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All Journal Jurnal Transformatika Register: Jurnal Ilmiah Teknologi Sistem Informasi Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal Pengembangan Rekayasa dan Teknologi JATI (Jurnal Mahasiswa Teknik Informatika) Jurnal Tekinkom (Teknik Informasi dan Komputer) JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Computer Science and Information Technologies Aiti: Jurnal Teknologi Informasi JUSTIN (Jurnal Sistem dan Teknologi Informasi) SEMINAR NASIONAL PENELITIAN DAN PENGABDIAN KEPADA MASYARAKAT Tematik International Journal of Artificial Intelligence and Science Jurnal DIMASTIK
Lenny Margaretta Huizen
Universitas Semarang
Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Energy Engineering Law, Crime, Criminology & Criminal Justice Mechanical Engineering Nursing Social Sciences Transportation

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Optimizing costs for vaccine control using the reorder point approach Huizen, Lenny Margaretta; Handayani, Titis; Cholil, Saifur Rohman; Faradilah, Yanti
Register: Jurnal Ilmiah Teknologi Sistem Informasi Vol 7, No 1 (2021): January
Publisher : Information Systems - Universitas Pesantren Tinggi Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26594/register.v7i1.2099

Abstract

Vaccines are biological products that have an important role in human immunity. In Indonesia, some vaccines are categorized as compulsory vaccines and additional vaccines. The demand for additional vaccines is less predictable because they are not mandatory for use. This of course makes the amount of demand for vaccines less predictable. Also, the price of additional vaccines is not cheap when compared to the price of mandatory vaccines. So that the management of vaccines in the pharmacy warehouse is needed so that the amount of supply and demand is balanced so that the costs incurred will be more optimal. The information system regarding vaccine reordering is carried out using a reorder point so that the pharmacy warehouse can order according to the right need and at the right time.  The data used are demand data, prices, storage costs, and message costs. The results of calculations using reorder points within four months with a total purchase for the Rotavirus vaccine was 62 for IDR 28,274,948 and 70 for the hospital of IDR 31,801,500 with a difference of IDR 3,528,552. The calculation result using the reorder point for the Hexaxim vaccine with a total purchase for 4 months was 61 with a nominal value of IDR 58,380,060 while the calculation in the hospital was 67 with a nominal value of IDR 63,971,000 so that a nominal difference of IDR 5,590,940 was obtained.  Use of the return point can be used to alarm when and how many vaccines to order. This can be seen from the cost difference between the pharmacy warehouse and the calculation using the reorder point for the Hexaxim vaccine and the Rotavirus vaccine.
Pendekatan Model Predictive Control untuk Optimalisasi Biaya Penyediaan Vaksin dengan Reorder Point Huizen, Lenny Margaretta; Handayani, Titis; Prathivi, Rastri
JUSTIN (Jurnal Sistem dan Teknologi Informasi) Vol 9, No 4 (2021)
Publisher : Jurusan Informatika Universitas Tanjungpura

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (321.029 KB) | DOI: 10.26418/justin.v9i4.44888

Abstract

Pengendalian persediaan sangat penting bagi penyedia barang, tujuannya adalah agar terjadi keseimbangan antara persediaan dan permintaan. Pengelolaan persediaan pada rumah sakit sangat penting untuk diperhatikan agar kebutuhan kesehatan tetap terpenuhi. Salah satu kebutuhan yang harus terpenuhi adalah vaksin. Pengelolaan persediaan vaksin yang benar diperlukan agar terhindar dari kekurangan stok yang dapat menyebabkan aktifitas pelayanan menjadi terganggu dan sebaliknya jika suatu persediaan terlalu banyak dapat terjadi kelebihan biaya seperti biaya pembelian, penyimpanan serta pemeliharaan. Model Predictive Control dapat digunakan untuk menganalisa pengendalian stok berdasarkan biaya yang optimal karena Model Predictive Control merupakan sistem kendali dengan menggunakan hasil perhitungan prediksi dalam mengeluarkan kontrol input. Untuk mencari biaya yang minimal yaitu berdasarkan tingkat persediaan vaksin serta biaya vaksin sehingga dapat menjamin ketersediaan vaksin. Hasil yang didapat adalah biaya yang dikeluarkan untuk penyediaan vaksin dengan menggunakan pendekatan MPC sebesar Rp 61.886.332 berdasarkan jumlah pembelian vaksin 61 ampul lebih sedikit dibandingkan dengan rumah sakit sebesar Rp 64.007.000 atau sebesar pembelian 67 ampul. Hal ini tentu saja dapat mengurangi biaya untuk pengadaan vaksin. 
Komparasi Metode ELECTRE, SMART dan ARAS Dalam Penentuan Prioritas RENAKSI Pasca Bencana Alam Agusta Praba Ristadi Pinem; Titis Handayani; Lenny Margaretta Huizen
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 4 No 1 (2020): Februari 2020
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (837.141 KB) | DOI: 10.29207/resti.v4i1.1526

Abstract

Each organization must collect data as a result of the use of information technology. Over time the data is processed into information. The information collected is used as a basis for decision making. But not all information can be directly used for the decision making process. Necessary methods and weighting in the process of getting information. One model in a decision support system is Multi Criteria Decision Making (MCDM). The MCDM model makes it possible to provide the best choice of information from several choices of the many criteria and alternatives used. This study compares the MCDM model, namely the ELECTRE (Elimination Et Choix Traduisant la Realite) method, SMART (Simple Multi-Attribute Rating Technique), ARAS (Additive Ratio Assessment) as a priority determination for the handling of areas affected by natural disasters which must be addressed first in the RENAKSI (Reconstruction and Rehabilitation Action Planning), in this case earthquake natural disasters. The ELECTRE method has a different algorithmic process than SMART and ARAS. The validation test method ELECTRE, SMART and ARAS against dataset occurrence of the earthquake is become the results of this research. Spearman rank correlation values ​​for the three methods amounted to 0.96. And another correlation method value of 0.85 for the ARAS method and 0.82 for the ELECTRE and SMART methods.
Implementasi Pemilihan Fitur Metode Wrapper dan Embedded dalam Prediksi Ketepatan Kelulusan Mahasiswa Aria Hendrawan; Lenny Margaretta Huizen; Agusta Praba Ristadi Pinem; Dinar Anggit Wicaksana
Seminar Nasional Penelitian dan Pengabdian Kepada Masyarakat 2021: Prosiding Seminar Nasional Penelitian dan Pengabdian Kepada Masyarakat (SNPPKM 2021)
Publisher : Universitas Harapan Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (272.981 KB)

Abstract

Era Big Data saat ini, kumpulan data memiliki struktur yang sangat beragam serta dimensi yang tinggi. Dimensi tinggi ini memiliki independen atribut, dependen atribut, data yang tidak relevan dan tidak berguna yang menjadi sumber masalah dalam mendapatkan akurasi yang terbaik di proses penerapan metode klasifikasi prediksi. Pemilihan fitur pada setiap kasus klasifikasi prediksi sangat penting untuk dilakukan karena merupakan komponen dalam pembelajaran mesin dan alur kerja penelitian. Dalam penelitian ini, pemilihan fitur atribut data menggunakan metode wrapper dan embedded yang dilakukan pada dataset mahasiswa yang telah menyelesaikan sarjana di perguruan tinggi sebanyak 146 data yang memiliki 13 atribut data dan 1 label. Metode pemilihan fitur ini dilakukan untuk mendapatkan atribut data yang sesuai yang nantinya digunakan dalam proses klasifikasi prediksi mahasiswa yang telah lulus tepat waktu atau tidak. Hasil penelitian menunjukkan dengan menggunakan algoritma Random Forest Classification, nilai akurasinya sebesar 73% dan terjadi peningkatan akurasi setelah menggunakan metode pemilihan fitur wrapper dan embedded sebesar 100%.
Analisis Faktor yang Mempengaruhi Lama Studi Mahasiswa dengan Metode SMARTER Lenny Margaretta Huizen; Aria Hendrawan; Agusta Praba Ristiadi Pinem
AITI Vol 19 No 2 (2022)
Publisher : Fakultas Teknologi Informasi Universitas Kristen Satya Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24246/aiti.v19i2.213-227

Abstract

Salah satu kriteria dalam penilaian akreditasi perguruan tinggi adalah kelulusan mahasiswa tepat waktu. Faktor yang mempengaruhi lama studi mahasiswa perlu dianalisis. Dalam penelitian ini metode SMARTER digunakan untuk menemukan faktor-faktor tersebut. Data diperoleh dari kuesioner dengan 133 responden. Uji validitas dan reliabilitas dilakukan untuk mengetahui kevalidan alat uji. Pengujian dilakukan dengan uji signifikansi 0,05 untuk uji validitas dan uji reliabilitas sebesar 0,811 yang berarti reliabilitasnya sangat tinggi. Data diolah dengan metode SMARTER. Metode SMARTER merupakan metode penyelesaian dimana bobot dihitung menggunakan perhitungan pembobotan Rank Order Centroid (ROC) pada setiap kriteria dan sub kriteria. Data real menunjukkan bahwa faktor dosen merupakan faktor utama yang mempengaruhi lama studi mahasiswa, disusul dengan faktor mahasiswa, faktor sarana dan prasarana, serta faktor dari luar. Dari hasil metode SMARTER diperoleh bahwa faktor yang paling mempengaruhi kelulusan mahasiswa adalah faktor dosen dengan nilai utility sebesar 15,918. Faktor kedua adalah faktor mahasiswa yang mempunyai nilai utility sebesar 8,297, disusul faktor sarana dan prasarana sebesar 4,425, dan faktor dari luar sebesar 1,312. Dari hasil perhitungan metode SMARTER dan data real didapat bahwa faktor bimbingan dosen merupakan faktor yang mempunyai pengaruh besar dalam perhitungan lama studi mahasiswa.
Perbandingan Metode MOORA dan SMART dalam Kelayakan Pemberian Kredit pada Calon Debitur Koperasi Lenny Margaretta Huizen; Nurtriana Hidayati; Muhammad Basyier Ardima
AITI Vol 20 No 1 (2023)
Publisher : Fakultas Teknologi Informasi Universitas Kristen Satya Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24246/aiti.v20i1.95-110

Abstract

The Koperasi is a business entity whose activities are based on kinship. There are several types of Koperasi, including Savings and Loans Koperasi. Savings and Loans Koperasi is a type of Koperasi whose function is to serve members who are in it and who are not members to carry out savings or loan business services. Granting loans to prospective debtors, of course, must be with much consideration. The process for disbursing funds generally takes two working days. This is because several things must be analyzed regarding the feasibility of prospective debtors in receiving loan credit, ranging from salary, home ownership, how many loans are proposed, what is guaranteed, and other things that can be considered. The SMART method and the MOORA method are two of the existing methods in a decision support system. These two methods perform multi-attribute decision-making where each decision chooses the highest result in ranking several alternatives. The data taken is data from prospective debtors from December 2021-March 2022. The calculations between actual data and calculations of SMART and MOORA SPKs show that from the calculations with SMART, 69.072% have the same results as actual data, and 30.928% have different results from the actual data. In the MOORA method, 40.206% of data have the same as actual data, and 59.79%. have different results from actual data.
Meningkatkan kinerja SVM: Dampak berbagai teknik seleksi fitur pada akurasi prediksi Huizen, Lenny Margaretta; Ardima, Muhammad Basyier; Idris, Mochamad
AITI Vol 22 No 1 (2025)
Publisher : Fakultas Teknologi Informasi Universitas Kristen Satya Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24246/aiti.v22i1.1-14

Abstract

Pada akreditasi Perguruan Tinggi, kelulusan mahasiswa memainkan peran penting sebagai salah satu kriteria penilaian. Prediksi kelulusan merupakan fokus utama untuk membantu institusi dalam menilai seorang mahasiswa lulus tepat waktu. Penelitian ini mengambil data historis dari mahasiswa yang telah lulus, yang diambil melalui kuesioner dari mahasiswa Program Studi Sistem Informasi dan Teknik Informatika Universitas Semarang. Metode seleksi fitur digunakan untuk menyeleksi atribut yang paling relevan pada prediksi kelulusan. Hasil seleksi ini diujikan menggunakan Algoritma Support Vector Machine (SVM). Tujuan utama dari penelitian ini adalah untuk mengevaluasi dampak seleksi fitur terhadap prediksi kelulusan. Hasil pengujian menunjukkan bahwa SVM dengan seleksi fitur menggunakan weight by relief mencapai akurasi sebesar 82%, presisi 83,42%, dan recall 80,83%. Sebaliknya, SVM tanpa menggunakan weight by relief menunjukkan akurasi 69,23%, presisi 70,83%, dan recall 67,86%. Penggunaan seleksi fitur berhasil mengurangi fitur dari 27 menjadi empat fitur yang paling berpengaruh.
ANALISIS SENTIMEN TERHADAP ULASAN PENGGUNA APLIKASI DANA DI GOOGLE PLAYSTORE MENGGUNAKAN ALGORITMA SUPPORT VECTOR MACHINE (SVM) Willyarnandi, Muchammad Chadavi; Huizen, Lenny Margaretta
Jurnal Teknik Informasi dan Komputer (Tekinkom) Vol 8 No 1 (2025)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v8i1.2253

Abstract

In today's era, technological advancements have significantly facilitated various aspects of life, including the financial sector through the emergence of financial technology (fintech). One of the widely used fintech services in Indonesia is the DANA digital wallet. The abundance of user reviews generated from the use of this application reflects the level of user satisfaction or dissatisfaction with the services provided. However, this data is generally unstructured text, making it difficult to analyze manually. Therefore, an automatic analysis method is needed to categorize the sentiments contained in these reviews. Support Vector Machine (SVM) is one of the algorithms that can be used for sentiment classification, although its effectiveness in analyzing reviews of the DANA application still requires further investigation.This study aims to analyze sentiment in user reviews of the DANA application obtained from the Google Play Store using the SVM algorithm. A total of 2,000 reviews were collected through scraping and processed through several stages, including data cleaning, case folding, normalization, tokenization, stopword removal, and stemming. Text features were extracted using the Term Frequency-Inverse Document Frequency (TF-IDF) method before classification with SVM. SVM was chosen due to its ability to handle high-dimensional data and its strong performance in text classification tasks. The results indicate that SVM is capable of classifying sentiment with high accuracy, achieving around 90% or more, along with high precision, recall, and F1-score values. These findings are expected to help application developers understand user needs and complaints to enhance the quality of DANA’s services.
Sistem Monitoring Pekerjaan Proyek Menggunakan Metode Extreme Programming Prayoga, Mohamad Adrian; Huizen, Lenny Margaretta; Asmiatun, Siti
Journal of Information System Research (JOSH) Vol 5 No 3 (2024): April 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v5i3.5001

Abstract

Government agencies such as the Office of Public Works (PU) Bina Marga and Cipta Karya (BMCK) are in charge of managing and carrying out projects related to housing and road infrastructure development, maintenance, and oversight. There is a need to keep an eye on the road infrastructure projects going on at the Public Works Office of Bina Marga and Cipta Karya. Road building is slowed down, complicated, and prone to mistakes since the Public Works Office of Highways and Human Settlements does not yet have a framework in place to enable monitoring. The goal of this study is to develop a method for tracking road building progress that will make the process easier and faster. One development approach that streamlines the many phases of development to make it more adaptable and flexible is the Extreme Programming technique. This system is designed using UML(Unified Modeling Language) as a means to analyze and design the system. The test results using the Technology Acceptance Model (TAM) resulted in a value of 92.33%, which is considered very good and has met the expected criteria.
Speech-Driven Visitor Notification System Using Telegram Bot and Voice Activity Detection for Real-Time Retail Applications Setiaji, Aria; Hendrawan, Aria; Christioko, Bernadus Very; Huizen, Lenny Margaretta
International Journal of Artificial Intelligence and Science Vol. 2 No. 2 (2025): September
Publisher : Asosiasi Doktor Sistem Informasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63158/IJAIS.v2i2.44

Abstract

In the retail industry, fast and responsive service is essential for maintaining customer satisfaction and loyalty. A key challenge faced by store owners is delayed responses to customer arrivals, leading to dissatisfaction and potential lost sales. This project develops an automatic notification system using Speech-to-Text technology and a Telegram bot to detect voice keywords and send real-time notifications to store owners. The system was developed using the prototype methodology, allowing for iterative testing and refinement to ensure it met user needs and functional requirements. It integrates the Deepgram API for accurate speech transcription, the Telegram Bot API for notifications, and a web interface for managing keywords and monitoring system status. To enhance efficiency, a Voice Activity Detection (VAD) module was added, ensuring that only human speech is processed, thereby reducing unnecessary processing. Experimental results showed that the system achieved 100% accuracy in quiet environments and 80% in noisy conditions. The system's response time was also impressive, with an average time of 3.72 seconds in quiet conditions and 3.8 seconds in noisy environments. Word Error Rate (WER) and Character Error Rate (CER) evaluations indicated perfect accuracy in quiet conditions (WER 0%, CER 0%) and slight errors in noisy conditions (WER 13.33%, CER 12.5%). Overall, the system effectively improved service speed and responsiveness, offering store owners a valuable tool for enhancing customer experience in retail environments.
Co-Authors Agus Hartanto Agusta Praba Ristadi Pinem Alauddin Maulana Hirzan April Firman Daru Ardima, Muhammad Basyier Aria Hendrawan, Aria Aria Setiaji Asmiatun, Siti Atmoko Nugroho Badroe Zaman Charis Maulana Cholil, Saifur Rohman Faradilah, Yanti Febrian Wahyu Christanto Idris, Mochamad Irgo Satya Gemiwang Jeremia Maheswara Azri Saputra Kusumaningrum, Yulinda Nurtriana Hidayati Prayoga, Mohamad Adrian Rastri Prathivi Rizal Kurnia Setiaji, Aria Surono Titis Handayani Vensy Vydia Wahyu Maulana Hassanudin Whisnumurti Adhiwibowo Wicaksana, Dinar Anggit Willyarnandi, Muchammad Chadavi