Green campus is the creation of a green ecologically friendly environment that leads to smart campus establishment. In this study, green campus status is revealed by applying cross-campus community collaboration under green transportation bus. The purpose of this study was to develop a real-time Android-based tracking system, using the V model approach, aimed at green transportation movements and accessibility. The global positioning system of green transportation is interconnected via a back-end server that utilizing web-socket to incorporate client and server communications. The results are passenger app that enabling the passenger to track green transportation movement, acquire green transportation meta-information, perceive campus routes, and send awaiting notification. Further results are driver app for green transportation drivers to choose which vehicle to drive, change driving status, recognize other active coaches, locate nearer passengers stops, and identify campus routes. The created mobile app has successfully experimented on Android smartphones such as Samsung Galaxy Mega J5, Lenovo A6000, Xiaomi Redmi 3, Asus 2 Zenfone Laser, and Samsung J7 Prime.

The supply and demand of various fresh chili types correspond to one another simultaneously because they can be complementary or substitute products. This study aimed to simultaneously examine the supply and demand model of red chili and cayenne peppers to support innovative chili enterprise system development. The methodology is the simultaneous equation system panel data using the years 2010–2020 time-series and provincial cross-sectional data combined with data mining techniques. The two-stage least square method was used for the estimation and simulation of the models. The results of the models comprise three identities and ten structural equations. The resulting models are all statistically fit with some drawbacks owing to the micro-level data availabilities. The simulations on the labor wages, prices, demand, and production for red chili and cayenne peppers affected the other variables within the model. In conclusion, the chili supply and demand models could support the development of the innovative chili enterprise system; however, this requires proactive collaboration and participation from all the relevant institutions and actors. Moreover, this research model is potentially applicable to other horticultural commodities.

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<p>Lahan adalah campuran lingkungan fisik dan alam yang meliputi iklim, tanah, relief, dan hidrologi. Campuran tanah memiliki konsekuensi dari penggunaan lahannya. Di sisi lain, keberhasilan pertanian dan agroindustri dipengaruhi oleh keberhasilan budi daya pertaniannya. Penelitian ini bermaksud untuk membangun sistem pakar yang dapat digunakan untuk menentukan evaluasi lahan tanaman, khususnya untuk tanaman Nilam. Sistem Pakar Kesesuaian Lahan Nilam bertujuan untuk memberikan informasi tentang karakteristik lahan yang sesuai untuk tanaman Nilam. Peneliti memanfaatkan keahlian pakar untuk memberikan pengetahuan kepada sistem pakar yang dikembangkan. Input pemrosesan untuk sistem pakar terdiri atas dua format, yaitu input fuzzy dan input non-fuzzy. Pertama, Fuzzy Inference System (FIS) dengan metode Mamdani digunakan sebagai metode inferensi untuk output fuzzy diikuti dengan aplikasi input non-fuzzy. Sistem pakar menyediakan tiga kategori evaluasi, yaitu, pembudidayaan lahan yang sangat sesuai, sesuai, dan tidak sesuai untuk Nilam. Setiap kategori memiliki karakteristik lahan tertentu sesuai hasil evaluasi lahan. Selanjutnya, sistem pakar dinilai pada enam belas lahan berbeda untuk memverifikasi keakuratan sistem. Hasil penilaian menyajikan akurasi 75% ketika diverifikasi menggunakan penilaian ahli manusia.</p><p><br />Kata kunci: Fuzzy Inference System,FIS, Mamdani, Nilam, Sistem Pakar, Kesesuaian Lahan</p>