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All Journal Jurnal Masyarakat Informatika Jurnal Simetris Rekursif: Jurnal Informatika Jurnal Pseudocode Jurnal SOLMA Jurnal Eksplora Informatika Indonesian Journal of Computer Science and Engineering
Desi Andreswari
University of Bengkulu
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering Other

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Journal : Rekursif: Jurnal Informatika

 1 
Penerapan Konsep Gamifikasi Pada Pembelajaran Merangkai Kata dan Kalimat Aksara Kaganga Rejang Berbasis Android (Studi Kasus: SDN 17 Rejang Lebong) Andreswari, Desi; Coastera, Funny Farady; Juwita, Fatma
Rekursif: Jurnal Informatika Vol 11 No 2 (2023): Volume 11 Nomor 2 November 2023
Publisher : Universitas Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33369/rekursif.v11i2.30245

Abstract

Abstract: The Ulu script (Kaganga) is one of the heritage scripts in the Southern (coastal) Sumatra region. There are several types of this script, namely Kaganga Rejang, Kaganga Lampung, Kaganga Serawai, Kaganga Pasemah and Kaganga Palembang. In Rejang Lebong, efforts are made to preserve and study Kaganga Rejang in schools as a Local Content subject. However, the lack of interest and low motivation to learn is a factor in hindering the learning process in students. Gamification is the application of concepts by incorporating game elements into non-game problems that have been proven to increase user motivation and retention. Therefore, there is a need for an application for learning the Kaganga Rejang script with a gamification concept that can help students in the learning process. The test results using the SUS (System Usability Scale) method are grade scale "B" and adjective "Excellent" with a score of 70 for material experts and 70.71 for students. Keywords: Kaganga Rejang, Gamification, Android, Application, Game.
Implementasi Metode Certainty Factor Dalam Sistem Pakar Diagnosis Awal Tanda Bahaya Gangguan Menstruasi Andreswari, Desi; Erlansari, Aan; Coastera, Funny Farady; Hasian Lumbanraja, Joi Pebrianty
Rekursif: Jurnal Informatika Vol 11 No 2 (2023): Volume 11 Nomor 2 November 2023
Publisher : Universitas Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33369/rekursif.v11i2.30654

Abstract

Menstrual disorders are disorders that occur in the menstrual cycle including changes that occur in the cycle, blood count, and other changes related to the menstrual cycle. Most women do not feel symptoms at the time of menstruation, but a small percentage feel pain. Menstrual disorders or also called abnormal uterine bleeding is a complaint that often causes a woman to come to the doctor for immediate treatment. Complaints of menstrual disorders vary from mild to severe. To help overcome these obstacles, expert systems can be a solution. This expert system was created using the certainty factor method consisting of 46 symptoms with 12 types of diseases. This system produces output in the form of a percentage of the type of possible diagnosis of the disease experienced by the user and suggestions based on the symptoms experienced by the user. The functionality testing process of this expert system went well using black box testing and resulted in 100% functional success. Evaluation of the accuracy of the certainty factor method for diagnosing menstrual disorders resulted in an accuracy rate of 84.61%. Keywords: Menstruation, Menstrual disorders, Certainty Factor, Expert System, Diagnosis
Aplikasi Sistem Pakar Diagnosis Specific Learning Disability Menggunakan Metode Naïve Bayes Berbasis Game Andreswari, Desi; Coastera, Funny Farady; Tiara Sella, Miranda
Rekursif: Jurnal Informatika Vol 12 No 1 (2024): Volume 12 Nomor 1 Maret 2024
Publisher : Universitas Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33369/rekursif.v12i1.32890

Abstract

This research aims to develop a game-based expert system application for the diagnosis of Specific Learning Disability (SLD) using the Naïve Bayes method. SLD is a learning disorder that affects an individual’s academic skills in one or more areas, such as reading, writing,or mathematics. In effort to enchance the efficiency of SLD diagnosis, this application utilizes the Naïve Bayes method, a classification technique based on probability. The application is designed in the form of an interactive game to capture the user’s attention, particularly children who may be experiencing SLD. By combining gaming elements with the diagnostic process, it expected that users can be more engaged in the evaluation without compromising the educational aspect. The Naïve Bayes method is employed to generate diagnostic predictions based on information input by the user through a series of questions and tasks integrated into game. This research was conducted by testing 15 test data, and resulted in a system accuracy of 100%. Thus, this application can serve as a tool for early identification of SLD in children. It is anticipated that the development of this application can make a positive contribution to the field of education, particularly in supporting the identification and intervention processes for individuals experiencing SLD.
Sistem Pakar Untuk Mendiagnosa Penyakit Bakteri Pada Ayam Petelur Menggunakan Metode Variable Centered Intelligent Rule System (VCIRS) dan Certainty Factor Berbasis Website (Studi Kasus: Peternakan Ayam Petelur Di Tahura) Andreswari, Desi; Suteky, Tatik; Winda P, Desi Ade
Rekursif: Jurnal Informatika Vol 12 No 1 (2024): Volume 12 Nomor 1 Maret 2024
Publisher : Universitas Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33369/rekursif.v12i1.33933

Abstract

Laying chickens are a type of poultry that is in demand by the public. One of the commodities currently being developed in Indonesia is poultry because the eggs produced are very much in demand by the Indonesian people. However, to achieve egg production and produce good eggs and make quite a large profit, farmers must pay attention to health and take good care of laying hens so that they are not susceptible to disease. There are several types of diseases that attack laying hens, one of which is a type of bacteria that causes many chickens to die and egg production decreases. Therefore, we need a system that can diagnose bacterial diseases in laying hens by applying the web-based Variable-Centered Intelligent Rule System and Certainty Factor methods, so that this system can help breeders solve problems without having to meet with experts directly. Test results from 25 test data carried out, this system is able to diagnose bacterial diseases correctly with an accuracy value of 92%. It can be concluded that this system can diagnose bacterial diseases in laying hens well. Keywords: Laying Chickens, Disease, Variable-Centered Intelligent Rule System, Certainty Factor, Expert System.
Implementasi Metode Naïve Bayes Dalam Sistem Pakar Diagnosis Penyakit Pada Itik Mojosari Andreswari, Desi; Suteky, Tatik; Epana Sari, Renti
Rekursif: Jurnal Informatika Vol 12 No 2 (2024): Volume 12 Nomor 2 November 2024
Publisher : Universitas Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33369/rekursif.v12i2.32507

Abstract

Mojosari ducks are a type of duck that has potential as an egg producer, so many duck breeders are interested in it. Delays in treating disease in Mojosari ducks can result in various losses, such as decreased egg quality and quantity, disease transmission to other ducks, and can cause death of the ducks. Therefore, researchers built an expert system that can carry out quick and accurate diagnoses of duck diseases as well as correct countermeasures. This system was built by applying the Naïve Bayes method to an expert system to diagnose Mojosari duck disease by calculating the prior probability value of each disease based on input of symptoms that appear in the ducks. This system can detect 10 types of diseases and 40 symptoms that attack Mojosari ducks. This research was carried out with 30 test data and resulted in a system accuracy of 90%. Keywords: Mojosari Ducks, Diseases, Diagnose, Ducks, Expert Systems, Naïve Bayes.
Analisis Komparatif Metode Peningkatan Kontras Citra Bawah Air Menggunakan HE, AHE, dan CLAHE Ernawati, Ernawati; Oktoeberza, Widhia KZ; Andreswari, Desi; Purnama Sari, Julia; Erlansari, Aan; Farady Coastera, Funny; Dwi Jayanto, Paksi
Rekursif: Jurnal Informatika Vol 13 No 1 (2025): Volume 13 Nomor 1 Maret 2025
Publisher : Universitas Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33369/rekursif.v13i1.42151

Abstract

significant challenge in the field of digital image processing due to poor lighting conditions and uneven intensity distribution. This study aims to compare three contrast enhancement techniques Histogram Equalization (HE), Adaptive Histogram Equalization (AHE), and Contrast Limited Adaptive Histogram Equalization (CLAHE) applied to underwater imagery. The evaluation was conducted using quantitative metrics including entropy, contrast (RMS), and Structural Similarity Index (SSIM) to assess the improvement in image detail, intensity distribution, and structural similarity to the original image. Experimental results indicate that AHE achieves the highest entropy values, reflecting a significant enhancement of local information. HE provides the highest contrast values but tends to compromise the structural integrity of the image. CLAHE demonstrates the most balanced performance, producing the highest SSIM scores while maintaining stable enhancements in both contrast and detail. Based on these findings, CLAHE is recommended as the most effective contrast enhancement technique for underwater images, as it improves visual quality while preserving the original image structure. Key words : Underwater image enhancement; Contrast enhancement; CLAHE; HE; AHE.
Penerapan Metode Multi Attribute Utility Theory (MAUT) Untuk Menentukan Prioritas Penerima Bantuan Bencana Alam (Studi Kasus: BPBD Bengkulu Tengah) Wahyudi, Rahmat Fikri; Andreswari, Desi; Purnama Sari, Julia
Rekursif: Jurnal Informatika Vol 13 No 2 (2025): Volume 13 Nomor 2 November 2025
Publisher : Universitas Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33369/rekursif.v13i2.43289

Abstract

Indonesia, as an equatorial archipelago located between the Asian and Australian continents, faces high risks of natural disasters, particularly floods and landslides. These disasters cause various adverse impacts, such as infrastructure damage, psychological trauma, and social and economic losses for victims. The Regional Disaster Management Agency (BPBD), as the primary institution for disaster response, must provide effective services for community recovery, thus requiring a fast and accurate system. Therefore, this research aims to develop a Decision Support System (DSS) using the Multi-Attribute Utility Theory (MAUT) method to assist BPBD in determining priority recipients of disaster aid. The advantage of the MAUT method lies in its ability to process multi-criteria decisions, consider stakeholder preferences, and produce quantitative and transparent outputs. The system was built using PHP and designed with Unified Modeling Language (UML). Testing was conducted on 16 alternative datasets, producing a priority ranking based on the highest scores. Accuracy tests showed an 87.5% success rate, while black-box testing achieved 100%. The highest preference score (0.92083) proves MAUT's accuracy in decision-making.
Co-Authors Aan Erlansari Alfareza, Muhammad Yusril Azaharah, Diyah Ishita Balqis, Nabilatul Coastera, Funny Faraday Dwi Jayanto, Paksi Dwi Safitri, Dania Egisthi, Vonny Afriyona Endina Putri Purwandari Epana Sari, Renti Ernawati Ernawati Ernawati Funny Farady Coastera Funny Farady Coastera, Funny Farady Ginting , Sempurna br. Ginting, Sempurna br Hasian Lumbanraja, Joi Pebrianty Julia Purnama Sari Julia Purnama Sari Juwita, Fatma Manurung, Wahyu Ozorah Mochammad Yusa, Mochammad Monica, Exca Wella Oktoeberza, Widhia KZ Rima Yanti Nasution, Nofa Rusdi Efendi Safitri, Hanifah Nur Sarwono, Sarwit Siregar, Michael Exaudi Syafitri, Arinda Tatik Suteky Tiara Sella, Miranda Wahyudi, Rahmat Fikri Wijanarko, Andang Winda P, Desi Ade Yudi Setiawan