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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) ComEngApp : Computer Engineering and Applications Journal Jurnal Ilmu Komputer dan Informasi Jupiter Bulletin of Electrical Engineering and Informatics Scientific Journal of Informatics ICON-CSE Annual Research Seminar PROCEEDING IC-ITECHS 2014 Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) JPPPF (Jurnal Penelitian dan Pengembangan Pendidikan Fisika) Dinamisia: Jurnal Pengabdian Kepada Masyarakat Jurnal Inovasi Hasil Pengabdian Masyarakat (JIPEMAS) Jurnal Linguistik Komputasional Sriwijaya Journal of Informatics and Applications Jurnal Generic JITSI : Jurnal Ilmiah Teknologi Sistem Informasi Jurnal Pengabdian Kolaborasi dan Inovasi IPTEKS Jurnal Pendidikan IPA Indonesia
Novi Yusliani
Department Informatics Engineering, Faculty Of Computer Science, Sriwijaya University
Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Library & Information Science Physics Social Sciences Other

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Penggunaan Media Animasi Untuk Penanaman Pola Berfikir Komputasional Pada Siswa SMA di Palembang Muhammad Fachrurrozi; Novi Yusliani; Osvari Arsalan; Kanda Januar Miraswan; Anna Dwi Marjusalinah
Annual Research Seminar (ARS) Vol 2, No 2 (2016): Special Issue : Penelitian, Pengabdian Masyarakat
Publisher : Annual Research Seminar (ARS)

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Pemikiran komputasional, pertama kali dikemukakan oleh Jeannette Wing dalam penelitiannya, merupakan salah satu kemampuan mendasar yang harus dimiliki oleh setiap orang. Kemampuan ini sama pentingnya dengan kemampuan membaca, menulis dan aritmatika yang harus dimiliki oleh setiap orang [1]. Namun, saat ini teknik yang digunakan untuk mengajarkan materi pemikiran komputasional ini masih menjadi kendala. Riset dilakukan terhadap Siswa-siswa SMA di Palembang dengan memberikan permasalahan komputasional. Siswa diajarkan untuk mencari pemecahannya dengan 2 teknik yaitu dengan penyelesaian menggunakan pemrograman dan dengan menggunakan media animasi. Hasilnya, kecenderungan siswa lebih memilih pemecahan masalah menggunakan media animasi disbanding dengan pemrograman. Selain media animasi dirasakan lebih menarik juga teknik ini lebih mudah untuk disampaikan.
Rancang Bangun Sistem Pengecekan Ambiguitas Kalimat Berbahasa Indonesia Menggunakan Harmony Search Algorithm Tristi Dwi Rizki; Novi Yusliani
Annual Research Seminar (ARS) Vol 2, No 1 (2016)
Publisher : Annual Research Seminar (ARS)

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Masyarakat Indonesia sehari-harinya berkomunikasi dan berinteraksi menggunakan bahasa Indonesia.  Dalam penggunaannya, masih ada bahasa Indonesia yang tidak sesuai dengan kaidah yang berlaku yaitu masih ada kesalahan-kesalahan dalam penggunaannya. Salah satu jenis kesalahan dalam berbahasa dan berkomunikasi ialah karena adanya ambiguitas. Pada penelitian ini diusulkan sebuah rancangan pengecekan ambiguitas kalimat Berbahasa Indonesia menggunakan Harmony Search Algorithm. Harmony Seacrh Algorithm digunakan untuk  menentukan pola pembentuk kalimat. Metode ini menghasilkan sebuah pengecekan kalimat ambigu atau tidak ambigu.
Indonesian-English Machine Translation Using Rule-Based Method Novi Yusliani; Yunita Yunita; Wenty Octaviani
Annual Research Seminar (ARS) Vol 1, No 1 (2015)
Publisher : Annual Research Seminar (ARS)

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Rule-Based Machine Translation (RBMT) used a set of linguistic information to translate source language to target language. POS tagger and Shift-Reduce-Parsing (SRP) could be used to get the linguistic information. POS tagger was used to get word class of each word in sentence and SRP was used to get the function of each word in sentence. SRP was also used to get the structure of sentence. In this research, POS tagger and SRP were used to get the linguistic information of source sentence. Translation process was done by using billingual dictionary. Last, a set of rules was used to generate the target sentence. The accuracy of Indonesian-English machine translation was 100% for the S-P-Adv pattern, but for the S-P pattern and S-P-O pattern is 93,33%.
Sosialisasi dan Pelatihan Computational Thinking untuk Guru TK, SD, dan SMP di Sekolah Alam Indonesia (SAI) Palembang Mastura Diana Marieska; Dian Palupi Rini; Nabila Rizky Oktadini; Novi Yusliani; Yunita Yunita
Annual Research Seminar (ARS) Vol 5, No 2 (2019): Special Issue : Pengabdian Kepada Masyarakat
Publisher : Annual Research Seminar (ARS)

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Computational thinking umumnya hanyadipahami oleh kelompok tertentu, terutama orang yangbekerja di bidang informatika. Padahal computationalthinking merupakan skill yang penting untuk dikuasai padaera digital seperti sekarang ini. Di berbagai negara maju,pelajaran wajib yaitu STEM (Science, Technology,Engineering, and Mathematics) telah diperluas menjadiSTEM-C, yaitu penambahan computational thinking sebagaipelajaran wajib di sekolah. Diperlukan sosialisasi yang luasagar masyarakat Indonesia mengenal dan menyadaripentingnya kemampuan computational thinking. Salah satubentuk sosialisasi yang efektif adalah dengan memberipelatihan pada para guru. Pada tanggal 3 November 2018,telah dilakukan sosialisasi dan pelatihan computationalthinking pada guru TK, SD, dan SMP di Sekolah AlamIndonesia Palembang. Pencapaian dari pelatihan ini adalahpara guru memahami lebih dalam mengenai computationalthinking dan memiliki strategi yang nyata untuk menerapkanpembelajaran computational thinking di kelasnya masing-masing.
Pengoreksian Ejaan Kata Berbahasa Indonesia Menggunakan Algoritma Levensthein Distance Muhammad Omar Braddley; Muhammad Fachrurrozi; Novi Yusliani
Annual Research Seminar (ARS) Vol 3, No 1 (2017): ARS 2017
Publisher : Annual Research Seminar (ARS)

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 Kesalahan penulisan pada dokumen bisa saja terjadi tanpa disengaja, hal ini berpengaruh pada informasi yang didapat oleh pembaca. Sistem pengoreksi ejaan kata secara otomatis mampu mengurangi tingkat kesalahan penulisan. Salah satu metode dalam pengoreksian ejaan kata adalah Approximate String Matching, metode ini menerapkan pendekatan pencarian string. Algoritma Levensthein Distance merupakan salah satu bagian metode Approximate String Matching. Algoritma Levensthein Distance memiliki 3 macam operasi string yaitu penghapusan, penambahan dan pengubahan. Operasi-operasi ini digunakan untuk menghitung jarak antara 2 string, semakin kecil jaraknya maka 2 buah string dikatakan cocok. Pengujian dilakukan dengan 90 data yang terdiri dari 3 skenario yaitu penghapusan, penambahan dan pengubahan karakter. Hasil pengujian akurasi rata-rata sebesar 100% dan waktu 23 mili detik pada operasi penghapusan karakter, hasil 96% dan waktu 5 mili detik pada operasi pengubahan karakter dan hasil 93% dan waktu 88 mili detik pada operasi penambahan.
Rancang Bangun Sistem Peringkasan Teks Multi-Dokumen Gilbert Christopher; Novi Yusliani
Annual Research Seminar (ARS) Vol 2, No 1 (2016)
Publisher : Annual Research Seminar (ARS)

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Seiring dengan bertumbuhnya jumlah dokumen digital yang sangat pesat, membuat pengguna membutuhakan suatu sistem yang dapat melakukan peringkasan teks.  Pada penelitian ini diusulkan sebuah rancangan peringksan teks multi-dokumen berbasis pendekatan clustering dan pemilihan kalimat. Metode yang digunakan proses clustering kalimat adalah Latent Semantic Indexing (LSI) dan Similarity Based Histogram Clustering (SHC). Metode LSI dilakukan untuk menghitung tingkat kemiripan antarpasangan kalimat dan metode SHC digunakan untuk mengelompokkan kalimat-kalimat ke dalam cluster. Sedangkan metode yang digunakan dalam pemilihan kalimat adalah Sentences Information Density (SID). Metode tersebut merupakan metode pemilihan berbasis positional text graph. Kombinasi metode tersebut mampu menghasilkan sebuah peringkasan teks multi-dokumen yang mengandung coverage, diversity dan koherensi yang tinggi.
Questions Classification Software based on Bloom’s Cognitive Levels using Naive Bayes Classifier Method Muhammad Fachrurrozi; Lidya Irfiyani Silaban; Novi Yusliani
IC-ITECHS Vol 1 (2014): Prosiding IC-ITECHS 2014
Publisher : IC-ITECHS

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Questions Classification is one way to know how the student understanding some lessons. Those questions can be collected and classified based on cognitive Bloom level. Bloom Cognitive Level organized question in groups that represents contents of those questions. Words contained in every question have certain meaning and can be used as base to determine category of question. This study aims to classify amounts of questions based on cognitive Bloom level with Naive Bayes Classifier method. According to Bloom's taxonomy of cognitive level divided into six levels of the Knowledge (C1), Comprehension (C2), Application (C3), Analysis (C4), Synthesis (C5), and Evaluation (C6). In this study, questions classified into 3 classes based on cognitive Bloom level, Knowledge (C1), Comprehension (C2), Application (C3). The amount of collective data used for training process is 240 questions. Result of this study generates accuracy of 75 % from 60 question samples tested. Susceptibility often occured because of same vocabularies from each categories, thus cause mistakes in classification.
The Effect of Brill Tagger on The Classification Results of Sentiment Analysis Using Multinomial Naïve Bayes Algorithm Astero Nandito; Abdiansah Abdiansah; Novi Yusliani
Sriwijaya Journal of Informatics and Applications Vol 2, No 1 (2021)
Publisher : Fakultas Ilmu Komputer Universitas Sriwijaya

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Twitter is a good indicator for influence in research, the problem thatarises in research in the field of sentiment analysis is the large numberof factors such as the use of informal or colloquial language and otherfactors that can affect the results of sentiment classification. Toimprove the results of sentiment classification, an informationextraction process can be carried out. One part of the informationextraction feature is a part of speech tagging, which is the giving ofword classes automatically. The results of part of speech tagging areused for weighting words based on part of speech. This studyexamines the effect of Part of Speech Tagging with the method BrillTagger in sentiment analysis using the Naive Bayes Multinomialalgorithm. Testing were carried out on 500 twitter tweet texts andobtained the results of the sentiment classification with implementingpart of speech tagging precision by 73,2%, recall by 63,2%, f-measureby 67,6%, accuracy by 60,7% and without implementing part ofspeech tagging precision by 65,2%, recall by 60,6%, f-measure by62,4% accuracy by 53,3%. From the results of the accuracy obtained,it shows that the application of part of speech tagging in sentimentanalysis using the Multinomial Naïve Bayes algorithm has an effectwith an increase in classification performance.
Spelling Checker using Algorithm Damerau Levenshtein Distance and Cosine Similarity Nur Hamidah; Novi Yusliani; Desty Rodiah
Sriwijaya Journal of Informatics and Applications Vol 1, No 1 (2020)
Publisher : Fakultas Ilmu Komputer Universitas Sriwijaya

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Writing is an embodiment of the author's ideas that are to be conveyed to others. A writer often experiences typos in typing the script, so that it can influence the meaning of the text. Therefore, a system is needed to detect word errors. In this study, checking is done by using the Dictionary Lookup method and giving the candidate words using the Damerau Levenshtein Distance algorithm. Candidates will then determine the ranking by breaking the word into Bigram form and calculating the similarity value using the Cosine Similarity algorithm. The test results based on the data used yield different Mean Reciprocal Rank (MRR) values for each type of error. The type of error deletion produces an MRR value of 88.89%, the type of insertion error produces an MRR value of 97.78%, the type of substitution error produces an MRR value of 88.89%, the type of transposition error produces an MRR value of 89%
Effect of N-Gram on Document Classification on the Naïve Bayes Classifier Algorithm Fitria Khoirunnisa; Novi Yusliani, M.T.; Desty Rodiah, M.T.
Sriwijaya Journal of Informatics and Applications Vol 1, No 1 (2020)
Publisher : Fakultas Ilmu Komputer Universitas Sriwijaya

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News has become a major need for everyone, with news we can get the information needed. News can be distributed in the form of print mass media, electronic mass media and online media. The means of spreading the news now have grown very rapidly, making the amount of information being managed are bigger and word management classified also not small.  herefore, we need a system for classifying documents that are not structured. In this study, word processing in a document is done by N-Gram as a feature generation. The document classification process is carried out using the Naïve Bayes Classifier algorithm. This study examines the effect of N-Gram on document classification on the Naïve Bayes Classifier algorithm. The results of the classification accuracy of documents by applying N-Gram is 32.68% and without applying N-Gram is 84.97%. A decrease in the classification results occurs the number of features that result from solving N-Gram that is unique or dominant to another category. The accuracy of the results obtained shows that the application of N-Gram in the classification of documents using the Naïve Bayes Classifier algorithm gives a decreased effect on the performance of the classification
Co-Authors Abdiansah Abdiansah, Abdiansah Abdiansyah Ahmad Fali Oklilas Aini Nabilah Al Fatih, Zaky Alvi Syahrini Alvi Syahrini Utami Angelia, Nadya Anna Dwi Marjusalinah Annisa Darmawahyuni Ari Firdaus Ari Firdaus Ari Wedhasmara Ari Widodo Ariska, Meli Armansyah, Risky Armenia Yuhafiz Aruda, Syechky Al Qodrin Aspirani Utari Astero Nandito Ayu Purwarianti Az Zahra, Lutfiah Betharia Sri Fitrianti Danny Matthew Saputra Darmawahyuni, Annisa Darmawahyuni, Annisa Deris Stiawan Desty Rodiah Desty Roodiah Dhiya Fairuz Diah Kartika Sari Dian Palupi Rini Dian Palupi Rini Dian Palupi Rini Fadel Muhammad, Fadel Firdaus Firdaus Fitria Khoirunnisa Ghita Athalina Gilbert Christopher Jambak, Muhammad Ihsan Kanda Januar Miraswan Kartika, Diah Lidya Irfiyani Silaban M Fachrurrozi M. Fachrurrozi . Mastura Diana Marieska Melly Ariska Milka, Ikbal Adrian Muhammad Fachrurrozi Muhammad Fachurrozi Muhammad Naufal Rachmatullah Muhammad Omar Braddley Muhammad Raihan Habibullah Muhammad Rizqi Assabil Muharromi Maya Agustin Nur Hamidah Nurul Izzah Oktadini, Nabila Rizky Osvari Arsalan Plakasa, Gerald Rahma Haniffia Rahmannisa, Amanda Rahmat Fadli Isnanto Raisha Fatiya Reyhan Navind Shaquille Ridho Putra Sufa Rifka Widyastuti Rizki Kurniati Rizki Ramadandi Rusdi Efendi Saputra, Danny Mathew Saputra, Danny Matthew Sari, Tri Kurnia septi ana Siti Nurmaini Syechky Al Qodrin syechky al qodrin aruda Tiara Dewangga Tristi Dwi Rizki Wenty Octaviani Winda Kurnia Sari Yenny Anwar Yesi Novaria Kunang YUNITA Yunita Yunita Yunita Yunita Yunita Yunita