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All Journal Jurnal Media Infotama Jurnal Inspiration JUKI : Jurnal Komputer dan Informatika Journal of Innovation Information Technology and Application (JINITA) Indonesian Journal of Engineering Research Jurnal Komputer, Informasi dan Teknologi Jurnal Dehasen Untuk Negeri Jurnal Media Computer Science SATIN - Sains dan Teknologi Informasi Pandawa : Pusat Publikasi Hasil Pengabdian Masyarakat Jurnal Kewirausahaan dan Bisnis
Fredricka, Jhoanne
Universitas Dehasen Bengkulu
Agriculture, Biological Sciences & Forestry Humanities Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mechanical Engineering Public Health Social Sciences Other

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Sistem Digitalisasi di Era Revolusi 5.0 Lena Elfianty; Jhoanne Fredricka; Achmad Fikri Sallaby; Nofi Qurniati; Juju Jumadi; Annisa Putri Pratiwi
Jurnal Dehasen Untuk Negeri Vol 1 No 2 (2022): Juli
Publisher : Universitas Dehasen Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37676/jdun.v1i2.2836

Abstract

This community service activity in the form of socializing the digitalization system in the 5.0 revolution era aims to help students at SMA Negeri 3 Seluma in getting information about technological advances related to digitalization in the 5.0 revolution era. The subjects in this service activity are students of SMA Negeri 3 Seluma. This socialization process is carried out by providing information about artificial intelligence that pays attention to the human side and will transform millions of data collected through the internet in all areas of life. The results of this community service activity are so that students can be better prepared to face the era of revolution 5.0 in Indonesia by utilizing existing Human Resources (HR) because domestic human resources are no less qualified than foreign human resources, it is also expected that with the 5.0 Revolution This can develop human resources in Indonesia. The conclusion of this community service activity at SMA Negeri 3 Seluma is that the younger generation of students at SMA Negeri 3 Seluma Bengkulu Selatan have creative and inspiring behavior, tend to build their learning patterns with strong interpersonal skills. Young generations who are creative, innovative and productive, from an early age need to be enriched with soft skills as contained in the 5.0 revolution. Of course, this plenary ability is expected to succeed in winning the competition in the disruptive era and the world without borders.
Application Of Importance Performance Analysis Method In Measuring Satisfaction Level Students On Learning In School David Tri Julian; Herlina Latipa Sari; Jhoanne Fredricka
Jurnal Media Computer Science Vol 1 No 2 (2022): Juli
Publisher : Fakultas Ilmu Komputer Universitas Dehasen Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37676/jmcs.v1i2.2709

Abstract

Pelita Kasih High School which is a private school located in Bengkulu City. So far, the learning process at Pelita Kasih High School often makes students feel bored and lack understanding and mastery of the material that has been taught. This makes the school, especially the teacher, must conduct an analysis to determine the level of student satisfaction with the learning system every semester. However, the obstacle that occurs is that Pelita Kasih High School does not yet have a forum that can help students to provide assessments related to learning satisfaction in schools that are ongoing per semester. Applications measuring the level of student satisfaction with learning at Pelita Kasih High School Bengkulu are used to assist the school in knowing the level of student satisfaction per semester per academic year based on filling out the questionnaire form that has been done by students. The application to measure the level of student satisfaction has applied the IPA (Importance Performance Analysis) method which is used to determine the level of suitability of respondents based on the level of interest and level of satisfaction that has been given by students. The application to measure the level of student satisfaction with learning at SMA Pelita Kasih Bengkulu was made using the Visual Basic .Net programming language. Based on the assessment of 18 students in the Even Semester of the 2021/2022 Academic Year, the average respondent suitability level (TKi) was 91.57% and showed that the level of student satisfaction with learning at school was very satisfied..
Implementasi Algortima C-Means Dan Algoritma Mixture Dalam Pengclusteran Data Mahasiswa Drop Out Jhoanne Fredricka; Lena Elfianty; Jusuf Wahyudi
JUKI : Jurnal Komputer dan Informatika Vol. 4 No. 2 (2022): JUKI : Jurnal Komputer dan Informatika, Edisi November 2022
Publisher : Yayasan Kita Menulis

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Abstract

Clustering merupakan salah satu metode machine learning dan termasuk dalam unsupervised learning. Tujuan dari clustering yaitu mencari pola data yang mirip sehingga memiliki kemungkinan dalam mengelompokan data data yang mirip. Banyak Algoritma yang dapat digunakan untuk melakukan proses clustering data. Algoritma C-Means dan algoritma Mixture merupakan bentuk algoritma yang dapat digunakan dalam melakukan proses clustering data.. Algoritma C-Means adalah suatu tehnik pengklusteran data yang mana keberadaan tiap – tiap titik data dalam suatu cluster ditentukan oleh derajat keanggotaan. Sedangkan Algoritma Mixture merupakan salah satu jenis data clustering dimana dalam permodelannya, data dalam satu kelompok diasumsikan terdistribusi sesuai dengan salah satu jenis distribusi statistik yang ada. Pada penelitian ini akan dilakukan perbandingan antara Algoritma C-Means dan Algoritma Mixture dalam hal klasterisasi data mahasiswa drop out, dengan melihat hasil performance vector yang di hasilkan pada metode c-means yaitu avg.within centroid distance pada setiap cluster , Sedangkan pada algoritma mixture melihat hasil performance vector dan jumlah number of clusters.
Penerapan Model Kooperatif Tipe Numbered Heads Together Menggunakan Aplikasi MATLAB dalam Pembelajaran Matematika Nofi Qurniati; Jhoanne Fredricka; Lena Elfianty
JUKI : Jurnal Komputer dan Informatika Vol. 4 No. 2 (2022): JUKI : Jurnal Komputer dan Informatika, Edisi November 2022
Publisher : Yayasan Kita Menulis

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Abstract

Belajar matematika di kelas selalu menggunakan metode konvensional sehingga dilakukan penelitian. Penelitian ini bertujuan untuk mengetahui motivasi belajar dan hasil belajar pada model pembelajaran Cooperative Numbered Heads Together menggunakan aplikasi MATLAB pada Pembelajaran Matematika Siswa .Metodologi yang digunakan dalam penelitian ini adalah desain eksperimen dengan desain The One Shot Case Study yaitu penelitian yang hanya dilakukan pada satu kelompok sampel.Subyek penelitian ini adalah siswa kelas X SMA Negeri 11 Padang.Data hasil belajar yang diperoleh dianalisis dengan menghitung skor masing-masing siswa.Kemudian tentukan jumlah siswa yang mencapai ketuntasan.sedangkan untuk motivasi belajar dianalisis dengan membandingkan penjumlahan skor angket motivasi awal dengan skor angket motivasi akhir siswa. Secara klasikal, dari 38 siswa yang mengikuti ujian akhir, 28 orang atau 73,68% telah mencapai ketuntasan. Motivasi belajar diperoleh 31 siswa yang motivasinya meningkat dan hanya 7 siswa yang motivasinya menurun.
Sistem Pendukung Keputusan Hasil Rekomendasi Jurusan Perguruan Tinggi Menggunakan Metode Naive Bayes dan AHP Devina Ninosari; Jhoanne Fredricka
SATIN - Sains dan Teknologi Informasi Vol 8 No 1 (2022): SATIN - Sains dan Teknologi Informasi
Publisher : STMIK Amik Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (456.003 KB) | DOI: 10.33372/stn.v8i1.834

Abstract

Pada penelitian ini peneliti menggabungkan algoritma naïve bayes dan Analytical Hierarchi Proses untuk membantu calon mahasiswa baru dalam memilih jurusan pada perguruan tinggi sesuai dengan kemampuan bidangya. Naïve bayes digunakan untuk memprediksi calon mahasiswa baru diterima atau tidak diterima, setelah dinyatakan diterima maka akan dikalsifikasikan lagi potensi diterima dan tidak diterima dengan tiga potensi tinggi, sedang dan rendah. Setelah didapatkan potensi maka akan dijadikan salah satu kriteria pada algoritma Analytical Hierarchy Proses untuk selanjutnya dapat mengahsilkan rekomendasi paling tinggi maka akan dijadikan rekomendasi jurusan calon mahasiswa baru. Setelah dilakukan penggabungan kedua metode antara Analytical Hierarchy Proses (AHP) dan Naïve bayes dan dilakukan pengujian secara berulang kali maka didapatkan hasil rekomendasi jurusan yang tepat untuk calon mahasiswa agar terhindar dari heregistrasi jurusan dan Droup out (DO). Akurasi yang dihasilkan pada metode naïve bayes tingkat akurasi yang paling tinggi sebesar 98% presisi sebesar 90% dan nilai eror sebesar 3% dari hassil rekomendasi pada algoritma Analytical Hierarchy Proses didaptkan nilai akurasi 93%, Sistem computer 90% dan akutansi 91, 76%.
Determination of Recipients of Livestock Assistance for Villages Using the Simple Additive Weighting Method Anisyah Juniarti; Siswanto Siswanto; Jhoanne Fredricka
Jurnal Media Computer Science Vol 2 No 2 (2023): Juli
Publisher : Fakultas Ilmu Komputer Universitas Dehasen Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37676/jmcs.v2i2.3945

Abstract

Decision support systems are systems capable of providing data and information. In today's digital and globalization era, where the need for fast, precise and accurate information is very important. What's more, currently various public and private agencies will develop their businesses, one of which is to make changes by utilizing sophisticated technology such as computers as a substitute for human labor, The simple additive weighting method is one of the methods used to solve the problem of fuzzy multiple attribute decision making (FMADM). The simple additive weighting (SAW) method is a method used to find optimal alternatives from a number of alternatives with certain criteria. The result of this research is a software that adopts the SAW method which is able to assist the agriculture and animal husbandry department for decision making in determining recipients of livestock assistance every year.
Sistem Pendukung Keputusan Calon Penerima BPJS-PBI Pada Dinas Sosial Kota Bengkulu Menggunakan Metode K-Nearest Neighbor (KNN) Aziz Ali Mahendra; Dewi Suranti; Jhoanne Fredricka
Jurnal Media Infotama Vol 19 No 2 (2023): Oktober
Publisher : UNIVED Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37676/jmi.v19i2.4290

Abstract

Abstract-Health Social Security Organizing Agency for Contribution Assistance Recipient groups is assistance for the poor and disadvantaged people who are financed by the Government. The goal of the Health Social Security Administrative Body is to improve access and quality of health services for all underprivileged and incapable people to achieve optimal public health status effectively and efficiently. One of the problems faced by the Bengkulu City Social Service in determining beneficiaries of Health Social Security Administering Body assistance for the Contribution Assistance Beneficiary group is the process carried out by the Bengkulu City Social Service in making decisions on receiving Contribution assistance Health Social Security Administrative Body for poor families, still uses the manual method so it takes time. long to process. This decision support system for determining beneficiaries applies the K-Nearest Neighbor method to assist the selection process of citizens who are entitled to receive the Health Social Security Administrative Body so that it is easier to assess the criteria for residents. K-Nearest Neighbor can perform a mathematically based procedure to evaluate the values ​​of these criteria into an accurate description of the data classification. This decision support system is designed using the PHP Programming Language and MySQL Database. This decision support system can provide convenience for the Bengkulu City Social Service in determining beneficiaries of Health Social Security Administering Body assistance for groups of Contribution Assistance Recipients in Bengkulu City.
Penerapan Metode Certainty Factor Untuk Mendiagnosa Penyakit Erosi Pada Gigi : (Studi Kasus Klinik Sehati Bengkulu) Reza Ardiansyah; Maryaningsih Maryaningsih; Jhoanne Fredricka
Pandawa : Pusat Publikasi Hasil Pengabdian Masyarakat Vol. 1 No. 3 (2023): Juli : Pandawa : Pusat Publikasi Hasil Pengabdian Masyarakat
Publisher : Asosiasi Riset Ilmu Pendidikan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/pandawa.v1i3.142

Abstract

Dental erosion is described as the loss of the enamel on the teeth. At first, people who experience tooth erosion will not feel that their teeth are experiencing tooth erosion, until when tooth erosion has reached the dentin. Tooth erosion that has reached the dentin is characterized by, among other things, a feeling of pain in the teeth. However, there are many people who are unfamiliar with dental erosion, so a system that can be accessed online is needed to help patients or the public to consult independently. This expert system is designed using the PHP Programming Language and MySQL Database and the method used is a certainty factor. The result of concultationtest with the system is able to determine the disease along with the intial treatment or treatment that be must be carried out based on the symstoms selected by the user.
Socialization Of Computer-Based Semester Exam System (CBT) Siswanto; Hermawansa; Utami, Feri Hari; Alianse, Rizka Tri; Fredricka , Jhoanne
Jurnal Kewirausahaan dan Bisnis Vol. 1 No. 1 (2019): Februari
Publisher : Universitas Dehasen Bengkulu

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Abstract

Information Technology, which is a technology in the field of computer science, is a type of field of science that always experiences many advances, both in data processing, image processing or a combination of the two. This happened because of the development of processor technology which is the main component of computer machines, where with the development of processor technology, software manufacturers also moved to follow the existing technology. Situation analysis of partners, obtained an illustration of the teacher's lack of understanding of the development of information technology, especially in terms of CBT-based semester exams. This is due to new assumptions about existing terms, therefore the school conveys the need for socialization of the intended technology directly to the teachers of SMA N 6 Bengkulu Tengah. Part of the field of computer science that continues to grow, such as artificial intelligence, which continues to try to make computer machines as tools and substitutes for functions carried out by humans. The progress shown by the ability of computers to serve users to search for education through internet facilities certainly requires its users to keep abreast of existing developments. The results obtained from these activities are the level of teacher interest in information technology knowledge which includes CBT-based exams which are shown by the enthusiasm of teachers in participating in activities
Interpretable Deep Learning Model for Grape Leaf Disease Classification Based on EfficientNet with Grad-CAM Visualization Castaka Agus Sugianto; Dini Rohmayani; Jhoanne Fredricka; Mohamed Doheir
Journal of Innovation Information Technology and Application (JINITA) Vol 7 No 1 (2025): JINITA, June 2025
Publisher : Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/jinita.v7i1.2745

Abstract

Grape leaf diseases pose a significant threat to agricultural productivity, especially in regions with fluctuating climatic conditions that create favorable environments for pathogen growth. Early and accurate disease detection is essential for preventing severe crop losses. Traditional manual inspection methods are inefficient and prone to human error, highlighting the need for an automated approach. This study proposes a computer vision-based solution using Convolutional Neural Networks (CNN) improved by EfficientNetB0 to classify grape leaf diseases. The model was trained on a publicly available dataset from Kaggle, which consists of 9,027 images in four classes: ESCA, Leaf Blight, Black Rot, and Healthy. Each image has a resolution of 300 × 300 pixels with a 24-bit color depth, ensuring sufficient detail for analysis. To enhance model performance, data augmentation and hyperparameter tuning were applied. The EfficientNetB0 model was employed due to its strong feature extraction capabilities and computational efficiency. The proposed model achieved 99.36% accuracy, with evaluation metrics including precision (99%), recall (99%), and F1-score (99%), demonstrating its reliability in distinguishing disease categories. Further analysis using a confusion matrix and Grad-CAM visualization provided insights into the model’s decision-making process. The results indicate that this deep learning-based approach is highly effective for grape leaf disease classification. Future research can explore real-time field data collection, attention mechanisms, and self-supervised learning to further improve classification accuracy and model generalization for large-scale agricultural applications.
Co-Authors Aji Sukmo Alianse, Rizka Tri Anisyah Juniarti Annisa Putri Pratiwi Asnawati Asnawati Aziz Ali Mahendra Castaka Agus Sugianto David Tri Julian Devina Ninosari Dewi Suranti Dini Rohmayani Feri Hari Utami Feri Hari Utami, Feri Hari Fezi Fadwa Rendika Herlina Latipa Sari Hermawansa Juju Jumadi Jusuf Wahyudi Kanedi, Indra Kanedi Lena Elfianty Leni Natalia Zulita Liza Yulianti M. Ajis Akbar Kurniawan Maryanigsih, Maryanigsih Maryaningsih Maryaningsih Maryaningsih Maryaningsih Migi Migi Mohamed Doheir Nofi Qurniati Novita Sari Perlius Septria Reza Ardiansyah Rizka Tri Alinse Roni Ardiwan Sallaby, Achmad Fikri Sari, Novita Siswanto Siswanto Siswanto Siswanto, Siswanto, Surya Ramadhan Toibah Umi Kalsum Venny Novita Sari Yupianti, Yupianti