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All Journal International Journal of Electrical and Computer Engineering Proceedings of KNASTIK TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Indonesian Journal on Computing (Indo-JC) JIKO (Jurnal Informatika dan Komputer) MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Aiti: Jurnal Teknologi Informasi Idealis : Indonesia Journal Information System J-SAKTI (Jurnal Sains Komputer dan Informatika) International Journal Software Engineering and Computer Science (IJSECS) Algoritme Jurnal Mahasiswa Teknik Informatika Jurnal Nasional Teknik Elektro dan Teknologi Informasi IT-Explore: Jurnal Penerapan Teknologi Informasi dan Komunikasi Innovative: Journal Of Social Science Research Jurnal Ilmu Komputer dan Sistem Informasi Jurnal Indonesia : Manajemen Informatika dan Komunikasi Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) The Indonesian Journal of Computer Science Limits: Journal of Mathematics and Its Applications
Alz Danny Wowor
Universitas Kristen Satya Wacana
Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Public Health Other

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Implementasi Algoritma Long Short-Term Memory dalam Prediksi Konsentrasi Gas Metana (CH4) di Kota Salatiga Putri, Febyola Kurnia Tiara; Wowor, Alz Danny
Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 8 No 2 (2024): APRIL-JUNE 2024
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jtik.v8i2.1917

Abstract

Implementation of the Long Short Term Memory (LSTM) algorithm is done to build a prediction model that can handle complex time series data. Model development uses training and testing data and combines multiple time series to improve prediction accuracy. Model testing is done by measuring the root mean square error (RMSE) value as a performance indicator. The test results show that the application of the LSTM algorithm to the (CH4) sensor provides an optimal RMSE value, namely with a value for training data of 20% (0.09) and test data of 80% (0.14), indicating the prediction accuracy of methane gas (CH4) concentration is potentially unexploded, the results obtained have important implications for safety monitoring. This test contributes to the development of predictive methods to monitor and manage potential risks associated with (CH4) concentrations. The application of LSTM to (CH4) sensors not only improves prediction accuracy but also opens up opportunities for the development of safety systems that can more effectively predict and prevent potentially harmful phenomena due to methane gas.
Chaos CSPRNG Design As a Key in Symmetric Cryptography Using Logarithmic Functions Nathanael, Hizkia; Wowor, Alz Danny
Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika Vol 21, No 1 (2024): Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika
Publisher : Ilmu Komputer, FMIPA, Universitas Pakuan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33751/komputasi.v21i1.9265

Abstract

 This research uses the logarithm function as a key component in generating random numbers in the Chaos CSPRNG framework. The main problem addressed here is the generation of keys for cryptography, recognizing the important role of cryptographic keys in safeguarding sensitive information. By using mathematical functions, specifically logarithmic functions, as a key generation method, this research explores the potential for increasing the uncertainty and strength of cryptographic keys.The proposed approach involves the systematic utilization of various mathematical functions to generate diverse and unpredictable data sets. This data set, derived from the application of logarithmic functions, serves as the basis for generating random numbers. Through a series of tests such as Randomness Test and Cryptography Test, this research shows that the data generated from these functions can be utilized effectively as a reliable source for generating random numbers, and has a low correlation value, thereby contributing to the overall security of a symmetric cryptographic system.
Identifikasi Pengaruh Kualitas Udara Terhadap Pasien Covid-19 dengan Algoritma Naïve Bayes, K-NN dan SVM (Kasus Kota Jakarta dan Singapura) Pakpahan, Andrian Roland Kenedy; Wowor, Alz Dany
Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Vol 6, No 1 (2025): Edisi Januari
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/kesatria.v6i1.540

Abstract

The COVID-19 pandemic has emerged as a significant global outbreak, seriously impacting public health. This study examines the influence of air quality on COVID-19 patients in Singapore and Jakarta, utilizing Naive Bayes, Support Vector Machine (SVM), and K-Nearest Neighbor (K-NN) algorithms for data analysis. The findings indicate that better air quality in Singapore contributes to a reduction in disease severity, with 100% accuracy in predicting positive cases and hospitalizations using the SVM algorithm. Additionally, Naive Bayes successfully predicted 100% of mortality cases at a 90/10 ratio, demonstrating that even with relatively good air quality, its impact on patient severity remains significant. Conversely, in Jakarta, where air quality is poorer, there is variability in accuracy results. The K-NN algorithm achieved 100% accuracy for positive cases and isolation, while the SVM only reached 46.15% accuracy for positive case predictions. These findings underscore the significant influence of air quality on the severity and mortality of COVID-19 patients. In countries with better air quality, the impact on severity appears more manageable, whereas in those with poorer air quality, patient severity tends to be higher. This research aims to encourage the Indonesian public to pay closer attention to air quality for public health
Optimalisasi Database Mysql Pada Sistem Perancangan Sistem Housekeeping Transaction History Dengan Pentaho Data Integration Simanjuntak, Yohanes Albryan; Wowor, Alz Danny
Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Vol 6, No 1 (2025): Edisi Januari
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/kesatria.v6i1.542

Abstract

The volume of transaction data in the banking industry is growing with the increase in customers and transaction complexity. Ineffi-cient data management can lead to server overload, affect system performance, and hinder the delivery of fast, accurate services. Housekeeping processes are needed to move inactive data to sepa-rate storage, allowing the main server to function more efficiently. Pentaho Data Integration (PDI) offers an effective solution for man-aging the ETL (Extract, Transform, Load) process, which is crucial for data housekeeping. This research aims to optimize the manage-ment of banking transaction data using PDI to reduce server load and improve operational efficiency. This quantitative study applies an experimental method, with the ETL process managing Bank XYZ’s transaction data older than six months. The study uses trans-action data from Bank XYZ’s MySQL server, which will be trans-ferred to a data warehouse. The analysis applies clustering algo-rithms to filter and separate active from inactive transactions. The implementation of PDI for housekeeping effectively reduces server load and improves data management efficiency, significantly lower-ing processing time. The combined use of clustering algorithms and PDI delivers substantial improvements in managing banking transac-tion data, enhancing operational efficiency while significantly re-ducing the load on the main server
Perancangan Distribusi Hasil Produk Textil dengan Rute Terdekat dengan Algoritma Greedy Wibowo, Alvin Cahyo; Wowor, Alz Danny
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 7, No 1 (2023): EDISI MARET
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v7i1.592

Abstract

Delivery is one of the keys to a business because if there is no delivery, the work or flow of a business will be disrupted. The textile industry is one of many industries that really need delivery services with the closest route in order to save time. Greedy algorithm is an algorithm that is heuristic and its logical sequence is arranged based on problem solving steps that are arranged systematically. This study aims to design the distribution of textile products with the closest route using the Greedy Algorithm with a case study of CV. Karya Cahaya Lestari with the benefit of speeding up delivery times and helping drivers to save travel time. The final result of designing the distribution of textile products is in the form of a graph, specifically the Directed Graph, a map like the one in the picture basically only shows interconnected points, with a certain distance at each point..
Identifikasi Nilai Keacakan Berdasarkan Reposisi Fungsi XOR Pada Blok Kedua LFSR A5/1 Pallangan, Jorghie Theodore Kenzo; Wowor, Alz Danny
Journal of Information System Research (JOSH) Vol 6 No 1 (2024): Oktober 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v6i1.6112

Abstract

This research plans a random number generation method using the Linear Feedback Shift Register (LFSR) method with the A5/1 scheme which involves three feedback functions. XOR is used to determine the new output bit value in the next iteration in the feedback mechanism. The test material produces random output for an input using Run Test, Mono Bit, and Block bit. Tests using three feedback functions were carried out to compare with previous research which generated random numbers. Testing of plaintext and ciphertext encryption shows a very small level of correlation with an average value close to 0. The use of LFSR with the A5/1 scheme which involves three XOR functions, creates random output and can be used against Stream Chipers.
Analisis Sentimen Terhadap Kualitas Perbandingan Satelit Starlink dan Telkom Menggunakan Pendekatan Machine Learning Aneria, Gianina Dea; Wowor, Alz Danny
Innovative: Journal Of Social Science Research Vol. 5 No. 4 (2025): Innovative: Journal Of Social Science Research
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/innovative.v5i4.21085

Abstract

The development of satellite communication technology has created opportunities for high-speed internet services across various regions, including remote areas. Starlink, which operates using low Earth orbit (LEO) satellites, and Telkom, which utilizes geostationary (GEO) satellites alongside terrestrial infrastructure, are two major providers in Indonesia. This study examines sentiment analysis of the service quality of Starlink and Telkom using a machine learning approach. Data were collected from the X (Twitter) platform and processed through cleaning, case folding, tokenization, slang word normalization, stopword removal, and stemming. Three classification algorithms were employed: Naïve Bayes, Decision Tree, and Random Forest. The results show that Decision Tree achieved the highest accuracy of 100%, followed by Random Forest at 96% and Naïve Bayes at 80%. Sentiment analysis revealed that Starlink was favored for its speed and connection stability, whereas Telkom was more appreciated for its affordability and service coverage. These findings provide an objective overview of user perceptions that can be utilized to improve service quality and strategic planning.
Air Quality and COVID-19 Patient Conditions in Jakarta: A Comparative Analysis of Classification Algorithms Wowor, Alz Danny; Jesajas, Marthen Billy; Dimara, Indri; Salama, Aditya; Pakereng, Magdalena Ariance Ineke
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol. 11 No. 3 (2025): September
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v11i3.30826

Abstract

The COVID-19 pandemic has become a global challenge, with environmental factors such as air quality contributing to disease severity. This study analyzes the relationship between air pollution parameters (PM2.5, PM10, NO2, SO2, CO, and O3) and COVID-19 patient conditions in Jakarta, categorized into three groups: positive, recovered, and deceased. A comparative evaluation was conducted using five classification algorithms: Na¨ıve Bayes, Random Forest, k-Nearest Neighbors (kNN), Decision Tree, and Support Vector Machine (SVM). The results show that kNN achieved the highest accuracy of 80.71%, while Na¨ıve Bayes obtained the highest recall of 91.83% and a precision of 80.75%. This study contributes by evaluating the effectiveness of classification techniques in mapping the impact of air quality on patient conditions and by identifying the most accurate predictive model. The findings suggest that classification methods can serve as reliable predictive tools to assess the health impacts of air pollution on the population.
The Implementation of f(x) = 3(x 3 − x 2 − x) + 2 as CSPRNG Chaos-Based Random Number Generator Yopeng, Maria Rosalina; Wowor, Alz Danny
Indonesian Journal on Computing (Indo-JC) Vol. 6 No. 1 (2021): April, 2021
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34818/INDOJC.2021.6.1.546

Abstract

This research implemented the cubic function f(x) = 3(x^3 − x^2 − x) + 2 using a FixedPoint Iteration to produce several iteration functions that can be used as random number generator. The test results obtain six iteration functions, and based on graphic visualizationwith Scatter plot and randomness test with mono bit test, bit block, and run test, the results only obtain two iteration functions namely x2 − 1 + 2/(3x) and f(x) = 1 + 1/x − 2/(3x^2)which can produce CSPRNG Chaos-based random number. Encryption testing shows that both functions can generate keys that make plaintext and ciphertext statistically unrelated, so the f(x) = 1 + 1/x − 2/(3x^2) function can be used as a CSPNRG chaos-based random number generator function.
Sistem Pakar Indikasi Penyakit Berasal Dari Virus Menggunakan Forward Chaining Juanito, Yunias; Wowor, Alz Danny
Innovative: Journal Of Social Science Research Vol. 5 No. 3 (2025): Innovative: Journal Of Social Science Research
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/innovative.v5i3.19936

Abstract

Peningkatan kasus penyakit atau kematian yang signifikan dan berpotensi menjadi wabah disebut sebagai Kejadian Luar Biasa (KLB). KLB tidak hanya disebabkan oleh penyakit menular, tetapi juga penyakit tidak menular dan keracunan. Keterbatasan informasi mengenai penyakit virus yang dapat memicu KLB menjadi kendala dalam pencegahan. Oleh karena itu, deteksi dini sangat penting untuk memberikan informasi kepada masyarakat agar tindakan pengobatan dan pencegahan dapat dilakukan sedini mungkin. Sistem pakar, yang merupakan program dengan basis pengetahuan dan sistem inferensi menawarkan solusi untuk deteksi dini penyakit virus. Sistem ini menggunakan metode Forward Chaining untuk menarik kesimpulan. Sistem pakar yang dihasilkan mampu mendeteksi tujuh jenis penyakit virus, menyajikan informasi berupa penyakit, nilai kepercayaan atau persentase, dan nilai kepercayaan gejala terhadap penyakit yang lain
Co-Authors A.A. Ketut Agung Cahyawan W Andeka Rocky Tanaamah Aneria, Gianina Dea Ardika, Zefanya Aryatama, Andrew Ananta Bambang Susanto Claudio Canavaro Danie Abdillah Iskandar David Lihananto Dimara, Indri Erwien Christianto Fajar Legianto Asmin Febriyanti, Monica Dias Felix David Geizka Wasito Adi Dwi Hussein Nurrokhim Jehzkiel Rangga Sere Jesajas, Marthen Billy Juanito, Yunias Kadek Widiana Kaho, Monica Louisa Ratu Kuniarti Paraditasari Kuniarti Paraditasari Liwandouw, Vania Beatrice Magdalena A. Ineke Pekereng Magdalena Ariance Ineke Pakereng Maria Rosalina Yopeng Marthen Billy Jesajas Nathanael, Hizkia Ondihon Parlinggoman Munthe Pakpahan, Andrian Roland Kenedy Pallangan, Jorghie Theodore Kenzo Pambudi, Rizky Satya Putra, Gidion Albeth Anoraga Putri, Febyola Kurnia Tiara Ramadhani, Ahmad Sakalaty, Alfa Krisnanugrah Salama, Aditya Simanjuntak, Yohanes Albryan Susilo Wibowo, Ayub Teguh Septianto Nahading Theis Huyo Rooney Bakar Vania Beatrice Liwandouw Vania Beatrice Liwandouw Vincent Exelcio Susanto Wibowo, Alvin Cahyo Yopeng, Maria Rosalina Yos Richard Beeh