form, and based on the test results using root mean square error (RMSE), it can be said that the recommendation system with the content-based filtering method that has been implemented produces quite good recommendations with a value of 0.356359182.
Pelatihan Aplikasi Augmented Reality Pengenalan Buah-Buahan bagi Guru Pendidikan Anak Usia Dini (PAUD) Pandehen Kristianti, Novera; Ressa Priskila; Widiatry; Viktor Handrianus Pranatawijaya; Putu Bagus Adidyana Anugrah Putra; Nova Noor Kamala Sari; Efrans Christian; Septian Geges
Jurnal Atma Inovasia Vol. 4 No. 4 (2024)
Publisher : Lembaga Penelitian dan Pengabdian pada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/jai.v4i4.9437

Abstract

Pelatihan aplikasi Augmented Reality (AR) pengenalan buah-buahan ini diselenggarakan untuk guru Pendidikan Anak Usia Dini (PAUD) di Pandehen dengan tujuan meningkatkan kualitas pembelajaran dan keterampilan guru dalam memanfaatkan teknologi modern. Dalam pelatihan ini, guru-guru PAUD diperkenalkan dengan aplikasi AR yang dirancang khusus untuk membantu anak-anak mengenal berbagai jenis buah-buahan secara interaktif dan menyenangkan. Metode pelatihan meliputi sesi teori dan praktik, di mana para peserta diajarkan cara mengoperasikan aplikasi AR, memahami fitur-fiturnya, serta bagaimana mengintegrasikannya ke dalam kegiatan belajar mengajar di kelas. Hasil dari pelatihan ini diharapkan dapat meningkatkan kemampuan guru dalam menggunakan teknologi sebagai alat bantu edukatif, memperkaya pengalaman belajar anak-anak, serta menciptakan lingkungan pembelajaran yang lebih dinamis dan interaktif. Evaluasi terhadap efektivitas pelatihan dilakukan melalui observasi langsung, kuesioner, dan wawancara dengan para peserta. Ditemukan bahwa pelatihan ini secara signifikan meningkatkan pengetahuan dan keterampilan guru dalam menggunakan aplikasi AR, serta memberikan dampak positif terhadap minat dan partisipasi anak-anak dalam kegiatan belajar. Kesimpulannya, pelatihan ini berhasil mencapai tujuan yang diharapkan dan direkomendasikan untuk diterapkan secara lebih luas di berbagai lembaga pendidikan PAUD.
Analisis Sentimen Berbasis Aspek pada Ulasan Aplikasi Gojek Rahman, Resha Ananda; Pranatawijaya, Viktor Handrianus; Sari, Nova Noor Kamala
KONSTELASI: Konvergensi Teknologi dan Sistem Informasi Vol. 4 No. 1 (2024): Juni 2024
Publisher : Program Studi Sistem Informasi Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/konstelasi.v4i1.8922

Abstract

Penggunaan aplikasi mobile meningkat pesat di era digital, termasuk Gojek, aplikasi populer di Indonesia yang menyediakan layanan transportasi, pesan antar makanan, dan pembayaran digital. Ulasan pengguna di Play Store menunjukkan berbagai masalah yang memerlukan perhatian. Ulasan ini memberikan wawasan tentang pandangan pengguna, memungkinkan identifikasi masalah, dan pengembangan layanan. Dengan teknik Aspect Based Sentiment Analysis (ABSA), pandangan pengguna dapat dipahami lebih baik, membantu evaluasi dan perbaikan aplikasi Gojek untuk meningkatkan kualitas layanan dan kepuasan pengguna. Penelitian ini bertujuan menganalisis sentimen berdasarkan aspek-aspek dalam ulasan pengguna aplikasi Gojek di Play Store dalam bahasa Inggris, dengan mencari pola sentimen yang akurat dan mengidentifikasi aspek yang perlu diperbaiki. Data diambil dari ulasan pengguna aplikasi Gojek di Google Play Store. Teknik pemodelan topik Latent Dirichlet Allocation (LDA) digunakan untuk mengidentifikasi topik-topik relevan. Pelabelan sentimen dilakukan menggunakan model BERT, sementara evaluasi sentimen dan aspek dilakukan dengan model distilbert-base-uncased-finetuned-sst-2-english. Hasil menunjukkan bahwa model BERT mencapai akurasi tertinggi untuk sentimen sebesar 96.67% dan aspek Service sebesar 98.78%. Terdapat ruang untuk perbaikan terutama pada aspek user experience, service, dan payment. Faktor-faktor yang mempengaruhi akurasi termasuk distribusi sentimen, jumlah data, preprocessing, dan model yang digunakan. Mobile app usage is increasing rapidly in the digital era, including Gojek, a popular app in Indonesia that provides transportation, food delivery, and digital payment services. User reviews in the Play Store indicate various issues that require attention. These reviews provide insight into user views, enabling problem identification and service development. With the Aspect Based Sentiment Analysis (ABSA) technique, user views can be better understood, helping evaluate and improve the Gojek application to improve service quality and user satisfaction. This research aims to analyze sentiment based on aspects of user reviews of the Gojek application on the Play Store in English by finding accurate sentiment patterns and identifying aspects that need to be improved. The data was taken from user reviews of the Gojek application on the Google Play Store. Latent Dirichlet Allocation (LDA) topic modeling technique was used to identify relevant topics. Sentiment labeling was performed using the BERT model, while sentiment and aspect evaluation were performed with the distilbert-base-uncased-finetuned-sst-2-english model. The results showed that the BERT model achieves the highest accuracy for sentiment at 96.67% and Service aspects at 98.78%. There is room for improvement, especially in the user experience, service, and payment aspects. Factors affecting accuracy include sentiment distribution, amount of data, preprocessing, and the model used.
IMPLEMENTASI API CHATGPT SUMMARIZER BERBASIS WEBSITE Syahrohim, Imam; Saputra, Septian Dwi; Pranatawijaya, Viktor Handrianus; Sari, Nova Noor Kamala
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.v12i3.4313

Abstract

Penelitian ini memaparkan implementasi API ChatGPT sebagai komponen utama dalam membangun sistem peringkas teks otomatis berbasis website. Dengan semakin melimpahnya informasi dalam bentuk teks di era digital, kebutuhan untuk meringkas konten menjadi ringkasan yang padat namun informatif menjadi semakin penting. Sistem yang diusulkan mengintegrasikan model peringkasan teks canggih dari OpenAI, yakni ChatGPT, ke dalam aplikasi web agar dapat diakses secara luas oleh pengguna. Implementasi mencakup pembangunan antarmuka pengguna yang intuitif, server backend untuk memroses permintaan, serta mekanisme integrasi dengan API ChatGPT. Hasil evaluasi menunjukkan bahwa sistem mampu menghasilkan ringkasan berkualitas. Analisis mendalam terhadap output ringkasan juga dilakukan untuk mengidentifikasi area perbaikan seperti peningkatan kemampuan identifikasi informasi penting, optimalisasi kejelasan, penyesuaian gaya bahasa, dan penambahan fitur kontrol bagi pengguna. Penelitian ini berkontribusi pada pemanfaatan teknologi AI terkini untuk memfasilitasi akses terhadap informasi penting dari teks panjang secara efisien melalui platform website.
PENERAPAN TEKNOLOGI AI DARI GEMINI UNTUK MENINGKATKAN LAYANAN PEMINJAMAN BUKU ONLINE PADA APLIKASI COZYBOOK lena, Martha; Florensia, Nela Puspita; Patimah, Yulia; Pranatawijaya, Viktor Handrianus; Sari, Nova Noor Kamala
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.v12i3.4396

Abstract

Penelitian ini bertujuan untuk mengembangkan aplikasi peminjaman buku online bernama CozyBook yang berbasis mobile. Aplikasi ini menggunakan teknologi Flutter dan mengintegrasikan API dari proyek website serta Artificial Intelligence (AI) dari Gemini. CozyBook menawarkan solusi bagi keterbatasan ruang fisik perpustakaan tradisional dan memungkinkan pengguna untuk mengakses layanan perpustakaan digital dengan mudah melalui perangkat mobile. Implementasi AI dalam CozyBook bertujuan untuk meningkatkan pengalaman pengguna dan efektivitas layanan peminjaman buku online. Fitur AI ini mencakup chatbot untuk layanan pengguna. Dengan demikian, CozyBook diharapkan dapat menjadi alternatif yang efisien dan inovatif untuk sistem peminjaman buku konvensional, serta mendorong minat baca di kalangan masyarakat.
Co-Authors ., Widiatry ., Widiatry Agus Sehatman Saragih Agustin, Ria Ainah, Saripah Alparez Rati , Rizky Amrullah, Rizaldi Anak Agung Istri Sri Wiadnyani Ananda Khairunnisa, Puteri Ananingtyas, Arifatul Andini, Wafik Annisa, Norul Anorgi, Andrew Aprilia, Salsabila Aprilita Aprilita Aprimikardo, Aprimikardo Arief, Muhammad Risman Ariesta Lestari Arifatul Ananingtyas Armadyah Amborowati Aryabimo, Agsa Rakha Bamulki, Margareta Bernady, Delon Cahya Kamilla, Adinda Candra Wijaya, Candra Candrawati, Nuri Chitayae, Nadya Christian , Efrans Cristian Harati, Cadeck Dewi Masitoh, Reina Dhia Yusrana, Rafif Diantoro, Ironaldo DWI SURYANTO Dwiwicaksono, Ardhy Dwiyankie, Ravema Nanda Efrans Christian Ema Utami Fajari, Rizqi Felicia Sylviana Ferry Wahyudi Firdo, Daud Florensia, Nela Puspita Gunawan, Vincentius Abdi Hadi, Muhammad Ilmiannor Handrianus Pranatawijaya, Viktor Hariyadi Hariyadi Imamsyah, Rasyid Noor Irma Kristiani Putri Jakkirahman , Jakkirahman Jordi Irawan Jovito, Felik Rolantius Kevin Obajha Kristianti, Novera Kristianto, Hefi Lena, Martha Leonardo, Tomas licantik licantik Licantik Licantik Licantik, Licantik Lusia Kiareni, Cindi Maharani, Audry Marhayu Marhayu Marhayu, Marhayu Marsha Zahra Martha lena Munthe, Samuel Septa Nasution, Annio Indah Lestari Nazarius, Atong Nela Puspita Florensia Noor Hasanah Novanti, Anastia Ivanabilla Novia Fitriani Novita, Rebecca Nur Chusnul Khotimah, Yusie Nurdin Nurdin Olpah, Syahrida Patimah, Yulia Priskila, Ressa Priyani, Natasya Purba, Fernata Firdaus Purmasari Putra, Putu Bagus A.A. Putra, Putu Bagus Adidyana Anugrah Rahman, Resha Ananda Ramanda Kalawa Putri, Maria Rebecca Novita Resha Ananda Rahman Ressa Priskila Revelin Putri, Nadya Ronaldo, Deddy Saputra, Ferry Saputra, Septian Dwi Septian Geges Septian Geges Sihite, Putri Simorangkir, Anastasya Sinta Septiani, Clara Sorisa, Cinda Surana, Yogi Andy Pratama Syahrohim, Imam Tomas Leonardo Valentine, Virginia Vianus, Rezaski Yoan Viktor Handrianus Pranatawijaya Viktor Handrianus Pranatawijaya Widiatry Widiatry Widiatry, Widiatry Yudhistira, Aditya Septian Yukandri, Yukandri Yulia Patimah Zahra, Marsha Zakharia Zakharia Zakharia, Zakharia