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All Journal International Journal of Electrical and Computer Engineering IAES International Journal of Robotics and Automation (IJRA) IAES International Journal of Artificial Intelligence (IJ-AI) Bulletin of Electrical Engineering and Informatics Scientific Journal of Informatics Proceeding of the Electrical Engineering Computer Science and Informatics Sistemasi: Jurnal Sistem Informasi Jurnal Teknologi dan Sistem Komputer Informatika Mulawarman: Jurnal Ilmiah Ilmu Komputer SISFOTENIKA IJCIT (Indonesian Journal on Computer and Information Technology) Knowledge Engineering and Data Science IT JOURNAL RESEARCH AND DEVELOPMENT JOURNAL OF APPLIED INFORMATICS AND COMPUTING JURNAL REKAYASA TEKNOLOGI INFORMASI SINTECH (Science and Information Technology) Journal JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Sebatik ILKOM Jurnal Ilmiah Digital Zone: Jurnal Teknologi Informasi dan Komunikasi MIND (Multimedia Artificial Intelligent Networking Database) Journal Prosiding SAKTI (Seminar Ilmu Komputer dan Teknologi Informasi) EXPLORE TELKA - Telekomunikasi, Elektronika, Komputasi dan Kontrol Jurnal SITECH : Sistem Informasi dan Teknologi Building of Informatics, Technology and Science JISKa (Jurnal Informatika Sunan Kalijaga) Sains, Aplikasi, Komputasi dan Teknologi Informasi Journal of Innovation Information Technology and Application (JINITA) Innovation in Research of Informatics (INNOVATICS) Jurnal Pengabdian UNDIKMA Jurnal Teknik Informatika (JUTIF) Vivabio : Jurnal Pengabdian Multidisiplin Jurnal PTI (Jurnal Pendidikan Teknologi Informasi) JP2KG AUD (Jurnal Pendidikan, Pengasuhan, Kesehatan dan Gizi Anak Usia Dini) JUSTIN (Jurnal Sistem dan Teknologi Informasi) BIOS : Jurnal Teknologi Informasi dan Rekayasa Komputer JAIA - Journal of Artificial Intelligence and Applications EXPLORE Jurnal Bina Komputer JAPI: Jurnal Akses Pengabdian Indonesia Data Sciences Indonesia (DSI) Jurnal Masyarakat Madani Indonesia Journal Of Artificial Intelligence And Software Engineering The Indonesian Journal of Computer Science Inovasi Teknologi Masyarakat Jurnal Pengabdian Siliwangi
Puspitasari, Novianti
Program Studi Informatika, Fakultas Teknik, Universitas Mulawarman
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Biochemistry, Genetics & Molecular Biology 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 Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Nursing Physics Public Health Social Sciences Other

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Quality Classification of Palm Oil Varieties Using Naive Bayes Classifier Puspitasari, Novianti; Rosmasari, Rosmasari; Pratama, Fhanji Wilis; Sulastri, Heni
Digital Zone: Jurnal Teknologi Informasi dan Komunikasi Vol. 13 No. 1 (2022): Digital Zone: Jurnal Teknologi Informasi dan Komunikasi
Publisher : Publisher: Fakultas Ilmu Komputer, Institution: Universitas Lancang Kuning

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31849/digitalzone.v13i1.9773

Abstract

As one of the leading commodities of the Indonesian economy, the ever-increasing production of palm oil has created intense competition among palm oil (CPO) producers. This causes CPO producers to increase their palm oil production without compromising the quality of the palm oil produced. CPO producers are required to be able to objectively determine the quality of superior and precise oil palm varieties in order to produce high economic value palm oil. Therefore, a model is needed to determine the quality of oil palm from several existing varieties. The Naive Bayes Classifier method in this study was used to classify the quality of oil palm based on predetermined variables using a data set of 28 oil palm varieties. Method testing is done by using a confusion matrix and K-fold cross-validation scheme. This study shows a reasonably high accuracy value of 64.25% and a low error rate of 35.7%, indicating that the Naive Bayes Classifier can classify the quality of oil palm varieties quite well.
Preparing Retro Arcade Fighting Game Asset Design Arifin, Zainal; Waksito, Alan Zulfikar; Firdaus, Muhammad Bambang; Puspitasari, Novianti
JAIA - Journal of Artificial Intelligence and Applications Vol. 3 No. 2 (2023): JAIA - Journal of Artificial Intelligence and Applications
Publisher : STMIK Amik Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33372/jaia.v3i2.1062

Abstract

Games are increasingly popular in Indonesia because of the many things that make them exciting, such as esports. The Fighting Game genre is one that contains a fight between two characters in a place or arena with the aim of depleting the opponent's HP (health points). Fighting Games use 2-dimensional and/or 3-dimensional graphics where players play characters who can punch, jump or squat when fighting characters. other. In designing video game assets, researchers used the GDLC (Game Development Life Cycle) methodology so that this research proceeded systematically and focused on the design of game asset components. In designing a video game there are many elements, in this research the author focuses more on the control assets of the Combo Hit System on a game character called Brawl Tale.
Classification of tea leaf disease using convolutional neural network approach Hairah, Ummul; Septiarini, Anindita; Puspitasari, Novianti; Tejawati, Andi; Hamdani, Hamdani; Eka Priyatna, Surya
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 3: June 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i3.pp3287-3294

Abstract

Leaf diseases on tea plants affect the quality of tea. This issue must be overcome since preparing tea drinks requires high-quality tea leaves. Various automatic models for identifying disease in tea leaves have been developed; however, their performance is typically low since the extracted features are not selective enough. This work presents a classification model for tea leaf disease that distinguishes six leaf classes: algal spot, brown, blight, grey blight, helopeltis, red spot, and healthy. Deep learning using a convolutional neural network (CNN) builds an effective model for detecting tea leaf illness. The Kaggle public dataset contains 5,980 tea leaf images on a white background. Pre-processing was performed to reduce computing time, which involved shrinking and normalizing the image prior to augmentation. Augmentation techniques included rotation, shear, flip horizontal, and flip vertical. The CNN model was used to classify tea leaf disease using the MobileNetV2 backbone, Adam optimizer, and rectified linear unit (ReLU) activation function with 224×224 input data. The proposed model attained the highest performance, as evidenced by the accuracy value 0.9455.
Dipterocarpaceae trunk texture classification using two-stage convolutional neural network-based transfer learning model Wati, Masna; Puspitasari, Novianti; Hairah, Ummul; Widians, Joan Angelina; Tjikoa, Ade Fiqri
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 6: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i6.pp6874-6882

Abstract

The importance of plant identification has been recognized by academia and industry. There have been several attempts to utilize leaves and flowers for identification. However, the trunk can also be helpful, especially for tall trees. In Borneo, the Dipterocarpaceae family are the main constituents of the tropical rainforest ecosystem. This research focuses on the classification of the dipterocarp family, which can reach a height of between 70 and 85 m. Leveraging convolutional neural network (CNN) models, this research proposes a two-stage transfer learning strategy. In the first stage, the pre-trained CNN models are refined by only modifying the classification layer while keeping the feature layer frozen. The second stage involves selecting and freezing several convolutional layers to adapt the model to classify dipterocarp stems. The dataset consists of 857 images of different dipterocarp species. Experiments show that the VGG16 model with a two-stage transfer learning strategy achieves a high accuracy of 98.246%. This study aims to accurately identify species, benefiting conservation and ecological studies by enabling fast and reliable tree species classification based on stem texture images.
The color features and k-nearest neighbor algorithm for classifying betel leaf image Hamdani, Hamdani; Septiarini, Anindita; Puspitasari, Novianti; Tejawati, Andi; Alameka, Faza
IAES International Journal of Robotics and Automation (IJRA) Vol 13, No 3: September 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijra.v13i3.pp330-337

Abstract

Piper betle L. (betel) is a species that belongs to the genus Piper and is a type of medicinal plant that is quite well known to the general population. The varieties of the leaf color may distinguish are red, green, and black betel. However, consumers still need assistance determining the differences between the many types of betel leaf. Therefore, using image processing techniques, this research contributes to building a classification method for distinguishing betel leaves based on color attributes. This approach anoints for the region of interest detection, feature extraction, and classification. In addition, three different classifiers, naïve Bayes, support vector machine, and k-nearest neighbors (k-NN), were used during the classification process. The evaluation for this study used a percentage split to divide a total of 180 images between the training and testing phases. The method’s performance provided the highest accuracy value possible, 100%, by utilizing the color characteristics with the k-NN classifier.
REKOMENDASI BUKU PERPUSTAKAAN KAMPUS DENGAN METODE ITEM-BASED COLLABORATIVE FILTERING Rosita, Aliffia; Puspitasari, Novianti; Kamila, Vina Zahrotun
Sebatik Vol. 26 No. 1 (2022): Juni 2022
Publisher : STMIK Widya Cipta Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46984/sebatik.v26i1.1551

Abstract

Artikel ini menawarkan alternatif solusi atas banyaknya jumlah buku yang terdapat dalam perpustakaan sehingga membuat beberapa mahasiswa kesulitan dalam menentukan pilihan mengenai buku yang tepat sesuai dengan ketertarikan mahasiswa. Metode rekomendasi yang akurat bisa menjadi sebuah solusi untuk mengatasi permasalahan tersebut. Metode item-based collaborative filtering merupakan metode yang memberikan prediksi sebuah item kepada pengguna berdasarkan ketertarikan dan opini dari pengguna lain. Penelitian ini menggunakan metode item-based collaborative filtering yang diterapkan pada rekomendasi untuk memberikan rekomendasi buku kepada mahasiswa. Data yang digunakan pada penelitian ini adalah data buku dan pengunjung dari tahun 2016 hingga 2019. Metode item-based collaborative bekerja dengan mencari nilai kemiripan suatu item yang belum pernah diberikan rating dengan item yang telah diberi rating menggunakan persamaan cosine similarity. Hasil perhitungan kemiripan antar item digunakan pada perhitungan prediksi rating menggunakan persamaan Weighted sum yang nilai prediksinya akan dijadikan rekomendasi kepada mahasiswa. Hasil penelitian menunjukkan bahwa metode item-based collaborative filtering mampu memberikan rekomendasi kepada mahasiswa dengan persentase pengujian akurasi MAPE sebesar 22% dan pengujian akurasi MAE sebesar 0.568.
Sistem Pakar Pemilihan Serum Wajah Menggunakan Metode Certainty Factor (Studi Kasus Produk Avoskin) Puspitasari, Novianti; Mulia, Amalia Budiana; Hamdani, Hamdani; Masa, Amin Padmo Azam
BIOS : Jurnal Teknologi Informasi dan Rekayasa Komputer Vol 5 No 1 (2024): March
Publisher : Puslitbang Sinergis Asa Professional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37148/bios.v5i1.85

Abstract

More and more people are aware of the importance of caring for facial skin, resulting in skincare production proliferating. Various kinds of skincare products are on the market, including facial serum. Facial serum is superior because it contains higher levels of active substances than other skincare products. The content and composition of a facial serum varies greatly and has different functions because the skin types and problems experienced are different. This means that users cannot use facial serum carelessly. Through this research, an expert system was created by applying the Certainty Factor method to identify facial serums, especially Avoskin products, which are expected to help the public determine facial serums that suit the type and skin problems they are experiencing. This study used 21 data on facial skin symptoms with eight types of Avoskin Your Skin Bae serum products. Based on the test results using the system accuracy percentage method, an accuracy of 85% was obtained so that the expert system created could run well.
SISTEM PAKAR BAWANG DAYAK SEBAGAI OBAT ALTERNATIF Widians, Joan Angelina; Puspitasari, Novianti; Kurniawan, Tri Basuki
Jurnal Bina Komputer Vol 3 No 1 (2021): Jurnal Bina Komputer
Publisher : Jurnal Ilmiah Terpadu Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1111.735 KB) | DOI: 10.33557/binakomputer.v2i2.976

Abstract

The medicinal plants that have been developed especially in East Kalimantan is the dayak onion (Eleutherine palmifolia (L.) Merr). The Dayak onion herb has long been used by the Dayak tribe as an alternative medicine. Information of the possibility of people affected by the disease and how to process Dayak onion ingredients , an expert system needs to build that is able to diagnose the disease and how to process Dayak onion ingredients. The result of this research is an expert system with Certainty Factor that helps the general public in early diagnosis of ten diseases and provides alternative treatment solutions and ways of Dayak onion as an alternative medicine.
Teknologi Arsip Digital sebagai Upaya Peningkatan Layanan Administrasi di Kelurahan Sungai Pinang Luar Kota Samarinda Puspitasari, Novianti; Septiarini, Anindita; Hakim, Muhammad Irvan; Afifah, Dinda Nur; Salsabila, Zahra; Fornia, Daviana Dwitasari Enka; Wahyudi, Moh Ikhwan; Pramudya, Pranata Eka; Hanif, Ahmad Luthfi
Inovasi Teknologi Masyarakat (INTEKMAS) Vol. 1 No. 1 (2023): June 2023
Publisher : Wadah Inovasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53622/intekmas.v1i1.189

Abstract

Pelayanan prima merupakan hal yang sangat penting dilakukan bagi organisasi maupun instansi. Di dalam sebuah instansi khususnya instansi yang menyediakan pelayanan administrasi untuk masyarakat sangat penting untuk melakukan transformasi digital dalam hal pengelolaan kearsipan (dokumen). Namun, saat ini instansi yang melayani administrasi berkaitan dengan dokumen masyarakat khususnya surat menyurat masih belum maksimal dalam pelayanan dan pengelolaan arsipnya. Masalah inilah yang ditemui di Kelurahan Sungai Pinang Luar. Proses pelayanan administrasi terkait pembuatan surat menyurat masih dilakukan secara konvesional. Masyarakat harus mendatangi pihak kelurahan untuk membuat surat, kemudian perangkat desa membuat surat tersebut dengan waktu tunggu yang cukup lama. Selain itu dokumen yang telah selesai dibuat tidak berbentuk digital sehingga perangkat desa terkadang kesulitan untuk menemukan kembali dokumen yang dibutuhkan dengan cepat. Oleh karena itu, diperlukan manajemen kearsipan melalui transformasi digital pada proses pelayanan administrasi. Kegiatan pengabdian masyarakat ini mengusulkan proses digitalisasi dokumen berupa metode pendampingan peningkatan keterampilan Sumber Daya Manusia (SDM) berbasis teknologi yang merupakan program kemitraan masyarakat antara perguruan tinggi dengan perangkat desa dan masyarakat. Program ini mentransfer pengetahuan tentang digitalisasi dokumen dan teknologi QR-Code berupa sosialisasi dan pelatihan tentang penggunaan QR-Code, LinkTree dan Google Form untuk mengelola arsip, menyebarkan dokumen dan mempermudah masyarakat untuk mengurus dokumen kependudukannya. Hasil dari kegiatan ini mampu memberikan pemahaman kepada perangkat desa dan masyarakat serta diterapkan secara berkelanjutan oleh masyarakat serta perangkat desa.
Pengaplikasian Google Docs Dan Google Slides Dalam Membantu Mengerjakan Tugas Siswa Di SMPN 44 Samarinda Septiarini, Anindita; Puspitasari, Novianti; Irfan, Aliya; Wintin, Chintia Liu; Wibisono, Bramantyo Ardi Harimurti; Maharani, Agustina Dwi; Fuad, Natalie; Laraswati, Sherina; Gunawan, Ayu Lestari
Inovasi Teknologi Masyarakat (INTEKMAS) Vol. 1 No. 1 (2023): June 2023
Publisher : Wadah Inovasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53622/intekmas.v1i1.192

Abstract

Kegiatan pelayanan masyarakat ini bertujuan untuk memberikan pengenalan dan pemahaman mengenai penggunaan Google Docs dan Google Slides kepada siswa-siswa SMPN 44 Palaran Samarinda. Hal ini dilakukan untuk mendukung pemahaman siswa terhadap materi yang diajarkan di SMPN 44 Palaran Samarinda. Aplikasi Google Docs dan Google Slides sangat cocok bagi siswa yang ingin bekerja sama secara langsung dalam satu berkas. Dalam praktiknya, pengetahuan dan penggunaan aplikasi Google Docs dan Google Slides di SMPN 44 Palaran Samarinda masih kurang. Oleh karena itu, melalui kegiatan ini dilakukan sosialisasi dan pelatihan penggunaan Google Docs dan Google Slides untuk memberikan pengetahuan kepada siswa bahwa bekerja sama dalam satu berkas menggunakan Google Docs atau Google Slides tidaklah sesulit yang dibayangkan, serta memberikan edukasi tentang pentingnya bekerja sama dalam satu berkas. Selain itu, kegiatan ini juga bertujuan untuk memberikan informasi mengenai manfaat Google Docs dan Google Slides bagi pemula.
Co-Authors Abu Bakar Adelowys Sinaga Adhistya Erna Permanasari Adnan, Fahrizal Afifah, Dinda Nur AHMAD ANSYORI Ahmad Suryadi, Ahmad Ahmad Wahbi Fadillah Ajay, Muhammad Aji Ayu Muvita Putri Alameka, Faza Alameka, Faza Alfajriani Alfajriani Alfredo Sinaga Ali Sholihin Alif Rifa’i Almasari Aksenta Alvito Gabbriel Saputra Ambari, Nasser Andre Ardin Maulana Anindita Septiarini, Anindita Anton Prafanto Arinda Mulawardani Kustiawan Asdar Zulkiawan Awang Harsa Kridalaksana Azzahra, Raudhya Brins Leonard Pailan Budiman, Edy Didit Suprihanto, Didit Eka Priyatna, Surya Ery Burhandenny, Aji Fahrul Agus Fairil Anwar Fajar Fatimah Farisha Rizky Amalia Fathia Nuq Qamarina Fauzan, Ahmad Nur Fayza Virdana Addiza Faza Alameka Faza Alameka Fazma Urmila Jannah Helmi Puadi Firdaus, Muhammad Firdaus, Muhammad Bambang Fornia, Daviana Dwitasari Enka Frans Karta Sayoga Sitohang Fuad, Natalie Gerda, Misselina Madya Gubtha Mahendra Putra Gunawan, Ayu Lestari Gunawan, Santika Haeruddin, Haeruddin Hairah, Ummul Hairah, Ummul Hakim, Muhammad Irvan Hamdani Hamdani Hamdani Hamdani Hanif, Ahmad Luthfi Hanung Adi Nugroho Hatta, Heliza Rahmania Haviluddin Haviluddin Haviuddin, Haviluddin Heliza Hatta Heliza Rahmania Hatta, Heliza Rahmania Helmi Puadi, Fazma Urmila Jannah Hemelia, Junita Henderi . Heni Sulastri Herman Santoso Pakpahan Hidayat, Ahmad Nur Hijratul Aini Iin Nurkarima Indah Wulan Lestari Irfan, Aliya Islamiyah Islamiyah Joan Angelina Widians, Joan Angelina Julius Rinaldi Simanungkalit Kalista, Nazwa Nur Maulida Qintani Kamila, Vina Zahrotun Kurniati, Wendy Kurniawan, Tri Basuki Lalu Delsi Samsumar, M.Eng. Laraswati, Sherina Latifa Gorriana Gusmaningrum Lempas, Gidion M. Rizky Nilzamyahya Maharani, Agustina Dwi Mahendra, Dicky Alvian Masa, Amin Padmo Azam Masna Wati Maya Agustina Mega Yoalifa Mewengkang, Alfrina Muhammad Abdillah Muhammad Dzacky Muhammad Firdaus Mulia, Amalia Budiana Nataniel Dengen Noval Bayu Setiawan Nur Hasanah Nurhidayat, Rifki Nurkarima, Iin Nursari, Ayla Nurul Kusuma Dewi, Nurul Kusuma Olivia Octavia Paripurna, Rian Bintang Pasorong, Hillary Bella Patricia Chandra Pebianoor, Pebianoor Prafanto, Anton Pramudya, Pranata Eka Pratama, Fhanji Wilis Pusparini, Faradilla Rahayu, Ervina Rahayu, Rizqi Widya Rahmat Kamara Raihanfitri Adi Kalipaksi Ramadhaniaty, Dinda Rantetana, Stevie Falentino Rayner Alfred Reza Nur Muhammad Rezky, Muhammad Rima Yustika Hasnida Rita Diana Rizky Pratama Putra Rondongalo Rismawati Rosita, Aliffia Rosmasari Rosmasari Rosmasari Rosmasari Rosmasari Rosmasari, Rosmasari Rosmasari, Rosmasari Saipul, Saipul Sandyanegara, Aryasena Bela Sarira, Brayen Tisra Septiani, Reni D. Septirini, Anindita Setyadi, Hario Jati Sihombing, Yobel Fernanda Simanungkalit, Julius Rinaldi Stefanie Stefanie Sugandi Sugandi Sulastri, Heni Sumaini Sumaini Suryani Junita Patandianan Syachmiral, Zidane Althaariq Syarah, May Siti Taruk, Medi Tejawati, Andi Tjikoa, Ade Fiqri Vicky Pranandika Wijaksana Wahyudi, Moh Ikhwan Waksito, Alan Zulfikar Wati, Masna Wibisono, Bramantyo Ardi Harimurti Widians, Joan Angelina Wijaya, Zhienka Putri Willyardo Tampubolon Wintin, Chintia Liu Yasmin, Annisa Yuyun Nabilawati Rumbia zahra salsabila Zainal Arifin Zali, Wahyu Noor