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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) ComEngApp : Computer Engineering and Applications Journal Jupiter Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Indonesian Journal of Electrical Engineering and Informatics (IJEEI) JURNAL ILMIAH PENDIDIKAN FISIKA AL BIRUNI JUSIFO : Jurnal Sistem Informasi Annual Research Seminar PROSIDING SEMINAR KIMIA JURNAL NASIONAL TEKNIK ELEKTRO Jurnal Tadris Kimiya Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) JURNAL MEDIA INFORMATIKA BUDIDARMA Momentum: Physics Education Journal SINTECH (Science and Information Technology) Journal SEINASI-KESI Jambura Journal of Educational Chemistry CSRID (Computer Science Research and Its Development Journal) Jurnal Informatika Global Jurnal Informatika dan Rekayasa Elektronik Journal of Information Systems and Informatics Jurnal Generic Bivalen: Chemical Studies Journal CHEDS: Journal of Chemistry, Education, and Science Manajemen dan Kewirausahaan Journal of Educational Sciences DFAME Digital Financial Accounting Management Economics Journal Jurnal Medika: Medika Jurnal Sains dan Kesehatan
Sukemi Sukemi
Fakultas Ilmu Komputer Universitas Sriwijaya
Religion Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Library & Information Science Materials Science & Nanotechnology Medicine & Pharmacology Nursing Physics Public Health Social Sciences Other

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Implementation of Fuzzy C-Means and Topsis in College Rankings Joko Purnomo; Sukemi Sukemi; Parwito Parwito; Ermatita Ermatita
Journal of Information System and Informatics Vol 4 No 4 (2022): Journal of Information Systems and Informatics
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v4i4.409

Abstract

Prior to now, the ranking of higher education institutions, particularly those at the Regional II Palembang Higher Education Service Institution, was based on one component of the work unit's criteria. This makes the university ranking results superior on one criterion but inferior on another. The number of instructors and the number of students at 100 universities in the South Sumatra region were split into two groups based on the outcome of the fuzzy c means algorithm grouping and regional criteria and calculated based on the resulting mean value. The grouping results using a topsis algorithm decision-making system with a weight determined by the number of lecturers with functional positions, college accreditation, number of certified lecturers, and percentage level of higher education database reports are used as a reference to rank universities. Based on the mean value of the fuzzy c means algorithm and the grouping results, seven colleges were chosen. Using the topsis method's way of making decisions, the final score for the highest-ranked college is 0.850.
An adaptable sentence segmentation based on Indonesian rules Johannes Petrus; Ermatita Ermatita; Sukemi Sukemi; Erwin Erwin
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 12, No 3: September 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v12.i3.pp1491-1499

Abstract

Sentence segmentation that breaks textual data strings into individual sentences is an important phase in natural language processing (NLP). Each word in the string that is added a punctuation mark such as a period, question mark, or exclamation point, becomes the location for splitting the string. Humans can easily see the punctuation and split the string into sentences, but not machines. Basically, the three punctuation marks also perform other functions so that the sentence segmentation process must really be able to detect whether a word marked with punctuation is a sentence boundary or not. This research proposes a sentence segmentation system called segmentasi kalimat bahasa Indonesia (SKBI) or Indonesian language sentence segmentation by applying a set of rules and can be used in Indonesian texts and can be adapted for English. There are 34 rules built with a combination of 27 fairly complete features that contribute to this research. The experimental results for the Indonesian text show that the SKBI is able to achieve an F1-Score of 96.89% and 97.07% for English. Both need to be improved but now better than previous research.
Path Loss Prediction Accuracy Based On Random Forest Algorithm in Palembang City Area Sukemi Sukemi; Ahmad Fali Oklilas; Muhammad Wahyu Fadli; Bengawan Alfaresi
JURNAL NASIONAL TEKNIK ELEKTRO Vol 12, No 1: March 2023
Publisher : Jurusan Teknik Elektro Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jnte.v12n1.1052.2023

Abstract

Path loss is a mechanism where the signal from the transmitting antenna to the receiver in a wireless network is attenuated during transmission across a medium due to external field conditions. In the telecommunication design, precise and efficient calculations are required. Random forest, as a machine learning-based path loss prediction model, is used in this study. Machine learning-based path loss prediction, random forest, has a low level of complexity and a high level of predictability. The data was collected using the drive test method at the Trans Musi busway area on the 4G network in Palembang, South Sumatra, Indonesia. The data ratio comprised 20% of the testing set and the rest of the training set. As a result, it was obtained that the prediction accuracy of 9.24% of mean absolute percentage error (MAPE) and root mean square error (RMSE) was 13.6 decibels (dB).  Using hyperparameter tuning for random forest results in optimizing the model used, resulting in accuracy prediction for 8.00% of MAPE and RMSE was 11.8 dB, which is better than the previous results.
Deep Learning Berbasis CNN Untuk Pengenalan Pola Partial Discharge Isolasi Silicone Rubber Ferlian Seftianto; Sukemi Sukemi; Zainuddin Nawawi
SINTECH (Science and Information Technology) Journal Vol. 6 No. 2 (2023): SINTECH Journal Edition Agustus 2023
Publisher : Prahasta Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31598/sintechjournal.v6i2.1390

Abstract

Partial discharge (PD) activity measurements have been carried out by selecting noise signals (de-noising) using Support Vector Machine (SVM)and then recognized using Convolutional Neural Network (CNN). CNN testing was carried out using various models such as activation methods: Sigmoid, Softmax, Relu, Tanh, Swish. Number of layers used is 1, 2, 3, 4 with filter sizes of 32, 64, 128, 256  and kernel sizes 3x3, 2x2, 1x1, 1x2,  1x3 in the MaxPooling and AveragePooling pooling methods. The results obtained, On sigmoid method the MaxPooling and AveragePooling with  1 layers  having a low accuracy around 14.40% but the other layers configurations gets a high accuracy around 98.99% both has been done with or without de-noising. In Softmax activation method, MaxPooling pooling method has an accuracy around 84.94% and has de-noising 90.66%. The AveragePooling pooling method has an accuracy 65.25% and around 75.29% with de-noised. The result shows that SVM de-noising increases the accuracy around 11.12% in the Softmax activation method. In the Tanh, Relu, and Swish activation methods, a low level of accuracy is obtained with an average of 14.40%, and SVM de-noising doesn’t increase the accuracy, so CNN-based deep learning with SVM de-noising is more suitable using the Sigmoid and Softmax.
LITERATURE REVIEW: ANALYSIS OF WEAKNESS AND INHIBITING FACTORS IN THE IMPLEMENTATION OF THE MERDEKA CURRICULUM Akbar, Muhammad; Putri, Noni Khaisha; Febriani, Sarah; Abunoya, Juleha Ilfri; Sukemi, Sukemi
PROSIDING SEMINAR KIMIA Vol 2 No 1 (2023): Prosiding SNK 2023
Publisher : Jurusan Kimia Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Mulawarman

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Abstract

The Merdeka Curriculum issued by the Ministry of Education, Culture, Research and Technology is expected to be a program that is able to overcome educational problems due to the Covid-19 Pandemic. This curriculum offers three functions, namely project-based learning characterized by the Pancasila Student Profile, study of subject matter and a more flexible curriculum structure. An application of the curriculum has weaknesses and inhibiting factors. This literacy study was conducted to examine the weaknesses and inhibiting factors in implementing the Merdeka Curriculum. The method used is a narrative literature review with a literature search using keywords in the range of 2019 to March 2023 and 30 relevant articles were found. Weaknesses and inhibiting factors found in the implementation of the Merdeka Curriculum, namely teacher unpreparedness, lack of training related to the Merdeka Curriculum, lack of facilities and infrastructure, and a less than optimal learning system. The results of this literature review indicate that it is necessary to analyze and evaluate the Merdeka Curriculum so that solutions are found and actions that can overcome weaknesses and inhibiting factors that ultimately it is hoped that the implementation of the Merdeka Curriculum can run well. Keywords: Pancasila Student Profile, Merdeka Curriculm, Inhibiting factor
DISCOVERY LEARNING MODELS FOR TRAINING SCIENCE LITERACY OF STUDENTS IN COLOID MATERIALS Norbaiti, Norbaiti; Erika, Farah; Sukemi, Sukemi
PROSIDING SEMINAR KIMIA Vol 2 No 1 (2023): Prosiding SNK 2023
Publisher : Jurusan Kimia Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Mulawarman

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Abstract

Scientific literacy ability is one of the abilities that must be mastered by students in the 21st century, to be able to solve problems in everyday life using the chemical concepts they are learning. Therefore, we need a learning that is able to relate learning material to the processes of everyday life, namely the effectiveness of the Discovery Learning model. The purpose of this research is to improve students' scientific literacy skills in colloid material. This Discovery Learning model focuses on student activities in learning with the teacher as the facilitator. The research method used was the pre-experimental method with a one-group pre-test-post-test design. The population in this study were all 52 students in class XI IPA at SMA Negeri 3 Muara Muntai in the 2022/2023 academic year, which were divided into 2 classes selected using a saturated sampling technique. The instruments used to measure students' scientific literacy skills are essay test techniques and non-test techniques in the form of student observation sheets and student response questionnaires. The results showed that the increase in students' scientific literacy skills was in the medium category with an effect size classified as a very strong category, as well as a positive response from students. Based on the research that has been done, it can be concluded that the effectiveness of the Discovery Learning learning model can increase students' scientific literacy in colloidal material. Keywords: Scientific Literacy, Discovery Learning Model, Colloid
Membandingkan Nilai Akurasi BERT dan DistilBERT pada Dataset Twitter Fajri, Faisal; Tutuko, Bambang; Sukemi, Sukemi
JUSIFO : Jurnal Sistem Informasi Vol 8 No 2 (2022): JUSIFO (Jurnal Sistem Informasi) | December 2022
Publisher : Program Studi Sistem Informasi, Fakultas Sains dan Teknologi, Universitas Islam Negeri Raden Fatah Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19109/jusifo.v8i2.13885

Abstract

The growth of digital media has been incredibly fast, which has made consuming information a challenging task. Social media processing aided by Machine Learning has been very helpful in the digital era. Sentiment analysis is a fundamental task in Natural Language Processing (NLP). Based on the increasing number of social media users, the amount of data stored in social media platforms is also growing rapidly. As a result, many researchers are conducting studies that utilize social media data. Opinion mining (OM) or Sentiment Analysis (SA) is one of the methods used to analyze information contained in text from social media. Until now, several other studies have attempted to predict Data Mining (DM) using remarkable data mining techniques. The objective of this research is to compare the accuracy values of BERT and DistilBERT. DistilBERT is a technique derived from BERT that provides speed and maximizes classification. The research findings indicate that the use of DistilBERT method resulted in an accuracy value of 97%, precision of 99%, recall of 99%, and f1-score of 99%, which is higher compared to BERT that yielded an accuracy value of 87%, precision of 91%, recall of 91%, and f1-score of 89%.
Utilizing IoT-Enhanced Multilayer Perceptron and Run Length Encoding for Classifying Plant Suitability Based on pH and Soil Humidity Parameters Pratama, Yogi Tiara; Sukemi, Sukemi; Tutuko, Bambang
Journal of Information System and Informatics Vol 6 No 3 (2024): September
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v6i3.811

Abstract

This research proposes an IoT-based system for classifying plant suitability using pH data and soil humidity parameters. The system utilizes Run-Length Encoding (RLE) to compress sensor data, which is transmitted to a database server via the Esp8266 module. A Multilayer Perceptron (MLP) algorithm is employed to classify the data, achieving an accuracy of 0.82 with only two parameters. The classification results are displayed on a website, providing real-time recommendations for farmers. The system's performance is evaluated using a dataset from Kaggle. The Kaggle dataset contains 2200 instances for 22 different plants and the results show that the proposed system can effectively classify plant suitability based on environmental factors. This research contributes to the development of IoT-based recommendation systems for precision agriculture, and future studies can build upon this work to improve accuracy and quality.
Apakah Organizational Justice dan Teamwork Berpengaruh Terhadap Kinerja Melalui Kepuasan Kerja Pada Perusahaan Di Banten? Dewi, Santi Riana; Andari, Andari; Deviyantoro, Deviyantoro; Sukemi, Sukemi
Manajemen dan Kewirausahaan Vol. 5 No. 2 (2024): Manajemen & Kewirausahaan
Publisher : Manajemen FEB Unima

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53682/mk.v5i2.10447

Abstract

Penelitian ini dilatarbelakangi adanya gap antara kinerja yang diharapkan dengan kinerja yang ada pada saat ini. Tujuannya untuk mengetahui ada tidaknya pengaruh antara variabel organizational justice dan teamwork terhadap kinerja dengan kepuasan kerja sebagai variabel intervening. Metode yang digunakan adalah metode kuantitatif dengan pendekatan survey, sampel 52 karyawan diambil dengan teknik sampel jenuh, data diolah menggunakan SPSS 22. Adapun analisis yang digunakan adalah analisis regresi linier berganda, uji determinasi, uji F, uji T, uji validitas, uji reliabilitas, uji normalitas. Hipotesis terdiri dari terdapat pengaruh organizational justice terhadap kepuasan kerja, teamwork terhadap kepuasan kerja, organizational justice terhadap kinerja, teamwork terhadap kinerja, kepuasan kerja terhadap kinerja, pengaruh tidak langsung organizational justice terhadap kinerja, dan pengaruh tidak langsung teamwork terhadap kinerja. Hasil dari penelitian adalah organizational justice berpengaruh langsung terhadap kepuasan kerja, dan teamwork berpengaruh langsung terhadap kepuasan kerja, kepuasan kerja berpengaruh langsung terhadap kinerja, tidak terdapat pengaruh langsung organizational justice terhadap kinerja, teamwork berpengaruh langsung terhadap kinerja, organizational justice berpengaruh secara tidak langsung terhadap kinerja melalui kepuasan kerja, teamwork berpengaruh secara tidak langsung terhadap kinerja melalui kepuasan kerja. Impak penelitian adalah memberikan kontribusi terhadap pengambilan kebijakan dan keputusan manajemen untuk meningkatkan kepuasan kerja dan kinerja karyawan di perusahaan. This research is motivated by the gap between expected performance and current performance. The aim is to determine whether there is an influence between organizational justice and teamwork variables on performance with job satisfaction as an intervening variable. The method used is quantitative with a survey approach, a sample of 52 employees taken using the total sampling technique, and data processed using SPSS 22. The analysis used is multiple linear regression analysis, determination test, F-test, T-test, validity test, reliability test, and normality test. The hypothesis consists of the influence of organizational justice on job satisfaction, teamwork on job satisfaction, organizational justice on performance, teamwork on performance, job satisfaction on performance, indirect influence of organizational justice on performance, and indirect influence of teamwork on performance. The results of the study are that organizational justice has a direct effect on job satisfaction, and teamwork has a direct effect on job satisfaction, job satisfaction has a direct effect on performance, there is no direct influence of organizational justice on performance, teamwork has a direct effect on performance, organizational justice has an indirect effect on performance through job satisfaction, teamwork has an indirect effect on performance through job satisfaction. The impact of the research is that it can contribute to policy-making, and management decisions to improve employee job satisfaction and performance in the company.
PEWARNAAN SERAT DAUN DOYO MENGGUNAKAN PEWARNA ALAMI DARI EKSTRAK DAUN KETAPANG Nursilawati, Nursilawati; Awaliyah, Nabilah Nailah; Pakaenoni, Frederich; Larasati, Herlin Alfiana; Hartandi, Dimas; Rahmadani, Agung; Wirhanuddin, Wirhanuddin; Sukemi, Sukemi
PROSIDING SEMINAR KIMIA Vol 3 No 1 (2024): Prosiding SNK 2024
Publisher : Jurusan Kimia Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Mulawarman

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Abstract

Ulap Doyo is a traditional woven fabric of the Dayak Benuaq tribe in East Kalimantan. Ulap Doyo is made from doyo (Curculigo latifolia) leaf fibers with the base color of whitish cream. Natural dye is used to create patterns. Ketapang (Terminalia catappa L.) leaves contain tannins that can be used as natural dyes. This study aimed to determine the color change of doyo leaf fibers dyed using aqueous ketapang leaf extract. The natural dye was extracted by decoction technique with distilled water as solvent. Tannin content was analyzed using phytochemical tests and permanganometric titration. The dyeing process used the dye bath technique at 92°C of dyeing temperature, 1:100 (w/v) of MLR, and 135 minutes of dyeing time. Before dyeing process, the extract and fibers were treated using 5 mL of 1 M acetic acid (AA) and 5 mL of 1 M ammonia (Am). The color change of the dyed fibers: untreated fiber - untreated extract (UF-UE), treated fiber - untreated extract (TFAA-UE, TFAm-UE), untreated fiber - treated extract (UF-TEAA, UF-TEAm), and treated fiber - treated extract (TFAA-TEAA, TFAm-TEAm) were measured using ImageJ application and shown in term of ∆I. This research results shows that the extract was dark brown solution with 0,280 ± 0,001 % (w/w) of tannin content. The color shade of the dyed doyo leaf fibers is pale brown to brown. The treatment of the extract using acetic acid (UF-TEAA) produce the highest colour shade and ∆I value. This study shows that the ketapang leaf extract can be used as dye for ulap doyo. Keywords : ulap doyo, Curculigo latifolia, Terminalia catappa L., dyeing bath technique
Co-Authors Abunoya, Juleha Ilfri Ade Iriani Sapitri Ade Iriani Sapitri Adha, Syahida Afif, Hasnan Agustina, Reny Agustini, Meily P Ahmad Fali Oklilas Aidil Putrasyah Akbar, M. Agung Andari Andari, Andari Andre Hardoni Anggraeni, Egi Syahrah Angraini, Zihan Nur Apit Fathurohman Apriansyah Putra Aprilisa, Shinta Arif, Ainun Rezkiva Arifian, Hanggara Arni Arni Awaliyah, Nabilah Nailah Ayu Meida Bambang Tutuko Bengawan Alfaresi Buchari, Muhammad Ali Cahyadi, Gabriel Ekoputra Hartono Carunisa, Chofifah Darmawahyuni, Annisa Deviyantoro, Deviyantoro Dian Oktavian Dian Palupi Dian Palupi Rini Dian Palupi Rini Dian Palupi Rini Dian Palupi Rini Dwi Saputri, Rindiani Elza Fitriana Saraswita Endy Suherman Enos Tangke Arung, Enos Tangke Ermatita - Erni Erni Erwin, Erwin Esti Susiloningsih Evi Purnamasari Fadhilah Dirayati Fadhilah Dirayati Fadhilah Dirayati Fadjri, Luthfi Talitha Fairuzy Faisal Fajri Fajri, Faisal Farah Erika Farah, Harra Ismi Fatimah, Neni Hasnah Febriani, Sarah Ferlian Seftianto Fitriah Khoirunnisa Gabriel Ekoputra H.C Gizcha Putri Destriana Gunawan, Rony Hadipurnama Satria Hamid Rahman Hardiman Hardiman Hartandi, Dimas Herliani Herliani Hikmatul Rabiah, Nasya Huda Ubaya Hutauruk, Kevin Jeremia Ida Sriyanti Iis Intan Widiyowati Indah Nuraini, Indah Irfan, Ade Iriyanti, Novia Dwi Irmawati Irmawati Ishmah, Rismananda Islami, Agustina Amalia Ismali, Dicky Taopik Ismali Jaidan Jauhari Johannes Petrus Joko Purnomo Joko Purnomo Kadir, Nurdianah Abdul Kurdiati, Lintang Auliya Kusumattaqiin, Fataa Laode Rijai Larasati, Herlin Alfiana Lestari, Wahyu Yunita Lia Andiani Lia Andiani M. Naufal Rachmatullah Mahmudah, Sofia Maqom Al Mardian, Yessi Maulida Marjusalinah, Anna Dwi Marlina Sylvia Megah Mulya Meily P Agustini muflihah muflihah Muhammad Ridwansyah Muhammad Wahyu Fadli Murniati . Nadia Nadia Norbaiti, Norbaiti Nur Aliah, Nur Nur Apriani Nurfitriani, Ditalia Nursilawati, Nursilawati Octaria, Orissa Oktadini, Nabila Rizky Olii, Nova Yunita Putri Pakaenoni, Frederich Pandito Dewa Putra Parwito Pintaka Kusumaningtyas Prasiwi, Dinar Pratama, Yogi Tiara Purwita, Rahmadina Puspasari, Dewi Puspasari Putri, Noni Khaisha Rahmadani, Agung Rahmatullah, Agung Nugraha Ratna Kusumawardani, Ratna Rengganis, Ajeng Ayu Rifkie Primartha Rifkie Primartha Rindoi, Muhamad Rindoi, Muhammad Riyanto Riyanto RR. Ella Evrita Hestiandari Salam, Supriatno Samsuryadi Samsuryadi Samsyuryadi Samsyuryadi Samsyuryadi Samsyuryadi Sandhira, Aura Chrismania Santi Riana Dewi, Santi Riana Saputri, Deveronica Karning Saputri, Mitha Sari, Eadvin Rosrinda Awang Sela Defi Alib Pradani, Sela Defi Alib Simarmata, Ruth Helen Siti Mariah, Siti Siti Nurmaini Sitti Rahma, Sitti Sobirin Sobirin Sri Lestari Suniyati, Suniyati Syamsiar, Syamsiar Tasya, Indriana Turista, Dora Dayu Rahma Usman Usman Wati, Della Syaras Watulingas, Maasje C. Watulingas, Maasje Catherine Wirhanuddin, Wirhanuddin Yogi Tiara Pratama Yogi Tiara Pratama Yudha Pratomo Yulianti, Evi Yusa Virginiawan Guntara Zainuddin Nawawi