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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Jurnal Informatika dan Teknik Elektro Terapan CESS (Journal of Computer Engineering, System and Science) Jurnal Informatika Upgris Jurnal Sains dan Informatika Matrix : Jurnal Manajemen Teknologi dan Informatika Simtek : Jurnal Sistem Informasi dan Teknik Komputer Technologia: Jurnal Ilmiah JURNAL TEKNIK Jurnal Teknologi Informasi : Jurnal Keilmuan dan Aplikasi Bidang Teknik Informatika JATI (Jurnal Mahasiswa Teknik Informatika) Jurnal Teknologi Informatika dan Komputer Jurnal Atma Inovasia JOINTECOMS (Journal of Information Technology and Computer Science) Diteksi : Jurnal Pengabdian Kepada Masyarakat

Priskila, Ressa

Universitas Palangka Raya

Author-ID : 3041841

Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Social Sciences Other

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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

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.

Chatbot Berbasis Whatsapp Teknik Informatika Universitas Palangkaraya: Rules Based System Saputra, Ferry; Handoko, Rifky Mustaqim; Putra, Wahyuni; Priskila, Ressa; Pranatawijaya, Viktor Handrianus
Jurnal Teknologi Informatika dan Komputer Vol. 10 No. 1 (2024): Jurnal Teknologi Informatika dan Komputer
Publisher : Universitas Mohammad Husni Thamrin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37012/jtik.v10i1.2111

Penelitian ini membahas pengembangan Chatbot Berbasis WhatsApp dengan Rules Based System untuk Teknik Informatika Universitas Palangkaraya. Dengan menerapkan aturan yang telah dirumuskan berdasarkan studi literatur dan kebutuhan pengguna, chatbot ini mampu merespon pertanyaan dan permintaan pengguna secara tepat dan konsisten. Selain itu, pemanfaatan API dari OpenAI, Optical Character Recognition (OCR), dan file CSV untuk menyimpan data turut mendukung pengembangan chatbot ini. Dengan adopsi teknologi yang lengkap, chatbot dapat memberikan respon kompleks dan kontekstual terhadap permintaan pengguna tanpa perlu menentukan aturan secara manual. Hasil penelitian ini memberikan gambaran tentang potensi chatbot dalam meningkatkan interaksi antara pengguna dan sistem informasi, dengan ini akan membantu para mahasiswa, dosen, dan pihak-pihak terkait pada Teknik Informatika Universitas Palangkaraya.

ENSEMBLE MAJORITY VOTING UNTUK ANALISIS SENTIMEN DAN EMOSI PADA KOMENTAR YOUTUBE: STUDI KASUS RESIDENT EVIL 4 REMAKE Ahmad Abdul Hadi; Priskila, Ressa; Viktor Handrianus Pranatawijaya; Kristianti, Novera
Jurnal Teknologi Informasi: Jurnal Keilmuan dan Aplikasi Bidang Teknik Informatika Vol. 19 No. 2 (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.v19i2.22397

Currently, social media can be said to be one of the important things in the fields of marketing, broadcasting and entertainment, such as the gaming industry. In this case, Sentiment Analysis and Emotion Detection can be a tool for understanding the public's response and perception of the content presented. One of them is for the game Resident Evil 4 Remake, which was announced on March 24, 2023, and received a lot of public response on various social media platforms such as YouTube, one of which received responses in the form of 7177 comments between June 3 2022 and February 9, 2024. The research methodology used includes data collection methodology and simulation methodology, by combining the Naive Bayes algorithm, SVM and BERT using the Majority Voting method where these algorithms were previously trained using two different datasets which showed Naive Bayes performance with an accuracy of 84%, SVM with 89%, BERT with 93% and the Majority Voting Method with 90% accuracy with training using the Resident Evil 4 Remake dataset. And in training with the Steam Game Review dataset, Naive Bayes and SVM were obtained with an accuracy of 53%, BERT with 66%, and the Majority Voting Method with an accuracy of 57%. The Majority Voting classification model trained on the Resident Evil 4 dataset was used to perform Sentiment Analysis classification on comments from the YouTube video entitled "Resident Evil 4 Remake: Reveal Trailer" from the IGN Channel. The ratio of positive and negative sentiments was 60.2% and 39%. .8% with the frequency of emotions of anger, excitement and anticipation appearing most frequently.

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

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

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.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37012/jtik.v10i1.2111

PERBANDINGAN ANALISIS SENTIMEN SETELAH PILPRES 2024 DI TWITTER MENGGUNAKAN ALGORITMA MACHINE LEARNING Syahrohim, Imam; Saputra, Septian Dwi; Saputra, Rizal Wahyu; Pranatawijaya, Viktor Handrianus; Priskila, Ressa
Jurnal Informatika dan Teknik Elektro Terapan Vol. 12 No. 2 (2024)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jitet.v12i2.4249

Penelitian ini bertujuan untuk menganalisis sentimen opini masyarakat di media sosial Twitter setelah Pemilihan Presiden 2024 menggunakan beberapa algoritma machine learning yaitu Naive Bayes, Support Vector Machine, dan Logistic Regression. Data yang digunakan bersumber dari Twitter dengan total 4.260 data yang terdiri dari 3 dataset calon presiden (Ganjar Pranowo, Anies Baswedan, dan Prabowo Subianto). Dilakukan proses crawling data, pembersihan data, pelabelan data menggunakan Vader, dan pelatihan data dengan TF-IDF sebelum dilakukan klasifikasi sentimen. Hasil eksperimen menunjukkan bahwa algoritma Logistic Regression memiliki performa terbaik pada dataset Ganjar Pranowo dengan akurasi 84,39%, presisi 84,92%, recall 84,39%, dan f-measure 81,52%. Penelitian ini memberikan insight tentang perbandingan performa algoritma klasifikasi dalam kasus analisis sentimen pada media sosial yang dapat digunakan sebagai referensi untuk penelitian serupa di masa mendatang.

SISTEM PAKAR REKOMENDASI OBAT BERDASARKAN GEJALA PENYAKIT MENULAR UMUM DI MASYARAKAT MENGGUNAKAN METODE FORWARD CHAINING Aprilia, Salsabila; Agustin, Ria; Marthalena, Marthalena; Pranatawijaya, Viktor Handrius; Priskila, Ressa
Jurnal Informatika dan Teknik Elektro Terapan Vol. 12 No. 2 (2024)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jitet.v12i2.4258

Abstrak. Penyakit menular umum menjadi masalah kesehatan yang serius dikalangan masyarakat dengan dampak yang signifikan dan dapat mengganggu kegiatan sehari hari. Agar dapat membantu menangani diagnosa gejala awal penyakit menular dan memberikan rekomendasi obat yang sesuai, penelitian ini mengembangkan sistem pakar berbasis website untuk merekomendasikan obat berdasarkan gejala penyakit menular umum, dengan menggunakan metode forward chaining. Forward chaining merupakan penalaran berdasarkan fakta dan dimulai dari bawah ke atas. Forward chaining dimulai dari fakta yang sebelumnya sudah diketahui terlebih dahulu, baru setelah itu fakta-fakta akan dicocokkan dengan IF dari aturan IF-THEN. Sistem ini memberikan diagnosa awal dan saran pengobatan yang relevan. Penelitian ini mencakup identifikasi masalah, pengumpulan data, analisis, perancangan, implementasi, dan pengujian sistem. Hasil Implementasi menunjukkan sistem mampu memproses gejala dan memberikan rekomendasi obat yang tepat. Penelitian ini berperan penting dalam meningkatkan efektivitas penanganan penyakit menular di masyarakat melalui teknologi informasi.

IMPLEMENTASI SISTEM PAKAR DIAGNOSA PENYAKIT PADA SAPI BERBASIS WEB MENGGUNAKAN METODE FORWARD CHAINING Puspitarani, Siska; Andini, Wafik; Masitoh, Reina Dewi; Pranatawijaya, Viktor Handrianus; Priskila, Ressa
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.v12i3.4368

Kemajuan informasi teknologi telah membuka jalan bagi terciptanya sistem yang dapat membantu dalam mendiagnosa penyakit pada sapi dan hewan ternak lainnya. Tulisan ini membahas proses pembuatan sistem pakar berbasis web yang menggunakan pendekatan Forward Chaining untuk mendiagnosa penyakit sapi. Pendekatan ini memungkinkan sistem untuk membuat diagnosis penyakit menggunakan gejala yang diinputkan oleh pengguna. Tantangan yang dihadapi oleh para peternak sapi dalam mengenali gejala-gejala penyakit ternak yang berpotensi mendorong dilakukannya penelitian ini. Sistem pakar yang disarankan akan membantu dalam diagnosis penyakit sapi dan menyediakan perawatan yang sesuai. Instalasi sistem, tahap penelitian, dan hasil pengujian langsung dalam artikel ini. Penelitian ini bertujuan untuk meningkatkan kesehatan hewan, khususnya sapi, dan berfungsi sebagai sumber daya bagi mereka yang akan membuat sistem pakar di masa depan.

PERANCANGAN SISTEM INFORMASI PENYEWAAN GEDUNG PERTEMUAN DI KOTA PALANGKA RAYA BERBASIS WEB sari, purma; Priskila, Ressa
Jurnal Teknik Vol. 13 No. 1 (2024): Januari - Juli 2024
Publisher : Universitas Muhammadiyah Tangerang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31000/jt.v13i1.12284

AbstrakSistem informasi penyewaan gedung pertemuan ini dibangun dengan tujuan sebagai sarana yang dapat membantu pengelola gedung dalam menyampaikan informasi ketersediaan gedung, fasilitas gedung, kapasitas gedung, harga sewa gedung, dan membantu penyewa dalam mendapatkan informasi ketersediaan gedung pertemuan di kota Palangka Raya serta melakukan pemesanan, tanpa harus datang langsung ke pengelola gedung. Selain untuk memberikan informasi kepada penyewa sistem juga dapat membantu pengelola gedung dalam mengelola penyewaan gedung seperti penjadwalan, pemesanan gedung, pencatatan penyewaan dan pencatatan pembayaran. Metodologi dalam pembuatan website ini menggunakan metode waterfall, yang terdiri atas beberapa tahapan, yaitu analysis, design, coding, dan testing. Bahasa pemrograman yang digunakan adalah PHP dan MySQL sebagai database.Â Pada tahap testing website ini menggunakan black box testing. Black-Box Testing fokus pada spesifikasi fungsional dari program. Setelah melakukan testing, dapat dilihat hasil dari pembuatan website dapat berjalan dengan baik. Untuk penelitian lebih lanjut, dapat menambahkan fitur live chat yang digunakan pengunjung untuk berkomunikasi dengan admin gedung secara langsung melalui website.Â Kata kunci: sistem informasi penyewaan gedung pertemuan, website, PHP, MySQL, waterfall

Co-Authors ., Yukandri Ade Chandra Saputra Agus Sehatman, Saragih Agustin, Ria Ahmad Abdul Hadi Ahmad Fadli Ahmad Iqbal Ananda Khairunnisa, Puteri Andika Prayoga Andini, Wafik Annisa, Norul Aprilia, Salsabila Apriliani Natasya Arief, Muhammad Risman Arvin Ardianto Putra Aryapati Soebagijo, Rafael Azmiara Ahmadiham, Ahsana Cahya Kamilla, Adinda Damar Suryo Sasono Damayanti, Novrina Debora, Jessica Kurnia Delon Pratama, Ryan Depro Winoto Desta Aditia, Veven Dimas Lumban Gaol Efrans Christian Fajar, M Fajari, Rizqi Felicia Sylviana Firmansyah, Muhammad Rizal Florensiana Talentina Angela Seda Gavin Berylian Josepto Gebri Meizeri Cordias Hana Husna Safitri Handoko, Rifky Mustaqim Handrianus Pranatawijaya , Viktor Handrianus Pranatawijaya, Viktor Intani Sihite, Putri Isachar, Michael Jadiaman Parhusip Jadiaman Parhusip, Jadiaman Jama, Luniko Kalawa Putri, Maria Ramanda Kristianti, Novera Leonardo, Tomas Licantik Licantik Licantik, Licantik limbong, Theodorus Lusia Kiareni, Cindi M Fajar Magnus, Thomas Zugildo Marthalena Marthalena marthalena, marthalena Masitoh, Reina Dewi Nazarius, Atong Nelda, Lia Nova Noor Kamala Sari Nova Noor Kamala Sari Novera Kristianti Nur Safa, Yunisa Nurdin Nurdin Patimah, Yulia Pranatawijaya, Viktor Handrius Priyani, Natasya Purmasari Purmasari Purmasari Puspita Florensia, Nela Puspitarani, Siska Putra, Putu Bagus Adidyana Anugrah Putra, Wahyuni Putri, Oktaviani Enjela Re Manuel Putra Sihombing, Thomas Ria Agustin Rueh Daya Leluni, Ekat Sagita Amaria Christie Salsabila Aprilia Saputra, Ferry Saputra, Rizal Wahyu Saputra, Septian Dwi Sari, Purma Senas, Jonathan Markus Septian Geges Septian Geges Simorangkir, Anastasya Sinta Septiani, Clara Sorisa, Cinda Sunardi Sunardi Surana, Yogi Andy Pratama Syahrohim, Imam Tayah, Hernila Tomas Leonardo Tryastie, Melisa Valentine, Virginia Viktor Handrianus Pranatawijaya Viktor Handrius Pranatawijaya Widiatry Widiatry, Widiatry Winoto, Depro Yolanda Hevin, Tirza Yosia Wibowo, Lucky Yudhistira, Aditya Septian

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