Garuda - Garba Rujukan Digital

COMPARISON OF K-N EAREST NEIGHBOR AND NAÏVE BAYES ALGORITHMS FOR PREDICTION OF APTIKOM MEMBERSHIP ACTIVITY EXTENSION IN 2023 Fauzia, Fathia Alisha; Adjani, Kannisa; Juliane, Christina
Sinkron : jurnal dan penelitian teknik informatika Vol. 7 No. 2 (2023): Research Article, Volume 7 Issue 2 April, 2023
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i2.12081

So far APTIKOM as the Informatics and Computer Higher Education Association has provided many opportunities for registered members to participate in discussions on the development of science among fellow association members, access to various professional experts, as well as technical and non-technical guidelines in the field of education. With the various opportunities above, it is hoped that all members will support the activities of each member who has joined or has just joined so that a good association can be created. This study aims to find out about the problems that occur in APTIKOM, namely members who have registered as members but rarely renew their membership which results in data accumulation in APTIKOM. This research method uses the k-nn and naïve Bayes algorithms by using data sets from 2012 to 2022. The dataset used is APTIKOM member data and has 5 attributes namely name, gender, last education, institution and validation secret. To calculate the research test using a rapid miner. The purpose of this study is to predict whether in the following year there will be a membership renewal process for all APTIKOM members who have been recorded from 2012 to 2022. Furthermore, the results of this study have a different level of accuracy. Where for k-nn the resulting accuracy is 94.00% and for the result of naïve Bayes is 91.35%.

Evaluasi Kepuasan Pengguna Aplikasi My APTIKOM Melalui Pendekatan Technology Acceptance Model Adjani, Kannisa; Hudawiguna, Sigit
Jurnal Algoritma Vol 20 No 2 (2023): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.20-2.1246

In the current era, Information Technology (IT) has become an essential need for almost all organizations, given its recognized role in increasing the efficiency and effectiveness of business processes. Associations, especially APTIKOM (Informatics and Computer Higher Education Association), also realize the importance of good IT management to achieve organizational success and achieve its goals. Therefore, evaluating user satisfaction of the My APTIKOM application is a relevant step. This research uses the Technology Acceptance Model (TAM) method to analyze the factors that influence users' attitudes towards the My APTIKOM application, namely perceptions of perceived usefulness (Perceived Usefulness) and ease of use (Perceived Ease of Use). The research results show that perceptions about the benefits of the application (Perceived Usefulness) have a significant positive influence on user attitudes (Attitude Toward Using), with a relationship level of around 47.5%. However, no significant influence was found between perceptions of ease of use (Perceived Ease of Use) and user attitudes (Attitude Toward Using), which indicates that ease of use may not be the main factor in forming users' positive attitudes towards the application. In addition, the results showed that perceived usefulness and ease of use together had a significant positive influence on user attitudes (Attitude Toward Using), with a relationship level of 19.2%. This research provides insight into the factors that influence user attitudes towards the My APTIKOM application, which can be used as a basis for further development and improvement. In addition, this conclusion can be used by organizations, including APTIKOM, to improve IT management and ensure the applications they offer meet user needs and expectations regarding user attitudes (Attitude Toward Using), with a relationship rate of 19.2%.

Pengembangan Mallverse sebagai Toko Virtual di Metaverse Adjani, Kannisa; Yusuf, Ahmad; Wardiah, Isna; Murtadha, Muhammad Rizki
Eksplora Informatika Vol 14 No 2 (2025): Jurnal Eksplora Informatika
Publisher : Institut Teknologi dan Bisnis STIKOM Bali

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30864/eksplora.v14i1.1277

Pengembangan Mallverse sebagai toko virtual di metaverse bertujuan untuk menyediakan platform belanja yang interaktif dan imersif. Studi ini menyajikan proses pengembangan Mallverse, yang melibatkan analisis kebutuhan pengguna, penentuan konsep, pembuatan purwarupa, pembuatan lingkungan, dan implementasi. Mallverse dibangun menggunakan dua platform utama, yaitu Unity dan Roblox Studio, yang memungkinkan pengembangan lingkungan virtual yang realistis dan interaktif. Hasil pengujian menunjukkan bahwa Mallverse mampu meningkatkan pengalaman belanja pengguna melalui navigasi yang intuitif dan interaksi produk yang mendalam. Selain itu, fitur sosial yang disediakan meningkatkan keterlibatan dan interaksi antar pengguna, memberikan nilai tambah bagi bisnis. Sistem beroperasi dengan stabil dan memiliki latensi yang dapat diterima, menunjukkan bahwa infrastruktur teknis yang digunakan cukup kuat untuk mendukung interaksi real-time. Kesimpulannya, Mallverse menunjukkan performa yang baik dan memenuhi sebagian besar kriteria keberhasilan yang ditetapkan, dengan beberapa rekomendasi untuk peningkatan lebih lanjut.

Pengembangan Mallverse sebagai Toko Virtual di Metaverse Adjani, Kannisa; Yusuf, Ahmad; Wardiah, Isna; Murtadha, Muhammad Rizki
Eksplora Informatika Vol 14 No 2 (2025): Jurnal Eksplora Informatika
Publisher : Institut Teknologi dan Bisnis STIKOM Bali

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30864/eksplora.v14i1.1277

Pengembangan Mallverse sebagai toko virtual di metaverse bertujuan untuk menyediakan platform belanja yang interaktif dan imersif. Studi ini menyajikan proses pengembangan Mallverse, yang melibatkan analisis kebutuhan pengguna, penentuan konsep, pembuatan purwarupa, pembuatan lingkungan, dan implementasi. Mallverse dibangun menggunakan dua platform utama, yaitu Unity dan Roblox Studio, yang memungkinkan pengembangan lingkungan virtual yang realistis dan interaktif. Hasil pengujian menunjukkan bahwa Mallverse mampu meningkatkan pengalaman belanja pengguna melalui navigasi yang intuitif dan interaksi produk yang mendalam. Selain itu, fitur sosial yang disediakan meningkatkan keterlibatan dan interaksi antar pengguna, memberikan nilai tambah bagi bisnis. Sistem beroperasi dengan stabil dan memiliki latensi yang dapat diterima, menunjukkan bahwa infrastruktur teknis yang digunakan cukup kuat untuk mendukung interaksi real-time. Kesimpulannya, Mallverse menunjukkan performa yang baik dan memenuhi sebagian besar kriteria keberhasilan yang ditetapkan, dengan beberapa rekomendasi untuk peningkatan lebih lanjut.

Evaluasi Kepuasan Pengguna Aplikasi My APTIKOM Melalui Pendekatan Technology Acceptance Model Adjani, Kannisa; Hudawiguna, Sigit
Jurnal Algoritma Vol 20 No 2 (2023): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.20-2.1246

In the current era, Information Technology (IT) has become an essential need for almost all organizations, given its recognized role in increasing the efficiency and effectiveness of business processes. Associations, especially APTIKOM (Informatics and Computer Higher Education Association), also realize the importance of good IT management to achieve organizational success and achieve its goals. Therefore, evaluating user satisfaction of the My APTIKOM application is a relevant step. This research uses the Technology Acceptance Model (TAM) method to analyze the factors that influence users' attitudes towards the My APTIKOM application, namely perceptions of perceived usefulness (Perceived Usefulness) and ease of use (Perceived Ease of Use). The research results show that perceptions about the benefits of the application (Perceived Usefulness) have a significant positive influence on user attitudes (Attitude Toward Using), with a relationship level of around 47.5%. However, no significant influence was found between perceptions of ease of use (Perceived Ease of Use) and user attitudes (Attitude Toward Using), which indicates that ease of use may not be the main factor in forming users' positive attitudes towards the application. In addition, the results showed that perceived usefulness and ease of use together had a significant positive influence on user attitudes (Attitude Toward Using), with a relationship level of 19.2%. This research provides insight into the factors that influence user attitudes towards the My APTIKOM application, which can be used as a basis for further development and improvement. In addition, this conclusion can be used by organizations, including APTIKOM, to improve IT management and ensure the applications they offer meet user needs and expectations regarding user attitudes (Attitude Toward Using), with a relationship rate of 19.2%.

BIG DATA ANALYTICS DAN MACHINE LEARNING UNTUK MEMPREDIKSI PERILAKU KONSUMEN DI E-COMMERCE Djihadul Mubarok; Kannisa Adjani; Brian Damastu Ridho Hutama; Muhamad Malik Mutoffar; Rina Indrayani
Jurnal Informatika dan Rekayasa Elektronik Vol. 8 No. 1 (2025): JIRE APRIL 2025
Publisher : LPPM STMIK Lombok

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36595/jire.v8i1.1561

Dalam era digital yang berkembang pesat, marketplace digital menjadi salah satu platform utama bagi konsumen dalam melakukan transaksi online. Pemanfaatan Big Data Analytics dalam menganalisis aktivitas konsumen dapat memberikan pengetahuan mendalam untuk pelaku usaha dalam meningkatkan strategi pemasaran dan layanan pelanggan. Penelitian ini bertujuan untuk mengeksplorasi penerapan Big Data Analytics dalam memahami pola pembelian konsumen serta faktor yang mempengaruhi loyalitas pelanggan di marketplace digital. Metode penelitian yang digunakan mencakup pengumpulan data primer melalui survei terhadap 1.000 responden serta data sekunder yang diperoleh dari web scraping dan teknik data mining. Data yang dikumpulkan dianalisis menggunakan teknik analisis Big Data dan algoritma Machine Learning untuk mengidentifikasi tren perilaku konsumen. Hasil penelitian menunjukan bahwa faktor harga, kecepatan pengiriman, serta pengalaman pengguna memiliki pengaruh signifikan terhadap loyalitas pelanggan. Selain itu, penerapan analisis prediktif berbasis Machine Learning mampu meningkatkan akurasi prediksi perilaku konsumen hingga 85%. Pada temuan ini, dapat memberikan pengetahuan bagi pelaku bisnis dalam menentukan ploda dan strategi pemasaran lebih efektif dalam meningkatkan kepuasan pelanggan. Penelitian ini dapat menjadikan peluang bagi penelitian berikutnya mengenai optimalisasi algoritma Machine Learning dalam segmentasi pelanggan untuk personalisasi pengalaman belanja.

Strengthening Production Capacity and Business Management through Co-Creation as a Foundation for Digital Transformation in Community-Based Producer Groups Melissa Indah Fianty; Sy. Yuliani; Wanda Gema Prasadio Akbar Hidayat; Kannisa Adjani
I-Com: Indonesian Community Journal Vol 6 No 3 (2026): I-Com: Indonesian Community Journal (September 2026)
Publisher : Fakultas Sains Dan Teknologi, Universitas Raden Rahmat Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70609/icom.v6i3.11091

Limited organizational capacity and manual business management remain significant barriers to digital transformation in productive community enterprises. This community empowerment program aimed to strengthen the capacity of the Dewata Farm aquaculture group and the Mekar Lestari food processing group through knowledge transfer and co-creation as the foundation for digital transformation. The program employed a participatory approach consisting of needs assessment, workshops, mentoring, prototype design, and evaluation using a five-point Likert-scale questionnaire analyzed descriptively. The results indicated a very high level of partner acceptance and readiness for digital solution implementation, reflected by a Readiness for Prototype Implementation score of 4.92 and a Knowledge Transfer Effectiveness score of 4.91. In addition, the program produced functional system requirements and a prototype tailored to the operational characteristics of both partner groups. These findings demonstrate that participatory capacity building can enhance organizational readiness and establish a strong foundation for sustainable digital transformation in rural productive enterprises.

Advertising Promotion, Price Sensitivity, and Brand Image as Determinants of Purchase Decisions at Bersamastore: A Fashion MSME on Tokopedia Bandung Khidhir Akbar Ghofar; Ghani Saepuloh; Entis Sutisna; Melsa Ulfie Wahyudianty; Kannisa Adjani
Jurnal Ilmu Manajemen Terapan Vol. 8 No. 1 (2026): Jurnal Ilmu Manajemen Terapan (September - Oktober 2026)
Publisher : Dinasti Review Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38035/jimt.v8i1.9572

This study examines the effects of advertising promotion, price sensitivity, and brand image on consumer purchase decisions at Bersamastore, a fashion micro, small, and medium enterprise (MSME) operating on the Tokopedia e-commerce platform in Bandung, Indonesia. Prior research has tended to examine these variables separately or within broader multi-category B2C contexts; studies focusing on all three within a single-platform MSME setting remain relatively scarce. A quantitative approach was used, with data collected via structured Likert-scale questionnaires from 101 purposively sampled respondents who had made repeat purchases at Bersamastore more than twice in the preceding year. Multiple linear regression was applied for analysis. The majority of respondents were female (58.4%), aged 22–26 years (40.6%), and employed in the private sector (41.6%). Results indicate that advertising promotion (β = 0.467, t = 5.216, p < 0.001), price sensitivity (β = 0.284, t = 3.723, p < 0.001), and brand image (β = 0.225, t = 3.262, p = 0.002) each show a significant positive effect on purchase decisions. Together, the three variables account for 80.2% of the variance in purchase decisions (Adjusted R² = 0.802, F = 135.958, p < 0.001). The Glejser test confirmed no heteroscedasticity across predictors. A Harman single factor test yielded a first-factor variance of 55.54%, which exceeds the conventional 50% threshold and is acknowledged as a study limitation. Advertising promotion emerged as the strongest predictor. The findings carry practical implications for single-platform fashion MSMEs, particularly in allocating promotional resources and building brand recognition within competitive marketplace environments.

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