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All Journal IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Indonesian Journal on Computing (Indo-JC) JOIN (Jurnal Online Informatika) Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Visualita : Jurnal Online Desain Komunikasi Visual Journal of Data Science and Its Applications BERNAS: Jurnal Pengabdian Kepada Masyarakat eProceedings of Engineering Jurnal INFOTEL
Annisa Aditsania
Universitas Telkom
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mathematics Neuroscience Nursing Public Health Social Sciences Veterinary Other

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Perancangan Signage Lapangan Gasmin Kota Bandung Soedewi, Sri; Murdowo, Djoko; Wulandari, Ratri; Yuniati, Arnanti Primiana; Gunawan, Putu Harry; Aditsania, Annisa; Adrin, Athaya Fatharani; Prabasworo, Bhanu
Visualita Jurnal Online Desain Komunikasi Visual Vol 9 No 1 (2020)
Publisher : Universitas Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (471.194 KB) | DOI: 10.34010/visualita.v9i1.3335

Abstract

The Gasmin Field is a public facility area located in Antapani, Bandung city. This field often uses for general community activities such as sports, gatherings, bazaars, ceremonies, and other activities. The condition of the environment around the Gasmin Field area is not well maintained. The absence of signage makes comfortless and makes it difficult for visitors when they want to find the target area. Therefore, signage and wayfinding designs are needed to make it easier to access locations around the Gasmin Field and increase visitor convenience. Design-based research use as a design method for Environmental Graphic Design (EGD) includes predesign, design, and post-design and data collection. Observations, interviews, and literature studies were carried out to obtain data and analyzed. The results of data analysis used to design signage and wayfinding in the Gasmin Field, Bandung City, West Java.
Implementasi Newton Raphson Termodifikasi pada Prediksi Distribusi Tekanan Pipa Transmisi Gas Alam Annisa Aditsania; Isman Kurniawan
Indonesia Journal on Computing (Indo-JC) Vol. 1 No. 2 (2016): September, 2016
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21108/INDOJC.2016.1.2.53

Abstract

Prediksi profil distribusi tekanan disepanjang jaringan pipa transmisi merupakan salah satu prosedur penting untuk mengevaluasi performa desain jaringan pipa. Pada penelitian ini, distribusi tekanan untuk setiap segmen pipa dimodelkan menggunakan korelasi Panhandle A sebagai fungsi dari properti fluida, properti segmen pipa dan properti lingkungan jaringan pipa. Korelasi Panhandle A secara matematis dapat dipandang sebagai persamaan non-linear. Pada penelitian-penelitian terdahulu, metode Newton Raphson dipilih sebagai metode untuk mendapatkan solusi numerik, karena orde konvergensi tinggi. Sebagai upaya untuk mengoptimalkan waktu komputasi dari perhitungan distribusi jaringan, pada penelitian kali ini, metode Newton Raphson termodifikasi dipilih sebagai metode pencarian solusi numerik. Hasil simulasi menunjukan bahwa profile distribusi tekanan menggunakan metode newton Raphson termodifikasi akurat dengan error relative maksimum 0.28% untuk batas toleransi error  bila dibandingkan dengan profile distribusi tekanan data lapangan 
Pemodelan Dan Simulasi Produksi Biogas Dari Substrat Glukosa Menggunakan Anaerobic Digestion Model No. 1 (ADM1) Isman Kurniawan; Annisa Aditsania
Indonesia Journal on Computing (Indo-JC) Vol. 1 No. 1 (2016): March, 2016
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21108/INDOJC.2016.1.1.54

Abstract

This research focus in modeling of biogas production using Anaerobic Digestion Model No. 1 (ADM1). Initial simulation was performed using recommended parameter and its result will be used to determine the accuracy. Simulation result shows similar trend compare to experimental data even it is less accurate. The accuracy of calculation is improved by optimize the simulation parameter. The number of parameter is reduced by calculate the sensivity indices of each parameter. Optimization process using genetic algorithm result new optimized parameter value. The value of mean average percentage error (MAPE) of simulation using standard parameter and optimized parameter are 22,54% and 0,08%, respectively. It shows that simulation using optimized parameter give better accuracy. Simulation results shows the glucose concentration decrease significantly in the beginning of process and methane concentration increase simultaneously. The final concentration of methan after 500 mgCOD/L of glucose decomposed is 354,79 mgCOD/L.
Deteksi Kanker berdasarkan Klasifikasi Data Microarray menggunakan Functional Link Neural Network dengan Seleksi Fitur Genetic Algorithm Putri Tsatsabila Ramadhani; Untari Novia Wisesty; Annisa Aditsania
Indonesia Journal on Computing (Indo-JC) Vol. 2 No. 2 (2017): September, 2017
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21108/INDOJC.2017.2.2.173

Abstract

Di beberapa tahun terakhir, pemanfaatan teknologi microarray memiliki pengaruh besar dalam menentukan gen informatif yang menyebabkan kanker. Micorarray mampu menentukan ekspresi ribuan gen dan secara simultan memantau proses bilogis yang sedang berlangsung. Dengan melakukan analisa terhadap data micorarray, selanjutnya ekspresi dari ribuan gen yang merepresentasikan suatu jaringan pada manusia, akan diklasifikasikan sebagai jaringan kanker atau bukan. Dalam penulisan penelitian penelitian, penulis meng-implementasikan Functional Link Neural Network dengan fungsi basis Legendre Polynomial untuk klasifikasi data yang akurat dan menggunakan Genetic Algorithm sebagai seleksi fitur untuk mereduksi data berdimensi tinggi yang sering ditemukan pada data microarray. Dengan serangkaian proses yang telah dilakukan, maka diperoleh kinerja tertinggi terhadap klasifikasi data microarray Colon Tumor sebesar 92.3% dan Leukemia sebesar 87.5%. Perbedaan kinerja yang diperoleh disebabkan oleh perbedaan karakteristik masing-masing data.
Penentuan Prioritas Perbaikan Jalan dengan Menggunakan Metode Analytic Hierarchy Process (AHP) dan COPRAS-G di Kota Tangerang Rifaldi Rizqi Pratama; Mahmud Imrona; Annisa Aditsania
Indonesia Journal on Computing (Indo-JC) Vol. 3 No. 1 (2018): Maret, 2018
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21108/INDOJC.2018.3.1.219

Abstract

Seiring dengan bertambahnya usia, jalan pasti mengalami kerusakan. Sebagian jalan yang telah dibangun kurang mendapat perawatan dan perbaikan. Perbaikan yang dilakukan biasanya kurang tepat sasaran. Salah satu masalahnya yaitu anggaran yang dialokasikan kurang memenuhi kebutuhan. Untuk mengatasi masalah perbaikan jalan, dibutuhkan sistem yang menentukan urutan prioritas jalan mana yang diperbaiki terlebih dahulu, sehingga mengoptimalkan anggaran yang terbatas. Untuk menentukan urutan prioritas perbaikan jalan tersebut, metode yang digunakan adalah Analytic Hierarchy Process (AHP) dan COPRAS-G. Dari hasil penelitian diperoleh bobot kepentingan setiap kriteria, yaitu pertama adalah Tataguna Lahan dengan bobot 0,51, kedua Klasifikasi Jalan dengan bobot 0,26, ketiga adalah Kondisi Kerusakan Jalan dengan bobot 0,12, keempat adalah Volume Kendaraan dengan bobot 0,06 dan terakhir adalah Kecepatan Kendaraan dengan bobot 0,03, dengan nilai CR 0,03 menunjukan bahwa penilaian bobot kepentingan antar kriteria tersebut bersifat konsisten. Jadi, urutan prioritas ruas jalan yang diperoleh yaitu, pertama kode ruas jalan J53 adalah Jalan Manis 2 KM 1 dengan tingkat kepentingan Ni sebesar 100%, kedua yaitu kode ruas jalan J55 adalah Jalan Kasir 2 KM 1 dengan tingakat kepentingan Ni sebesar 90,96% dan ketiga yaitu pada kode ruas jalan J67-5 adalah Jalan Imam Bonjol KM 5 dengan tingakat kepentingan Ni sebesar 86,5% dan seterusnya.
Rayleigh Ritz Cubic Spline method for Displacement Simulation Sucker Rod Lazuardy Azhari Bacharuddin Noor; Annisa Aditsania; Putu Harry Gunawan
Indonesia Journal on Computing (Indo-JC) Vol. 4 No. 3 (2019): December, 2019
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34818/INDOJC.2019.4.3.350

Abstract

Artificial Lift adalah salah satu mekanisme pengangkatan buatan minyak bumi. Mekanisme ini digunakan bila minyak sudah tidak dapat mengalir akibat menurunnya tekanan pada lubang sumur. Sucker beam rod pump adalah salah satu jenis pengangkatan buatan. Penelitian bertujuan menganalisis desain sistem pemompaan berdasarkan renggangan atau displacement dari sucker rod. Sucker rod adalah salah satu komponen dari sistem sucker rod beam pump yang terletak dalam sumur penambangan. Batang ini berfungsi sebagai tempat bergantungnya muatan minyak. Displacement atau renggangan dimodelkan sebagai persamaan gelombang. Perhitungan numerik dilakukan untuk  menentukan solusi persamaan displacement sucker rod. Solusi dari persamaan displacement ini pada tahap berikutnya dapat digunakan sebagai informasi tambahan bagi operator sucker rod beam pump untuk mengetahui kondisi dari sucker rod di sumur. Pada penelitian ini metode Rayleigh Ritz digunakan untuk menentukansolusi numeerik persamaan tersebut. Solusi yang didapat dari perhitungan numerik ini adalahmatriks yang menunjukan perenggangan terhadap segmen sucker rod dan waktu. Hasil yangdidapat memiliki galat 1:43 10????13.
Polish Rod Displacement Simulation on Sucker Rod Pump Using the Piecewise-Linear Basis Method I Gde Made Bagus Nurseta Wijaya; Annisa Aditsania; Putu Harry Gunawan
Indonesia Journal on Computing (Indo-JC) Vol. 5 No. 1 (2020): Maret, 2020
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34818/INDOJC.2020.5.1.352

Abstract

Sucker Rod Pump (SRP) is a heavy equipment used to pump oil(fluid) from the ground. The purpose of this study is to determine the numerical solution of displacement problems on the polish rod in the sucker rod pump. From previous studies displacement can be simulated and calculated numerical solutions using the Finite Difference method. But in this study the method that will be used is the Piecewise-Linear Base method to simulate displacement on the polish rod and compared to the analytic simulation of the problem. From the simulation results both methods obtained an error rate 2.00911 x 10−17 at ∆x = 0.2, 3.30195 x 10−17 at ∆x = 0.05 and 1.45114 x 10−16 at ∆x = 0.02.
Cancer Detection based on Microarray Data Classification Using Principal Component Analysis and Functional Link Neural Network Iyon Priyono; Adiwijaya Adiwijaya; Annisa Aditsania
Journal of Data Science and Its Applications Vol 3 No 2 (2020): Journal of Data Science and Its Applications
Publisher : Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34818/jdsa.2020.3.52

Abstract

Cancer is a deadly disease caused by abnormal growth of tissue cells that are not controlled in the body. In 2018, according to Globocan data, the number of cancer sufferers has increased from the previous years which was 18.1 million people, with a mortality rate of 9.6 million. In recent years, cancer prediction using DNA microarrays data can help medical experts in analyzing whether a person has cancer or not. DNA microarray data have very large and complex gene expression, therefore a dimensional reduction method is needed. Then, the dimension reduction results will be used for classification into types of cancer or not. In this paper, Principal Component Analysis (PCA) is used as a feature extraction to reduce dimension and Functional Link Neural Network as a classifier. Based on the simulation, the average of accuracy using the FLNN and PCA about 76.08%. Keywords: cancer detection, Microarray data, Functional Link Neural Network, Principal Component Analysis.
QSAR Study on Aromatic Disulfide Compounds as SARS-CoV Mpro Inhibitor Using Genetic Algorithm-Support Vector Machine Rizki Amanullah Hakim; Annisa Aditsania; Isman Kurniawan
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 7, No. 2, May 2022
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v7i2.1428

Abstract

COVID-19 is a type of pneumonia caused by the Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2). This virus causes severe acute respiratory syndrome and 2 million active cases of COVID-19 have been found worldwide. A new strain of the SARS-CoV-2 virus emerged that proved to be more virulent than its predecessor. Regarding the design of a new inhibitor for this strain, SARS-CoV Main Protease (Mpro) was used as the target inhibitor. In the in silico development, the Quantitative Structure-Activity Relationship (QSAR) method is commonly used to predict the biological activity of unknown compounds to improve the process of drug design of a disease, including COVID-19. In this study, we aim to develop a QSAR model to predict the activity of aromatic disulfide compounds as SARS-CoV Mpro inhibitors using Genetic Algorithm (GA) – Support Vector Machine (SVM). GA was used for feature selection, while SVM was used for model prediction. The used dataset is set of features of aromatic disulfide compounds, along with information on the toxicity activity. We found that the best SVM model was obtained through the implementation of the polynomial kernel with the value of R2­­train and R2test­ scores are 0.952 and 0.676, respectively.
Implementation of BERT, IndoBERT, and CNN-LSTM in Classifying Public Opinion about COVID-19 Vaccine in Indonesia Siti Saadah; Kaenova Mahendra Auditama; Ananda Affan Fattahila; Fendi Irfan Amorokhman; Annisa Aditsania; Aniq Atiqi Rohmawati
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 6 No 4 (2022): Agustus 2022
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (557.978 KB) | DOI: 10.29207/resti.v6i4.4215

Abstract

COVID-19 was classified as a pandemic in March 2020, and then in July 2021, this virus had its variance that spreads all over the world including Indonesia. The probability of the detrimental of its effect cannot be avoided, because this virus has a huge transmission risk during daily activity. To prevent suffering from COVID-19, people certainly need to be vaccinated. In responding to its vaccine, the citizen of Indonesia become expressive, so they try to express opinions, for example by uploading text on Twitter. Those expressions can be learned using deep learning frameworks which are BERT, CNN-LSTM, and IndoBERTweet to get knowledge about negative speech categories such as anxiety, panic, and emotion, or positive speech such as vaccines whether worked well. By then, these three methods accomplish in carrying out the prediction of sentiments about vaccination using dataset tweets on Twitter from January-2021 to March-2022, for instance using IndoBERT succeeds to classify sentiments as positive sentiment at around 80%, and then IndoBERTweet at 68%, in addition using CNN-LSTM reach 53% with the total of using 2020 dataset from Twitter. According to these results, a lesson learned for continued improvement for Indonesia's Government or authorities can be acquired in ending the COVID-19 pandemic.
Co-Authors A Rakha Ahmad Taufiq Aditya Iftikar Riaddy Adiwijaya Adrin, Athaya Fatharani Aisyah Aisyah Aldi Riyadi Ramadhan Amalya Citra Pradana Ananda Affan Fattahila Andhika Rama Putra ANDI FUTRI HAFSAH MUNZIR Andrianawati, Aida Aniq Atiqi R Aniq Atiqi Rohmawati Arfian Nurdiansyah Arnanti Primiana Yuniati Choiryaldi Setya Pratama Danang Triantoro Murdiansyah Danu Ardiyanto Deni Saepudin Djoko Murdowo EKA ANDHIKA KURNIAWAN Erlangga, Samuel Erwin Budi Setiawan Fadhlika Hadi Faturachman Nugraha Sasmita Fendi Irfan Amorokhman Fhira Nhita I Gde Made Bagus Nurseta Wijaya Idhar Resmadi Indwiarti Isman Kurniawan Iyon Priyono Jondri Jondri Kaenova Mahendra Auditama Kaisa Sekaring Pertiwi Kamil, Nabilla Lazuardy Azhari Bacharuddin Noor M Ikhsan Perdana Putra Maharani Padma Utami Mahmud Imrona Mela Mai Anggraini Monica Triyani Muhamad Paisal Hanip Muhammad Arief Priambodo Muhammad Fikrie Abdillah Muhammad Wildan Putra Aldi Nabilla Kamil Nuklianggraita, Tita Nurul Oki Virgiawan Pramudita Oscar Ramadhan P. H. GUNAWAN Prabasworo, Bhanu Putri Tsatsabila Ramadhani Putu Harry Gunawan Ratri Wulandari Redi Nurjamin Rendy Pandita B Rian Febrian Umbara Rian Putra Mantovani Rifaldi Rizqi Pratama Rizki Amanullah Hakim Roizal Manullang Siti Saadah Sri Soedewi Theo Andrew Theresya Margharetha Panjaitan Tita Nurul Nuklianggraita Triyani, Monica Ulky Parulian Wibowo UMMU SALAMAH Untari Novia Wisesty Vika Haristianti Wibisono Tegar GP Yuliant Sibaroni