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All Journal International Journal of Evaluation and Research in Education (IJERE) ComEngApp : Computer Engineering and Applications Journal Jurnal Ilmu Komputer dan Informasi Computer Engineering and Applications Journal (ComEngApp) TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics JUITA : Jurnal Informatika Proceeding of the Electrical Engineering Computer Science and Informatics Computer Engineering and Applications Journal (ComEngApp) Jurnal Informatika Upgris Sinkron : Jurnal dan Penelitian Teknik Informatika JIEET (Journal of Information Engineering and Educational Technology) Jurnal Ilmiah Matrik Indonesian Journal of Information System BAREKENG: Jurnal Ilmu Matematika dan Terapan JITK (Jurnal Ilmu Pengetahuan dan Komputer) JMM (Jurnal Masyarakat Mandiri) SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan Martabe : Jurnal Pengabdian Kepada Masyarakat Jurdimas (Jurnal Pengabdian Kepada Masyarakat) Royal Jurnal Informatika Global Jurnal Ilmiah Binary STMIK Bina Nusantara Jaya Jurnal Abdimas Mandiri Indonesian Journal of Electrical Engineering and Computer Science Reswara: Jurnal Pengabdian Kepada Masyarakat Journal of Computer Networks, Architecture and High Performance Computing Lumbung Inovasi: Jurnal Pengabdian Kepada Masyarakat Brilliance: Research of Artificial Intelligence Indonesian Community Journal International Journal of Advanced Science Computing and Engineering JEECS (Journal of Electrical Engineering and Computer Sciences) AnoaTIK: Jurnal Teknologi Informasi dan Komputer Jurnal INFOTEL Journal of Computer Science Application and Engineering
Ahmad Sanmorino
Universitas Indo Global Mandiri
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Physics Public Health Social Sciences Transportation Other

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A SARIMA APPROACH WITH PARAMETER OPTIMIZATION FOR ENHANCING FORECAST ACCURACY FOR NATIVE CHICKEN EGG PRODUCTION Gustriansyah, Rendra; Dewi, Deshinta Arrova; Puspasari, Shinta; Sanmorino, Ahmad
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 20 No 2 (2026): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol20iss2pp1331-1344

Abstract

This study aims to accurately forecast monthly native chicken egg production using the Seasonal Autoregressive Integrated Moving Average (SARIMA) model with parameter optimization. The optimization process was conducted through a combination of auto.arima() initialization and an exhaustive grid search across the parameter space, evaluated using multiple performance metrics. The dataset comprised monthly production data from Magelang City, Indonesia, spanning the period from 2016 to 2022. The best-performing model, SARIMA (2,1,2)(1,0,1,12), achieved an R² of 0.89, MAE of 82.13, RMSE of 92.92, MAPE of 7.21%, and MASE of 0.67 on the testing set, indicating satisfactory forecasting performance. Compared with the non-optimized SARIMA baseline, the optimized model showed improved predictive accuracy. However, the residuals did not follow a normal distribution, suggesting potential limitations in model assumptions. Moreover, the study is limited by its focus on a single geographic location and native chicken production data, which may restrict its generalizability. Despite these limitations, the findings demonstrate that parameter optimization in SARIMA enhances forecast accuracy and can support better planning for food security initiatives.
Penguatan Kompetensi Guru SMK PGRI Kota Palembang Melalui Pemanfaatan Artificial Intelligence Dalam Perencanaan Pembelajaran Ahmad Sanmorino; Hendra Di Kesuma; Indah Pratiwi Putri; Lastri Widya Astuti; Imelda Saluza; Tasmi; Nining Ariati; Dhamayanti; Faradillah; Fery Antony; Dona Marcelina; Rudi Heriansyah
Jurdimas (Jurnal Pengabdian Kepada Masyarakat) Royal Vol. 9 No. 1 (2026): Januari 2026
Publisher : STMIK Royal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33330/jurdimas.v9i1.4131

Abstract

Abstract: The development of artificial intelligence (AI) technology presents new opportunities in education, particularly in lesson planning. However, most vocational high school teachers in Palembang City, including those at SMK PGRI 2, still have limited knowledge and skills in utilizing AI. This problem is the background to the implementation of community service activities (PkM) with the aim of improving teacher competency in using Large Language Models (LLM) such as Gemini and ChatGPT to develop Lesson Implementation Plans (RPP). The methods used included needs surveys, interactive workshops, hands-on practice, and evaluation through post-tests and participant feedback. The results of the activity showed a significant increase, where teacher knowledge increased from 20% to 80% and the application of AI in lesson plans increased from 10% to 65%. The contribution of this activity lies in improving teachers' ability to utilize AI to develop lesson plans more effectively and providing a scientific basis for the application of LLM in lesson planning in vocational education. Keywords: artificial intelligence, lesson planning, vocational school teachers Abstrak: Perkembangan teknologi kecerdasan buatan (Artificial Intelligence) menghadirkan peluang baru dalam dunia pendidikan, khususnya dalam perencanaan pembelajaran. Namun, sebagian besar guru SMK di Kota Palembang, termasuk di SMK PGRI 2, masih memiliki keterbatasan dalam pengetahuan dan keterampilan pemanfaatan AI. Permasalahan ini melatarbelakangi dilaksanakannya kegiatan pengabdian kepada masyarakat (PkM) dengan tujuan meningkatkan kompetensi guru dalam menggunakan Large Language Models (LLM) seperti Gemini dan ChatGPT untuk menyusun Rencana Pelaksanaan Pembelajaran (RPP). Metode yang digunakan meliputi survei kebutuhan, workshop interaktif, praktik langsung, serta evaluasi melalui post-test dan umpan balik peserta. Hasil kegiatan menunjukkan adanya peningkatan signifikan, di mana pengetahuan guru meningkat dari 20% menjadi 80% dan penerapan AI dalam RPP naik dari 10% menjadi 65%. Kontribusi kegiatan ini terletak pada peningkatan kemampuan guru dalam memanfaatkan AI untuk menyusun RPP secara lebih efektif serta penyediaan dasar ilmiah bagi penerapan LLM dalam perencanaan pembelajaran di pendidikan vokasi. Kata kunci: artificial intelligence, guru SMK, perencanaan pembelajaran
ENHANCING ELEMENTARY STUDENT’S KNOWLEDGE THROUGH WEB SECURITY FUNDAMENTALS COUNSELING Sanmorino, Ahmad; Gustriansyah, Rendra; Puspasari, Shinta
JMM (Jurnal Masyarakat Mandiri) Vol 8, No 2 (2024): April
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jmm.v8i2.21724

Abstract

Abstract: This Community Service Program (PkM) focuses on delivering fundamental web security concepts tailored to the age-specific needs of young learners. Collaborative efforts among teachers, and parents, ensure a cohesive implementation of web security measures within the school environment. This PkM activity aims to enhance elementary school student's knowledge about the importance of web security. The method used is by giving lectures and interactive discussions to PkM participants. The total number of participants involved in this PkM is around 25 people, consisting of teachers and students. Evaluation of this PkM activities based on questionnaire feedback from PkM participants. According to feedback from participants, there has been a noticeable improvement in understanding the significance of web security. Before engaging in PkM activities, only approximately 5 percent of students possessed knowledge regarding the importance of web security. However, post-PkM activities, approximately 90 percent of students affirmed their awareness of the significance of web security. 
Penyuluhan aman dalam berbisnis pada usaha kue dan snack di Keluruahan Talang Jambe Palembang Ahmad Sanmorino; Rendra Gustriansyah; Shinta Puspasari
SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan Vol 9, No 4 (2025): Juli
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jpmb.v9i4.31489

Abstract

AbstrakMaraknya penipuan digital melalui WhatsApp dan media sosial menjadi ancaman serius bagi pelaku usaha kue dan snack rumahan di Kelurahan Talang Jambe, Palembang. Kegiatan Pengabdian kepada Masyarakat (PkM) ini bertujuan meningkatkan literasi digital pelaku usaha dalam mengidentifikasi dan mencegah modus penipuan daring. Metode yang digunakan meliputi presentasi materi dan diskusi interaktif, dengan pendekatan berbasis teori Digital Literacy dan Technology Acceptance Model (TAM). Kegiatan ini dilaksanakan pada Mei 2025 dengan melibatkan pelaku UMKM lokal. Hasil evaluasi menunjukkan peningkatan pemahaman peserta terhadap berbagai jenis penipuan, dari rata-rata 65% sebelum kegiatan menjadi 90,8% setelahnya. Diskusi juga mengungkap pengalaman peserta yang sebelumnya nyaris menjadi korban penipuan. Temuan ini menunjukkan bahwa pendekatan edukatif langsung efektif meningkatkan kesadaran dan kesiapsiagaan digital pelaku usaha. Diharapkan kegiatan ini dapat direplikasi untuk memperkuat keamanan digital UMKM secara lebih luas. Kata kunci: keamanan digital; usaha kue dan snack; penipuan online; pengabdian kepada masyarakat. AbstractThe rise of digital fraud through WhatsApp and social media poses a serious threat to home-based cake and snack businesses in Talang Jambe, Palembang. This Community Service (PkM) initiative aimed to enhance digital literacy among business owners by equipping them with practical knowledge to identify and prevent common online scams. The program employed presentations and interactive discussions, guided by the frameworks of Digital Literacy and the Technology Acceptance Model (TAM). Conducted in May 2025, the activity engaged local micro-entrepreneurs who actively use digital platforms for marketing. Evaluation results showed a significant increase in participants’ understanding of various types of fraud—from an average of 65% before the program to 90.8% afterward. Discussions revealed that several participants had previously been close to falling victim to such scams. These findings highlight the effectiveness of direct educational approaches in strengthening cybersecurity awareness. The program is expected to serve as a model for similar efforts aimed at improving the digital resilience of MSMEs. Keywords: digital security; cake and snack business; online fraud; community service.
Metode Pembelajaran Mesin untuk Memprediksi Status Gizi Balita Rendra Gustriansyah; Nazori Suhandi; Shinta Puspasari; Ahmad Sanmorino
JURNAL INFOTEL Vol 16 No 1 (2024): February 2024
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v15i4.988

Abstract

Malnutrition is one of the leading health problems experienced by toddlers in various countries. Based on the 2022 Indonesian Nutritional Status Survey results, malnutrition in children under five in Indonesia is higher than the average malnutrition in Africa and globally. Therefore, a way is needed to predict the nutritional status of children under five early and quickly so that the Government (through District Health Office) can immediately provide the necessary treatment. This study aims to predict or classify the toddlers' nutritional status based on age, body mass index (BMI), weight, and body length using various machine learning (ML) methods, namely naïve Bayes, linear discriminant analysis, decision tree, k-nearest neighbor, random forest, and support vector machine. The predictive performance of each ML method was evaluated based on accuracy, sensitivity, specificity, the area under curve, and Cohen's Kappa coefficient. The test results show that the RF method is the most recommended for predicting toddlers' nutritional status. The study's contribution is to obtain information about toddlers' nutritional status easier.
A Data Processing Information System for Oil Palm Harvest Results Febrianza, M; Sanmorino, Ahmad
Journal of Computer Science Application and Engineering (JOSAPEN) Vol. 4 No. 1 (2026): JOSAPEN - January
Publisher : PT. Lentera Ilmu Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70356/josapen.v4i1.91

Abstract

Oil palm plantations require accurate and timely harvest data to support effective operational and managerial decision making. However, many plantations still rely on manual data recording methods that are prone to delays, errors, and data inconsistency. This study develops a data processing information system for oil palm harvest results using the Agile–Scrum approach to improve efficiency and data reliability. The system supports structured harvest data entry, automated processing, and real time reporting. Black-box testing was conducted to evaluate functional correctness, and the results show that all tested system functions operated as expected, with a 100% pass rate across key scenarios, including data entry, validation, and report generation. Performance comparison results indicate that the proposed system reduces data entry time by approximately 70%, decreases error rates by up to 85%, and shortens daily report preparation time from several hours to less than five minutes. These results demonstrate that the developed system effectively enhances accuracy, efficiency, and data accessibility in oil palm harvest management.
Co-Authors Ade Fathurahman Agustina Heryati Aldri Frinaldi Amalia, Rianti Amirah Antony, Fery Anwar, Yatama Zahra Aprianita Kartini Ariati, Nining Aulia, Beta DEWI SARTIKA Dewi, Deshinta Arrova Dhamayanti Dhamayanti Dhamayanti Dhamayanti Dhamayanti Dhamayanti, Dhamayanti Ditho Hersilava Dona Marcelina Dwi Asa Verano Ermatita - Faradillah Faradillah Faradillah Febrianza, M Fery Antony Fery Antony Hartini Hartini Haversyalapa, Ditho Hendra Di Kesuma Heryati, Agustina Imelda Saluza Imelda Saluza, Imelda Indah Pratiwi Putri Isabella Isabella Isabella, Isabella Juhaini Alie Juliansyah, Muhammad Agung Karimah, Fitrah Kesuma, Hendra Di Lastri Widya Astuti Marcellina, Dona Marnisah, Luis Masroni Dedi Kiswanto Maulana, Muhammad Mico Megat Norulazmi Megat Mohamed Noor Muhammad Farhan Nazori Suhandi nining ariati Purbasari, Nadira Putri Rendra Gustriansyah Ristina, Andan Rudi Heriansyah Rudi Heriansyah Sartika, Dewi Setiadi Yazid, Setiadi Setiawan, Ichan Shinta Puspasari Shinta Puspasari Suharmanto, Arvia Fildzah Sunardi, Hastha Suryati Suryati Sutrisna, Rangga Tasmi Terttiaavini Terttiaavini, Terttiaavini Terttiaavini, Terttiaavini Terttiavini Verano, Dwi Asa Wiyanto, Ari Wulanda, Sanza Vittria Yovita, Sukma Yulianti, Evi