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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) IJCCS (Indonesian Journal of Computing and Cybernetics Systems) TEKNIK INFORMATIKA JURNAL SISTEM INFORMASI BISNIS Bulletin of Electrical Engineering and Informatics POSITIF Journal of Tropical Biodiversity and Biotechnology KLIK (Kumpulan jurnaL Ilmu Komputer) (e-Journal) JOIV : International Journal on Informatics Visualization Jurnal Komputasi Jurnal SOLMA Jurnal Teknoinfo Jurnal Tekno Kompak Indonesian Journal of Electrical Engineering and Computer Science Jurnal Pengabdian Kepada Masyarakat (JPKM) Tabikpun Journal of Multidisciplinary Applied Natural Science Buguh: Jurnal Pengabdian Kepada Masyarakat Jurnal Pepadun AMMA : Jurnal Pengabdian Masyarakat Seminar Nasional Teknologi dan Multidisiplin Ilmu Integra: Journal of Integrated Mathematics and Computer Science Journal of Digital Market and Digital Currency Jurnal Komputasi Jurnal Elektronika dan Telekomunikasi
Admi Syarif
Jurusan Ilmu Komputer, Fakultas Matematika Dan Ilmu Pengetahuan Alam, Universitas Lampung
Agriculture, Biological Sciences & Forestry Arts Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Immunology & microbiology Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Nursing Physics Social Sciences Other

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Peningkatan Potensi Desa Dengan Personal Branding Produk Admi Syarif; Ghraito Arip; Dimas A. Dhafa; Yokie Rahman; Anggun N. Azizah; Ami Zuraida; Nabila Z. Muhammad; Ni K. Aprilliani
Jurnal Pengabdian Kepada Masyarakat (JPKM) TABIKPUN Vol. 4 No. 1 (2023)
Publisher : Faculty of Mathematics and Natural Sciences - Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jpkmt.v4i1.108

Abstract

Di era saat ini, Usaha Mikro Kecil Menengah (UMKM) menjadi level usaha yang mendominasi usaha di Indonesia. Namun, masih banyak pelaku UMKM, termasuk di Desa Kota Besi yang tidak mementingkan merek dagang dan kemasan yang digunakan. Selain itu, produk yang dihasilkan hanya diperjualbelikan di sekitar desa saja. Padahal, dengan adanya perkembangan teknologi ini, pelaku UMKM perlu menyiapkan strategi seperti menawarkan produknya secara online karena sebagian besar konsumen cenderung mengikuti perkembangan zaman yang serba canggih. Agar tidak kalah saing, pelaku UMKM juga perlu memperbaiki kualitas kemasan agar lebih menarik konsumen untuk membeli produk dan memiliki merek dagang yang menjadi ciri khas produk sehingga lebih dikenal. Oleh karena itu, mahasiswa sebagai agent of change berkewajiban untuk memberi pemahaman dan pelatihan kepada pelaku UMKM sehingga nantinya produk yang dihasilkan memiliki nilai jual tinggi dan meningkatkan pendapatan. Kegiatan ini berjalan dengan baik berkat dukungan dari tim pengabdian KKN, kepala desa, maupun pelaku UMKM.
Stomata characters of sugarcane (Saccharum officinarum L.) mutants of GMP3 variety at PT Gunung Madu Plantations, Lampung, Indonesia Mahfut, Mahfut; Kendari, Putri; Syarif, Admi; Wahyuningsih, Sri; Susiyanti, Endah
Journal of Tropical Biodiversity and Biotechnology Vol 8, No 3 (2023): December
Publisher : Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/jtbb.79860

Abstract

The induction of colchicine mutations is one method of breeding. PT Gunung Madu Plantations, for example, has induced mutations of commercial sugarcane (Saccharum officinarum L.) varieties, however, investigations on the impact of colchicine on stomatal characters have received less attention. Therefore, this study aimed to analyse the stomata character of 21 sugarcane mutants of the GMP3 variety at PT Gunung Madu Plantations, Lampung, Indonesia with a focused look at stomata aperture width, stomata length and width, number of stomata, stomatal density, and stomata index. The collected data were analysed using cluster and Principal Component Analysis (PCA) through MVSP software. This study showed that all GMP3 mutants had Graminae-type stomata. In terms of stomata length and width, the average size of the GMP3 variety mutant was greater than that of the control. The diversity of stomata characters is fairly high due to differences in stomata size between GMP3 and control mutants. With a similarity index of 0.20, the phenetic analysis of 21 mutants of the GMP3 variety revealed that the relationship between mutants and controls was getting further. A six-character principal component analysis revealed that axis I's total variation accounted for 40.54 percent of the variation and had an eigenvalue of 2.43, whereas axis II's contribution to the variation was 19.02 percent and had an eigenvalue of 1.14. The findings indicate that stomata are excellent taxonomic evidence for identifying and analysing sugarcane varieties induced by colchicine-induced breeding. 
Performance evaluation of feature selections on some ML approaches for diagnosing the narcissistic personality disorder Sulistiani, Heni; Syarif, Admi; Muludi, Kurnia; Warsito, Warsito
Bulletin of Electrical Engineering and Informatics Vol 13, No 2: April 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i2.6717

Abstract

Narcissistic personality disorder (NPD) is a personality disorder that affects various aspects of life, including relationships, employment, school, and finances. Persons with NPD usually feel unhappy and disappointed when no one helps them and is not praised for their achievements. Diagnosing narcissism is generally done using a screening test that consumes time and costs a lot. This research aims to evaluate the performance of several feature selection (FS) approaches on machine learning (ML) techniques (support vector machine (SVM), random forest classifier (RFC), and Naive Bayes). Three scenarios of FS (all features, the information gain technique and the gain ratio (GR) feature technique) are used for each ML method. Several experiments using the benchmark narcissistic disorder dataset have been done. It adopts the k-fold cross-validation (10-fold cross-validation) strategy. We evaluate the method’s performance by measuring its accuracy, error rate, and processing time. It is shown that the RFC GR strategy gives the best performance with an accuracy of 100%.
TRANSFORMASI BERKELANJUTAN: BANK SAMPAH DAN TANAM HIDROPONIK MENGUKIR JEJAK POSITIF DI DESA BAKAUHENI Miswar, Dedy; Yarmaidi, Yarmaidi; Aristoteles, Aristoteles; Syarif, Admi; Zahra, Rizka Aulia
BUGUH: JURNAL PENGABDIAN KEPADA MASYARAKAT Vol. 4 No. 1 (2024): Maret 2024
Publisher : Badan Pelaksana Kuliah Kerja Nyata Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/buguh.v4n1.2558

Abstract

Bank Sampah merupakan sistem pengelompokkan sampah yang dilakukan sebagai penanggulangan masalah penumpukan sampah yang tidak terorganisisir. Di samping itu, penanggulangan masalah sampah melalui bank sampah dapat melahirkan pemanfaatan sampah anorganik sebagai media Sistem Tanam Hidroponik. Kegiatan ini dibuat untuk menggambarkan realisasi program positif bank sampah dan sosialisasi sistem tanam hidroponik. Kegiatan ini dilakukan oleh Mahasiswa KKN Universitas Lampung di Dusun Simpang Tiga, Desa Bakauheni. Kegiatan ini melibatkan masyarakat untuk belajar, berkolaborasi, serta mempraktikkan secara langsung sistem tanam hidroponik yang dapat menjadi alternatif sistem tanam tradisional. Dampak nyata dari kegiatan ini adalah menerapkan ilmu dan keterampilan yang telah didapat dalam kehidupan sehari-hari.
Implementation of fuzzy logic approach for thalassemia screening in children Redy Susanto, Erliyan; Syarif, Admi; Warsito, Warsito; Nisa Berawi, Khairun; Ayu Sangging, Putu Ristyaning; Wantoro, Agus
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 13, No 4: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v13.i4.pp4062-4070

Abstract

Thalassemia is one of the most dangerous blood disorders that can lead to severe complications. It is an inherited disease, usually detected after a child is two to four years old. Identification of thalassemia is a complex task, involving many variables. Doctors generally diagnose thalassemia by using a complete blood count (CBC) and high-performance liquid chromatography (HPLC) test results. However, HPLC tests are expensive and time consuming, hence the need for other methods to identify thalassemia. There are many studies on the application of artificial intelligence for medical applications. In this study, we developed a new fuzzy-based approach to identify thalassemia based on a patient’s blood laboratory results. First, we analyzed the CBC data for blood disorder prediction. Secondly, we adopt the test results of peripheral blood smear (PBS) to identify whether the person has thalassemia. We conducted several experiments using 30 (thirty) hospital patient data and the results were compared with the results provided by experts. The experimental results show that the system can determine blood disorders with 93% accuracy and 100% precision in thalassemia prediction. This system is very effective to help doctors in diagnosing thalassemia patients.
RANCANG BANGUN GAME STOCK STREET SAGA BERDASARKAN ANALISIS TEKNIKAL Tristiyanto; Yuliyanto, Kurniawan Dwi; Syarif, Admi; Wulansari, Ossy Endah Dwi
POSITIF : Jurnal Sistem dan Teknologi Informasi Vol 10 No 2 (2024): Positif : Jurnal Sistem dan Teknologi Informasi
Publisher : P3M Politeknik Negeri Banjarmasin

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This research focuses on the development of the "Stock Street Saga" game, which effectively integrates technical analysis concepts using indicators such as volume, momentum, trend, and oscillator. The game is designed to provide a simulation that allows players, especially beginners, to practice and understand technical analysis without financial risk. The research utilized the Game Development Life Cycle (GDLC) method, ensuring a systematic approach from initiation to production and testing. User Acceptance Testing (UAT) results from 40 respondents, consisting of novice traders and game developers, showed that the game effectively facilitates learning technical analysis. With an average UAT score of 75.57%, it indicates that the game meets the criteria of being a good educational tool, successfully implementing technical analysis concepts and offering an effective learning experience
Determining the Grade of Robusta Coffee Beans of Lampung, Bengkulu, and South Sumatra Provinces by Using the Analytical Hierarchy Process (AHP) Yuniarthe, Yodhi; Syarif, Admi; Gitosaputro, Sumaryo; Warsito, Warsito
JOIV : International Journal on Informatics Visualization Vol 9, No 1 (2025)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.9.1.2667

Abstract

Coffee is an important commodity for the world business community. One of the world's leading coffee producers is Indonesia. In Indonesia, several provinces produce coffee beans, especially in Sumatra island. They generally cultivate robusta-type coffee. The determination of coffee quality here is still done manually. Recently, along with the increasing recognition of computers, several decision-support system approaches have been introduced, including the Analytical Hierarchy Process (AHP). This research aims to implement the AHP to assess Indonesian robusta coffee beans (Lampung, Bengkulu, and South Sumatra). The researchers use a systematic process, including the preparation stage, data collection using datasets, determination of criteria and alternatives, hierarchical structure, creation of matrices to compare pairs, calculation of priority vectors and eigenvector values, and accuracy testing. This research uses six criteria with 19 sub-criteria and seven alternatives. From the rankings calculated using the AHP method for coffee production areas, the best quality coffee bean is in West Lampung, with the highest value of  0.28. The results of this study are compared with those given by an expert. The results show the MAPE error of 4.42%, a very accurate category.  Thus, it is shown that this method provides excellent results. Future research can be conducted to develop a more sophisticated and efficient AHP method for multi-criteria decision-making in various fields such as business management, engineering, environment, and health.
Trends in machine learning for predicting personality disorder: a bibliometric analysis Sulistiani, Heni; Syarif, Admi; Warsito, Warsito; Berawi, Khairun Nisa
Indonesian Journal of Electrical Engineering and Computer Science Vol 38, No 2: May 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v38.i2.pp1299-1307

Abstract

Over the last decade, research on artificial intelligence (AI) in the medical field has increased. However, unlike other disciplines, AI in personality disorders is still in the minority. For this reason, we conduct a map research using bibliometric and build a visualization map using VOSviewer in AI to predict personality disorders. We conducted a literature review using the systematic literature review (SLR) method, consisting of three stages: planning, implementation, and reporting. The evaluation involved 22 scientific articles on AI in predicting personality disorders indexed by Scopus Quartile Q1–Q4 from the Google Scholar database during the last five years, from 2018–2023. In the meantime, the results of bibliometric analysis have led to the discovery of information about the most productive publishers, the evolution of scientific articles, and the quantity of citations. In addition, VOSviewer’s visualization of the most frequently occurring terms in abstracts and titles has made it easier for researchers to find novel and infrequently studied subjects in AI on personality disorders.
Molecular Phylogeny of rDNA-ITS on Native Dendrobium in Lampung Mahfut, Mahfut; Syarif, Admi; Wahyuningsih, Sri
Journal of Multidisciplinary Applied Natural Science Vol. 5 No. 2 (2025): Journal of Multidisciplinary Applied Natural Science
Publisher : Pandawa Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47352/jmans.2774-3047.263

Abstract

Dendrobium, a flagship collection of the Liwa Botanical Garden, is an endemic flora of the Southern Sumatra that requires preservation. One of the challenges in its conservation and potential development is the molecular identification. This molecular identification utilizes DNA barcoding with the rDNA-ITS marker as a practical, rapid, accurate, effective, and efficient alternative, complementing previous species-level identification results based on morphological characteristics. Amplification results from 5 selected samples showed specific bands measuring 300 bp. Sequence data analysis using BioEdit and MEGA V.11.0.11 software with 1000 bootstraps grouped all accessions into the same main cluster with a similarity range of 94–100%. Phylogenetic analysis revealed that accession D2 is similar to D. signatum from Japan (AB593662.1), and accession D3 to D. densiflorum (HQ114255), D4 to D. nobile (LC011413.1), accession D6 to D. trigonopus (KF143730.1), and accession D12 to D. faciferum (LC192955.1) from China. The results of this study will enrich the taxonomic and phylogenetic data of Dendrobium, which is essential for conservation and serves as a foundation for its development as a medicinal herbal plant.
Application of Random Forest Method Classification for Glycosylation in Lysine Protein Sequences Fitriyana, Silfia; Syarif, Admi; Rossyking, Favorisen; Faisal, Mohammad Reza
Integra: Journal of Integrated Mathematics and Computer Science Vol. 1 No. 2 (2024): July
Publisher : Magister Program of Mathematics, Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26554/integrajimcs.20241218

Abstract

Grouping glycosylated lysine proteins into groups according to the type of glycosylation seen in the lysine protein sequence is known as glycosylation in the lysine protein sequence. In this work, the sensitivity, specificity, accuracy, and Matthew’s correlation coefficient (MCC) of the random forest approach for classifying the glycosylation of lysine protein sequences were examined. With 214 positive and 406 negative data, the lysine protein dataset derived from benchmark data contains 620 total proteins with a protein length of 15 sequences. 90% of the dataset is used for training, while 10% is used for testing. Using the R package BioSeqClass version 1.44.0, feature extraction employed protein descriptors, specifically AA Index, CTD, and PseAAC, with a total of 60 features. The Random Forest classification algorithm was used to reprocess the results with Mtry values of 4, 8, and 16. The number of trees (ntree) was randomly set to 250, 500, 750, and 1000. The best results were achieved with a dataset split of 90% training data and 10% test data, using Mtry of 42 and 1000 trees, resulting in 89.97% sensitivity, 92.79% specificity, 80.76% MCC, and 90.42% accuracy. These results demonstrate that the combination of feature extraction and the Random Forest algorithm is effective in classifying lysine proteins.
Co-Authors Adhim, M. Abdul Afdhaluddin, Muhammad Agung Pambudi Agus Rahardi, Agus Agus Wantoro AGUSTINA RAHAYU AKBAR RISMAWAN TANJUNG Akmal Junaidi Ami Zuraida Andrian, Rico Anggi Puspitasari Anggun N. Azizah Ani Kurniawati Aqshal Dwi Setiawan Arafia Isnayu Akaf Ari Ardianto Arie Setya Putra Aristoteles, Aristoteles Asmanto, Budi Ayu Nadila Ayu Sangging, Putu Ristyaning Azi Mediantara Bambang Hermanto Dedy Miswar Deswita Sari Dimas A. Dhafa Dwi Sakethi Edi Arif Effendi Erika Fadia Salsabila Faiqa Marina Fatimah Fahurian Fazri, Yudistira Febi Eka Febriansyah Fitriyana, Silfia Ghraito Arip Greacella Risky Amanda Hari Soetanto Heni Sulistiani Heningtyas, Yunda Iva Mutiara Indah Kendari, Putri Khairun Nisa Krisna Rendi Awalludin Kurnia Muludi Kurnia Muludi Lumbanraja, Favorisen R M Said Hasibuan M. Juandhika Rizky Machudor Yusman Mahfut Maya Asterita Michelle Jovelyna Mohammad Surya Akbar Muhammad Irfan Ardiansyah Muhammad Jamaludin Muhammad Reza Faisal, Muhammad Reza Muhammad Rizki Muhammad Tegar Sabilillah Nabila Z. Muhammad Ni K. Aprilliani Nisa Berawi, Khairun Nisar Zaidal Noverina Rahmaniyanti Novita Dwilestari Nur Indriani Prabowo, Rizky Prabowo, Rizky Putri Ayu Penita Qory Aprilarita Raden Mohamad Herdian Bhakti Rahmat Safe'i Raras Silviana Redy Susanto, Erliyan Rifandi, Raihan Salsabila, Diana Shofi, Imam Marzuki Shofiana, Dewi Asiah Sholehurrohman, Ridho Sintiya Paramitha Sri Ratna Sulistiyanti Sri Wahyuningsih Sugaluh Yulianti Sukamto, Ika Sumiyarsi Sumaryo Gitosaputro Susiyanti, Endah Sutyarso Sutyarso Syachrul Priyo Wibowo TANJUNG, AKBAR RISMAWAN Timotius Pascha Tristiyanto Tundjung Tripeni Handayani Wahyu Caesarendra Wahyu Caesarendra Warsito . Wildhan Wahyudi Wulansari, Ossy Endah Dwi Yarmaidi Yarmaidi Yoannisa Egeustin Yodhi Yuniarthe Yokie Rahman Yulia K. Wardani Yulia Kusuma Wardani Yuliyanto, Kurniawan Dwi Zahra, Rizka Aulia