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All Journal CogITo Smart Journal Sebatik Jurnal Sisfokom (Sistem Informasi dan Komputer) JOURNAL OF INFORMATION SYSTEM MANAGEMENT (JOISM) JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) TEPIAN Servitium Smart Journal
Maringka, Raissa
Universitas Klabat
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering

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KLASIFIKASI PERINGKAT APLIKASI ANDROID DI GOOGLE PLAY STORE MENGGUNAKAN ALGORITMA RANDOM FOREST DENGAN PREPROCESSING SQL SERVER Maringka, Rodney Giovanni; Khoirunnita, Aulia; Maringka, Raissa
Sebatik Vol 24 No 2 (2020): Desember 2020
Publisher : STMIK Widya Cipta Dharma

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Abstract

Semakin banyaknya aplikasi Android yang tersedia di Google Play Store dengan keuntungan yang didapatkan pengembangnya telah menarik perhatian banyak pengembang aplikasi Android. Untuk mendapatkan keuntungan dari mengembangkan aplikasi Android, salah satu caranya adalah dengan mengetahui karakteristik aplikasi berperingkat tinggi di Google Play Store. Penelitian ini akan menyelidiki fitur size, installs, reviews, type(gratis/bayar), rating, category, content rating, dan price pada aplikasi di Google Play Store untuk mengetahui karakteristik aplikasi berperingkat tinggi. Penelitian ini menggunakan algoritma Random Forest untuk mengidentifikasi fitur yang paling berpengaruh pada aplikasi dengan peringkat tinggi di Google Play Store. Pada tahap preprocessing, penelitian ini menggunakan metode data cleaning dan data reduction menggunakan sql server. Penelitian ini menggunakan feature important untuk mengetahui atribut yang paling berpengaruh pada peringkat tinggi aplikasi Android di Google Play Store. Untuk mengklasifikasi aplikasi berperingkat tinggi penulis menggunakan 8-fold cross validation menggunakan algoritma Random Forest dan mendapatkan hasil yang lebih baik dibandingkan dengan algoritma Gradient Boost, K-NN, dan Decision Tree yaitu dengan akurasi sebesar 83% . Hasil dari algoritma Random Forest ini juga mempunyai performa yang lebih baik dibandingkan dengan algoritma dari kesimpulan penelitian sebelumnya, dengan 0,8% penambahan akurasi.
MENINGKATKAN KUALITAS BASIS DATA DENGAN MENERAPKAN ASPEK KONSISTENSI PADA PENAMAAN FIELD DAN TABEL Khoirunnita, Aulia; Maringka, Raissa; Maringka, Rodney Giovanni
Sebatik Vol 24 No 2 (2020): Desember 2020
Publisher : STMIK Widya Cipta Dharma

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Abstract

Basis data merupakan salah satu tolak ukur yang berpengaruh pada kualitas sistem informasi. Suatu sistem informasi efektif tentunya memiliki basis data yang berkualitas. Aspek-aspek yang dapat diukur untuk menentukan kualitas basis data adalah aspek kebenaran, konsistensi, jangkauan, tingkat detail, kelengkapan, minimalitas, kemampuan untuk berintegrasi dan kemampuan untuk dibaca. Salah satu kesalahan yang sering didapati dalam basis data adalah berhubungan dengan aspek konsistensi. Aspek konsistensi yang tidak terlalu diperhatikan penerapannya dapat menimbulkan konflik data akibat ambiguitas serta duplikasi data. Penelitian ini bertujuan untuk meningkatkan kualitas basis data dengan menerapkan konsistensi pada penamaan field dan tabel. Suatu metode penamaan untuk menghasilkan konsistensi dalam standarisasi diterapkan pada penelitian ini. Dari hasil pengujian menggunakan SQL Server didapati bahwa metode yang ditawarkan dalam penelitian ini dapat menjadi salah satu solusi dari penamaan field dan tabel yang tidak konsisten dan menimbulkan ambiguitas.
Improving Database Quality by Applying Consistency Aspects to Naming Fields and Tables Raissa Maringka; Aulia Khoirunnita; Rodney Maringka; Ema Utami; Kusnawi
TEPIAN Vol 2 No 1 (2021): March 2021
Publisher : Politeknik Pertanian Negeri Samarinda

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (317.497 KB) | DOI: 10.51967/tepian.v2i1.304

Abstract

The database is one of the benchmarks that affect the quality of information systems. An effective information system certainly has a quality database. Aspects that can be measured to determine the quality of the database are aspects of truth, consistency, range, level of detail, completeness, minimalism, ability to integrate and readability. One of the mistakes that are often encountered in databases is related to the consistency aspect. Consistency aspects that are not paid much attention to its application can lead to data conflicts due to ambiguity and data duplication. This study aims to improve the quality of the database by applying consistency to the naming of fields and tables. A naming method to produce consistency in standardization was applied in this study.
Android App Rating Classification on Google Play Store Using Random Forest Algorithm with SQL Server Preprocessing Raissa Maringka; Aulia Khoirunnita; Rodney Maringka; Erna Utami; Kusnawi
TEPIAN Vol 2 No 2 (2021): June 2021
Publisher : Politeknik Pertanian Negeri Samarinda

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (530.483 KB) | DOI: 10.51967/tepian.v2i2.404

Abstract

The increasing number of Android applications available on the Google Play Store with the benefits the developers get has attracted the attention of many Android application developers. To benefit from developing Android apps, one way is to know the characteristics of highly rated apps on the Google Play Store. This research will investigate the features of size, installs, reviews, type (free / paid), rating, category, content rating, and price on applications on the Google Play Store to determine the characteristics of high-rated applications. This study uses the Random Forest algorithm to identify the most influential features in high ranking applications on the Google Play Store. At the preprocessing stage, this research uses data cleaning methods and data reduction using SQL Server. This study uses feature important to find out the attributes that most influence the high ranking of Android apps on the Google Play Store. To classify high-ranking applications, the authors use 8-fold cross validation using the Random Forest algorithm and get better results than the Gradient Boost, K-NN, and Decision Tree algorithms with an accuracy of 83%. The results of the Random Forest algorithm also have better performance than the algorithm from the previous research conclusions, with a 0.8% increase in accuracy. To classify high-ranking applications, the authors use 8-fold cross validation using the Random Forest algorithm and get better results than the Gradient Boost, K-NN, and Decision Tree algorithms with an accuracy of 83%. The results of the Random Forest algorithm also have better performance than the algorithm from the previous research conclusions, with a 0.8% increase in accuracy. To classify high-ranking applications, the authors use 8-fold cross validation using the Random Forest algorithm and get better results than the Gradient Boost, K-NN, and Decision Tree algorithms with an accuracy of 83%. The results of the Random Forest algorithm also have better performance than the algorithm from the previous research conclusions, with a 0.8% increase in accuracy.
Exploratory Data Analysis Faktor Pengaruh Kesehatan Mental di Tempat Kerja Raissa Maringka; Kusnawi Kusnawi
CogITo Smart Journal Vol 7, No 2 (2021): Cogito Smart Journal
Publisher : Fakultas Ilmu Komputer, Universitas Klabat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31154/cogito.v7i2.312.215-226

Abstract

Gangguan kesehatan mental pada lingkungan kerja merupakan hal yang sering ditemui di kalangan para pengerja. Menurut prediksi World Health Organization (WHO) pada tahun 2011 menyatakan bahwa pada tahun 2030, depresi akan menjadi penyakit yang membebankan dunia. Mempertahankan lingkungan pekerjaan yang bebas stres merupakan faktor yang penting untuk memiliki karyawan yang lebih produktif dalam bekerja. Untuk itu, mendeteksi gangguan kesehatan mental lebih awal merupakan hal yang penting harus dilakukan. Pada penelitian ini, peneliti mengambil data yang bersumber dari OSMI (Open Sourcing Mental Illness). Dataset ini mencakup data para pengerja secara per orangan yang berhubungan dengan bagaimana pekerjaan mereka mempengaruhi kesehatan mental. Peneliti berharap dengan exploratory data analysis berbasis python pada faktor-faktor yang mempengaruhi kesehatan mental di lingkungan kerja dapat membantu dalam mengevaluasi suatu perusahaan atau lingkungan pekerjaan dalam menolong para karyawan atau pengerja untuk lebih produktif dan sehat secara mental ataupun fisik. Pendekatan ini juga diharapkan dapat membantu para manajer atau HR untuk lebih mengerti akan kebutuhan karyawan serta mengambil langkah untuk mencegah masalah yang dapat mempengaruhi kesehatan mental para karyawan
Analisa Perkembangan Musik Pada Spotify Menggunakan Structured Query Language (SQL) Raissa Camilla Maringka; Aulia Khoirunnita; Rodney Maringka; Ema Utami; Kusnawi Kusnawi
CogITo Smart Journal Vol 7, No 1 (2021): Cogito Smart Journal
Publisher : Fakultas Ilmu Komputer, Universitas Klabat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31154/cogito.v7i1.287.1-14

Abstract

Musik mengalami perubahan dan berevolusi hingga mencapai abad ke 21. Tidak seperti jaman purbakala, generasi digital saat ini dapat menggunakan teknologi dalam menikmati musik. Spotify menjadi salah satu aplikasi yang banyak digunakan sebagai platform dalam music streaming. Perubahan musik yang signifikan setiap tahunnya mempengaruhi pembentukan pola pikir masyarakat terhadap preferensi pilihan musik. Oleh karena itu perlu dilakukan pemantauan terhadap trend perkembangan musik serta mengetahui faktor-faktor yang mempengaruhinya untuk melihat perubahan apa saja yang terjadi serta menjadi tolak ukur untuk membantu industri musik dalam menghasilkan musik yang layak didengarkan serta membawa pengaruh positif. Penelitian ini akan memberikan hasil analisa dari perkembangan trend perkembangan musik khususnya pada aplikasi Spotify menggunakan Structured Query Language. Dari hasil analisa didapatkan visualisasi dari trend genre musik dan fitur audio dalam jangkauan tahun 2010 hingga 2020 yang diolah menggunakan Power BI. Diharapkan hasil tersebut dapat membantu indusri musik dalam menghasilkan musik yang digemari serta memberikan pengetahuan yang baik terhadap penggemar musik.Kata kunci—Musik, Spotify, SQL, Power BI
Designing User Interface (UI) And User Experience (UX) of a Sport Space Rental Application using Design Thinking Method Raissa Maringka; Cherry Lumingkewas
CogITo Smart Journal Vol. 10 No. 1 (2024): Cogito Smart Journal
Publisher : Fakultas Ilmu Komputer, Universitas Klabat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31154/cogito.v10i1.692.613-624

Abstract

This study aims to enhance the design and streamline the process of renting sports facilities through the development of a user interface (UI) and user experience (UX) for a sport space rental application. Utilizing the Design Thinking method, the research addresses inefficiencies in the current manual booking process and proposes innovative solutions, including search features, user reviews, availability notifications, and direct booking options. The state of the art in this study is represented by the application of user-centric design principles and iterative prototyping to meet the evolving needs of sports enthusiasts. Usability testing, conducted through detailed task scenarios on the MAZE platform, yielded positive results, with an average completion rate of 80% and insights into areas for improvement. The findings suggest that the proposed UI/UX design significantly enhances the efficiency and user experience of renting sports facilities, providing a more convenient and engaging platform for users.
Emotion Mining User Review of the BRImo Mobile Banking Application Using the Decision Tree Algorithm Sondakh, Debby Erce; Maringka, Raissa C; Ayorbaba, Ferlien P; Mangi, Joanne S. C. B. T.; Pungus, Stenly Richard
Jurnal Sisfokom (Sistem Informasi dan Komputer) Vol 12, No 3 (2023): NOVEMBER
Publisher : ISB Atma Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32736/sisfokom.v12i3.1721

Abstract

As consumer transaction preferences shifted from analog to digital, banks were compelled to develop digital transactions in the form of mobile banking. Users of mobile banking provide feedback regarding the application's usability. The opinions of users can be emotive. Emotions influence what a person emits or applies. Emotions are the behavioral response of a person when he is happy or unhappy. Thus, the manifestation of a person's emotions, whether in the form of facial expressions, verbal communication, written text, or judgment, can be used as a source of information to aid in decision making. The objective of this study is to apply emotion mining to the analysis of user evaluations of the BRImo application, one of the three most popular platforms in Indonesia as of August 2022, with a total of 800,000 reviews on the Play Store. Emotion Mining can be used to analyze the four categories of emotions expressed by users in the comments section: happy, angry, sad, and afraid. According to BRImo user evaluations, the decision tree algorithm is used to categorize happy, sad, afraid, and angry feelings. Using a decision tree to manage large data category sets is effective. The obtained dataset included 2959 happy classes, 2196 sad classes, 387 angry classes, and 81 scared classes. According to the findings of the analysis, a significant number of users of the BRImo application express positive sentiments in their evaluations, which are indicative of happy emotions. The Decision Tree algorithm yields results with a performance specification of 84.5%, sensitivity of 85.5%, and precision of 84.4%.
Memperkenalkan Algoritma dan Berpikir Algoritmik kepada Siswa Sekolah Dasar Menggunakan CS Unplugged Sondakh, Debby Erce; Pungus, Stenly Richard; Maringka, Raissa C; Tangka, George M. W
Servitium Smart Journal Vol 2 No 2 (2024): Servitium Smart Journal
Publisher : Universitas Klabat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31154/servitium.v2i2.29

Abstract

A community service was conducted aiming at introducing the concept of algorithms and algorithmic thinking to elementary school students, using the Computer Science Unplugged approach. Two main activities, "Sorting Network" and "Move It, Move It," were implemented. A total of 35 students from elementary schools in rural areas in North Sulawesi, where computer equipment is not available. The assessment of the success of these activities was based on behavioral observations, student participation, and their feedback on the activities. The results of this activity showed an increase in students' understanding of the concept of algorithms and strengthening their ability to apply algorithmic thinking. In addition, this activity also succeeded in increasing students' interest in computer science and demonstrating the importance of interactive learning in basic education.
Perancangan Desain UI/UX Aplikasi Mobile Defisit Kalori Menggunakan Metode Design Thinking Metty Wuisang; Joe Yuan Mambu; Raissa Maringka
Journal of Information System Research (JOSH) Vol 5 No 4 (2024): Juli 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v5i4.5511

Abstract

The increasing prevalence of lifestyle-related health issues highlights the necessity for innovative solutions to promote healthier habits. This study aims to design a better and more suitable user interface (UI) for the user experience (UX) of a mobile calorie deficit application using the Design Thinking method. The primary objective is to create a user-centric UI design that enhances user engagement and supports weight management goals. Through a comprehensive Design Thinking process, which includes empathizing with users, defining problems, ideating solutions, prototyping, and testing, we developed a UI design tailored to the needs of individuals seeking to manage their calorie intake effectively. The testing phase involved two scenarios. The first scenario achieved a miss click rate of 0-9% and a usability score ranging from 91 to 100. User feedback was continuously integrated to refine the design, ensuring usability and functionality. The results demonstrate that the well-structured UI design effectively improves user satisfaction and interaction. This research underscores the value of Design Thinking in developing user-centered interfaces for health management applications.
Co-Authors Ayorbaba, Ferlien P Cherry Lumingkewas Chrisanti, Ibrena Reghuella Ema Utami Erna Utami George Morris William Tangka Green Arther Sandag Jacquline Waworundeng Joe Yuan Mambu Khoirunnita, Aulia Kusnawi Kusnawi Makarawung, Reynard Justino Nehemia Mangi, Joanne S. C. B. T. Maringka, Rodney Giovanni Metty Wuisang Rodney Maringka Sondakh, Debby Erce Stenly Richard Pungus