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All Journal JITEK (Jurnal Ilmiah Teknosains) Jurnal TAM (Technology Acceptance Model) Jusikom : Jurnal Sistem Komputer Musirawas JMM (Jurnal Masyarakat Mandiri) JUTIM (Jurnal Teknik Informatika Musirawas) Martabe : Jurnal Pengabdian Kepada Masyarakat MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Jurnal Informatika Global Jurnal Informatika dan Rekayasa Elektronik Jurnal Ilmiah Betrik : Besemah Teknologi Informasi dan Komputer Ngabdimas : Pengabdian Pada Masyarakat PAKDEMAS : Jurnal Pengabdian Kepada Masyarakat Informatics and Enginering Dedication Knowbase : International Journal of Knowledge in Database Jurnal Hasil Pengabdian Masyarakat (JURIBMAS) Jurnal Pengabdian Kepada Masyarakat Ngabdimas Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Jurnal TAM (Technology Acceptance Model) Smatika Jurnal : STIKI Informatika Jurnal
Dedi Setiadi
Institut Teknologi Pagar Alam, Indonesia
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SISTEM PENDUKUNG KEPUTUSAN REKOMENDASI HOMESTAY DI KOTA PAGAR ALAM DENGAN METODE TOPSIS Masdalipa, Risnaini; Setiadi, Dedi; Syahri, Riduan
(JITEK)Jurnal Ilmiah Teknosains Vol 9, No 2/Nov (2023): JiTek
Publisher : Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/jitek.v9i2/Nov.17247

Abstract

Technological developments can be used appropriately and properly will provide benefits and facilitate human work. The decision support system is an information system that can be used to assist in decision making, in this case, namely providing homestay recommendations to tourists who will visit the city of Pagar Alam which is a tourist destination in South Sumatra. Tourists who will stay at homestays must come directly to several homestays to ask about the rental price and facilities provided by the homestay manager. Sometimes people who are looking for a homestay don't immediately match the homestay they are visiting, so they have to find another homestay that is suitable and in accordance with the available budget so that this situation is not optimal, because the process for people to find a suitable homestay can take a long time. The method used is Technique for Order of Preference by Similiarty to Ideal Solution, which is a method for solving Multi Attribute Decision Making problems. The system development uses the Rapid Application Development (RAD) method, which is a process model used in incremental software development, especially for short processing times, which consists of three stages, namely requirements planning, design workshop, implementation. From the calculation results of the TOPSIS method with four criteria determined for several alternatives, according to the selection of criteria by the user, as well as the results of ranking alternatives with the highest preference value, namely 0.5962, and kia homestay as a recommendation according to what is expected by the user.
SOSIALISASI PENGOLAHAN LIMBAH KULIT KOPI MENJADI TEH CASCARA UNTUK MENINGKATKAN PENDAPATAN MASYARAKAT Dedi Setiadi; Syerina Raihatul Jannah; Willy Wijayanti
JMM (Jurnal Masyarakat Mandiri) Vol 8, No 5 (2024): Oktober
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jmm.v8i5.26598

Abstract

Abstrak: Masyarakat desa Talang Pagar Agung menggantungkan penghasilan dari menjual biji kopi, ketika musim kopi datang. Selama ini limbah kulit kopi hanya dibiarkan menumpuk di pekarangan rumah penduduk tanpa pengelolaan yang baik sehingga mencemari lingkungan, Kegiatan pengabdian ini bertujuan untuk memberikan pengetahuan dan kemampuan baru bagaimana cara mengolah limbah kulit kopi menjadi produk yang memiliki nilai jual yaitu teh cascara, sehingga bisa meningkatkan penghasilan petani. Peserta kegiatan ini yaitu masyarakat yang tergabung dalam kelompok tani Maju Jaya Sejahtera di desa Talang Pagar Agung. Metode yang digunakan pada kegiatan ini, dengan tahapan-tahapannya yaitu Analisis kebutuham, Perancangan, Sosialisasi dan Pendampingan serta Evaluasi dengan indikatornya yaitu masyarakat mengetahui dan dapat mengolah limbah kulit kopi menjadi teh cascara dengan baik. Secara keseluruhan, evaluasi menunjukkan bahwa program sosialisasi dan pendampingan ini berhasil mencapai tujuannya, terlihat dari peningkatan yang baik dari nilai pretest 9,09% sebelum sosialisasi dan setelah sosialisasi dengan nilai posttest 100%, dimana semua peserta menjadi kenal dengan teh cascara. Abstract: The people of Talang Pagar Agung village depend on income from selling coffee beans, when the coffee season comes. So far, coffee skin waste has only been left to pile up in people's yards without proper management, thus polluting the environment. This community service activity aims to provide new knowledge and skills on how to process coffee skin waste into products that have a selling value, namely cascara tea, so that it can increase farmers' income. Participants in this activity are people who are members of the Maju Jaya Sejahtera farmer group in Talang Pagar Agung village. The method used in this activity, with its stages, namely Needs Analysis, Design, Socialization and Mentoring and Evaluation with indicators that the community knows and can process coffee skin waste into cascara tea properly. Overall, the evaluation shows that this socialization and mentoring program has succeeded in achieving its goals, as seen from the good increase from the pretest value of 9.09% before socialization and after socialization with a posttest value of 100%, where all participants became familiar with cascara tea.
Electronic Tourism Using Decision Support Systems to Optimize the Trips Dedi Setiadi; Yogi Isro Mukti
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 23 No. 1 (2023)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v23i1.3331

Abstract

Pagar Alam is a tourist destination city in the province of South Sumatra, which has many very diverse tourist destinations. The problem is that there is still a lack of information about tourism that tourists can access. This research aimed to build electronic tourism to make it easier for tourists to get the best information and recommendations about tourism in the city of Pagar Alam, which can be accessed anytime and anywhere, as well as improve tourist experience in planning their tourist trips because this electronic tourism platform includes decision making support system, which helps tourists manage their tours according to their needs and abilities. The research method used was analysis by collecting data by observing tourist attractions, calculating predictions using the simple additive weighting method, and from the results of testing with several alternatives, it can be concluded that electronic tourism meets the criteria chosen by tourists after being carried out. The calculation produced the highest preference value for tourist attractions, namely Tugu Rimau, with a value of 13.25. The highest preference value for hotels is Villa Gunung Gare Pagar Alam, with a score of 8.91, and the highest preference score for eating places is Warung Ridwan, with a score of 13.25. The next stage was system design using data flow diagrams, and the final stage was implementation by building electronic tourism using the CodeIgniter framework.
Improving the Performance of Convolutional Neural Networks (CNN) in Identification of Agricultural Plant Diseases Dedi Setiadi; Fido Rizki
SMATIKA JURNAL : STIKI Informatika Jurnal Vol 16 No 02 (2026): SMATIKA Jurnal : STIKI Informatika Jurnal
Publisher : LPPM Universitas Bhinneka Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/smatika.v16i02.2372

Abstract

This study aims to improve the performance of the Convolutional Neural Network (CNN) algorithm in detecting coffee leaf diseases using the Inception V3 architecture. The main challenge of this classification is the subtle visual similarity in color, texture, and symptom patterns between diseases. To overcome this, Inception V3 is implemented because of its superiority in multi-scale feature extraction through convolution factorization which reduces parameters while increasing accuracy. The dataset used consists of 1,120 images, evenly distributed into four classes (three types of diseases and one healthy class, each with 280 images), with a training, validation, and test data split ratio of 896:112:112. As a comparison, a conventional basic CNN architecture consisting of 3 convolution layers (3 X 3, stride 1), 3 max-pooling, and 1 dense layer, trained with the same hyperparameters (Adam optimizer, learning rate 0.001, batch size 32) is used. The experimental results show a significant performance improvement; Model accuracy increased from 74.4% on a standard CNN to 97.0% after integrating Inception V3. The scientific contribution of this research lies in mapping overlapping visual characteristics of coffee diseases through multi-scale feature optimization, which demonstrates that computational efficiency can go hand in hand with accuracy improvements on complex agricultural image datasets. These findings confirm that the Inception V3 architecture provides a robust and efficient solution for automating plant disease diagnosis in the field.
Hotspot Management Training Using Mikrotik RouterBoard to Support Independent Internet Access for the Community Dedi Setiadi; Riduan Syahri; Febriansyah; Debi Gusmaliza; Risnaini Masdalipa
JURIBMAS : Jurnal Hasil Pengabdian Masyarakat Vol 5 No 1 (2026): Juli 2026
Publisher : LKP KARYA PRIMA KURSUS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62712/juribmas.v5i1.1015

Abstract

Currently, the internet has become one of the basic needs for society, one of which is in the field of education. Where many students or college students are constrained in participating in learning or searching for materials due to internet access constraints, so hotspot creation training is needed. The creation of this hotspot aims to ensure that all activities that require internet access can run smoothly. The training is carried out through community service activities as a solution to problems that occur in the community. The stages of implementing this community service consist of 4 (four) stages, namely the first stage of preparation by conducting surveys and interviews, the second stage of training implementation is carried out by delivering materials and practicing hotspot creation, the third stage is an evaluation by giving questionnaires to participants to determine the understanding of each participant, and the fourth stage is making reports and publications as outputs of community service activities. Based on the evaluation that has been carried out, it is known that the level of understanding and knowledge of the training participants has increased significantly. Before participating in the training, only 50% of participants knew about computer networks, increasing to 95%. Before participating in the training, only 5% of participants had ever created a hotspot with a Mikrotik router board, increasing to 90%. Before participating in the training, only 5% of participants were able to configure Mikrotik, increasing to 90%. Before the training, only 5% of participants were able to create a hotspot using a Mikrotik router board, increasing to 80%. Before the training, only 50% of participants understood the functions of the internet and hotspot, increasing to 95% after the training
Pelatihan Pengembangan Aplikasi Machine Learning Berbasis Streamlit untuk Mendukung Penyelesaian Tugas Akhir Mahasiswa Febriansyah; Dedi Setiadi; Riduan Syahri
JURIBMAS : Jurnal Hasil Pengabdian Masyarakat Vol 5 No 1 (2026): Juli 2026
Publisher : LKP KARYA PRIMA KURSUS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62712/juribmas.v5i1.1350

Abstract

Mahasiswa Teknik Informatika yang mengangkat topik machine learning dalam tugas akhir masih mengalami kesulitan dalam mengimplementasikan model yang telah dibangun ke dalam aplikasi yang dapat digunakan secara langsung oleh pengguna. Kegiatan pengabdian kepada masyarakat ini bertujuan untuk meningkatkan kompetensi mahasiswa dalam mengembangkan aplikasi machine learning berbasis Streamlit guna mendukung penyelesaian tugas akhir. Kegiatan diikuti oleh 35 mahasiswa tingkat akhir Program Studi Teknik Informatika Institut Teknologi Pagar Alam (ITPA) dan dilaksanakan melalui pelatihan, demonstrasi, praktik langsung, pendampingan, serta evaluasi menggunakan pre-test dan post-test. Hasil kegiatan menunjukkan peningkatan kompetensi peserta yang ditandai dengan kenaikan nilai rata-rata dari 54,3 pada pre-test menjadi 86,7 pada post-test. Selain itu, sebanyak 31 peserta (88,6%) berhasil membangun aplikasi berbasis Streamlit dan 27 peserta (77,1%) berhasil mengintegrasikan model machine learning ke dalam aplikasi yang dikembangkan. Tingkat kepuasan peserta mencapai 92,5%, menunjukkan respons yang sangat positif terhadap kegiatan. Hasil ini menunjukkan bahwa pelatihan berbasis Streamlit efektif dalam meningkatkan keterampilan implementasi machine learning serta mendukung penyelesaian tugas akhir yang lebih aplikatif.
PEMBUATAN BUBUK CABAI MERAH (BUCAMER) UNTUK MENGOPTIMALKAN PRODUKSI DAN PEMASARAN CABAI DI KOTA PAGAR ALAM Inda Anggraini; Dedi Setiadi; Anggia Martiana
PAKDEMAS : Jurnal Pengabdian Kepada Masyarakat Vol 5 No 1 (2025): Desember
Publisher : Fakultas Pertanian

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58222/pakdemas.v5i1.585

Abstract

This Community Partnership Program (PKM) activity aims to increase the capacity of farmer groups in processing red chilies into value-added products as an effort to overcome fluctuations in the price of fresh chilies in Pagar Alam City. The activity partner is the Sukamaju Farmer Group in Lubuk Buntak Village/Subdistrict, which faces major problems in the form of limited post-harvest processing skills, poor packaging quality, and suboptimal agricultural product marketing strategies. To address these issues, the PKM team provided solutions in the form of training on making red chili powder (BuCaMer), applying appropriate technology (drying equipment, grinders, and sealers), assistance with product packaging and label design, and training on digital marketing through social media and marketplaces. The implementation methods included field observations, demonstration-based training, intensive assistance, and evaluation through pre-tests 2,6 and post-tests 4,02. The results of the activities showed a significant improvement in the partners' skills in the production, packaging, and marketing of products. BuCaMer products were successfully produced with improved hygiene smooth texture, and longer shelf life. Product packaging became more attractive and informative, while the digital marketing capabilities of farmer group members improved through the practice of using social media as a promotional tool. Pretest and posttest evaluations showed a ±40% increase in participants' knowledge, confirming the effectiveness of the program.
PEMANFAATAN IOT JERAMI PADI-KOPI UNTUK BUDIDAYA JAMUR MERANG (JADI-JARANG) PAADA KELOMPOK TANI TUNAS BARU Risnaini masda Masdalipa; Dedi Setiadi; Edowinsyah Edowinsyah
FORDICATE Vol 5 No 1 (2025): November 2025
Publisher : Universitas Multi Data Palembang, Fakultas Ilmu Komputer dan Rekayasa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/fordicate.v4i3.13546

Abstract

Agricultural residues such as rice straw and coffee husks are often underutilized, despite their potential as cultivation media for straw mushroom (Volvariella volvacea). This study aimed to develop a rice straw–coffee husk-based cultivation model (Jadi-Jarang) within the Tunas Baru Farmer Group to promote business diversification, increase farmers’ income, and encourage environmentally friendly waste management. The cultivation process included media preparation, fermentation, spawn inoculation, mushroom house maintenance, harvesting, and post-harvest handling. Evaluations were carried out on mycelium growth, mushroom productivity, product quality, and socio-economic impacts. Results indicated that the combination of rice straw and coffee husks effectively supported mushroom growth, with evenly distributed mycelium, relatively short harvesting time (14–18 days), and fresh mushrooms of high market value. Moreover, this initiative enhanced farmers’ skills, reduced agricultural waste, and provided additional income. Therefore, the rice straw–coffee husk model offers both economic benefits and sustainable farming practices based on zero waste farming, making it a promising approach for farmer groups.
Analysis of Drug Inventory Patterns Using the K-Means Algorithm Dedi Setiadi; Debi Gusmaliza
Knowbase : International Journal of Knowledge in Database Vol. 5 No. 2 (2025): December 2025
Publisher : Universitas Islam Negeri Sjech M. Djamil Djambek Bukittinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30983/knowbase.v5i2.10420

Abstract

Efficient drug inventory management is a critical challenge for the Sandar Angin Community Health Center to ensure the availability of drugs needed by customers without incurring excessive storage costs. Data mining with the K-Means algorithm was used to determine drug inventory more effectively. Drug data for the past year was used as a sample in this study. The Elbow method was used to determine the optimal number of clusters, and the results showed that three clusters were most appropriate for grouping drug sales data. The first cluster consisted of drugs with high and consistent sales, the second cluster included drugs with moderate and fluctuating sales, while the third cluster contained drugs with low and inconsistent sales. The results of this clustering provide clear guidance in drug inventory management. Drugs in the first cluster require larger stocks, the second cluster requires moderate stocks and promotional strategies tailored to the season, while the third cluster requires minimal stocks and regular evaluations to determine the continuation of its supply. The implementation of the K-Means method has proven effective in reducing storage costs, increasing customer satisfaction, and optimizing inventory management. This study concluded that data mining using the K-Means algorithm can help the Sandar Angin Community Health Center make better decisions regarding drug inventory. The results showed that out of a total of 506 drug data sets, 496 fell into cluster 0, or 98% of the data. One drug data set fell into cluster 1, and nine drug data set fell into cluster 2.
Co-Authors Abdi NAsrullah Asep Syaputra Dedy Syamsuar Dhiniati, Fameira Edowinsyah Edowinsyah Edowinsyah Efan, Efan Febriansyah . Fido Rizki Gusmaliza, Debi Inda Anggraini Lesi Anggraini Lily Endah Diansari Martiana, Anggia Masagus Taswin Masdalipa, Risnaini Melza Yolanda Risnaini masda Masdalipa Rosmawati, Henni Sasmita Sasmita Sasmita Sasmita Syahri, Riduan Syerina Raihatul Jannah Tri Susanti Tri Susanti Tri Susanti Willy Wijayanti Yogi Isro Mukti Yogi Isro Mukti, Yogi Isro