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All Journal Jurnal Teknologi Industri Pertanian Teknotan: Jurnal Industri Teknologi Pertanian Dharmakarya : Jurnal Aplikasi Ipteks Untuk Masyarakat Jurnal Aplikasi Teknologi Pangan Indonesian Journal of Chemistry IKRA-ITH Humaniora : Jurnal Sosial dan Humaniora JOURNAL OF APPLIED INFORMATICS AND COMPUTING SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Indonesian Food Science and TechnologyJournal Conference on Innovation and Application of Science and Technology (CIASTECH) Jurnal RESISTOR (Rekayasa Sistem Komputer) IKRA-ITH ABDIMAS Pontianak Nutrition Journal (PNJ) Journal of Industrial and Information Technology in Agriculture Canrea Journal: Food Technology, Nutritions, and Culinary Journal Techno Xplore : Jurnal Ilmu Komputer dan Teknologi Informasi Jurnal Abdi Insani JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Food ScienTech Journal Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Jurnal Teknik Informatika (JUTIF) KLIK: Kajian Ilmiah Informatika dan Komputer SN-Biosper Scientific Student Journal for Information, Technology and Science Jurnal Buana Pengabdian Pontianak Nutrition Journal (PNJ) Composite Jurnal Sains dan Teknologi Pangan Jurnal Komtika (Komputasi dan Informatika)
Yana Cahyana
Fakultas Teknologi Industri Pertanian, Universitas Padjadjaran
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Prediksi Persediaan Obat Pada Apotek Menggunakan Algoritma Decision Tree Pratiwi, Sinta Amanda; Fauzi, Ahmad; Puspita Lestari, Santi Arum; Cahyana, Yana
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 4 No. 4 (2024): Februari 2024
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v4i4.1681

Abstract

A pharmacy is a place for buying and selling drugs and must have an adequate stock of drug supplies so that it can serve consumers in need. In some pharmacies there are problems related to drug supply. Often the drugs needed by the community are empty in stock, while the drugs that are less needed are stored in the warehouse. Therefore, this study aims to conduct a prediction model of drug supply so that it can meet consumer needs. This study uses drug inventory data at Kaligandu Pharmacy, the data has 2745 rows and 5 attributes consisting of "Item Name", "Unit", "Previous Stock", "Rill Stock", and "Restock". The method used in this case is the Decision Tree algorithm with Accuracy, Precision, Recall, and F1-Score evaluation methods to see which drugs are available and not available based on "Unit". The results showed that the Decision Tree algorithm obtained good results by using a data comparison of 80 to 20 resulting in an accuracy value of 98.71%. In addition, the resulting values of Precision, Recall, and F1-Score are not much different, namely 0.9872, 0.9872, and 0.9867. The 70 to 30 data comparison produces a smaller value but is not much different from the results of 80 to 20, namely the accuracy of 98.28%, Precision 0.9832, Recall 0.9828, and F1-Score 0.9804. with these results this research can be continued by implementing drug inventory prediction using Decision Tree into an application
PERSEPSI ORANGTUA TERHADAP FENOMENA PENGGUNAAN GADGET PADA ANAK-ANAK DI DESA TALUNAJAYA Yana Cahyana
JURNAL BUANA PENGABDIAN Vol. 5 No. 2 (2023): JURNAL BUANA PENGABDIAN
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat, Universitas Buana Perjuangan Karawang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36805/jurnalbuanapengabdian.v5i2.5789

Abstract

Dalam era modernisasi yang sedang berlangsung saat ini, banyak hal yang terjadi dalam kehidupan manusia, termasuk pada bidang teknologi dan sosial budaya. Teknologi dapat digunakan secara luas sehingga menyebabkan pergeseran tatanan masyarakat bahkan masalah lingkungan. Oleh karena itu di lakukan penelitian yang ini yang berjudul persepsi orangtua terhadap fenomena penggunaan gadget pada anak-anak di desa Talunajaya Dengan bertujuan unutk mengedukasi orang tua untuk lebih memperhatikan anak-anak dari pengaruh gadget dalam kehidupan sehari hari. Penelitian ini menggunakan metode kualitatif melibatkan pendekatan Studi Kasus dengan menggunakan Teknik pengumpulan data melalui wawancara. Lanjutan
CLASSIFICATION OF RICE PLANTS AFFECTED BY RATS USING THE SUPPORT VECTOR MACHINE (SVM) ALGORITHM Nofie Prasetiyo; Baihaqi, Kiki Ahmad; Lestari, Santi Arum Puspita; Cahyana, Yana
Jurnal Teknik Informatika (Jutif) Vol. 5 No. 2 (2024): JUTIF Volume 5, Number 2, April 2024
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2024.5.2.1949

Abstract

In the era of Indonesia's agrarian economy which is supported by the agricultural sector, rice plants play an important role in meeting food needs. However, pest attacks, especially field mice, can cause significant losses in rice production. To overcome this, this research proposes the use of the Support Vector Machine (SVM) algorithm with the Particle Swarm Optimization method in predicting rat pest attacks on rice plants. This research involves the process of collecting data from drone photos to identify affected agricultural land. The preprocessing stage involves changing colors from RGB to GRAY and zoom augmentation. Feature extraction is carried out using Histogram of Oriented Gradients (HOG) and Local Binary Pattern (LBP). Testing was carried out involving the SVM/SVC model and performance evaluation was carried out using accuracy, precision and recall metrics. The preprocessing test results showed an increase in performance with training accuracy of 68.33%. However, the actual prediction on the original image results in a low accuracy of around 25%. However, image testing after involving the entire process, including preprocessing and model prediction, shows a higher level of accuracy, reaching around 90%.
IMPLEMENTATION OF THE YOLOV8 METHOD TO DETECT WORK SAFETY HELMETS Direja, Azhar Ferbista; Cahyana, Yana; Rahmat, Rahmat; Baihaqi, Kiki Ahmad
Jurnal Teknik Informatika (Jutif) Vol. 5 No. 3 (2024): JUTIF Volume 5, Number 3, June 2024
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2024.5.3.2005

Abstract

Work safety helmets are an important tool in OHS (Occupational Health and Safety) that must be used by workers. Workers who work with heavy equipment must wear work safety helmets as an obligation. Unfortunately, there are still many workers who do not comply with this rule. They will only wear helmets if there is supervision from a supervisor. However, if the supervisor is not on site, many workers will remove their helmets. The need for supervision of workers is important in reducing work accidents. From these problems, a work safety helmet detection model was created using the YOLOv8 method. This implementation aims to increase the accuracy values ​​obtained and can reduce workload and increase efficiency in checking violations of the use of work safety helmets among workers. The method used consists of several stages, namely image acquisition of 670 images, image labeling, preprocessing, augmentation in roboflow, YOLOv8x model training with 100 epochs, image testing with a distance of 1, 3, 5 meters between the object and the camera, evaluation of test results. Based on the results of training with 467 images, the mAP50 reached 99.5%. Meanwhile, the test results with 100 images showed an accuracy of 99%.
Perbandingan Metode Decision Tree Dan K-Nearest Neighbor Terhadap Ulasan Pengguna Aplikasi Mypertamina Menggunakan Confusion Matrix Syahril, Ade; Cahyana, Yana; Kusumaningrum, Dwi Sulistya; Rohana, Tatang
Journal of Information System Research (JOSH) Vol 5 No 4 (2024): Juli 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v5i4.5639

Abstract

The large number of vehicles in Indonesia makes fuel oil (BBM) very important, especially for cars and motorbikes. The Indonesian government works closely with PT Pertamina Persero and requires transactions using the MyPertamina application to ensure that fuel subsidies are properly targeted. However, the MyPertamina app has received mixed feedback and criticism from users, such as complaints about frequent bugs, instability of the app during use and difficulties in the registration or login process. User feedback on the app has been both positive and negative. Users also provided their ratings and reviews on the Google Play Store. The purpose of this research is to analyse the opinions of MyPertamina application user comments and compare the accuracy of the Decision Tree and K-Nearest Neighbor algorithms. This research includes scraping, text preprocessing, weighting, algorithm implementation and evaluation. The data used was obtained from Google Play Store as much as 10,000 data based on the latest reviews, after data cleaning such as removing duplicate data and missing values obtained 8,072 reviews. The data is then grouped into positive classes (2,506 reviews) and negative classes (5,566 reviews), with more negative data. The classification results using the Decision Tree and K-NN methods, it is known that the Decision Tree method has a higher accuracy of 83%, while K-NN method is 58%. This finding indicates that the Decision Tree method is more effective in analysing user reviews of the MyPertamina application compared to the K-NN method.
Analisa Perbandingan Algoritma Support Vector Machine dan K-Nearest Neighbors Terhadap Ulasan Aplikasi Vidio Gumilar, Rizki Bintang; Cahyana, Yana; Sukmawati, Cici Emilia; Siregar, Amril Mutoi
Journal of Information System Research (JOSH) Vol 5 No 4 (2024): Juli 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v5i4.5640

Abstract

Internet usage in Indonesia reached 77% of the total population in January 2023, with Over The Top (OTT) services showing user growth of 25% every year. The Vidio application, one of the popular OTT platforms with downloads exceeding 50 million, has a 3.5 star rating based on 649 thousand reviews on the Google Play Store. Despite its popularity, Vidio faces complaints regarding limited film selection, payment errors, and excessive advertising, which affects user satisfaction. This research aims to analyze the opinions of Vidio application user comments by applying the SVM (Support Vector Machine) method and the KNN (K-Nearest Neighbors) method to determine the model with the best accuracy. 15,000 review data were collected through scraping, then processed using text preprocessing and TF-IDF vectorization techniques. Model evaluation shows that SVM has an accuracy value of 82%, a precision value of 82%, a recall value of 83%, and an F1-score value of 82%, while KNN has an accuracy of 69%, precision 74%, recall 73%, and F1-score 69% . The research results show that SVM is superior to KNN in classifying the sentiment of Vidio application reviews. It is hoped that these findings can be used by application developers in an effort to improve service and satisfaction of Vidio application users.
Edukasi Penggunaan Media Sosial Yang Bijak dan AmanBagi Santri Baitul Qur’an Karawang Cahyana, Yana
IKRA-ITH ABDIMAS Vol. 9 No. 2 (2025): Jurnal IKRAITH-ABDIMAS Vol 9 No 2 Juli 2025
Publisher : Universitas Persada Indonesia YAI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37817/ikra-ithabdimas.v9i2.4086

Abstract

ABSTRAK Pada era globalisasi media sosial merupakan perangkat penting yang digunakan hamper oleh seluruh masyarakat. Namun, Seiring dengan meningkatnya penggunaan media sosial, beberapa orang tidak memperhatikan hal-hal etika dalam menggunakan media sosial dengan bijak. Kegiatan Sosialisasi Edukasi media sosial pada santri dilaksanakan di Baitul Qur'an. Pelaksanaan kegiatan ini dilakukan melalui metode ceramah. Kegiatan pengabdian ini dimulai dengan mengurus perizinan serta berkoordinasi dengan pihak mitra terkait sasaran program yaitu tenaga pengajar atau guru. Pada kegiatan inti pelaksana melakukan sosialisasi secara langsung kepada Santri Baitul Qur'an Karawang. Akhir dari kegiatan ini berupa evaluasi yaitu dengan menggunakan teknik wawancara. Kegiatan ini bertujuan untuk memberikan edukasi terhadap penggunaan media sosial agar santri mampu menggunakan media sosial secara aman dan bijak. ABSTRACTIn the era of globalization, social media is an essential tool used by almost everyone. However, as the use of social media increases, some people do not pay attention to ethical considerations when using social media wisely. A social media education outreach event was held for the students at Baitul Qur'an. This event was conducted using the lecture method. The outreach activity began with obtaining permissions and coordinating with the partner parties regarding the program's target, which were the teachers. During the main activity, the implementation team conducted direct outreach to the students of Baitul Qur'an Karawang. The event concluded with an evaluation using interview techniques. The purpose of this activity was to educate the students on using social media so that they can use it safely and wisely.
Evaluasi Kinerja Algoritma Random Forest Dan Gradient Boosting Untuk Klasifikasi Penyakit Jantung Ridwan, Ridwan; Handayani, Hanny Hikmayanti; Lestari, Santi Arum Puspita; Cahyana, Yana
Jurnal Komtika (Komputasi dan Informatika) Vol 9 No 1 (2025)
Publisher : Universitas Muhammadiyah Magelang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31603/komtika.v9i1.13450

Abstract

Penyakit jantung masih menjadi salah satu penyebab kematian utama di dunia, sehingga diperlukan diagnosis dini yang akurat untuk mengurangi risiko yang ditimbulkan. Kemajuan teknologi machine learning memberikan peluang baru untuk membantu tenaga medis dalam memprediksi penyakit jantung secara lebih efisien dan tepat. Penelitian ini bertujuan untuk mengevaluasi dan membandingkan kinerja dua algoritma pembelajaran terawasi yang populer, yaitu Random Forest dan Gradient Boosting, dalam klasifikasi penyakit jantung. Dataset yang digunakan terdiri dari 1.000 baris data dengan sejumlah fitur yang merepresentasikan berbagai faktor risiko penyakit jantung. Evaluasi dilakukan dengan menggunakan metrik akurasi, presisi, recall, dan F1-score. Hasil penelitian menunjukkan bahwa Random Forest unggul dibandingkan Gradient Boosting dalam seluruh metrik evaluasi. Random Forest memperoleh akurasi sebesar 99,5%, sementara Gradient Boosting memperoleh 98,5%. Selain itu, Random Forest mencapai nilai sempurna (100%) pada presisi kelas 0, recall kelas 1, dan F1-score kelas 1, menunjukkan kemampuannya yang tinggi dalam klasifikasi penyakit jantung. Model yang dikembangkan ini memiliki potensi besar untuk diterapkan sebagai alat bantu pengambilan keputusan dalam sistem layanan kesehatan, terutama pada tahap skrining awal dan penilaian risiko pasien. Dengan mengidentifikasi pola dan fitur kunci yang berhubungan dengan penyakit jantung, model ini dapat mendukung tenaga medis dalam memberikan keputusan klinis yang lebih cepat dan tepat sasaran.
Development dark chocolate enriched with mangrove leaf powder (Sonneratia alba): Physico-chemical properties, antioxidant activity, and sensory quality Nizori, Addion; Mursyid, Mursyid; Ananda, Rizki; Latief, Madyawati; Tarigan, Indra Lasmana; humaryanto, Humaryanto; azima, Fauzan; Cahyana, Yana; Budiyanto, Budiyanto; Wazzan, Huda; Seow, Eng Keng
jurnal1 VOLUME 8 ISSUE 2, DECEMBER 2025
Publisher : Hasanuddin University Food Science and Technology Study Program

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/canrea.v8i2.1929

Abstract

The incorporation of mangrove leaf powder into food systems offers an emerging strategy for enhancing the functional value of confectionery products. This study evaluated the effects of Sonneratia alba (S. alba) mangrove-leaf powder on the physicochemical properties, antioxidant capacity, and sensory quality of dark chocolate. Leaves were processed into fine 60-mesh powder and added at concentrations of 0–5.5% (w/w). The analytical assessments included moisture content, total phenolic content (TPC), antioxidant activity using the DPPH method, CIELAB colour parameters, texture hardness, and consumer acceptance. The product underwent enrichment with S. alba produced significant (p < 0.05) increases in TPC (49.06–64.37 mg GAE/g) and antioxidant activity (60.45–69.45%). A strong linear relationship between TPC and DPPH inhibition (R² = 0.934) indicated that phenolics contributed directly to enhanced radical-scavenging performance. Colour measurements showed elevated a* and b* values with increasing leaf concentration, reflecting intensified red–yellow chromaticity from plant pigments. Meanwhile, hardness decreased from 135.33 to 98.95 g/F, suggesting that fibre components disrupted fat crystallisation and softened the chocolate matrix. Sensory evaluation demonstrated that intermediate enrichment levels (4.5%–5.5%) provided the most favourable consumer responses, yielding the highest scores for flavour, texture, and overall acceptance. Collectively, these results indicate that powder from S. alba leaves serves as an effective natural fortifying agent capable of improving the functional profile of dark chocolate without compromising sensory desirability. The findings highlight opportunities to use mangrove biomass as a sustainable, phenolic-rich ingredient for developing clean-label, functional chocolate products.
Perbandingan efektifitas pretreatment ozonolisis dan hydrothermal pressure dalam meningkatkan kandungan tanin dan kafein ekstrak kulit biji kakao (Theobroma cacao L.) Duhita D Utama; Mohammad Djali; Yana Cahyana; Melia Siti Ajijah
Composite : Jurnal Ilmu Pertanian Vol 6 No 1 (2024): Februari
Publisher : University of Insan Cendekia Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37577/composite.v6i1.629

Abstract

Kulit biji kakao, yang sering dianggap sebagai limbah dalam proses produksi cokelat, mengandung senyawa-senyawa bioaktif seperti tanin dan kafein. Guna mempermudah ekstraksi senyawa-senyawa bioaktif tersebut, diperlukan metode pretreatment delignifikasi seperti ozonolisis dan hydrothermal pressure. Tujuan dari penelitian ini adalah untuk membandingkan efektivitas metode ozonolisis dan hydrothermal pressure dalam meningkatkan perolehan senyawa tanin dan kafein pada ekstrak kulit biji kakao. Pada metode pretreatment ozonolisis menggunakan alat ozonizer, sedangkan pada metode hydrothermal pressure menggunakan alat autoklaf Sementara ekstraksi yang dilakukan yaitu dengan metode maserasi. Metode analisis data yang digunakan yaitu Rancangan Acak Kelompok (RAK) yang diuji dengan Analisis Varian (ANOVA) serta dilanjutkan Duncan Multiple Range Test (DMRT). Hasil penelitian ini menunjukkan bahwa perlakuan pretreatment ozonolisis dan hydrothermal pressure sebelum proses ekstraksi terbukti meningkatkan perolehan senyawa bioaktif ekstrak kulit biji kakao. Metode pretreatment tersebut menunjukkan pengaruh positif terhadap perolehan senyawa total tanin dan aktivitas antioksidan, sedangkan pada senyawa kafein tidak menunjukkan pengaruh nyata. Metode pretreatment ozonolisis menunjukkan hasil terbaik dalam meningkatkan perolehan kadar kafein sebesar 49,79% yaitu menjadi sebanyak 1,083 mg/g. sementara metode pretreatment hydrothermal pressure memberikan hasil terbaik dalam meningkatkan perolehan total tanin sebesar 55,19% yaitu menjadi sebanyak 9,42 mg/g. Selain itu diketahui juga bahwa semakin tinggi konsentrasi tanin, semakin tinggi pula nilai aktivitas antioksidan yang dihasilkan.
Co-Authors Abda Abda Abdullah Darussalam Addion Nizori Adi Rizky Pratama Adi Susilo Aenul Fuadah Agustin, Rachmayanti Tri Ahmad Fauzi Alifa, Naila Ratu Ambarwati, Evi Karlina Amid Rakhman amril siregar Anis, Ulfah Anisa Itiawanti Annisa Nurhalizah Aqib Zhaky Arina Fatharani Arum Galih Pertiwi Asep Mulyono Awal, Elsa Elvira Ayu Juwita Baihaqi, Kiki Ahmad Bramandito Affandi Budiyanto Budiyanto Deden Wahiddin Devi Silsia Dewi, Indah Purnama Didik Remaldhi Direja, Azhar Ferbista Duhita D Utama DWI KUSUMANINGRUM Edy Subroto Een Sukarminah Efri Mardawati Enjelia, Lola Faisal, Sutan Fauzan Azima Fauzi Ahmad Muda Fitri Nur Masruriyah, Anis Fitria, Denisa Gumilar, Rizki Bintang Hakiki Melanie Hanan, Sofiah Marwah Hanny Hikmayanti Handayani Hartini, Deta Heni Radiani Arifin Heri Hermawan Herlina Marta Hilda Novita Humaryanto, Humaryanto Iis Sadiah Imas Siti Setiasih In-In Hanidah Indira Lanti Kayaputri Indra Lasmana Tarigan Jaluwardhana, Rivan Satria Jovan Pangestu Juwita, Ayu Ratna Khayrani, Apriliana Cahya Kiki Baihaqi Kusumaningrum, Dwi Sulistya Lestari, Santi Arum Puspita M. Budi Kusarpoko Madyawati Latief Marsetio Marsetio Melia Siti Ajijah Miptahul Ulum Mochamad Djali Mohammad Djali Mohammad Djali Mohammad Djali Mohammad Djali Muhamad Amirrullah Muhammad Ramadhan Mursyid Djawas Narwan Nahrudin Nina Puspitaloka Nofie Prasetiyo Nova Wulandari Nurjayati, Ratih Praditya Putri Utami Pratiwi, Sinta Amanda Putri, Septiani Nuruldharma Rachmawati, Dhea Raden Duhita Diantiparamudita Utama Rahmat Rahmat Rahmat Rahmat Rahmat Restiana, Resti Ricky Steven Chandra Ridwan, Ridwan Rizka Ayu Permana Rizki Ananda Rizki Nur Annisa Rizky Nugraha Rizky Riyanto Robi Andoyo Rohana, Tatang Rossi Indiarto Sabirin Sandra Intan Sari Santi Lestari Seow, Eng Keng Siregar, Amril Siregar, Amril Mutoi Siregar, Amril Mutoi Siti Hanifah Khairun Nisa Suci Rahma Ajiaviaty Sukmawati, Cici Emilia Sulistya, Dwi Suningwar Mujiana Surya Martha Pratiwi Sutan Faisal Syahril, Ade Tatang Rohana Tita Rialita Tohirin Al Mudzakir Tsani Adiyanti Wahiddin, Deden Wazzan, Huda Wenda Adi Kusnaya Widiharto, Banani Yusuf Eka Wicaksana